DSO_574_Streaming_Platform_Project.ipynb

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      "source": [
        "## Data Import"
      ],
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      "source": [
        "from google.colab import drive\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "import re\n",
        "from collections import Counter\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib.ticker import FuncFormatter"
      ]
    },
    {
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      "source": [
        "drive.mount('/content/drive')"
      ],
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        "outputId": "046365f5-e3e2-4f8b-df38-fb01cd11df3a"
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          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "df_whole = pd.read_csv('/content/drive/MyDrive/DSO 574/Assignment 3/Database/ReelGood Data/Reel Good Data (Title+Service+Genre+Tag List).csv', index_col=0)"
      ],
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        "outputId": "77a83134-f94e-4454-804d-fe2963e31893"
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          "text": [
            "<ipython-input-22-00bcfcd6c8fe>:1: DtypeWarning: Columns (12) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df_whole = pd.read_csv('/content/drive/MyDrive/DSO 574/Assignment 3/Database/ReelGood Data/Reel Good Data (Title+Service+Genre+Tag List).csv', index_col=0)\n"
          ]
        }
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        "df_whole.shape"
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            "text/plain": [
              "(287834, 18)"
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          "execution_count": 23
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        "df_whole.columns"
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              "Index(['Title', 'URL', 'Type', 'Service', 'Genre', 'Tag', 'IMDB', 'ReelGood',\n",
              "       'AgeRating', 'Rated', 'Released Year', 'Duration Year', 'Seasons',\n",
              "       'What it's about', 'Where to Watch', 'Rent or Buy Available',\n",
              "       'Exclusive Service', 'Has Tag'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_whole[df_whole['Title'] == 'The Big Bang Theory']"
      ],
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              "                   Title                             URL Type    Service  \\\n",
              "302  The Big Bang Theory  /show/the-big-bang-theory-2007   tv    hbo_max   \n",
              "303  The Big Bang Theory  /show/the-big-bang-theory-2007   tv    hbo_max   \n",
              "304  The Big Bang Theory  /show/the-big-bang-theory-2007   tv  hulu_plus   \n",
              "305  The Big Bang Theory  /show/the-big-bang-theory-2007   tv  hulu_plus   \n",
              "306  The Big Bang Theory  /show/the-big-bang-theory-2007   tv        tbs   \n",
              "307  The Big Bang Theory  /show/the-big-bang-theory-2007   tv        tbs   \n",
              "\n",
              "       Genre                                                Tag  IMDB  \\\n",
              "302  Romance  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "303   Comedy  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "304  Romance  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "305   Comedy  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "306  Romance  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "307   Comedy  ['Science', 'Friendship', 'Science', 'Friendsh...   8.1   \n",
              "\n",
              "     ReelGood AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "302      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "303      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "304      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "305      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "306      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "307      90.0       16+  TV-14           2007     2007-2020     12.0   \n",
              "\n",
              "                                       What it's about  \\\n",
              "302  The Big Bang Theory is centered on five charac...   \n",
              "303  The Big Bang Theory is centered on five charac...   \n",
              "304  The Big Bang Theory is centered on five charac...   \n",
              "305  The Big Bang Theory is centered on five charac...   \n",
              "306  The Big Bang Theory is centered on five charac...   \n",
              "307  The Big Bang Theory is centered on five charac...   \n",
              "\n",
              "                                        Where to Watch  Rent or Buy Available  \\\n",
              "302  279 episodes (99%) are available to stream on ...                      1   \n",
              "303  279 episodes (99%) are available to stream on ...                      1   \n",
              "304  279 episodes (99%) are available to stream on ...                      1   \n",
              "305  279 episodes (99%) are available to stream on ...                      1   \n",
              "306  279 episodes (99%) are available to stream on ...                      1   \n",
              "307  279 episodes (99%) are available to stream on ...                      1   \n",
              "\n",
              "     Exclusive Service  Has Tag  \n",
              "302                  0        1  \n",
              "303                  0        1  \n",
              "304                  0        1  \n",
              "305                  0        1  \n",
              "306                  0        1  \n",
              "307                  0        1  "
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              "    60% {\n",
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              "    }\n",
              "    80% {\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
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              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_whole[df_whole['Title'] == 'The Big Bang Theory']\",\n  \"rows\": 6,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"The Big Bang Theory\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"/show/the-big-bang-theory-2007\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"hbo_max\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Comedy\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"['Science', 'Friendship', 'Science', 'Friendship', 'Science', 'Friendship']\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\n        \"min\": 8.1,\n        \"max\": 8.1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\n        \"min\": 90.0,\n        \"max\": 90.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          90.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"16+\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"TV-14\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 2007,\n        \"max\": 2007,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          2007\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"2007-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\n        \"min\": 12.0,\n        \"max\": 12.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          12.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"The Big Bang Theory is centered on five characters living in Pasadena, California\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"279 episodes (99%) are available to stream on a popular subscription service (HBO MAX). 14 episodes (5%) are available to stream on a popular TV everywhere service (TBS). 281 episodes (100%) are available to rent or buy from $1.99 on 5 services (iTunes, Google Play & 3 others).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# EDA and Data Preprocessing"
      ],
      "metadata": {
        "id": "BxTkyqvZhFz9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_whole.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 868
        },
        "id": "N5wWzNMVglWo",
        "outputId": "e594e37b-6038-4e6e-c6ce-68d0a817b5ab"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Title                         URL Type  Service  \\\n",
              "0     Breaking Bad     /show/breaking-bad-2008   tv  netflix   \n",
              "1     Breaking Bad     /show/breaking-bad-2008   tv  netflix   \n",
              "2  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "3  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "4  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "\n",
              "                Genre                                                Tag  \\\n",
              "0               Crime  ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...   \n",
              "1               Drama  ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...   \n",
              "2               Drama  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "3  Action & Adventure  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "4             Fantasy  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "\n",
              "   IMDB  ReelGood AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "0   9.5     100.0       18+  TV-MA           2008     2008-2020      5.0   \n",
              "1   9.5     100.0       18+  TV-MA           2008     2008-2020      5.0   \n",
              "2   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "3   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "4   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "\n",
              "                                     What it's about  \\\n",
              "0  When Walter White, a New Mexico chemistry teac...   \n",
              "1  When Walter White, a New Mexico chemistry teac...   \n",
              "2  Seven noble families fight for control of the ...   \n",
              "3  Seven noble families fight for control of the ...   \n",
              "4  Seven noble families fight for control of the ...   \n",
              "\n",
              "                                      Where to Watch  Rent or Buy Available  \\\n",
              "0  62 episodes (100%) are available to stream on ...                      1   \n",
              "1  62 episodes (100%) are available to stream on ...                      1   \n",
              "2  74 episodes (100%) are available to stream on ...                      1   \n",
              "3  74 episodes (100%) are available to stream on ...                      1   \n",
              "4  74 episodes (100%) are available to stream on ...                      1   \n",
              "\n",
              "   Exclusive Service  Has Tag  \n",
              "0                  0        1  \n",
              "1                  0        1  \n",
              "2                  0        1  \n",
              "3                  0        1  \n",
              "4                  0        1  "
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              "      <th>Title</th>\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8a8df8d3-5373-479c-bac5-9e4b4d13fb1e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_whole"
            }
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_whole.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "19iKz2zggvCA",
        "outputId": "28be64c5-e5a4-4463-9903-4f19fc649baa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Title                         0\n",
              "URL                           0\n",
              "Type                          0\n",
              "Service                       0\n",
              "Genre                         0\n",
              "Tag                           0\n",
              "IMDB                       4522\n",
              "ReelGood                    930\n",
              "AgeRating                121637\n",
              "Rated                    190270\n",
              "Released Year                 0\n",
              "Duration Year            264763\n",
              "Seasons                  264787\n",
              "What it's about          139788\n",
              "Where to Watch           153673\n",
              "Rent or Buy Available         0\n",
              "Exclusive Service             0\n",
              "Has Tag                       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Focus on TV only + top 20 streaming platform"
      ],
      "metadata": {
        "id": "xuiFa6XelSWC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = df_whole[df_whole['Type'] == 'tv']\n",
        "df = df.drop_duplicates(subset=df_whole.columns.difference(\n",
        "                        ['URL', 'Tag', 'IMDB', 'ReelGood' , 'AgeRating', 'Rated',\n",
        "                         'Released Year', 'Duration Year', 'Seasons', 'What it\\'s about',\n",
        "                         'Where to Watch', 'Rent or Buy Available', 'Exclusive Service',\n",
        "                         'Has Tag']))"
      ],
      "metadata": {
        "id": "ql_MCzWIhCtM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cDzFUm7fjwCs",
        "outputId": "276293f2-1075-426f-9f87-8b8267596cb5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50485, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# We observed there are null values in the data but it is not problematic at this point so we are not eliminating them\n",
        "df_whole.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jjszTgm3rWix",
        "outputId": "ca498346-e87b-44ca-d8d0-9395d2e41d3e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Title                         0\n",
              "URL                           0\n",
              "Type                          0\n",
              "Service                       0\n",
              "Genre                         0\n",
              "Tag                           0\n",
              "IMDB                       4522\n",
              "ReelGood                    930\n",
              "AgeRating                121637\n",
              "Rated                    190270\n",
              "Released Year                 0\n",
              "Duration Year            264763\n",
              "Seasons                  264787\n",
              "What it's about          139788\n",
              "Where to Watch           153673\n",
              "Rent or Buy Available         0\n",
              "Exclusive Service             0\n",
              "Has Tag                       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.groupby(['Service']).size().sort_values(ascending=False).head(25)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b5LitIIDD5je",
        "outputId": "15cda14e-4c89-428b-d7e6-e02a3921ffc1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Service\n",
              "free                          7581\n",
              "netflix                       4225\n",
              "hulu_plus                     3579\n",
              "Rent or Buy                   3213\n",
              "amazon_prime                  2901\n",
              "philo                         2792\n",
              "fubo_tv                       2522\n",
              "tubi_tv                       2428\n",
              "hoopla                        1738\n",
              "crunchyroll_free              1690\n",
              "funimation                    1610\n",
              "hbo_max                        974\n",
              "plutotv                        956\n",
              "imdb_tv                        718\n",
              "disney_plus                    595\n",
              "cbs_all_access                 570\n",
              "investigation_discovery_go     569\n",
              "britbox                        488\n",
              "peacock_free                   477\n",
              "acorntv                        443\n",
              "plex_free                      442\n",
              "hbo                            437\n",
              "vudu_free                      371\n",
              "starz                          371\n",
              "crunchyroll_premium            322\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We found there are \"free\" and \"Rent or Buy\" which aren't our target customers (streaming platform). However, it might be useful for question 2 (minor/potential market)."
      ],
      "metadata": {
        "id": "6eS_1tsJavwg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['Service'] == 'Rent or Buy']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "xhNixz6Bx9Ap",
        "outputId": "7f682d4d-ba7a-4ea9-ac75-b3f7caf2771e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                       Title  \\\n",
              "1010                                  Utopia   \n",
              "1011                                  Utopia   \n",
              "1012                                  Utopia   \n",
              "1251                                  Castle   \n",
              "1252                                  Castle   \n",
              "...                                      ...   \n",
              "50658  Kid President: Declaration of Awesome   \n",
              "50661                          Armed & Ready   \n",
              "50662                          Armed & Ready   \n",
              "50663                          Armed & Ready   \n",
              "50675                          Intersections   \n",
              "\n",
              "                                                   URL Type      Service  \\\n",
              "1010                                 /show/utopia-2013   tv  Rent or Buy   \n",
              "1011                                 /show/utopia-2013   tv  Rent or Buy   \n",
              "1012                                 /show/utopia-2013   tv  Rent or Buy   \n",
              "1251                                 /show/castle-2009   tv  Rent or Buy   \n",
              "1252                                 /show/castle-2009   tv  Rent or Buy   \n",
              "...                                                ...  ...          ...   \n",
              "50658  /show/kid-president-declaration-of-awesome-2014   tv  Rent or Buy   \n",
              "50661                           /show/armed-ready-2013   tv  Rent or Buy   \n",
              "50662                           /show/armed-ready-2013   tv  Rent or Buy   \n",
              "50663                           /show/armed-ready-2013   tv  Rent or Buy   \n",
              "50675                         /show/intersections-2010   tv  Rent or Buy   \n",
              "\n",
              "             Genre                               Tag  IMDB  ReelGood  \\\n",
              "1010       Reality             ['Doctor', 'Science']   8.4      79.0   \n",
              "1011         Drama             ['Doctor', 'Science']   8.4      79.0   \n",
              "1012       Mystery             ['Doctor', 'Science']   8.4      79.0   \n",
              "1251         Crime  ['Disney', 'Police', 'New York']   8.1      83.0   \n",
              "1252         Drama  ['Disney', 'Police', 'New York']   8.1      83.0   \n",
              "...            ...                               ...   ...       ...   \n",
              "50658  Documentary                             [nan]   NaN       NaN   \n",
              "50661      Reality                             [nan]   NaN       NaN   \n",
              "50662       Travel                             [nan]   NaN       NaN   \n",
              "50663  Documentary                             [nan]   NaN       NaN   \n",
              "50675        Sport                             [nan]   NaN       NaN   \n",
              "\n",
              "      AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "1010        18+  TV-MA           2013     2013-2020      2.0   \n",
              "1011        18+  TV-MA           2013     2013-2020      2.0   \n",
              "1012        18+  TV-MA           2013     2013-2020      2.0   \n",
              "1251        16+  TV-14           2009     2009-2020      8.0   \n",
              "1252        16+  TV-14           2009     2009-2020      8.0   \n",
              "...         ...    ...            ...           ...      ...   \n",
              "50658       NaN    NaN           2014           NaN      NaN   \n",
              "50661       NaN    NaN           2013           NaN      NaN   \n",
              "50662       NaN    NaN           2013           NaN      NaN   \n",
              "50663       NaN    NaN           2013           NaN      NaN   \n",
              "50675       NaN    NaN           2010           NaN      NaN   \n",
              "\n",
              "                                         What it's about  \\\n",
              "1010   The  Utopia Experiments is a legendary graphic...   \n",
              "1011   The  Utopia Experiments is a legendary graphic...   \n",
              "1012   The  Utopia Experiments is a legendary graphic...   \n",
              "1251   After a serial killer imitates the plots of hi...   \n",
              "1252   After a serial killer imitates the plots of hi...   \n",
              "...                                                  ...   \n",
              "50658                                                NaN   \n",
              "50661                                                NaN   \n",
              "50662                                                NaN   \n",
              "50663                                                NaN   \n",
              "50675                                                NaN   \n",
              "\n",
              "                                          Where to Watch  \\\n",
              "1010   12 episodes (67%) are available to rent or buy...   \n",
              "1011   12 episodes (67%) are available to rent or buy...   \n",
              "1012   12 episodes (67%) are available to rent or buy...   \n",
              "1251                                                 NaN   \n",
              "1252                                                 NaN   \n",
              "...                                                  ...   \n",
              "50658                                                NaN   \n",
              "50661                                                NaN   \n",
              "50662                                                NaN   \n",
              "50663                                                NaN   \n",
              "50675                                                NaN   \n",
              "\n",
              "       Rent or Buy Available  Exclusive Service  Has Tag  \n",
              "1010                       1                  1        1  \n",
              "1011                       1                  1        1  \n",
              "1012                       1                  1        1  \n",
              "1251                       1                  1        1  \n",
              "1252                       1                  1        1  \n",
              "...                      ...                ...      ...  \n",
              "50658                      1                  1        0  \n",
              "50661                      1                  1        0  \n",
              "50662                      1                  1        0  \n",
              "50663                      1                  1        0  \n",
              "50675                      1                  1        0  \n",
              "\n",
              "[3213 rows x 18 columns]"
            ],
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              "\n",
              "  <div id=\"df-2d848853-db9d-4826-987c-d3553a6a3e76\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Title</th>\n",
              "      <th>URL</th>\n",
              "      <th>Type</th>\n",
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              "      <th>Has Tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1010</th>\n",
              "      <td>Utopia</td>\n",
              "      <td>/show/utopia-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
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              "      <td>8.4</td>\n",
              "      <td>79.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>2.0</td>\n",
              "      <td>The  Utopia Experiments is a legendary graphic...</td>\n",
              "      <td>12 episodes (67%) are available to rent or buy...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1011</th>\n",
              "      <td>Utopia</td>\n",
              "      <td>/show/utopia-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Drama</td>\n",
              "      <td>['Doctor', 'Science']</td>\n",
              "      <td>8.4</td>\n",
              "      <td>79.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>2.0</td>\n",
              "      <td>The  Utopia Experiments is a legendary graphic...</td>\n",
              "      <td>12 episodes (67%) are available to rent or buy...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1012</th>\n",
              "      <td>Utopia</td>\n",
              "      <td>/show/utopia-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Mystery</td>\n",
              "      <td>['Doctor', 'Science']</td>\n",
              "      <td>8.4</td>\n",
              "      <td>79.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>2.0</td>\n",
              "      <td>The  Utopia Experiments is a legendary graphic...</td>\n",
              "      <td>12 episodes (67%) are available to rent or buy...</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1251</th>\n",
              "      <td>Castle</td>\n",
              "      <td>/show/castle-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Crime</td>\n",
              "      <td>['Disney', 'Police', 'New York']</td>\n",
              "      <td>8.1</td>\n",
              "      <td>83.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>After a serial killer imitates the plots of hi...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1252</th>\n",
              "      <td>Castle</td>\n",
              "      <td>/show/castle-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Drama</td>\n",
              "      <td>['Disney', 'Police', 'New York']</td>\n",
              "      <td>8.1</td>\n",
              "      <td>83.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
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              "      <td>After a serial killer imitates the plots of hi...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>50658</th>\n",
              "      <td>Kid President: Declaration of Awesome</td>\n",
              "      <td>/show/kid-president-declaration-of-awesome-2014</td>\n",
              "      <td>tv</td>\n",
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              "      <td>[nan]</td>\n",
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              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>50661</th>\n",
              "      <td>Armed &amp; Ready</td>\n",
              "      <td>/show/armed-ready-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Reality</td>\n",
              "      <td>[nan]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50662</th>\n",
              "      <td>Armed &amp; Ready</td>\n",
              "      <td>/show/armed-ready-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Travel</td>\n",
              "      <td>[nan]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50663</th>\n",
              "      <td>Armed &amp; Ready</td>\n",
              "      <td>/show/armed-ready-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Documentary</td>\n",
              "      <td>[nan]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2013</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50675</th>\n",
              "      <td>Intersections</td>\n",
              "      <td>/show/intersections-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>Rent or Buy</td>\n",
              "      <td>Sport</td>\n",
              "      <td>[nan]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3213 rows × 18 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2d848853-db9d-4826-987c-d3553a6a3e76')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-2d848853-db9d-4826-987c-d3553a6a3e76 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-2d848853-db9d-4826-987c-d3553a6a3e76');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
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              "\n",
              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-171dae54-8b20-45a9-ac1b-8e6adae547c2')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-171dae54-8b20-45a9-ac1b-8e6adae547c2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df['Service'] == 'Rent or Buy']\",\n  \"rows\": 3213,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1541,\n        \"samples\": [\n          \"The Comedy Get Down\",\n          \"Jamie Kennedy's Blowin' Up\",\n          \"Xtreme 4x4\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1544,\n        \"samples\": [\n          \"/show/the-comedy-get-down-2017\",\n          \"/show/beauty-and-the-geek-2005\",\n          \"/show/the-fashion-hero-2017\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Rent or Buy\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 27,\n        \"samples\": [\n          \"Stand-up & Talk\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 311,\n        \"samples\": [\n          \"['War', 'Teacher', 'World War II']\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2124662298560183,\n        \"min\": 1.7,\n        \"max\": 9.4,\n        \"num_unique_values\": 77,\n        \"samples\": [\n          7.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 13.399090903074578,\n        \"min\": 10.0,\n        \"max\": 83.0,\n        \"num_unique_values\": 69,\n        \"samples\": [\n          55.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"16+\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"TV-14\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 12,\n        \"min\": 1949,\n        \"max\": 2020,\n        \"num_unique_values\": 66,\n        \"samples\": [\n          1981\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 58,\n        \"samples\": [\n          \"2013-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3.5329579487782135,\n        \"min\": 1.0,\n        \"max\": 46.0,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          2.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 626,\n        \"samples\": [\n          \"NYC 22 follows six diverse NYPD rookies as they patrol the gritty streets of upper Manhattan. With unique backgrounds, personalities and reasons for being on the force, the new cops will make their share of rookie mistakes while they figure out how to relate to their boss, each other and the people they swore to protect\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 376,\n        \"samples\": [\n          \"10 episodes (63%) are available to rent or buy from $1.99 on 1 service (Prime Video).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Top 20 Platform"
      ],
      "metadata": {
        "id": "JpUf2x-Pl527"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "## Top 20 platform\n",
        "\n",
        "top_20 = ['netflix', 'hulu_plus', 'amazon_prime', 'philo', 'fubo_tv', 'tubi_tv', 'hoopla',\n",
        " 'crunchyroll_free', 'funimation', 'hbo_max', 'plutotv', 'imdb_tv', 'disney_plus',\n",
        " 'cbs_all_access', 'investigation_discovery_go', 'britbox', 'peacock_free', 'acorntv',\n",
        " 'plex_free', 'hbo']"
      ],
      "metadata": {
        "id": "QByM4sXF0p34"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top_20_platform_df = df[df['Service'].isin(top_20)]"
      ],
      "metadata": {
        "id": "kCTOTQ4xxgB3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top_20_platform_df['Genre'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ffl6U6uhdnyH",
        "outputId": "d33b727f-6903-418d-cbf9-18dd3be8c25c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Genre\n",
              "Drama                 3921\n",
              "Comedy                3414\n",
              "Action & Adventure    3053\n",
              "Documentary           3030\n",
              "Animation             2980\n",
              "Reality               2521\n",
              "Crime                 1973\n",
              "Family                1521\n",
              "Anime                 1137\n",
              "Children               886\n",
              "Mystery                767\n",
              "Fantasy                698\n",
              "Romance                649\n",
              "Science-Fiction        593\n",
              "Thriller               420\n",
              "History                417\n",
              "Food                   377\n",
              "Game Show              363\n",
              "Home & Garden          334\n",
              "Horror                 272\n",
              "Travel                 218\n",
              "Sport                  211\n",
              "Biography              174\n",
              "LGBTQ                   86\n",
              "Musical                 86\n",
              "Stand-up & Talk         38\n",
              "Cult                    15\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_20_platform_df.groupby(['Service']).mean(['IMDB'])[['IMDB', 'ReelGood']].sort_values(['IMDB'], ascending = False)"
      ],
      "metadata": {
        "id": "ER3ztkxIjR9d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 708
        },
        "outputId": "6b6f0e4d-1ad7-4e14-fa93-a505afc68acc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                IMDB   ReelGood\n",
              "Service                                        \n",
              "hbo                         7.523023  62.505747\n",
              "britbox                     7.519462  56.415984\n",
              "hbo_max                     7.491060  62.793422\n",
              "acorntv                     7.476136  53.902935\n",
              "investigation_discovery_go  7.275285  38.640708\n",
              "imdb_tv                     7.226294  57.211699\n",
              "netflix                     7.147528  57.678977\n",
              "hulu_plus                   7.138237  59.622030\n",
              "amazon_prime                7.136324  50.882026\n",
              "hoopla                      7.079651  52.240623\n",
              "funimation                  7.005247  51.295652\n",
              "crunchyroll_free            6.996348  52.106043\n",
              "plex_free                   6.982766  53.690045\n",
              "plutotv                     6.969829  49.640838\n",
              "peacock_free                6.962955  55.285115\n",
              "cbs_all_access              6.955950  60.687719\n",
              "tubi_tv                     6.928885  49.536142\n",
              "fubo_tv                     6.866804  51.413052\n",
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              "      <td>7.005247</td>\n",
              "      <td>51.295652</td>\n",
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              "      <td>52.106043</td>\n",
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              "      <td>60.687719</td>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"top_20_platform_df\",\n  \"rows\": 20,\n  \"fields\": [\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"hbo\",\n          \"fubo_tv\",\n          \"cbs_all_access\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.22998928668992588,\n        \"min\": 6.820658436213992,\n        \"max\": 7.523023255813953,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          7.523023255813953,\n          6.866804293971924,\n          6.95595026642984\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6.170287298419841,\n        \"min\": 38.640707964601766,\n        \"max\": 62.793422404933196,\n        \"num_unique_values\": 20,\n        \"samples\": [\n          62.50574712643678,\n          51.413052128929564,\n          60.68771929824561\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_20_platform_df.groupby(['Genre']).mean(['IMDB'])[['IMDB', 'ReelGood']].sort_values(['IMDB'], ascending = False)"
      ],
      "metadata": {
        "id": "RYhWHvmnjgwg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 927
        },
        "outputId": "c6a5ede4-51fc-4920-9d0b-cfca513a8136"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        IMDB   ReelGood\n",
              "Genre                                  \n",
              "LGBTQ               7.618605  67.767442\n",
              "Biography           7.550000  51.522989\n",
              "Cult                7.546667  64.866667\n",
              "History             7.527317  50.249395\n",
              "Crime               7.369465  54.236936\n",
              "Sport               7.362312  51.937198\n",
              "Thriller            7.311031  61.261905\n",
              "Drama               7.298701  58.519020\n",
              "Anime               7.285333  58.152155\n",
              "Travel              7.275385  43.688679\n",
              "Mystery             7.269814  58.081152\n",
              "Documentary         7.215004  43.580168\n",
              "Musical             7.186747  57.872093\n",
              "Stand-up & Talk     7.119444  53.947368\n",
              "Action & Adventure  7.083638  56.514576\n",
              "Science-Fiction     7.083103  59.045531\n",
              "Comedy              7.051770  56.142731\n",
              "Food                7.013554  42.676630\n",
              "Fantasy             7.004221  58.259312\n",
              "Romance             6.956735  56.675926\n",
              "Animation           6.954158  52.594222\n",
              "Horror              6.935606  57.680147\n",
              "Home & Garden       6.914085  40.287975\n",
              "Family              6.771247  51.020435\n",
              "Children            6.659397  49.923251\n",
              "Reality             6.524968  44.485347\n",
              "Game Show           6.524930  51.283747"
            ],
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              "      <td>43.580168</td>\n",
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              "      <th>Musical</th>\n",
              "      <td>7.186747</td>\n",
              "      <td>57.872093</td>\n",
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              "      <td>7.083638</td>\n",
              "      <td>56.514576</td>\n",
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              "      <th>Science-Fiction</th>\n",
              "      <td>7.083103</td>\n",
              "      <td>59.045531</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Comedy</th>\n",
              "      <td>7.051770</td>\n",
              "      <td>56.142731</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Food</th>\n",
              "      <td>7.013554</td>\n",
              "      <td>42.676630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fantasy</th>\n",
              "      <td>7.004221</td>\n",
              "      <td>58.259312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Romance</th>\n",
              "      <td>6.956735</td>\n",
              "      <td>56.675926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Animation</th>\n",
              "      <td>6.954158</td>\n",
              "      <td>52.594222</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Horror</th>\n",
              "      <td>6.935606</td>\n",
              "      <td>57.680147</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Home &amp; Garden</th>\n",
              "      <td>6.914085</td>\n",
              "      <td>40.287975</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Family</th>\n",
              "      <td>6.771247</td>\n",
              "      <td>51.020435</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Children</th>\n",
              "      <td>6.659397</td>\n",
              "      <td>49.923251</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Reality</th>\n",
              "      <td>6.524968</td>\n",
              "      <td>44.485347</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Game Show</th>\n",
              "      <td>6.524930</td>\n",
              "      <td>51.283747</td>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"top_20_platform_df\",\n  \"rows\": 27,\n  \"fields\": [\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 27,\n        \"samples\": [\n          \"Anime\",\n          \"Stand-up & Talk\",\n          \"Travel\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.2949391759306769,\n        \"min\": 6.524929971988795,\n        \"max\": 7.618604651162792,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          7.285333333333333,\n          7.1194444444444445,\n          7.275384615384616\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6.750235376441468,\n        \"min\": 40.287974683544306,\n        \"max\": 67.76744186046511,\n        \"num_unique_values\": 27,\n        \"samples\": [\n          58.152154793315745,\n          53.94736842105263,\n          43.68867924528302\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Question 3 (Successful TV shows)"
      ],
      "metadata": {
        "id": "oAj7tV5ioG2S"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 397
        },
        "id": "utAHTpB9pSTd",
        "outputId": "d25f88b0-ac81-47ba-bd45-1e93bb69eba5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Title                         URL Type  Service  \\\n",
              "0     Breaking Bad     /show/breaking-bad-2008   tv  netflix   \n",
              "1     Breaking Bad     /show/breaking-bad-2008   tv  netflix   \n",
              "2  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "3  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "4  Game of Thrones  /show/game-of-thrones-2011   tv  hbo_max   \n",
              "\n",
              "                Genre                                                Tag  \\\n",
              "0               Crime  ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...   \n",
              "1               Drama  ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...   \n",
              "2               Drama  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "3  Action & Adventure  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "4             Fantasy  ['War', 'Royalty', 'Political', 'Based on Book...   \n",
              "\n",
              "   IMDB  ReelGood AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "0   9.5     100.0       18+  TV-MA           2008     2008-2020      5.0   \n",
              "1   9.5     100.0       18+  TV-MA           2008     2008-2020      5.0   \n",
              "2   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "3   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "4   9.3      98.0       18+  TV-MA           2011     2011-2020      8.0   \n",
              "\n",
              "                                     What it's about  \\\n",
              "0  When Walter White, a New Mexico chemistry teac...   \n",
              "1  When Walter White, a New Mexico chemistry teac...   \n",
              "2  Seven noble families fight for control of the ...   \n",
              "3  Seven noble families fight for control of the ...   \n",
              "4  Seven noble families fight for control of the ...   \n",
              "\n",
              "                                      Where to Watch  Rent or Buy Available  \\\n",
              "0  62 episodes (100%) are available to stream on ...                      1   \n",
              "1  62 episodes (100%) are available to stream on ...                      1   \n",
              "2  74 episodes (100%) are available to stream on ...                      1   \n",
              "3  74 episodes (100%) are available to stream on ...                      1   \n",
              "4  74 episodes (100%) are available to stream on ...                      1   \n",
              "\n",
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              "0                  0        1  \n",
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              "      <th>Title</th>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d9fe264c-b8c3-47c9-810b-30f817d00ae7')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d9fe264c-b8c3-47c9-810b-30f817d00ae7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-d9fe264c-b8c3-47c9-810b-30f817d00ae7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-0ad5870f-921a-4c2a-bc71-05043bcb59ea\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0ad5870f-921a-4c2a-bc71-05043bcb59ea')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-0ad5870f-921a-4c2a-bc71-05043bcb59ea button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 50485,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 10771,\n        \"samples\": [\n          \"Hollywood Weapons\",\n          \"North and South\",\n          \"Mrs. America\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 10972,\n        \"samples\": [\n          \"/show/just-another-immigrant-2018\",\n          \"/show/long-haired-businessmen-2013\",\n          \"/show/burger-land-2012\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 175,\n        \"samples\": [\n          \"docu\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 27,\n        \"samples\": [\n          \"Thriller\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2104,\n        \"samples\": [\n          \"['Religion', 'Video Games', 'Suspense']\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.110241510260518,\n        \"min\": 1.2,\n        \"max\": 9.7,\n        \"num_unique_values\": 83,\n        \"samples\": [\n          6.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14.820446243803211,\n        \"min\": 10.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 86,\n        \"samples\": [\n          26.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"16+\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"TV-14\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 11,\n        \"min\": 1922,\n        \"max\": 2020,\n        \"num_unique_values\": 80,\n        \"samples\": [\n          1959\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 73,\n        \"samples\": [\n          \"2014-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.617165378719814,\n        \"min\": 1.0,\n        \"max\": 86.0,\n        \"num_unique_values\": 46,\n        \"samples\": [\n          42.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4244,\n        \"samples\": [\n          \"Adaptation of the novels written by Georges Simenon featuring his fictional French police commissioner Jules Maigret\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3024,\n        \"samples\": [\n          \"10 episodes (100%) are available to watch free online (PlutoTV). 10 episodes (100%) are available to rent or buy from $1.99 on 2 services (Prime Video & Vudu).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Tag']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "leJvMmlNTZy8",
        "outputId": "d6b74f08-4b4f-4843-c87a-e6c6c0235c10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...\n",
              "1        ['Drug', 'Doctor', 'Teacher', 'Gangster', 'Hig...\n",
              "2        ['War', 'Royalty', 'Political', 'Based on Book...\n",
              "3        ['War', 'Royalty', 'Political', 'Based on Book...\n",
              "4        ['War', 'Royalty', 'Political', 'Based on Book...\n",
              "                               ...                        \n",
              "50671                                      [nan, nan, nan]\n",
              "50672                                      [nan, nan, nan]\n",
              "50673                                      [nan, nan, nan]\n",
              "50674                                      [nan, nan, nan]\n",
              "50675                                                [nan]\n",
              "Name: Tag, Length: 50485, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5rGDDVuyofeF",
        "outputId": "9cf98550-0860-419d-d1c2-af65e9f022e1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Title                     object\n",
              "URL                       object\n",
              "Type                      object\n",
              "Service                   object\n",
              "Genre                     object\n",
              "Tag                       object\n",
              "IMDB                     float64\n",
              "ReelGood                 float64\n",
              "AgeRating                 object\n",
              "Rated                     object\n",
              "Released Year              int64\n",
              "Duration Year             object\n",
              "Seasons                  float64\n",
              "What it's about           object\n",
              "Where to Watch            object\n",
              "Rent or Buy Available      int64\n",
              "Exclusive Service          int64\n",
              "Has Tag                    int64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_whole.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sMhw112NpqnT",
        "outputId": "be5b2e7f-d1db-4965-f416-ade99cbaa503"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Title                         0\n",
              "URL                           0\n",
              "Type                          0\n",
              "Service                       0\n",
              "Genre                         0\n",
              "Tag                           0\n",
              "IMDB                       4522\n",
              "ReelGood                    930\n",
              "AgeRating                121637\n",
              "Rated                    190270\n",
              "Released Year                 0\n",
              "Duration Year            264763\n",
              "Seasons                  264787\n",
              "What it's about          139788\n",
              "Where to Watch           153673\n",
              "Rent or Buy Available         0\n",
              "Exclusive Service             0\n",
              "Has Tag                       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question3_df = df.groupby('Title').agg({\n",
        "    'URL': 'first',\n",
        "    'Type': 'first',\n",
        "    'Service': lambda x: list(set(x)), # Check the TV show is available on which platforms\n",
        "    'Genre': lambda x: list(set(x)),\n",
        "    'Tag': 'first',\n",
        "    'IMDB': 'mean',  # Mean IMDB rating\n",
        "    'ReelGood': 'mean',  # Mean ReelGood rating\n",
        "    'AgeRating': 'first',\n",
        "    'Rated': 'first', # first IMDB rating\n",
        "    'Released Year': 'first',  # first released year\n",
        "    'Duration Year': 'first',  # first duration years\n",
        "    'Seasons': 'max',  # Maximum number of seasons\n",
        "    'What it\\'s about': 'first',\n",
        "    'Where to Watch': 'first',  # first 'Where to Watch' values\n",
        "    'Rent or Buy Available': 'first',  # first of 'Rent or Buy Available' values\n",
        "    'Exclusive Service': 'first',  # first non-null 'Exclusive Service' values\n",
        "    'Has Tag': 'first'  # first of 'Has Tag' values\n",
        "}).reset_index()"
      ],
      "metadata": {
        "id": "B-xjDwSJzGeZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import ast\n",
        "\n",
        "# Function to safely convert string representation of lists to actual lists\n",
        "def safe_literal_eval(x):\n",
        "    try:\n",
        "        return ast.literal_eval(x)\n",
        "    except (SyntaxError, ValueError):\n",
        "        return x\n",
        "\n",
        "# Convert string representation of lists to actual lists\n",
        "question3_df['Tag'] = question3_df['Tag'].apply(safe_literal_eval)\n",
        "\n",
        "# Define a function to remove duplicates from a list\n",
        "def remove_duplicates(lst):\n",
        "    if isinstance(lst, list):\n",
        "        return list(set(lst))\n",
        "    else:\n",
        "        return lst\n",
        "\n",
        "# Apply the function to remove duplicates from each list in the 'Tag' column\n",
        "question3_df['Tag'] = question3_df['Tag'].apply(remove_duplicates)"
      ],
      "metadata": {
        "id": "WQmJZC-NYShV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "question3_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pc7N-FeHDNJg",
        "outputId": "8fb71d36-c0c6-407a-b179-be309d8ed266"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(10771, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question3_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M_Q4WgFxD1UD",
        "outputId": "d5168e7f-6f33-4373-a1ce-f6cb22225333"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Title                       0\n",
              "URL                         0\n",
              "Type                        0\n",
              "Service                     0\n",
              "Genre                       0\n",
              "Tag                         0\n",
              "IMDB                      633\n",
              "ReelGood                  150\n",
              "AgeRating                3516\n",
              "Rated                    7319\n",
              "Released Year               0\n",
              "Duration Year            6592\n",
              "Seasons                  6594\n",
              "What it's about          6592\n",
              "Where to Watch           7102\n",
              "Rent or Buy Available       0\n",
              "Exclusive Service           0\n",
              "Has Tag                     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "## the null mostly is due to missing data\n",
        "question3_df[question3_df['Seasons'].isna()].head(5)"
      ],
      "metadata": {
        "id": "ovARgmfRDUXG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        },
        "outputId": "c0db5133-0f6f-49c8-c91d-535cd5242062"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Title                                   URL Type  \\\n",
              "0                  #BlackLove                  /show/blacklove-2015   tv   \n",
              "1           #MeToo, Now What?             /show/metoo-now-what-2018   tv   \n",
              "2  #RichKids of Beverly Hills  /show/richkids-of-beverly-hills-2014   tv   \n",
              "4                 #killerpost                 /show/killerpost-2016   tv   \n",
              "5               $100 Makeover               /show/100-makeover-2010   tv   \n",
              "\n",
              "                                  Service                      Genre  \\\n",
              "0  [fyi_tveverywhere, fyi, plutotv, free]  [Romance, Reality, Drama]   \n",
              "1       [pbs, free, amazon_prime, hoopla]              [Documentary]   \n",
              "2                               [fubo_tv]                  [Reality]   \n",
              "4                    [free, peacock_free]       [Documentary, Crime]   \n",
              "5                         [plutotv, free]                  [Reality]   \n",
              "\n",
              "                    Tag  IMDB  ReelGood AgeRating Rated  Released Year  \\\n",
              "0  [nan, nan, nan, nan]   6.1      37.0       16+  None           2015   \n",
              "1  [nan, nan, nan, nan]   6.8      27.0      None  None           2018   \n",
              "2                 [nan]   3.1      38.0       16+  None           2014   \n",
              "4            [nan, nan]   7.0      38.0        7+  None           2016   \n",
              "5            [nan, nan]   NaN      38.0      None  None           2010   \n",
              "\n",
              "  Duration Year  Seasons What it's about Where to Watch  \\\n",
              "0          None      NaN            None           None   \n",
              "1          None      NaN            None           None   \n",
              "2          None      NaN            None           None   \n",
              "4          None      NaN            None           None   \n",
              "5          None      NaN            None           None   \n",
              "\n",
              "   Rent or Buy Available  Exclusive Service  Has Tag  \n",
              "0                      1                  0        0  \n",
              "1                      1                  0        0  \n",
              "2                      1                  0        0  \n",
              "4                      1                  0        0  \n",
              "5                      0                  0        0  "
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              "      <th></th>\n",
              "      <th>Title</th>\n",
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              "      <th>Type</th>\n",
              "      <th>Service</th>\n",
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              "      <th>IMDB</th>\n",
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              "      <th>AgeRating</th>\n",
              "      <th>Rated</th>\n",
              "      <th>Released Year</th>\n",
              "      <th>Duration Year</th>\n",
              "      <th>Seasons</th>\n",
              "      <th>What it's about</th>\n",
              "      <th>Where to Watch</th>\n",
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              "      <th>Exclusive Service</th>\n",
              "      <th>Has Tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>#BlackLove</td>\n",
              "      <td>/show/blacklove-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[fyi_tveverywhere, fyi, plutotv, free]</td>\n",
              "      <td>[Romance, Reality, Drama]</td>\n",
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              "      <td>0</td>\n",
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              "      <th>1</th>\n",
              "      <td>#MeToo, Now What?</td>\n",
              "      <td>/show/metoo-now-what-2018</td>\n",
              "      <td>tv</td>\n",
              "      <td>[pbs, free, amazon_prime, hoopla]</td>\n",
              "      <td>[Documentary]</td>\n",
              "      <td>[nan, nan, nan, nan]</td>\n",
              "      <td>6.8</td>\n",
              "      <td>27.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>2018</td>\n",
              "      <td>None</td>\n",
              "      <td>NaN</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>#RichKids of Beverly Hills</td>\n",
              "      <td>/show/richkids-of-beverly-hills-2014</td>\n",
              "      <td>tv</td>\n",
              "      <td>[fubo_tv]</td>\n",
              "      <td>[Reality]</td>\n",
              "      <td>[nan]</td>\n",
              "      <td>3.1</td>\n",
              "      <td>38.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>None</td>\n",
              "      <td>2014</td>\n",
              "      <td>None</td>\n",
              "      <td>NaN</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>#killerpost</td>\n",
              "      <td>/show/killerpost-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, peacock_free]</td>\n",
              "      <td>[Documentary, Crime]</td>\n",
              "      <td>[nan, nan]</td>\n",
              "      <td>7.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>None</td>\n",
              "      <td>2016</td>\n",
              "      <td>None</td>\n",
              "      <td>NaN</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>$100 Makeover</td>\n",
              "      <td>/show/100-makeover-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[plutotv, free]</td>\n",
              "      <td>[Reality]</td>\n",
              "      <td>[nan, nan]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>38.0</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>2010</td>\n",
              "      <td>None</td>\n",
              "      <td>NaN</td>\n",
              "      <td>None</td>\n",
              "      <td>None</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a7675711-f011-4809-a270-715d3ffe07dd');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "Out of range float values are not JSON compliant: nan"
            }
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "question3_df.sort_values(by='IMDB', ascending=False, inplace=True)\n",
        "question3_df.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 901
        },
        "id": "Y2nV37bl2_7K",
        "outputId": "f3e3d37c-6e5e-462c-c4e2-d8669613805d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                      Title  \\\n",
              "1237                                  Bluey   \n",
              "5306                           Malgudi Days   \n",
              "8920  The Last Drive-in With Joe Bob Briggs   \n",
              "1336                           Breaking Bad   \n",
              "6575                        Planet Earth II   \n",
              "662                                   Arnie   \n",
              "1678                              Chernobyl   \n",
              "839                        Band of Brothers   \n",
              "8869                    The Joy of Painting   \n",
              "6574                           Planet Earth   \n",
              "\n",
              "                                                  URL Type  \\\n",
              "1237                                 /show/bluey-2018   tv   \n",
              "5306                          /show/malgudi-days-1987   tv   \n",
              "8920  /show/the-last-drivein-with-joe-bob-briggs-2018   tv   \n",
              "1336                          /show/breaking-bad-2008   tv   \n",
              "6575                       /show/planet-earth-ii-2016   tv   \n",
              "662                                  /show/arnie-2014   tv   \n",
              "1678                             /show/chernobyl-2019   tv   \n",
              "839                       /show/band-of-brothers-2001   tv   \n",
              "8869                   /show/the-joy-of-painting-1983   tv   \n",
              "6574                          /show/planet-earth-2006   tv   \n",
              "\n",
              "                                                Service  \\\n",
              "1237  [disneynow, free, fubo_tv, disneynow_free, dis...   \n",
              "5306                                     [amazon_prime]   \n",
              "8920                                          [shudder]   \n",
              "1336                                          [netflix]   \n",
              "6575                                  [bbc_america_tve]   \n",
              "662                                [free, peacock_free]   \n",
              "1678                                     [hbo_max, hbo]   \n",
              "839                                      [hbo_max, hbo]   \n",
              "8869                   [tubi_tv, free, imdb_tv, hoopla]   \n",
              "6574                                      [Rent or Buy]   \n",
              "\n",
              "                                  Genre  \\\n",
              "1237      [Children, Animation, Family]   \n",
              "5306  [Comedy, Children, Drama, Family]   \n",
              "8920            [Cult, Comedy, Fantasy]   \n",
              "1336                     [Drama, Crime]   \n",
              "6575                      [Documentary]   \n",
              "662     [Sport, Biography, Documentary]   \n",
              "1678                   [History, Drama]   \n",
              "839         [Action & Adventure, Drama]   \n",
              "8869     [Reality, Documentary, Family]   \n",
              "6574                      [Documentary]   \n",
              "\n",
              "                                                    Tag  IMDB  ReelGood  \\\n",
              "1237                                      [Video Games]   9.7      66.0   \n",
              "5306                                              [nan]   9.5      63.0   \n",
              "8920                                              [nan]   9.5      59.0   \n",
              "1336     [Gangster, High School, Doctor, Drug, Teacher]   9.5     100.0   \n",
              "6575                            [Space, Animal, Jungle]   9.5      86.0   \n",
              "662                                          [nan, nan]   9.4      43.0   \n",
              "1678        [Adaptation, Disaster, Based On True Story]   9.4      95.0   \n",
              "839   [Military, War, Based On True Story, Kidnappin...   9.4      92.0   \n",
              "8869                               [nan, nan, nan, nan]   9.4      64.0   \n",
              "6574                                            [Space]   9.4      77.0   \n",
              "\n",
              "     AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "1237       all   TV-G           2018     2018-2020      3.0   \n",
              "5306       all   None           1987          None      NaN   \n",
              "8920       18+   None           2018          None      NaN   \n",
              "1336       18+  TV-MA           2008     2008-2020      5.0   \n",
              "6575       all   TV-G           2016     2016-2020      1.0   \n",
              "662       None   None           2014          None      NaN   \n",
              "1678       18+  TV-MA           2019     2019-2020      1.0   \n",
              "839        18+  TV-MA           2001     2001-2020      1.0   \n",
              "8869       all   None           1983          None      NaN   \n",
              "6574       all   TV-G           2006     2006-2020      1.0   \n",
              "\n",
              "                                        What it's about  \\\n",
              "1237  Bluey is an inexhaustible six year-old Blue He...   \n",
              "5306                                               None   \n",
              "8920                                               None   \n",
              "1336  When Walter White, a New Mexico chemistry teac...   \n",
              "6575  David Attenborough presents a documentary seri...   \n",
              "662                                                None   \n",
              "1678  The true story of one of the worst man-made ca...   \n",
              "839   Drawn from interviews with survivors of Easy C...   \n",
              "8869                                               None   \n",
              "6574  David Attenborough celebrates the amazing vari...   \n",
              "\n",
              "                                         Where to Watch  \\\n",
              "1237  6 episodes (7%) are available to watch free on...   \n",
              "5306                                               None   \n",
              "8920                                               None   \n",
              "1336  62 episodes (100%) are available to stream on ...   \n",
              "6575  6 episodes (86%) are available to stream on a ...   \n",
              "662                                                None   \n",
              "1678  5 episodes (100%) are available to stream on a...   \n",
              "839   10 episodes (100%) are available to stream on ...   \n",
              "8869                                               None   \n",
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              "\n",
              "      Rent or Buy Available  Exclusive Service  Has Tag  \n",
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              "662                       0                  0        0  \n",
              "1678                      1                  0        1  \n",
              "839                       1                  0        1  \n",
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              "type": "dataframe",
              "variable_name": "question3_df",
              "summary": "{\n  \"name\": \"question3_df\",\n  \"rows\": 10771,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10771,\n        \"samples\": [\n          \"Primeval: New World\",\n          \"Voyagers\",\n          \"The Runner-Up\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10771,\n        \"samples\": [\n          \"/show/primeval-new-world-2012\",\n          \"/show/voyagers-1982\",\n          \"/show/the-runner-up-2015\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1479196630116908,\n        \"min\": 1.2,\n        \"max\": 9.7,\n        \"num_unique_values\": 254,\n        \"samples\": [\n          5.900000000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15.425175619451345,\n        \"min\": 10.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 222,\n        \"samples\": [\n          54.333333333333336\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"18+\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"TV-MA\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 10,\n        \"min\": 1922,\n        \"max\": 2020,\n        \"num_unique_values\": 80,\n        \"samples\": [\n          2003\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 73,\n        \"samples\": [\n          \"2001-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.956376574746281,\n        \"min\": 1.0,\n        \"max\": 86.0,\n        \"num_unique_values\": 46,\n        \"samples\": [\n          28.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4172,\n        \"samples\": [\n          \"Comedy series about three young women living in Leeds who've graduated, had a year out, and are now struggling to find a job they're passionate about, a place to live that is half decent and a boyfriend they actually like. A sitcom about making terrible decisions, but having a brilliant time doing it. The show focuses on Meg, her eccentric cousin Bunny and their friend Laura as they discover that life might just be a bit tougher than they had imagined. From demeaning Promotions jobs complete with mad outfits to pursuing the men of their dreams - yet dating the men of their nightmares - the girls face '#FML-worthy' disasters in both their work and personal lives\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2983,\n        \"samples\": [\n          \"25 episodes (96%) are available to stream on a popular subscription service (Disney+). 26 episodes (100%) are available to rent or buy from $1.99 on 4 services (iTunes, Google Play & 2 others).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "top_20 = ['netflix', 'hulu_plus', 'amazon_prime', 'philo', 'fubo_tv', 'tubi_tv', 'hoopla',\n",
        " 'crunchyroll_free', 'funimation', 'hbo_max', 'plutotv', 'imdb_tv', 'disney_plus',\n",
        " 'cbs_all_access', 'investigation_discovery_go', 'britbox', 'peacock_free', 'acorntv',\n",
        " 'plex_free', 'hbo']"
      ],
      "metadata": {
        "id": "0UTXJhnn7Rlv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Big_5 = ['netflix', 'hulu_plus', 'amazon_prime', 'philo', 'fubo_tv']"
      ],
      "metadata": {
        "id": "9-J_G99S7TD-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Big_3 = ['netflix', 'hulu_plus', 'amazon_prime']"
      ],
      "metadata": {
        "id": "pEryhfJNGgoi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "test_filtered = question3_df[\n",
        "    (\n",
        "        (\n",
        "            ((question3_df['IMDB'] >= 9.0) |\n",
        "            (question3_df['ReelGood'] >= 85))\n",
        "            #  &\n",
        "            #  (question3_df['Service'].apply(lambda x: any(platform in x for platform in top_20)))\n",
        "        )  |\n",
        "        (question3_df['Seasons'] > 10.0)\n",
        "    )\n",
        "]\n",
        "test_filtered"
      ],
      "metadata": {
        "id": "qjW4P17DEmqD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "filtered_question3_df = question3_df[\n",
        "        (\n",
        "            ((question3_df['Exclusive Service'] == 1) | (question3_df['Service'].apply(len) == 1) | (question3_df['Service'].apply(len) >= 5)) &\n",
        "            (question3_df['Service'].apply(lambda x: any(platform in x for platform in Big_3))) &\n",
        "            ((question3_df['IMDB'] >= 9.0) | (question3_df['ReelGood'] >= 85)) &\n",
        "            (question3_df['Seasons'] >= 3.0)\n",
        "         )]\n",
        "filtered_question3_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "L5iQIb0QHvTz",
        "outputId": "70ca78b7-9b91-4c2f-8409-08d6941439dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                   Title  \\\n",
              "1336                        Breaking Bad   \n",
              "1920                              Cosmos   \n",
              "3969                       Horsepower TV   \n",
              "7003                      Rick and Morty   \n",
              "7483                            Sherlock   \n",
              "3515                       Gravity Falls   \n",
              "709                      Attack on Titan   \n",
              "4361   It's Always Sunny in Philadelphia   \n",
              "9526                       The West Wing   \n",
              "2128                                Dark   \n",
              "6475                      Peaky Blinders   \n",
              "6032                              Narcos   \n",
              "1156                        Black Mirror   \n",
              "7914                     Stranger Things   \n",
              "9619                          This Is Us   \n",
              "8519                           The Crown   \n",
              "1241                     BoJack Horseman   \n",
              "4002                               House   \n",
              "9007           The Marvelous Mrs. Maisel   \n",
              "7699                          South Park   \n",
              "9342                        The Simpsons   \n",
              "6448                Parks and Recreation   \n",
              "2339                              Dexter   \n",
              "5412                  Marvel's Daredevil   \n",
              "9576                         The X-Files   \n",
              "4556                           Justified   \n",
              "275                       Adventure Time   \n",
              "3663                            Hannibal   \n",
              "5782                           Mr. Robot   \n",
              "8626                         The Expanse   \n",
              "8763                 The Handmaid's Tale   \n",
              "10366          What We Do in the Shadows   \n",
              "5900                    My Hero Academia   \n",
              "8923                    The Last Kingdom   \n",
              "1377                         Broadchurch   \n",
              "1389                  Brooklyn Nine-Nine   \n",
              "8295                       The Americans   \n",
              "8018                        Supernatural   \n",
              "8944                 The Legend of Korra   \n",
              "473                 American Crime Story   \n",
              "5682                         Money Heist   \n",
              "6388                               Ozark   \n",
              "6686                        Prison Break   \n",
              "64                                    24   \n",
              "4028               How I Met Your Mother   \n",
              "7425                       Sex Education   \n",
              "4675                         Killing Eve   \n",
              "7401                              Sense8   \n",
              "4916                              Legion   \n",
              "1730                               Chuck   \n",
              "8638                            The Fall   \n",
              "10406                       White Collar   \n",
              "9508                    The Walking Dead   \n",
              "5204                             Lucifer   \n",
              "6320             Orange Is the New Black   \n",
              "5418              Marvel's Jessica Jones   \n",
              "5408     Marvel's Agents of S.H.I.E.L.D.   \n",
              "\n",
              "                                               URL Type  \\\n",
              "1336                       /show/breaking-bad-2008   tv   \n",
              "1920         /show/cosmos-a-spacetime-odyssey-2014   tv   \n",
              "3969                         /show/horsepower-2006   tv   \n",
              "7003                     /show/rick-and-morty-2013   tv   \n",
              "7483                           /show/sherlock-2010   tv   \n",
              "3515                      /show/gravity-falls-2012   tv   \n",
              "709                     /show/attack-on-titan-2013   tv   \n",
              "4361   /show/its-always-sunny-in-philadelphia-2005   tv   \n",
              "9526                      /show/the-west-wing-1999   tv   \n",
              "2128                               /show/dark-2017   tv   \n",
              "6475                     /show/peaky-blinders-2013   tv   \n",
              "6032                             /show/narcos-2015   tv   \n",
              "1156                       /show/black-mirror-2011   tv   \n",
              "7914                    /show/stranger-things-2016   tv   \n",
              "9619                         /show/this-is-us-2016   tv   \n",
              "8519                          /show/the-crown-2016   tv   \n",
              "1241                    /show/bojack-horseman-2014   tv   \n",
              "4002                              /show/house-2004   tv   \n",
              "9007           /show/the-marvelous-mrs-maisel-2017   tv   \n",
              "7699                         /show/south-park-1997   tv   \n",
              "9342                       /show/the-simpsons-1989   tv   \n",
              "6448               /show/parks-and-recreation-2009   tv   \n",
              "2339                             /show/dexter-2006   tv   \n",
              "5412                  /show/marvels-daredevil-2015   tv   \n",
              "9576                        /show/the-x-files-1993   tv   \n",
              "4556                          /show/justified-2010   tv   \n",
              "275                      /show/adventure-time-2010   tv   \n",
              "3663                           /show/hannibal-2013   tv   \n",
              "5782                           /show/mr-robot-2015   tv   \n",
              "8626                        /show/the-expanse-2015   tv   \n",
              "8763                 /show/the-handmaids-tale-2017   tv   \n",
              "10366         /show/what-we-do-in-the-shadows-2019   tv   \n",
              "5900                   /show/my-hero-academia-2016   tv   \n",
              "8923                   /show/the-last-kingdom-2015   tv   \n",
              "1377                        /show/broadchurch-2013   tv   \n",
              "1389                 /show/brooklyn-nine-nine-2013   tv   \n",
              "8295                      /show/the-americans-2013   tv   \n",
              "8018                       /show/supernatural-2005   tv   \n",
              "8944                /show/the-legend-of-korra-2012   tv   \n",
              "473                /show/american-crime-story-2016   tv   \n",
              "5682                        /show/money-heist-2017   tv   \n",
              "6388                              /show/ozark-2017   tv   \n",
              "6686                       /show/prison-break-2005   tv   \n",
              "64                                   /show/24-2001   tv   \n",
              "4028              /show/how-i-met-your-mother-2005   tv   \n",
              "7425                      /show/sex-education-2019   tv   \n",
              "4675                        /show/killing-eve-2018   tv   \n",
              "7401                             /show/sense8-2015   tv   \n",
              "4916                             /show/legion-2017   tv   \n",
              "1730                              /show/chuck-2007   tv   \n",
              "8638                           /show/the-fall-2013   tv   \n",
              "10406                      /show/white-collar-2009   tv   \n",
              "9508                   /show/the-walking-dead-2010   tv   \n",
              "5204                            /show/lucifer-2016   tv   \n",
              "6320            /show/orange-is-the-new-black-2013   tv   \n",
              "5418              /show/marvels-jessica-jones-2015   tv   \n",
              "5408           /show/marvels-agents-of-shield-2013   tv   \n",
              "\n",
              "                                                 Service  \\\n",
              "1336                                           [netflix]   \n",
              "1920   [natgeo, free, tubi_tv, fox, fox_tveverywhere,...   \n",
              "3969                                      [amazon_prime]   \n",
              "7003   [free, hulu_plus, hoopla, fubo_tv, adult_swim_...   \n",
              "7483                                           [netflix]   \n",
              "3515   [disneynow, free, disneynow_free, hulu_plus, d...   \n",
              "709    [adult_swim_tveverywhere, crunchyroll_premium,...   \n",
              "4361   [philo, fx_tveverywhere, fox_tveverywhere, vic...   \n",
              "9526                                           [netflix]   \n",
              "2128                                           [netflix]   \n",
              "6475                                           [netflix]   \n",
              "6032                                           [netflix]   \n",
              "1156                                           [netflix]   \n",
              "7914                                           [netflix]   \n",
              "9619   [nbc, free, nbc_tveverywhere, fubo_tv, hulu_pl...   \n",
              "8519                                           [netflix]   \n",
              "1241                                           [netflix]   \n",
              "4002   [nbc, free, peacock, nbc_tveverywhere, amazon_...   \n",
              "9007                                      [amazon_prime]   \n",
              "7699   [comedy, free, hulu_plus, philo, fubo_tv, come...   \n",
              "9342   [free, fox, fx_tveverywhere, fubo_tv, hulu_plu...   \n",
              "6448   [free, philo, nbc_tveverywhere, amazon_prime, ...   \n",
              "2339   [free, showtime, netflix, fubo_tv, showtime_free]   \n",
              "5412                                           [netflix]   \n",
              "9576      [free, philo, fox, bbc_america_tve, hulu_plus]   \n",
              "4556                                         [hulu_plus]   \n",
              "275    [free, cartoon_network_free, hulu_plus, hoopla...   \n",
              "3663                                           [netflix]   \n",
              "5782                                      [amazon_prime]   \n",
              "8626                                      [amazon_prime]   \n",
              "8763                                         [hulu_plus]   \n",
              "10366                                        [hulu_plus]   \n",
              "5900   [adult_swim_tveverywhere, crunchyroll_premium,...   \n",
              "8923                                           [netflix]   \n",
              "1377                                           [netflix]   \n",
              "1389   [nbc, free, peacock, nbc_tveverywhere, fubo_tv...   \n",
              "8295                                      [amazon_prime]   \n",
              "8018                [free, thecw, netflix, tnt, fubo_tv]   \n",
              "8944   [free, hoopla, abc_news, netflix, cbs_all_access]   \n",
              "473                                            [netflix]   \n",
              "5682                                           [netflix]   \n",
              "6388                                           [netflix]   \n",
              "6686                                         [hulu_plus]   \n",
              "64                                           [hulu_plus]   \n",
              "4028                                         [hulu_plus]   \n",
              "7425                                           [netflix]   \n",
              "4675   [amc_premiere, philo, bbc_america_tve, fubo_tv...   \n",
              "7401                                           [netflix]   \n",
              "4916                                         [hulu_plus]   \n",
              "1730                                      [amazon_prime]   \n",
              "8638   [free, hoopla, tubi_tv, plex_free, sundancenow...   \n",
              "10406                                        [hulu_plus]   \n",
              "9508        [amc_premiere, philo, netflix, fubo_tv, amc]   \n",
              "5204                                           [netflix]   \n",
              "6320                                           [netflix]   \n",
              "5418                                           [netflix]   \n",
              "5408                                           [netflix]   \n",
              "\n",
              "                                                   Genre  \\\n",
              "1336                                      [Drama, Crime]   \n",
              "1920                                       [Documentary]   \n",
              "3969                                             [Sport]   \n",
              "7003   [Comedy, Action & Adventure, Animation, Scienc...   \n",
              "7483                  [Action & Adventure, Drama, Crime]   \n",
              "3515    [Comedy, Action & Adventure, Fantasy, Animation]   \n",
              "709               [Action & Adventure, Animation, Anime]   \n",
              "4361                                            [Comedy]   \n",
              "9526                                             [Drama]   \n",
              "2128                             [Mystery, Drama, Crime]   \n",
              "6475                                      [Drama, Crime]   \n",
              "6032                           [Biography, Drama, Crime]   \n",
              "1156                   [Science-Fiction, Fantasy, Drama]   \n",
              "7914                            [Horror, Fantasy, Drama]   \n",
              "9619                                     [Comedy, Drama]   \n",
              "8519                                    [History, Drama]   \n",
              "1241                          [Animation, Comedy, Drama]   \n",
              "4002                            [Comedy, Mystery, Drama]   \n",
              "9007                    [Stand-up & Talk, Comedy, Drama]   \n",
              "7699                                 [Comedy, Animation]   \n",
              "9342                         [Comedy, Animation, Family]   \n",
              "6448                                            [Comedy]   \n",
              "2339                             [Mystery, Drama, Crime]   \n",
              "5412                  [Action & Adventure, Drama, Crime]   \n",
              "9576                   [Science-Fiction, Mystery, Drama]   \n",
              "4556                  [Action & Adventure, Drama, Crime]   \n",
              "275    [Action & Adventure, Fantasy, Animation, Child...   \n",
              "3663                              [Horror, Drama, Crime]   \n",
              "5782                            [Thriller, Drama, Crime]   \n",
              "8626                [Action & Adventure, Fantasy, Drama]   \n",
              "8763                            [Science-Fiction, Drama]   \n",
              "10366                          [Horror, Comedy, Fantasy]   \n",
              "5900              [Action & Adventure, Animation, Anime]   \n",
              "8923              [Romance, Action & Adventure, History]   \n",
              "1377                             [Mystery, Drama, Crime]   \n",
              "1389                 [Comedy, Action & Adventure, Crime]   \n",
              "8295                             [Mystery, Drama, Crime]   \n",
              "8018                            [Horror, Fantasy, Drama]   \n",
              "8944                     [Action & Adventure, Animation]   \n",
              "473                            [Biography, Drama, Crime]   \n",
              "5682               [Action & Adventure, Thriller, Crime]   \n",
              "6388                            [Thriller, Drama, Crime]   \n",
              "6686                  [Action & Adventure, Drama, Crime]   \n",
              "64                 [Action & Adventure, Thriller, Drama]   \n",
              "4028                                   [Romance, Comedy]   \n",
              "7425                              [LGBTQ, Comedy, Drama]   \n",
              "4675               [LGBTQ, Action & Adventure, Thriller]   \n",
              "7401                             [LGBTQ, Mystery, Drama]   \n",
              "4916        [Science-Fiction, Action & Adventure, Drama]   \n",
              "1730                 [Comedy, Action & Adventure, Drama]   \n",
              "8638                            [Thriller, Drama, Crime]   \n",
              "10406                 [Action & Adventure, Drama, Crime]   \n",
              "9508                                     [Horror, Drama]   \n",
              "5204                   [Science-Fiction, Fantasy, Crime]   \n",
              "6320                              [LGBTQ, Comedy, Crime]   \n",
              "5418                  [Action & Adventure, Drama, Crime]   \n",
              "5408                [Action & Adventure, Fantasy, Drama]   \n",
              "\n",
              "                                                     Tag  IMDB  ReelGood  \\\n",
              "1336      [Gangster, High School, Doctor, Drug, Teacher]   9.5     100.0   \n",
              "1920                                    [Space, Science]   9.3      82.0   \n",
              "3969                                            [Racing]   9.2      38.0   \n",
              "7003                [Time Travel, Space, Science, Alien]   9.2      96.0   \n",
              "7483         [Based on Books, Adaptation, Serial Killer]   9.1      94.0   \n",
              "3515                              [Supernatural, Disney]   8.9      87.0   \n",
              "709    [Supernatural, Dystopia, Monster, Political, A...   8.8      92.0   \n",
              "4361                             [Friendship, Political]   8.8      90.0   \n",
              "9526                                    [Political, Spy]   8.8      85.0   \n",
              "2128                               [Time Travel, Police]   8.8      94.0   \n",
              "6475         [Gangster, War, Drug, World War II, Racing]   8.8      91.0   \n",
              "6032               [Based On True Story, Gangster, Drug]   8.8      90.0   \n",
              "1156                       [Dystopia, Space, Technology]   8.8      92.0   \n",
              "7914   [Space, Science, Supernatural, Monster, Friend...   8.8      96.0   \n",
              "9619                                         [Feel-good]   8.7      87.0   \n",
              "8519                      [Political, Princess, Royalty]   8.7      88.0   \n",
              "1241   [Mature, Space, Psychology, Genius, Animal, Drug]   8.7      86.0   \n",
              "4002                                      [Doctor, Drug]   8.7      92.0   \n",
              "9007                               [New York, Feel-good]   8.7      87.0   \n",
              "7699   [Mature, Political, Feel-good, Time Travel, Pa...   8.7      90.0   \n",
              "9342   [Vampire, Cartoon, Supernatural, Parody, Frien...   8.7      91.0   \n",
              "6448                                         [Political]   8.6      90.0   \n",
              "2339         [Based on Books, Adaptation, Serial Killer]   8.6      91.0   \n",
              "5412   [Supernatural, Disney, Superhero, Comic Book, ...   8.6      90.0   \n",
              "9576   [Space, Vampire, Science, Alien, Supernatural,...   8.6      87.0   \n",
              "4556                                [Military, Gangster]   8.6      87.0   \n",
              "275                  [Magic, Princess, Cartoon, Royalty]   8.6      87.0   \n",
              "3663                                     [Serial Killer]   8.5      89.0   \n",
              "5782                          [Robot, Suspense, Science]   8.5      92.0   \n",
              "8626              [Dystopia, Science, Space, Futuristic]   8.5      89.0   \n",
              "8763   [Dystopia, Political, Based on Books, Doctor, ...   8.5      88.0   \n",
              "10366                            [Vampire, Supernatural]   8.5      85.0   \n",
              "5900   [Revenge, Supernatural, High School, Superhero...   8.5      88.0   \n",
              "8923                                [Political, Royalty]   8.4      86.0   \n",
              "1377                   [Police, Serial Killer, Religion]   8.4      86.0   \n",
              "1389                             [New York, Police, War]   8.4      91.0   \n",
              "8295                               [Political, War, Spy]   8.4      87.0   \n",
              "8018   [Vampire, Supernatural, Monster, Time Travel, ...   8.4      93.0   \n",
              "8944   [Supernatural, Political, Martial Arts, Feel-g...   8.4      87.0   \n",
              "473    [Based On True Story, Police, Adaptation, Seri...   8.4      86.0   \n",
              "5682                                            [Mature]   8.4      91.0   \n",
              "6388                                    [Gangster, Drug]   8.4      89.0   \n",
              "6686   [Gangster, Psychology, Escape, Prison, Suspens...   8.3      88.0   \n",
              "64                     [Revenge, Political, Spy, Prison]   8.3      85.0   \n",
              "4028                               [Friendship, College]   8.3      89.0   \n",
              "7425                           [Mature, Teen, Feel-good]   8.3      91.0   \n",
              "4675            [Based on Books, Psychology, Adaptation]   8.3      87.0   \n",
              "7401                       [Mature, Space, Supernatural]   8.3      86.0   \n",
              "4916   [Science, Supernatural, Psychology, Superhero,...   8.3      85.0   \n",
              "1730                    [Space, Police, Spy, Technology]   8.2      85.0   \n",
              "8638                   [Suspense, Police, Serial Killer]   8.2      89.0   \n",
              "10406                                         [New York]   8.2      85.0   \n",
              "9508   [Zombie, Dystopia, Survival, Comic Book, Adapt...   8.2      91.0   \n",
              "5204   [Supernatural, Police, Superhero, Comic Book, ...   8.2      91.0   \n",
              "6320                       [Based On True Story, Prison]   8.1      87.0   \n",
              "5418   [Supernatural, Psychology, Disney, Superhero, ...   7.9      85.0   \n",
              "5408   [Supernatural, Disney, Superhero, Comic Book, ...   7.5      87.0   \n",
              "\n",
              "      AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "1336        18+  TV-MA           2008     2008-2020      5.0   \n",
              "1920        all   TV-G           2014     2014-2020      3.0   \n",
              "3969        all   TV-G           2006     2006-2020      9.0   \n",
              "7003        18+  TV-MA           2013     2013-2020      4.0   \n",
              "7483        16+  TV-14           2010     2010-2020      4.0   \n",
              "3515         7+  TV-PG           2012     2012-2020      3.0   \n",
              "709         16+  TV-MA           2013     2013-2020      3.0   \n",
              "4361        18+  TV-MA           2005     2005-2020     15.0   \n",
              "9526        16+  TV-14           1999     1999-2020      7.0   \n",
              "2128        16+  TV-14           2017     2017-2020      3.0   \n",
              "6475        18+  TV-MA           2013     2013-2020      7.0   \n",
              "6032        18+  TV-MA           2015     2015-2020      4.0   \n",
              "1156        18+  TV-MA           2011     2011-2020      5.0   \n",
              "7914        16+  TV-14           2016     2016-2020      4.0   \n",
              "9619        16+  TV-14           2016     2016-2020      5.0   \n",
              "8519        18+  TV-MA           2016     2016-2020      4.0   \n",
              "1241        18+  TV-MA           2014     2014-2020      6.0   \n",
              "4002        16+  TV-14           2004     2004-2020      8.0   \n",
              "9007        18+  TV-MA           2017     2017-2020      4.0   \n",
              "7699        18+  TV-MA           1997     1997-2020     24.0   \n",
              "9342         7+  TV-PG           1989     1989-2020     32.0   \n",
              "6448        16+  TV-14           2009     2009-2020      7.0   \n",
              "2339        18+  TV-MA           2006     2006-2020      8.0   \n",
              "5412        18+  TV-MA           2015     2015-2020      3.0   \n",
              "9576        16+  TV-14           1993     1993-2020     11.0   \n",
              "4556        18+  TV-MA           2010     2010-2020      6.0   \n",
              "275          7+  TV-PG           2010     2010-2020     11.0   \n",
              "3663        18+  TV-MA           2013     2013-2020      3.0   \n",
              "5782        18+  TV-MA           2015     2015-2020      4.0   \n",
              "8626        16+  TV-14           2015     2015-2020      5.0   \n",
              "8763        18+  TV-MA           2017     2017-2020      4.0   \n",
              "10366       18+  TV-MA           2019     2019-2020      3.0   \n",
              "5900        16+  TV-14           2016     2016-2020      5.0   \n",
              "8923        18+  TV-MA           2015     2015-2020      4.0   \n",
              "1377        18+  TV-MA           2013     2013-2020      3.0   \n",
              "1389        16+  TV-14           2013     2013-2020      8.0   \n",
              "8295        18+  TV-MA           2013     2013-2020      6.0   \n",
              "8018        16+  TV-14           2005     2005-2020     16.0   \n",
              "8944         7+  TV-PG           2012     2012-2020      4.0   \n",
              "473         18+  TV-MA           2016     2016-2020      4.0   \n",
              "5682        18+  TV-MA           2017     2017-2020      3.0   \n",
              "6388        18+  TV-MA           2017     2017-2020      3.0   \n",
              "6686        16+  TV-14           2005     2005-2020      6.0   \n",
              "64          16+  TV-14           2001     2001-2020      9.0   \n",
              "4028        16+  TV-14           2005     2005-2020      9.0   \n",
              "7425        16+  TV-14           2019     2019-2020      3.0   \n",
              "4675        16+  TV-14           2018     2018-2020      4.0   \n",
              "7401        18+  TV-MA           2015     2015-2020      3.0   \n",
              "4916        16+  TV-14           2017     2017-2020      3.0   \n",
              "1730         7+  TV-PG           2007     2007-2020      5.0   \n",
              "8638        18+  TV-MA           2013     2013-2020      3.0   \n",
              "10406       16+  TV-14           2009     2009-2020      6.0   \n",
              "9508        18+  TV-MA           2010     2010-2020     10.0   \n",
              "5204        16+  TV-14           2016     2016-2020      5.0   \n",
              "6320        18+  TV-MA           2013     2013-2020      7.0   \n",
              "5418        18+  TV-MA           2015     2015-2020      3.0   \n",
              "5408        16+  TV-14           2013     2013-2020      7.0   \n",
              "\n",
              "                                         What it's about  \\\n",
              "1336   When Walter White, a New Mexico chemistry teac...   \n",
              "1920   Famed astrophysicist Neil deGrasse Tyson provi...   \n",
              "3969   Every gearhead wants power and this show revea...   \n",
              "7003   Rick is a mentally-unbalanced but scientifical...   \n",
              "7483   A modern update finds the famous sleuth and hi...   \n",
              "3515   Twin brother and sister Dipper and Mabel Pines...   \n",
              "709    Several hundred years ago, humans were nearly ...   \n",
              "4361   Four egocentric friends who run a neighborhood...   \n",
              "9526   The West Wing provides a glimpse into presiden...   \n",
              "2128   A missing child causes four families to help e...   \n",
              "6475   A gangster family epic set in 1919 Birmingham,...   \n",
              "6032   A gritty chronicle of the war against Colombia...   \n",
              "1156   A contemporary British re-working of The Twili...   \n",
              "7914   When a young boy vanishes, a small town uncove...   \n",
              "9619   Follows the lives and families of three adults...   \n",
              "8519   The gripping, decades-spanning inside story of...   \n",
              "1241   Meet the most beloved sitcom horse of the 90s ...   \n",
              "4002   Dr. Gregory House, a drug-addicted, unconventi...   \n",
              "9007   It’s 1958 Manhattan and Miriam “Midge” Maisel ...   \n",
              "7699   Follows the misadventures of four irreverent g...   \n",
              "9342   Set in Springfield, the average American town,...   \n",
              "6448   Hilarious ensemble comedy that follows Leslie ...   \n",
              "2339   Dexter Morgan, a blood spatter pattern analyst...   \n",
              "5412   Lawyer-by-day Matt Murdock uses his heightened...   \n",
              "9576   The exploits of FBI Special Agents Fox Mulder ...   \n",
              "4556   A character drama based on the 2001 Elmore Leo...   \n",
              "275    Hook up with Finn and Jake as they travel the ...   \n",
              "3663   Both a gift and a curse, Graham has the extrao...   \n",
              "5782   A contemporary and culturally resonant drama a...   \n",
              "8626   A thriller set two hundred years in the future...   \n",
              "8763   Set in a dystopian future, a woman is forced t...   \n",
              "10366  A documentary-style look into the daily (or ra...   \n",
              "5900   In a world where eighty percent of the populat...   \n",
              "8923   A show of heroic deeds and epic battles with a...   \n",
              "1377   The murder of a young boy in a small coastal t...   \n",
              "1389   A single-camera ensemble comedy following the ...   \n",
              "8295   Set during the Cold War period in the 1980s, T...   \n",
              "8018   When they were boys, Sam and Dean Winchester l...   \n",
              "8944   Avatar Korra, a headstrong, rebellious, feisty...   \n",
              "473    An anthology series centered around some of hi...   \n",
              "5682   To carry out the biggest heist in history, a m...   \n",
              "6388   A financial adviser drags his family from Chic...   \n",
              "6686   Due to a political conspiracy, an innocent man...   \n",
              "64     24 is an American television series produced f...   \n",
              "4028   A father recounts to his children - through a ...   \n",
              "7425   Inexperienced Otis channels his sex therapist ...   \n",
              "4675   A security consultant hunts for a ruthless ass...   \n",
              "7401   One gunshot, one death, one moment out of time...   \n",
              "4916   David Haller, AKA Legion, is a troubled young ...   \n",
              "1730   When Buy More computer geek Chuck Bartowski un...   \n",
              "8638   When the Police Service of Northern Ireland ar...   \n",
              "10406  Neal Caffrey, a con man, forger and thief, is ...   \n",
              "9508   Sheriff's deputy Rick Grimes awakens from a co...   \n",
              "5204   Bored and unhappy as the Lord of Hell, Lucifer...   \n",
              "6320   A crime she committed in her youthful past sen...   \n",
              "5418   After a tragic ending to her short-lived super...   \n",
              "5408   Agent Phil Coulson of S.H.I.E.L.D. (Strategic ...   \n",
              "\n",
              "                                          Where to Watch  \\\n",
              "1336   62 episodes (100%) are available to stream on ...   \n",
              "1920   2 episodes (7%) are available to watch free on...   \n",
              "3969   14 episodes (8%) are available to stream on a ...   \n",
              "7003   5 episodes (12%) are available to watch free o...   \n",
              "7483   12 episodes (92%) are available to stream on a...   \n",
              "3515   2 episodes (5%) are available to watch free on...   \n",
              "709    59 episodes (98%) are available to watch free ...   \n",
              "4361   146 episodes (95%) are available to stream on ...   \n",
              "9526   155 episodes (100%) are available to stream on...   \n",
              "2128   26 episodes (100%) are available to stream on ...   \n",
              "6475   30 episodes (100%) are available to stream on ...   \n",
              "6032   30 episodes (100%) are available to stream on ...   \n",
              "1156   21 episodes (95%) are available to stream on a...   \n",
              "7914   25 episodes (100%) are available to stream on ...   \n",
              "9619   11 episodes (15%) are available to watch free ...   \n",
              "8519   30 episodes (100%) are available to stream on ...   \n",
              "1241                                                None   \n",
              "4002   10 episodes (6%) are available to watch free o...   \n",
              "9007   26 episodes (100%) are available to stream on ...   \n",
              "7699   44 episodes (14%) are available to watch free ...   \n",
              "9342   4 episodes (1%) are available to watch free on...   \n",
              "6448   124 episodes (98%) are available to watch free...   \n",
              "2339   1 episodes (1%) are available to watch free on...   \n",
              "5412   39 episodes (100%) are available to stream on ...   \n",
              "9576   3 episodes (1%) are available to watch free on...   \n",
              "4556                                                None   \n",
              "275    1 episodes (0%) are available to watch free on...   \n",
              "3663   39 episodes (100%) are available to stream on ...   \n",
              "5782   45 episodes (100%) are available to stream on ...   \n",
              "8626   46 episodes (100%) are available to stream on ...   \n",
              "8763   37 episodes (100%) are available to stream on ...   \n",
              "10366  20 episodes (100%) are available to stream on ...   \n",
              "5900   86 episodes (92%) are available to watch free ...   \n",
              "8923   40 episodes (100%) are available to stream on ...   \n",
              "1377   24 episodes (100%) are available to stream on ...   \n",
              "1389   5 episodes (3%) are available to watch free on...   \n",
              "8295   75 episodes (100%) are available to stream on ...   \n",
              "8018   5 episodes (2%) are available to watch free on...   \n",
              "8944   1 episodes (2%) are available to watch free on...   \n",
              "473    19 episodes (95%) are available to stream on a...   \n",
              "5682   38 episodes (100%) are available to stream on ...   \n",
              "6388   30 episodes (100%) are available to stream on ...   \n",
              "6686   87 episodes (98%) are available to stream on a...   \n",
              "64     205 episodes (100%) are available to stream on...   \n",
              "4028   208 episodes (100%) are available to stream on...   \n",
              "7425   16 episodes (100%) are available to stream on ...   \n",
              "4675   16 episodes (67%) are available to stream on a...   \n",
              "7401                                                None   \n",
              "4916   27 episodes (100%) are available to stream on ...   \n",
              "1730   90 episodes (99%) are available to stream on a...   \n",
              "8638   27 episodes (93%) are available to watch free ...   \n",
              "10406  81 episodes (100%) are available to watch free...   \n",
              "9508   146 episodes (100%) are available to stream on...   \n",
              "5204   75 episodes (100%) are available to stream on ...   \n",
              "6320   91 episodes (99%) are available to stream on a...   \n",
              "5418   39 episodes (100%) are available to stream on ...   \n",
              "5408   123 episodes (90%) are available to stream on ...   \n",
              "\n",
              "       Rent or Buy Available  Exclusive Service  Has Tag  \n",
              "1336                       1                  0        1  \n",
              "1920                       1                  0        1  \n",
              "3969                       1                  0        1  \n",
              "7003                       1                  0        1  \n",
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              "709                        1                  0        1  \n",
              "4361                       1                  0        1  \n",
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              "2128                       0                  1        1  \n",
              "6475                       1                  0        1  \n",
              "6032                       0                  1        1  \n",
              "1156                       1                  0        1  \n",
              "7914                       0                  1        1  \n",
              "9619                       1                  0        1  \n",
              "8519                       0                  1        1  \n",
              "1241                       0                  1        1  \n",
              "4002                       1                  0        1  \n",
              "9007                       0                  1        1  \n",
              "7699                       1                  0        1  \n",
              "9342                       1                  0        1  \n",
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              "2339                       1                  0        1  \n",
              "5412                       1                  0        1  \n",
              "9576                       1                  0        1  \n",
              "4556                       1                  0        1  \n",
              "275                        1                  0        1  \n",
              "3663                       1                  0        1  \n",
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              "1389                       1                  0        1  \n",
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              "8944                       1                  0        1  \n",
              "473                        1                  0        1  \n",
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              "      <th></th>\n",
              "      <th>Title</th>\n",
              "      <th>URL</th>\n",
              "      <th>Type</th>\n",
              "      <th>Service</th>\n",
              "      <th>Genre</th>\n",
              "      <th>Tag</th>\n",
              "      <th>IMDB</th>\n",
              "      <th>ReelGood</th>\n",
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              "      <th>Rated</th>\n",
              "      <th>Released Year</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1336</th>\n",
              "      <td>Breaking Bad</td>\n",
              "      <td>/show/breaking-bad-2008</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama, Crime]</td>\n",
              "      <td>[Gangster, High School, Doctor, Drug, Teacher]</td>\n",
              "      <td>9.5</td>\n",
              "      <td>100.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2008</td>\n",
              "      <td>2008-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>When Walter White, a New Mexico chemistry teac...</td>\n",
              "      <td>62 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>1920</th>\n",
              "      <td>Cosmos</td>\n",
              "      <td>/show/cosmos-a-spacetime-odyssey-2014</td>\n",
              "      <td>tv</td>\n",
              "      <td>[natgeo, free, tubi_tv, fox, fox_tveverywhere,...</td>\n",
              "      <td>[Documentary]</td>\n",
              "      <td>[Space, Science]</td>\n",
              "      <td>9.3</td>\n",
              "      <td>82.0</td>\n",
              "      <td>all</td>\n",
              "      <td>TV-G</td>\n",
              "      <td>2014</td>\n",
              "      <td>2014-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Famed astrophysicist Neil deGrasse Tyson provi...</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "    <tr>\n",
              "      <th>3969</th>\n",
              "      <td>Horsepower TV</td>\n",
              "      <td>/show/horsepower-2006</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Sport]</td>\n",
              "      <td>[Racing]</td>\n",
              "      <td>9.2</td>\n",
              "      <td>38.0</td>\n",
              "      <td>all</td>\n",
              "      <td>TV-G</td>\n",
              "      <td>2006</td>\n",
              "      <td>2006-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>Every gearhead wants power and this show revea...</td>\n",
              "      <td>14 episodes (8%) are available to stream on a ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>7003</th>\n",
              "      <td>Rick and Morty</td>\n",
              "      <td>/show/rick-and-morty-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hulu_plus, hoopla, fubo_tv, adult_swim_...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Animation, Scienc...</td>\n",
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              "      <td>9.2</td>\n",
              "      <td>96.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
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              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7483</th>\n",
              "      <td>Sherlock</td>\n",
              "      <td>/show/sherlock-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Based on Books, Adaptation, Serial Killer]</td>\n",
              "      <td>9.1</td>\n",
              "      <td>94.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A modern update finds the famous sleuth and hi...</td>\n",
              "      <td>12 episodes (92%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3515</th>\n",
              "      <td>Gravity Falls</td>\n",
              "      <td>/show/gravity-falls-2012</td>\n",
              "      <td>tv</td>\n",
              "      <td>[disneynow, free, disneynow_free, hulu_plus, d...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Fantasy, Animation]</td>\n",
              "      <td>[Supernatural, Disney]</td>\n",
              "      <td>8.9</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2012</td>\n",
              "      <td>2012-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Twin brother and sister Dipper and Mabel Pines...</td>\n",
              "      <td>2 episodes (5%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>709</th>\n",
              "      <td>Attack on Titan</td>\n",
              "      <td>/show/attack-on-titan-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[adult_swim_tveverywhere, crunchyroll_premium,...</td>\n",
              "      <td>[Action &amp; Adventure, Animation, Anime]</td>\n",
              "      <td>[Supernatural, Dystopia, Monster, Political, A...</td>\n",
              "      <td>8.8</td>\n",
              "      <td>92.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Several hundred years ago, humans were nearly ...</td>\n",
              "      <td>59 episodes (98%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4361</th>\n",
              "      <td>It's Always Sunny in Philadelphia</td>\n",
              "      <td>/show/its-always-sunny-in-philadelphia-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[philo, fx_tveverywhere, fox_tveverywhere, vic...</td>\n",
              "      <td>[Comedy]</td>\n",
              "      <td>[Friendship, Political]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Four egocentric friends who run a neighborhood...</td>\n",
              "      <td>146 episodes (95%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9526</th>\n",
              "      <td>The West Wing</td>\n",
              "      <td>/show/the-west-wing-1999</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama]</td>\n",
              "      <td>[Political, Spy]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>1999</td>\n",
              "      <td>1999-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>The West Wing provides a glimpse into presiden...</td>\n",
              "      <td>155 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2128</th>\n",
              "      <td>Dark</td>\n",
              "      <td>/show/dark-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Time Travel, Police]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>94.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A missing child causes four families to help e...</td>\n",
              "      <td>26 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6475</th>\n",
              "      <td>Peaky Blinders</td>\n",
              "      <td>/show/peaky-blinders-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama, Crime]</td>\n",
              "      <td>[Gangster, War, Drug, World War II, Racing]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>A gangster family epic set in 1919 Birmingham,...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6032</th>\n",
              "      <td>Narcos</td>\n",
              "      <td>/show/narcos-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Biography, Drama, Crime]</td>\n",
              "      <td>[Based On True Story, Gangster, Drug]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A gritty chronicle of the war against Colombia...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1156</th>\n",
              "      <td>Black Mirror</td>\n",
              "      <td>/show/black-mirror-2011</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Science-Fiction, Fantasy, Drama]</td>\n",
              "      <td>[Dystopia, Space, Technology]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>92.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2011</td>\n",
              "      <td>2011-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>A contemporary British re-working of The Twili...</td>\n",
              "      <td>21 episodes (95%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7914</th>\n",
              "      <td>Stranger Things</td>\n",
              "      <td>/show/stranger-things-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Horror, Fantasy, Drama]</td>\n",
              "      <td>[Space, Science, Supernatural, Monster, Friend...</td>\n",
              "      <td>8.8</td>\n",
              "      <td>96.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>When a young boy vanishes, a small town uncove...</td>\n",
              "      <td>25 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9619</th>\n",
              "      <td>This Is Us</td>\n",
              "      <td>/show/this-is-us-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, nbc_tveverywhere, fubo_tv, hulu_pl...</td>\n",
              "      <td>[Comedy, Drama]</td>\n",
              "      <td>[Feel-good]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Follows the lives and families of three adults...</td>\n",
              "      <td>11 episodes (15%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8519</th>\n",
              "      <td>The Crown</td>\n",
              "      <td>/show/the-crown-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[History, Drama]</td>\n",
              "      <td>[Political, Princess, Royalty]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>88.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>The gripping, decades-spanning inside story of...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1241</th>\n",
              "      <td>BoJack Horseman</td>\n",
              "      <td>/show/bojack-horseman-2014</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Animation, Comedy, Drama]</td>\n",
              "      <td>[Mature, Space, Psychology, Genius, Animal, Drug]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2014</td>\n",
              "      <td>2014-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Meet the most beloved sitcom horse of the 90s ...</td>\n",
              "      <td>None</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4002</th>\n",
              "      <td>House</td>\n",
              "      <td>/show/house-2004</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, peacock, nbc_tveverywhere, amazon_...</td>\n",
              "      <td>[Comedy, Mystery, Drama]</td>\n",
              "      <td>[Doctor, Drug]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>92.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2004</td>\n",
              "      <td>2004-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Dr. Gregory House, a drug-addicted, unconventi...</td>\n",
              "      <td>10 episodes (6%) are available to watch free o...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9007</th>\n",
              "      <td>The Marvelous Mrs. Maisel</td>\n",
              "      <td>/show/the-marvelous-mrs-maisel-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Stand-up &amp; Talk, Comedy, Drama]</td>\n",
              "      <td>[New York, Feel-good]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>It’s 1958 Manhattan and Miriam “Midge” Maisel ...</td>\n",
              "      <td>26 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7699</th>\n",
              "      <td>South Park</td>\n",
              "      <td>/show/south-park-1997</td>\n",
              "      <td>tv</td>\n",
              "      <td>[comedy, free, hulu_plus, philo, fubo_tv, come...</td>\n",
              "      <td>[Comedy, Animation]</td>\n",
              "      <td>[Mature, Political, Feel-good, Time Travel, Pa...</td>\n",
              "      <td>8.7</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1997</td>\n",
              "      <td>1997-2020</td>\n",
              "      <td>24.0</td>\n",
              "      <td>Follows the misadventures of four irreverent g...</td>\n",
              "      <td>44 episodes (14%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9342</th>\n",
              "      <td>The Simpsons</td>\n",
              "      <td>/show/the-simpsons-1989</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, fox, fx_tveverywhere, fubo_tv, hulu_plu...</td>\n",
              "      <td>[Comedy, Animation, Family]</td>\n",
              "      <td>[Vampire, Cartoon, Supernatural, Parody, Frien...</td>\n",
              "      <td>8.7</td>\n",
              "      <td>91.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>1989</td>\n",
              "      <td>1989-2020</td>\n",
              "      <td>32.0</td>\n",
              "      <td>Set in Springfield, the average American town,...</td>\n",
              "      <td>4 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6448</th>\n",
              "      <td>Parks and Recreation</td>\n",
              "      <td>/show/parks-and-recreation-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, philo, nbc_tveverywhere, amazon_prime, ...</td>\n",
              "      <td>[Comedy]</td>\n",
              "      <td>[Political]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>90.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Hilarious ensemble comedy that follows Leslie ...</td>\n",
              "      <td>124 episodes (98%) are available to watch free...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2339</th>\n",
              "      <td>Dexter</td>\n",
              "      <td>/show/dexter-2006</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, showtime, netflix, fubo_tv, showtime_free]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Based on Books, Adaptation, Serial Killer]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2006</td>\n",
              "      <td>2006-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Dexter Morgan, a blood spatter pattern analyst...</td>\n",
              "      <td>1 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5412</th>\n",
              "      <td>Marvel's Daredevil</td>\n",
              "      <td>/show/marvels-daredevil-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Supernatural, Disney, Superhero, Comic Book, ...</td>\n",
              "      <td>8.6</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Lawyer-by-day Matt Murdock uses his heightened...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9576</th>\n",
              "      <td>The X-Files</td>\n",
              "      <td>/show/the-x-files-1993</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, philo, fox, bbc_america_tve, hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Mystery, Drama]</td>\n",
              "      <td>[Space, Vampire, Science, Alien, Supernatural,...</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>1993</td>\n",
              "      <td>1993-2020</td>\n",
              "      <td>11.0</td>\n",
              "      <td>The exploits of FBI Special Agents Fox Mulder ...</td>\n",
              "      <td>3 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4556</th>\n",
              "      <td>Justified</td>\n",
              "      <td>/show/justified-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Military, Gangster]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>A character drama based on the 2001 Elmore Leo...</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>275</th>\n",
              "      <td>Adventure Time</td>\n",
              "      <td>/show/adventure-time-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, cartoon_network_free, hulu_plus, hoopla...</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Animation, Child...</td>\n",
              "      <td>[Magic, Princess, Cartoon, Royalty]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>11.0</td>\n",
              "      <td>Hook up with Finn and Jake as they travel the ...</td>\n",
              "      <td>1 episodes (0%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3663</th>\n",
              "      <td>Hannibal</td>\n",
              "      <td>/show/hannibal-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Horror, Drama, Crime]</td>\n",
              "      <td>[Serial Killer]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Both a gift and a curse, Graham has the extrao...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5782</th>\n",
              "      <td>Mr. Robot</td>\n",
              "      <td>/show/mr-robot-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Robot, Suspense, Science]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>92.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A contemporary and culturally resonant drama a...</td>\n",
              "      <td>45 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8626</th>\n",
              "      <td>The Expanse</td>\n",
              "      <td>/show/the-expanse-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Drama]</td>\n",
              "      <td>[Dystopia, Science, Space, Futuristic]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>89.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>A thriller set two hundred years in the future...</td>\n",
              "      <td>46 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8763</th>\n",
              "      <td>The Handmaid's Tale</td>\n",
              "      <td>/show/the-handmaids-tale-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Drama]</td>\n",
              "      <td>[Dystopia, Political, Based on Books, Doctor, ...</td>\n",
              "      <td>8.5</td>\n",
              "      <td>88.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Set in a dystopian future, a woman is forced t...</td>\n",
              "      <td>37 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10366</th>\n",
              "      <td>What We Do in the Shadows</td>\n",
              "      <td>/show/what-we-do-in-the-shadows-2019</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Horror, Comedy, Fantasy]</td>\n",
              "      <td>[Vampire, Supernatural]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>85.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2019</td>\n",
              "      <td>2019-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A documentary-style look into the daily (or ra...</td>\n",
              "      <td>20 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5900</th>\n",
              "      <td>My Hero Academia</td>\n",
              "      <td>/show/my-hero-academia-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[adult_swim_tveverywhere, crunchyroll_premium,...</td>\n",
              "      <td>[Action &amp; Adventure, Animation, Anime]</td>\n",
              "      <td>[Revenge, Supernatural, High School, Superhero...</td>\n",
              "      <td>8.5</td>\n",
              "      <td>88.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>In a world where eighty percent of the populat...</td>\n",
              "      <td>86 episodes (92%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8923</th>\n",
              "      <td>The Last Kingdom</td>\n",
              "      <td>/show/the-last-kingdom-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Romance, Action &amp; Adventure, History]</td>\n",
              "      <td>[Political, Royalty]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A show of heroic deeds and epic battles with a...</td>\n",
              "      <td>40 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1377</th>\n",
              "      <td>Broadchurch</td>\n",
              "      <td>/show/broadchurch-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Police, Serial Killer, Religion]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>The murder of a young boy in a small coastal t...</td>\n",
              "      <td>24 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1389</th>\n",
              "      <td>Brooklyn Nine-Nine</td>\n",
              "      <td>/show/brooklyn-nine-nine-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, peacock, nbc_tveverywhere, fubo_tv...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Crime]</td>\n",
              "      <td>[New York, Police, War]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>A single-camera ensemble comedy following the ...</td>\n",
              "      <td>5 episodes (3%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8295</th>\n",
              "      <td>The Americans</td>\n",
              "      <td>/show/the-americans-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Political, War, Spy]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Set during the Cold War period in the 1980s, T...</td>\n",
              "      <td>75 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8018</th>\n",
              "      <td>Supernatural</td>\n",
              "      <td>/show/supernatural-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, thecw, netflix, tnt, fubo_tv]</td>\n",
              "      <td>[Horror, Fantasy, Drama]</td>\n",
              "      <td>[Vampire, Supernatural, Monster, Time Travel, ...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>93.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>16.0</td>\n",
              "      <td>When they were boys, Sam and Dean Winchester l...</td>\n",
              "      <td>5 episodes (2%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8944</th>\n",
              "      <td>The Legend of Korra</td>\n",
              "      <td>/show/the-legend-of-korra-2012</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hoopla, abc_news, netflix, cbs_all_access]</td>\n",
              "      <td>[Action &amp; Adventure, Animation]</td>\n",
              "      <td>[Supernatural, Political, Martial Arts, Feel-g...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2012</td>\n",
              "      <td>2012-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Avatar Korra, a headstrong, rebellious, feisty...</td>\n",
              "      <td>1 episodes (2%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>473</th>\n",
              "      <td>American Crime Story</td>\n",
              "      <td>/show/american-crime-story-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Biography, Drama, Crime]</td>\n",
              "      <td>[Based On True Story, Police, Adaptation, Seri...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>An anthology series centered around some of hi...</td>\n",
              "      <td>19 episodes (95%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5682</th>\n",
              "      <td>Money Heist</td>\n",
              "      <td>/show/money-heist-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Thriller, Crime]</td>\n",
              "      <td>[Mature]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>To carry out the biggest heist in history, a m...</td>\n",
              "      <td>38 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6388</th>\n",
              "      <td>Ozark</td>\n",
              "      <td>/show/ozark-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Gangster, Drug]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A financial adviser drags his family from Chic...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6686</th>\n",
              "      <td>Prison Break</td>\n",
              "      <td>/show/prison-break-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Gangster, Psychology, Escape, Prison, Suspens...</td>\n",
              "      <td>8.3</td>\n",
              "      <td>88.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Due to a political conspiracy, an innocent man...</td>\n",
              "      <td>87 episodes (98%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>24</td>\n",
              "      <td>/show/24-2001</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Thriller, Drama]</td>\n",
              "      <td>[Revenge, Political, Spy, Prison]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2001</td>\n",
              "      <td>2001-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>24 is an American television series produced f...</td>\n",
              "      <td>205 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4028</th>\n",
              "      <td>How I Met Your Mother</td>\n",
              "      <td>/show/how-i-met-your-mother-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Romance, Comedy]</td>\n",
              "      <td>[Friendship, College]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>89.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>A father recounts to his children - through a ...</td>\n",
              "      <td>208 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7425</th>\n",
              "      <td>Sex Education</td>\n",
              "      <td>/show/sex-education-2019</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Comedy, Drama]</td>\n",
              "      <td>[Mature, Teen, Feel-good]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2019</td>\n",
              "      <td>2019-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Inexperienced Otis channels his sex therapist ...</td>\n",
              "      <td>16 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4675</th>\n",
              "      <td>Killing Eve</td>\n",
              "      <td>/show/killing-eve-2018</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amc_premiere, philo, bbc_america_tve, fubo_tv...</td>\n",
              "      <td>[LGBTQ, Action &amp; Adventure, Thriller]</td>\n",
              "      <td>[Based on Books, Psychology, Adaptation]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A security consultant hunts for a ruthless ass...</td>\n",
              "      <td>16 episodes (67%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7401</th>\n",
              "      <td>Sense8</td>\n",
              "      <td>/show/sense8-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Mystery, Drama]</td>\n",
              "      <td>[Mature, Space, Supernatural]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>One gunshot, one death, one moment out of time...</td>\n",
              "      <td>None</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4916</th>\n",
              "      <td>Legion</td>\n",
              "      <td>/show/legion-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Action &amp; Adventure, Drama]</td>\n",
              "      <td>[Science, Supernatural, Psychology, Superhero,...</td>\n",
              "      <td>8.3</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>David Haller, AKA Legion, is a troubled young ...</td>\n",
              "      <td>27 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1730</th>\n",
              "      <td>Chuck</td>\n",
              "      <td>/show/chuck-2007</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Drama]</td>\n",
              "      <td>[Space, Police, Spy, Technology]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>85.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2007</td>\n",
              "      <td>2007-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>When Buy More computer geek Chuck Bartowski un...</td>\n",
              "      <td>90 episodes (99%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8638</th>\n",
              "      <td>The Fall</td>\n",
              "      <td>/show/the-fall-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hoopla, tubi_tv, plex_free, sundancenow...</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Suspense, Police, Serial Killer]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>When the Police Service of Northern Ireland ar...</td>\n",
              "      <td>27 episodes (93%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10406</th>\n",
              "      <td>White Collar</td>\n",
              "      <td>/show/white-collar-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[New York]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Neal Caffrey, a con man, forger and thief, is ...</td>\n",
              "      <td>81 episodes (100%) are available to watch free...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9508</th>\n",
              "      <td>The Walking Dead</td>\n",
              "      <td>/show/the-walking-dead-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amc_premiere, philo, netflix, fubo_tv, amc]</td>\n",
              "      <td>[Horror, Drama]</td>\n",
              "      <td>[Zombie, Dystopia, Survival, Comic Book, Adapt...</td>\n",
              "      <td>8.2</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>10.0</td>\n",
              "      <td>Sheriff's deputy Rick Grimes awakens from a co...</td>\n",
              "      <td>146 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5204</th>\n",
              "      <td>Lucifer</td>\n",
              "      <td>/show/lucifer-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Science-Fiction, Fantasy, Crime]</td>\n",
              "      <td>[Supernatural, Police, Superhero, Comic Book, ...</td>\n",
              "      <td>8.2</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Bored and unhappy as the Lord of Hell, Lucifer...</td>\n",
              "      <td>75 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6320</th>\n",
              "      <td>Orange Is the New Black</td>\n",
              "      <td>/show/orange-is-the-new-black-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Comedy, Crime]</td>\n",
              "      <td>[Based On True Story, Prison]</td>\n",
              "      <td>8.1</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>A crime she committed in her youthful past sen...</td>\n",
              "      <td>91 episodes (99%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5418</th>\n",
              "      <td>Marvel's Jessica Jones</td>\n",
              "      <td>/show/marvels-jessica-jones-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Supernatural, Psychology, Disney, Superhero, ...</td>\n",
              "      <td>7.9</td>\n",
              "      <td>85.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>After a tragic ending to her short-lived super...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5408</th>\n",
              "      <td>Marvel's Agents of S.H.I.E.L.D.</td>\n",
              "      <td>/show/marvels-agents-of-shield-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Drama]</td>\n",
              "      <td>[Supernatural, Disney, Superhero, Comic Book, ...</td>\n",
              "      <td>7.5</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Agent Phil Coulson of S.H.I.E.L.D. (Strategic ...</td>\n",
              "      <td>123 episodes (90%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1a58fdf3-c43e-4d40-949c-6b6b4a4fb883')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
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              "        document.querySelector('#df-1a58fdf3-c43e-4d40-949c-6b6b4a4fb883 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        element.appendChild(docLink);\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    border-radius: 50%;\n",
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              "    display: none;\n",
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              "    height: 32px;\n",
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              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
              "  .colab-df-spinner {\n",
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              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a3f1dbf9-85ce-4763-a909-f68c00d90fc3 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "filtered_question3_df",
              "summary": "{\n  \"name\": \"filtered_question3_df\",\n  \"rows\": 57,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"Breaking Bad\",\n          \"Gravity Falls\",\n          \"The Handmaid's Tale\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"/show/breaking-bad-2008\",\n          \"/show/gravity-falls-2012\",\n          \"/show/the-handmaids-tale-2017\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3381265649647141,\n        \"min\": 7.5,\n        \"max\": 9.5,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          8.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.5118119182883785,\n        \"min\": 38.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 14,\n        \"samples\": [\n          91.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"all\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"TV-G\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6,\n        \"min\": 1989,\n        \"max\": 2019,\n        \"num_unique_values\": 21,\n        \"samples\": [\n          2008\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 21,\n        \"samples\": [\n          \"2008-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.129158866392396,\n        \"min\": 3.0,\n        \"max\": 32.0,\n        \"num_unique_values\": 13,\n        \"samples\": [\n          16.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"When Walter White, a New Mexico chemistry teacher, is diagnosed with Stage III cancer and given a prognosis of only two years left to live. He becomes filled with a sense of fearlessness and an unrelenting desire to secure his family's financial future at any cost as he enters the dangerous world of drugs and crime\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 52,\n        \"samples\": [\n          \"124 episodes (98%) are available to watch free online (Peacock). 124 episodes (98%) are available to stream on a popular subscription service (Netflix, Hulu & 2 others). 11 episodes (9%) are available to stream on a TV everywhere service (NBC & Comedy Central). 124 episodes (98%) are available to rent or buy from $1.99 on 6 services (iTunes, Google Play, Prime Video & 4 others).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "filtered_question3_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S4MjpaVDxEn2",
        "outputId": "4e325b0b-5089-4705-b27b-5938940e0912"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(57, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "genres = [genre for sublist in filtered_question3_df['Genre'] if isinstance(sublist, list) for genre in sublist]\n",
        "\n",
        "# Count the occurrence of each genre and tag\n",
        "genre_counts = pd.Series(genres).value_counts()\n",
        "\n",
        "# Display the counts\n",
        "print(\"Genre Counts:\")\n",
        "print(genre_counts)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Zl8gWj4fKbK",
        "outputId": "13f834a0-9a77-48e1-cace-9f63033fbd54"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Genre Counts:\n",
            "Drama                 37\n",
            "Crime                 22\n",
            "Action & Adventure    21\n",
            "Comedy                16\n",
            "Animation              9\n",
            "Fantasy                9\n",
            "Mystery                7\n",
            "Science-Fiction        6\n",
            "Thriller               6\n",
            "Horror                 5\n",
            "LGBTQ                  4\n",
            "Anime                  2\n",
            "Biography              2\n",
            "History                2\n",
            "Romance                2\n",
            "Sport                  1\n",
            "Documentary            1\n",
            "Stand-up & Talk        1\n",
            "Family                 1\n",
            "Children               1\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Initialize an empty dictionary to store the maximum IMDB score and corresponding title for each genre\n",
        "max_imdb_by_genre = {}\n",
        "\n",
        "# Iterate over each row in the DataFrame\n",
        "for index, row in filtered_question3_df.iterrows():\n",
        "    # Iterate over each genre in the 'Genre' list of the current row\n",
        "    for genre in row['Genre']:\n",
        "        # Check if the genre already exists in the dictionary\n",
        "        if genre in max_imdb_by_genre:\n",
        "            # If it exists, update the maximum IMDB score and corresponding title if the current score is higher\n",
        "            if row['IMDB'] > max_imdb_by_genre[genre]['IMDB']:\n",
        "                max_imdb_by_genre[genre] = {'Title': row['Title'], 'IMDB': row['IMDB']}\n",
        "        else:\n",
        "            # If it doesn't exist, add the genre to the dictionary with the current IMDB score and title\n",
        "            max_imdb_by_genre[genre] = {'Title': row['Title'], 'IMDB': row['IMDB']}\n",
        "\n",
        "# Convert the dictionary to a pandas DataFrame for easier manipulation\n",
        "max_imdb_by_genre_df = pd.DataFrame.from_dict(max_imdb_by_genre, orient='index')\n",
        "\n",
        "# Display the result\n",
        "print(\"Top IMDB Score and Title by Genre:\")\n",
        "print(max_imdb_by_genre_df)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xOzNj6txh3sE",
        "outputId": "74e4be26-6099-417f-8bd1-c08f12193cdb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top IMDB Score and Title by Genre:\n",
            "                                        Title  IMDB\n",
            "Drama                            Breaking Bad   9.5\n",
            "Crime                            Breaking Bad   9.5\n",
            "Documentary                            Cosmos   9.3\n",
            "Sport                           Horsepower TV   9.2\n",
            "Comedy                         Rick and Morty   9.2\n",
            "Action & Adventure             Rick and Morty   9.2\n",
            "Animation                      Rick and Morty   9.2\n",
            "Science-Fiction                Rick and Morty   9.2\n",
            "Fantasy                         Gravity Falls   8.9\n",
            "Anime                         Attack on Titan   8.8\n",
            "Mystery                                  Dark   8.8\n",
            "Biography                              Narcos   8.8\n",
            "Horror                        Stranger Things   8.8\n",
            "History                             The Crown   8.7\n",
            "Stand-up & Talk     The Marvelous Mrs. Maisel   8.7\n",
            "Family                           The Simpsons   8.7\n",
            "Children                       Adventure Time   8.6\n",
            "Thriller                            Mr. Robot   8.5\n",
            "Romance                      The Last Kingdom   8.4\n",
            "LGBTQ                           Sex Education   8.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Initialize an empty dictionary to store the top 3 IMDB scores and corresponding titles for each genre\n",
        "top_imdb_by_genre = {}\n",
        "\n",
        "# Iterate over each row in the DataFrame\n",
        "for index, row in filtered_question3_df.iterrows():\n",
        "    # Iterate over each genre in the 'Genre' list of the current row\n",
        "    for genre in row['Genre']:\n",
        "        # Check if the genre already exists in the dictionary\n",
        "        if genre in top_imdb_by_genre:\n",
        "            # If it exists, update the list of top 5 IMDB scores and corresponding titles\n",
        "            top_imdb_by_genre[genre].append({'Title': row['Title'], 'IMDB': row['IMDB']})\n",
        "            top_imdb_by_genre[genre] = sorted(top_imdb_by_genre[genre], key=lambda x: x['IMDB'], reverse=True)[:3]\n",
        "        else:\n",
        "            # If it doesn't exist, add the genre to the dictionary with the current IMDB score and title\n",
        "            top_imdb_by_genre[genre] = [{'Title': row['Title'], 'IMDB': row['IMDB']}]\n",
        "\n",
        "# Convert the dictionary to a pandas DataFrame for easier manipulation\n",
        "top_imdb_by_genre_df = pd.DataFrame.from_dict({genre: data for genre, data in top_imdb_by_genre.items()}, orient='index')\n",
        "\n",
        "# Display the result\n",
        "print(\"Top 3 TV Shows by IMDB Score for Each Genre:\")\n",
        "print(top_imdb_by_genre_df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wUN7N4PQDxxZ",
        "outputId": "3b7def3d-4f90-4f1a-a895-396eb82f2b00"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Top 3 TV Shows by IMDB Score for Each Genre:\n",
            "                                                                    0  \\\n",
            "Drama                          {'Title': 'Breaking Bad', 'IMDB': 9.5}   \n",
            "Crime                          {'Title': 'Breaking Bad', 'IMDB': 9.5}   \n",
            "Documentary                          {'Title': 'Cosmos', 'IMDB': 9.3}   \n",
            "Sport                         {'Title': 'Horsepower TV', 'IMDB': 9.2}   \n",
            "Comedy                       {'Title': 'Rick and Morty', 'IMDB': 9.2}   \n",
            "Action & Adventure           {'Title': 'Rick and Morty', 'IMDB': 9.2}   \n",
            "Animation                    {'Title': 'Rick and Morty', 'IMDB': 9.2}   \n",
            "Science-Fiction              {'Title': 'Rick and Morty', 'IMDB': 9.2}   \n",
            "Fantasy                       {'Title': 'Gravity Falls', 'IMDB': 8.9}   \n",
            "Anime                       {'Title': 'Attack on Titan', 'IMDB': 8.8}   \n",
            "Mystery                                {'Title': 'Dark', 'IMDB': 8.8}   \n",
            "Biography                            {'Title': 'Narcos', 'IMDB': 8.8}   \n",
            "Horror                      {'Title': 'Stranger Things', 'IMDB': 8.8}   \n",
            "History                           {'Title': 'The Crown', 'IMDB': 8.7}   \n",
            "Stand-up & Talk     {'Title': 'The Marvelous Mrs. Maisel', 'IMDB':...   \n",
            "Family                         {'Title': 'The Simpsons', 'IMDB': 8.7}   \n",
            "Children                     {'Title': 'Adventure Time', 'IMDB': 8.6}   \n",
            "Thriller                          {'Title': 'Mr. Robot', 'IMDB': 8.5}   \n",
            "Romance                    {'Title': 'The Last Kingdom', 'IMDB': 8.4}   \n",
            "LGBTQ                         {'Title': 'Sex Education', 'IMDB': 8.3}   \n",
            "\n",
            "                                                                  1  \\\n",
            "Drama                            {'Title': 'Sherlock', 'IMDB': 9.1}   \n",
            "Crime                            {'Title': 'Sherlock', 'IMDB': 9.1}   \n",
            "Documentary                                                    None   \n",
            "Sport                                                          None   \n",
            "Comedy                      {'Title': 'Gravity Falls', 'IMDB': 8.9}   \n",
            "Action & Adventure               {'Title': 'Sherlock', 'IMDB': 9.1}   \n",
            "Animation                   {'Title': 'Gravity Falls', 'IMDB': 8.9}   \n",
            "Science-Fiction              {'Title': 'Black Mirror', 'IMDB': 8.8}   \n",
            "Fantasy                      {'Title': 'Black Mirror', 'IMDB': 8.8}   \n",
            "Anime                    {'Title': 'My Hero Academia', 'IMDB': 8.5}   \n",
            "Mystery                             {'Title': 'House', 'IMDB': 8.7}   \n",
            "Biography            {'Title': 'American Crime Story', 'IMDB': 8.4}   \n",
            "Horror                           {'Title': 'Hannibal', 'IMDB': 8.5}   \n",
            "History                  {'Title': 'The Last Kingdom', 'IMDB': 8.4}   \n",
            "Stand-up & Talk                                                None   \n",
            "Family                                                         None   \n",
            "Children                                                       None   \n",
            "Thriller                      {'Title': 'Money Heist', 'IMDB': 8.4}   \n",
            "Romance             {'Title': 'How I Met Your Mother', 'IMDB': 8.3}   \n",
            "LGBTQ                         {'Title': 'Killing Eve', 'IMDB': 8.3}   \n",
            "\n",
            "                                                                    2  \n",
            "Drama                         {'Title': 'The West Wing', 'IMDB': 8.8}  \n",
            "Crime                                  {'Title': 'Dark', 'IMDB': 8.8}  \n",
            "Documentary                                                      None  \n",
            "Sport                                                            None  \n",
            "Comedy              {'Title': 'It's Always Sunny in Philadelphia',...  \n",
            "Action & Adventure            {'Title': 'Gravity Falls', 'IMDB': 8.9}  \n",
            "Animation                   {'Title': 'Attack on Titan', 'IMDB': 8.8}  \n",
            "Science-Fiction                 {'Title': 'The X-Files', 'IMDB': 8.6}  \n",
            "Fantasy                     {'Title': 'Stranger Things', 'IMDB': 8.8}  \n",
            "Anime                                                            None  \n",
            "Mystery                              {'Title': 'Dexter', 'IMDB': 8.6}  \n",
            "Biography                                                        None  \n",
            "Horror              {'Title': 'What We Do in the Shadows', 'IMDB':...  \n",
            "History                                                          None  \n",
            "Stand-up & Talk                                                  None  \n",
            "Family                                                           None  \n",
            "Children                                                         None  \n",
            "Thriller                              {'Title': 'Ozark', 'IMDB': 8.4}  \n",
            "Romance                                                          None  \n",
            "LGBTQ                                {'Title': 'Sense8', 'IMDB': 8.3}  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "tags = [tag for sublist in filtered_question3_df['Tag'] if isinstance(sublist, list) for tag in sublist]\n",
        "tag_counts = pd.Series(tags).value_counts()\n",
        "print(tag_counts)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6kgnT135fSNF",
        "outputId": "f9cd19bd-c7e6-4c14-a7c8-103e96bc54f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Supernatural           15\n",
            "Adaptation             13\n",
            "Political              11\n",
            "Space                   9\n",
            "Police                  7\n",
            "Science                 7\n",
            "Serial Killer           7\n",
            "Spy                     6\n",
            "Friendship              6\n",
            "Superhero               6\n",
            "Gangster                6\n",
            "Comic Book              6\n",
            "Drug                    6\n",
            "Dystopia                5\n",
            "Psychology              5\n",
            "Mature                  5\n",
            "Feel-good               5\n",
            "Based on Books          4\n",
            "Suspense                4\n",
            "Disney                  4\n",
            "Time Travel             4\n",
            "Religion                4\n",
            "Vampire                 4\n",
            "Doctor                  4\n",
            "Prison                  3\n",
            "New York                3\n",
            "Royalty                 3\n",
            "Monster                 3\n",
            "Based On True Story     3\n",
            "War                     3\n",
            "Technology              2\n",
            "Apocalypse              2\n",
            "Racing                  2\n",
            "Princess                2\n",
            "Ghost                   2\n",
            "Alien                   2\n",
            "Cartoon                 2\n",
            "Teacher                 2\n",
            "Parody                  2\n",
            "High School             2\n",
            "Revenge                 2\n",
            "Fighting                1\n",
            "College                 1\n",
            "Escape                  1\n",
            "Teen                    1\n",
            "Coming of Age           1\n",
            "Martial Arts            1\n",
            "Zombie                  1\n",
            "Magic                   1\n",
            "Heroism                 1\n",
            "Futuristic              1\n",
            "Robot                   1\n",
            "Military                1\n",
            "Disaster                1\n",
            "Animal                  1\n",
            "Genius                  1\n",
            "World War II            1\n",
            "Survival                1\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "filtered_question3_df.sort_values(by = 'IMDB', ascending = False)\n",
        "# (by='Service', key=lambda x: x.str.len(), ascending=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0JTNSV3uMBuP",
        "outputId": "157fa66d-50cf-46e4-a7e8-42f09a124e71"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                   Title  \\\n",
              "1336                        Breaking Bad   \n",
              "1920                              Cosmos   \n",
              "3969                       Horsepower TV   \n",
              "7003                      Rick and Morty   \n",
              "7483                            Sherlock   \n",
              "3515                       Gravity Falls   \n",
              "6475                      Peaky Blinders   \n",
              "7914                     Stranger Things   \n",
              "1156                        Black Mirror   \n",
              "6032                              Narcos   \n",
              "9526                       The West Wing   \n",
              "2128                                Dark   \n",
              "4361   It's Always Sunny in Philadelphia   \n",
              "709                      Attack on Titan   \n",
              "9007           The Marvelous Mrs. Maisel   \n",
              "9342                        The Simpsons   \n",
              "7699                          South Park   \n",
              "8519                           The Crown   \n",
              "4002                               House   \n",
              "1241                     BoJack Horseman   \n",
              "9619                          This Is Us   \n",
              "6448                Parks and Recreation   \n",
              "2339                              Dexter   \n",
              "5412                  Marvel's Daredevil   \n",
              "9576                         The X-Files   \n",
              "4556                           Justified   \n",
              "275                       Adventure Time   \n",
              "8763                 The Handmaid's Tale   \n",
              "5900                    My Hero Academia   \n",
              "10366          What We Do in the Shadows   \n",
              "5782                           Mr. Robot   \n",
              "8626                         The Expanse   \n",
              "3663                            Hannibal   \n",
              "8923                    The Last Kingdom   \n",
              "1377                         Broadchurch   \n",
              "1389                  Brooklyn Nine-Nine   \n",
              "8295                       The Americans   \n",
              "8018                        Supernatural   \n",
              "8944                 The Legend of Korra   \n",
              "473                 American Crime Story   \n",
              "5682                         Money Heist   \n",
              "6388                               Ozark   \n",
              "4675                         Killing Eve   \n",
              "4916                              Legion   \n",
              "7401                              Sense8   \n",
              "4028               How I Met Your Mother   \n",
              "7425                       Sex Education   \n",
              "64                                    24   \n",
              "6686                        Prison Break   \n",
              "1730                               Chuck   \n",
              "8638                            The Fall   \n",
              "10406                       White Collar   \n",
              "9508                    The Walking Dead   \n",
              "5204                             Lucifer   \n",
              "6320             Orange Is the New Black   \n",
              "5418              Marvel's Jessica Jones   \n",
              "5408     Marvel's Agents of S.H.I.E.L.D.   \n",
              "\n",
              "                                               URL Type  \\\n",
              "1336                       /show/breaking-bad-2008   tv   \n",
              "1920         /show/cosmos-a-spacetime-odyssey-2014   tv   \n",
              "3969                         /show/horsepower-2006   tv   \n",
              "7003                     /show/rick-and-morty-2013   tv   \n",
              "7483                           /show/sherlock-2010   tv   \n",
              "3515                      /show/gravity-falls-2012   tv   \n",
              "6475                     /show/peaky-blinders-2013   tv   \n",
              "7914                    /show/stranger-things-2016   tv   \n",
              "1156                       /show/black-mirror-2011   tv   \n",
              "6032                             /show/narcos-2015   tv   \n",
              "9526                      /show/the-west-wing-1999   tv   \n",
              "2128                               /show/dark-2017   tv   \n",
              "4361   /show/its-always-sunny-in-philadelphia-2005   tv   \n",
              "709                     /show/attack-on-titan-2013   tv   \n",
              "9007           /show/the-marvelous-mrs-maisel-2017   tv   \n",
              "9342                       /show/the-simpsons-1989   tv   \n",
              "7699                         /show/south-park-1997   tv   \n",
              "8519                          /show/the-crown-2016   tv   \n",
              "4002                              /show/house-2004   tv   \n",
              "1241                    /show/bojack-horseman-2014   tv   \n",
              "9619                         /show/this-is-us-2016   tv   \n",
              "6448               /show/parks-and-recreation-2009   tv   \n",
              "2339                             /show/dexter-2006   tv   \n",
              "5412                  /show/marvels-daredevil-2015   tv   \n",
              "9576                        /show/the-x-files-1993   tv   \n",
              "4556                          /show/justified-2010   tv   \n",
              "275                      /show/adventure-time-2010   tv   \n",
              "8763                 /show/the-handmaids-tale-2017   tv   \n",
              "5900                   /show/my-hero-academia-2016   tv   \n",
              "10366         /show/what-we-do-in-the-shadows-2019   tv   \n",
              "5782                           /show/mr-robot-2015   tv   \n",
              "8626                        /show/the-expanse-2015   tv   \n",
              "3663                           /show/hannibal-2013   tv   \n",
              "8923                   /show/the-last-kingdom-2015   tv   \n",
              "1377                        /show/broadchurch-2013   tv   \n",
              "1389                 /show/brooklyn-nine-nine-2013   tv   \n",
              "8295                      /show/the-americans-2013   tv   \n",
              "8018                       /show/supernatural-2005   tv   \n",
              "8944                /show/the-legend-of-korra-2012   tv   \n",
              "473                /show/american-crime-story-2016   tv   \n",
              "5682                        /show/money-heist-2017   tv   \n",
              "6388                              /show/ozark-2017   tv   \n",
              "4675                        /show/killing-eve-2018   tv   \n",
              "4916                             /show/legion-2017   tv   \n",
              "7401                             /show/sense8-2015   tv   \n",
              "4028              /show/how-i-met-your-mother-2005   tv   \n",
              "7425                      /show/sex-education-2019   tv   \n",
              "64                                   /show/24-2001   tv   \n",
              "6686                       /show/prison-break-2005   tv   \n",
              "1730                              /show/chuck-2007   tv   \n",
              "8638                           /show/the-fall-2013   tv   \n",
              "10406                      /show/white-collar-2009   tv   \n",
              "9508                   /show/the-walking-dead-2010   tv   \n",
              "5204                            /show/lucifer-2016   tv   \n",
              "6320            /show/orange-is-the-new-black-2013   tv   \n",
              "5418              /show/marvels-jessica-jones-2015   tv   \n",
              "5408           /show/marvels-agents-of-shield-2013   tv   \n",
              "\n",
              "                                                 Service  \\\n",
              "1336                                           [netflix]   \n",
              "1920   [natgeo, free, tubi_tv, fox, fox_tveverywhere,...   \n",
              "3969                                      [amazon_prime]   \n",
              "7003   [free, hulu_plus, hoopla, fubo_tv, adult_swim_...   \n",
              "7483                                           [netflix]   \n",
              "3515   [disneynow, free, disneynow_free, hulu_plus, d...   \n",
              "6475                                           [netflix]   \n",
              "7914                                           [netflix]   \n",
              "1156                                           [netflix]   \n",
              "6032                                           [netflix]   \n",
              "9526                                           [netflix]   \n",
              "2128                                           [netflix]   \n",
              "4361   [philo, fx_tveverywhere, fox_tveverywhere, vic...   \n",
              "709    [adult_swim_tveverywhere, crunchyroll_premium,...   \n",
              "9007                                      [amazon_prime]   \n",
              "9342   [free, fox, fx_tveverywhere, fubo_tv, hulu_plu...   \n",
              "7699   [comedy, free, hulu_plus, philo, fubo_tv, come...   \n",
              "8519                                           [netflix]   \n",
              "4002   [nbc, free, peacock, nbc_tveverywhere, amazon_...   \n",
              "1241                                           [netflix]   \n",
              "9619   [nbc, free, nbc_tveverywhere, fubo_tv, hulu_pl...   \n",
              "6448   [free, philo, nbc_tveverywhere, amazon_prime, ...   \n",
              "2339   [free, showtime, netflix, fubo_tv, showtime_free]   \n",
              "5412                                           [netflix]   \n",
              "9576      [free, philo, fox, bbc_america_tve, hulu_plus]   \n",
              "4556                                         [hulu_plus]   \n",
              "275    [free, cartoon_network_free, hulu_plus, hoopla...   \n",
              "8763                                         [hulu_plus]   \n",
              "5900   [adult_swim_tveverywhere, crunchyroll_premium,...   \n",
              "10366                                        [hulu_plus]   \n",
              "5782                                      [amazon_prime]   \n",
              "8626                                      [amazon_prime]   \n",
              "3663                                           [netflix]   \n",
              "8923                                           [netflix]   \n",
              "1377                                           [netflix]   \n",
              "1389   [nbc, free, peacock, nbc_tveverywhere, fubo_tv...   \n",
              "8295                                      [amazon_prime]   \n",
              "8018                [free, thecw, netflix, tnt, fubo_tv]   \n",
              "8944   [free, hoopla, abc_news, netflix, cbs_all_access]   \n",
              "473                                            [netflix]   \n",
              "5682                                           [netflix]   \n",
              "6388                                           [netflix]   \n",
              "4675   [amc_premiere, philo, bbc_america_tve, fubo_tv...   \n",
              "4916                                         [hulu_plus]   \n",
              "7401                                           [netflix]   \n",
              "4028                                         [hulu_plus]   \n",
              "7425                                           [netflix]   \n",
              "64                                           [hulu_plus]   \n",
              "6686                                         [hulu_plus]   \n",
              "1730                                      [amazon_prime]   \n",
              "8638   [free, hoopla, tubi_tv, plex_free, sundancenow...   \n",
              "10406                                        [hulu_plus]   \n",
              "9508        [amc_premiere, philo, netflix, fubo_tv, amc]   \n",
              "5204                                           [netflix]   \n",
              "6320                                           [netflix]   \n",
              "5418                                           [netflix]   \n",
              "5408                                           [netflix]   \n",
              "\n",
              "                                                   Genre  \\\n",
              "1336                                      [Drama, Crime]   \n",
              "1920                                       [Documentary]   \n",
              "3969                                             [Sport]   \n",
              "7003   [Comedy, Action & Adventure, Animation, Scienc...   \n",
              "7483                  [Action & Adventure, Drama, Crime]   \n",
              "3515    [Comedy, Action & Adventure, Fantasy, Animation]   \n",
              "6475                                      [Drama, Crime]   \n",
              "7914                            [Horror, Fantasy, Drama]   \n",
              "1156                   [Science-Fiction, Fantasy, Drama]   \n",
              "6032                           [Biography, Drama, Crime]   \n",
              "9526                                             [Drama]   \n",
              "2128                             [Mystery, Drama, Crime]   \n",
              "4361                                            [Comedy]   \n",
              "709               [Action & Adventure, Animation, Anime]   \n",
              "9007                    [Stand-up & Talk, Comedy, Drama]   \n",
              "9342                         [Comedy, Animation, Family]   \n",
              "7699                                 [Comedy, Animation]   \n",
              "8519                                    [History, Drama]   \n",
              "4002                            [Comedy, Mystery, Drama]   \n",
              "1241                          [Animation, Comedy, Drama]   \n",
              "9619                                     [Comedy, Drama]   \n",
              "6448                                            [Comedy]   \n",
              "2339                             [Mystery, Drama, Crime]   \n",
              "5412                  [Action & Adventure, Drama, Crime]   \n",
              "9576                   [Science-Fiction, Mystery, Drama]   \n",
              "4556                  [Action & Adventure, Drama, Crime]   \n",
              "275    [Action & Adventure, Fantasy, Animation, Child...   \n",
              "8763                            [Science-Fiction, Drama]   \n",
              "5900              [Action & Adventure, Animation, Anime]   \n",
              "10366                          [Horror, Comedy, Fantasy]   \n",
              "5782                            [Thriller, Drama, Crime]   \n",
              "8626                [Action & Adventure, Fantasy, Drama]   \n",
              "3663                              [Horror, Drama, Crime]   \n",
              "8923              [Romance, Action & Adventure, History]   \n",
              "1377                             [Mystery, Drama, Crime]   \n",
              "1389                 [Comedy, Action & Adventure, Crime]   \n",
              "8295                             [Mystery, Drama, Crime]   \n",
              "8018                            [Horror, Fantasy, Drama]   \n",
              "8944                     [Action & Adventure, Animation]   \n",
              "473                            [Biography, Drama, Crime]   \n",
              "5682               [Action & Adventure, Thriller, Crime]   \n",
              "6388                            [Thriller, Drama, Crime]   \n",
              "4675               [LGBTQ, Action & Adventure, Thriller]   \n",
              "4916        [Science-Fiction, Action & Adventure, Drama]   \n",
              "7401                             [LGBTQ, Mystery, Drama]   \n",
              "4028                                   [Romance, Comedy]   \n",
              "7425                              [LGBTQ, Comedy, Drama]   \n",
              "64                 [Action & Adventure, Thriller, Drama]   \n",
              "6686                  [Action & Adventure, Drama, Crime]   \n",
              "1730                 [Comedy, Action & Adventure, Drama]   \n",
              "8638                            [Thriller, Drama, Crime]   \n",
              "10406                 [Action & Adventure, Drama, Crime]   \n",
              "9508                                     [Horror, Drama]   \n",
              "5204                   [Science-Fiction, Fantasy, Crime]   \n",
              "6320                              [LGBTQ, Comedy, Crime]   \n",
              "5418                  [Action & Adventure, Drama, Crime]   \n",
              "5408                [Action & Adventure, Fantasy, Drama]   \n",
              "\n",
              "                                                     Tag  IMDB  ReelGood  \\\n",
              "1336      [Gangster, High School, Doctor, Drug, Teacher]   9.5     100.0   \n",
              "1920                                    [Space, Science]   9.3      82.0   \n",
              "3969                                            [Racing]   9.2      38.0   \n",
              "7003                [Time Travel, Space, Science, Alien]   9.2      96.0   \n",
              "7483         [Based on Books, Adaptation, Serial Killer]   9.1      94.0   \n",
              "3515                              [Supernatural, Disney]   8.9      87.0   \n",
              "6475         [Gangster, War, Drug, World War II, Racing]   8.8      91.0   \n",
              "7914   [Space, Science, Supernatural, Monster, Friend...   8.8      96.0   \n",
              "1156                       [Dystopia, Space, Technology]   8.8      92.0   \n",
              "6032               [Based On True Story, Gangster, Drug]   8.8      90.0   \n",
              "9526                                    [Political, Spy]   8.8      85.0   \n",
              "2128                               [Time Travel, Police]   8.8      94.0   \n",
              "4361                             [Friendship, Political]   8.8      90.0   \n",
              "709    [Supernatural, Dystopia, Monster, Political, A...   8.8      92.0   \n",
              "9007                               [New York, Feel-good]   8.7      87.0   \n",
              "9342   [Vampire, Cartoon, Supernatural, Parody, Frien...   8.7      91.0   \n",
              "7699   [Mature, Political, Feel-good, Time Travel, Pa...   8.7      90.0   \n",
              "8519                      [Political, Princess, Royalty]   8.7      88.0   \n",
              "4002                                      [Doctor, Drug]   8.7      92.0   \n",
              "1241   [Mature, Space, Psychology, Genius, Animal, Drug]   8.7      86.0   \n",
              "9619                                         [Feel-good]   8.7      87.0   \n",
              "6448                                         [Political]   8.6      90.0   \n",
              "2339         [Based on Books, Adaptation, Serial Killer]   8.6      91.0   \n",
              "5412   [Supernatural, Disney, Superhero, Comic Book, ...   8.6      90.0   \n",
              "9576   [Space, Vampire, Science, Alien, Supernatural,...   8.6      87.0   \n",
              "4556                                [Military, Gangster]   8.6      87.0   \n",
              "275                  [Magic, Princess, Cartoon, Royalty]   8.6      87.0   \n",
              "8763   [Dystopia, Political, Based on Books, Doctor, ...   8.5      88.0   \n",
              "5900   [Revenge, Supernatural, High School, Superhero...   8.5      88.0   \n",
              "10366                            [Vampire, Supernatural]   8.5      85.0   \n",
              "5782                          [Robot, Suspense, Science]   8.5      92.0   \n",
              "8626              [Dystopia, Science, Space, Futuristic]   8.5      89.0   \n",
              "3663                                     [Serial Killer]   8.5      89.0   \n",
              "8923                                [Political, Royalty]   8.4      86.0   \n",
              "1377                   [Police, Serial Killer, Religion]   8.4      86.0   \n",
              "1389                             [New York, Police, War]   8.4      91.0   \n",
              "8295                               [Political, War, Spy]   8.4      87.0   \n",
              "8018   [Vampire, Supernatural, Monster, Time Travel, ...   8.4      93.0   \n",
              "8944   [Supernatural, Political, Martial Arts, Feel-g...   8.4      87.0   \n",
              "473    [Based On True Story, Police, Adaptation, Seri...   8.4      86.0   \n",
              "5682                                            [Mature]   8.4      91.0   \n",
              "6388                                    [Gangster, Drug]   8.4      89.0   \n",
              "4675            [Based on Books, Psychology, Adaptation]   8.3      87.0   \n",
              "4916   [Science, Supernatural, Psychology, Superhero,...   8.3      85.0   \n",
              "7401                       [Mature, Space, Supernatural]   8.3      86.0   \n",
              "4028                               [Friendship, College]   8.3      89.0   \n",
              "7425                           [Mature, Teen, Feel-good]   8.3      91.0   \n",
              "64                     [Revenge, Political, Spy, Prison]   8.3      85.0   \n",
              "6686   [Gangster, Psychology, Escape, Prison, Suspens...   8.3      88.0   \n",
              "1730                    [Space, Police, Spy, Technology]   8.2      85.0   \n",
              "8638                   [Suspense, Police, Serial Killer]   8.2      89.0   \n",
              "10406                                         [New York]   8.2      85.0   \n",
              "9508   [Zombie, Dystopia, Survival, Comic Book, Adapt...   8.2      91.0   \n",
              "5204   [Supernatural, Police, Superhero, Comic Book, ...   8.2      91.0   \n",
              "6320                       [Based On True Story, Prison]   8.1      87.0   \n",
              "5418   [Supernatural, Psychology, Disney, Superhero, ...   7.9      85.0   \n",
              "5408   [Supernatural, Disney, Superhero, Comic Book, ...   7.5      87.0   \n",
              "\n",
              "      AgeRating  Rated  Released Year Duration Year  Seasons  \\\n",
              "1336        18+  TV-MA           2008     2008-2020      5.0   \n",
              "1920        all   TV-G           2014     2014-2020      3.0   \n",
              "3969        all   TV-G           2006     2006-2020      9.0   \n",
              "7003        18+  TV-MA           2013     2013-2020      4.0   \n",
              "7483        16+  TV-14           2010     2010-2020      4.0   \n",
              "3515         7+  TV-PG           2012     2012-2020      3.0   \n",
              "6475        18+  TV-MA           2013     2013-2020      7.0   \n",
              "7914        16+  TV-14           2016     2016-2020      4.0   \n",
              "1156        18+  TV-MA           2011     2011-2020      5.0   \n",
              "6032        18+  TV-MA           2015     2015-2020      4.0   \n",
              "9526        16+  TV-14           1999     1999-2020      7.0   \n",
              "2128        16+  TV-14           2017     2017-2020      3.0   \n",
              "4361        18+  TV-MA           2005     2005-2020     15.0   \n",
              "709         16+  TV-MA           2013     2013-2020      3.0   \n",
              "9007        18+  TV-MA           2017     2017-2020      4.0   \n",
              "9342         7+  TV-PG           1989     1989-2020     32.0   \n",
              "7699        18+  TV-MA           1997     1997-2020     24.0   \n",
              "8519        18+  TV-MA           2016     2016-2020      4.0   \n",
              "4002        16+  TV-14           2004     2004-2020      8.0   \n",
              "1241        18+  TV-MA           2014     2014-2020      6.0   \n",
              "9619        16+  TV-14           2016     2016-2020      5.0   \n",
              "6448        16+  TV-14           2009     2009-2020      7.0   \n",
              "2339        18+  TV-MA           2006     2006-2020      8.0   \n",
              "5412        18+  TV-MA           2015     2015-2020      3.0   \n",
              "9576        16+  TV-14           1993     1993-2020     11.0   \n",
              "4556        18+  TV-MA           2010     2010-2020      6.0   \n",
              "275          7+  TV-PG           2010     2010-2020     11.0   \n",
              "8763        18+  TV-MA           2017     2017-2020      4.0   \n",
              "5900        16+  TV-14           2016     2016-2020      5.0   \n",
              "10366       18+  TV-MA           2019     2019-2020      3.0   \n",
              "5782        18+  TV-MA           2015     2015-2020      4.0   \n",
              "8626        16+  TV-14           2015     2015-2020      5.0   \n",
              "3663        18+  TV-MA           2013     2013-2020      3.0   \n",
              "8923        18+  TV-MA           2015     2015-2020      4.0   \n",
              "1377        18+  TV-MA           2013     2013-2020      3.0   \n",
              "1389        16+  TV-14           2013     2013-2020      8.0   \n",
              "8295        18+  TV-MA           2013     2013-2020      6.0   \n",
              "8018        16+  TV-14           2005     2005-2020     16.0   \n",
              "8944         7+  TV-PG           2012     2012-2020      4.0   \n",
              "473         18+  TV-MA           2016     2016-2020      4.0   \n",
              "5682        18+  TV-MA           2017     2017-2020      3.0   \n",
              "6388        18+  TV-MA           2017     2017-2020      3.0   \n",
              "4675        16+  TV-14           2018     2018-2020      4.0   \n",
              "4916        16+  TV-14           2017     2017-2020      3.0   \n",
              "7401        18+  TV-MA           2015     2015-2020      3.0   \n",
              "4028        16+  TV-14           2005     2005-2020      9.0   \n",
              "7425        16+  TV-14           2019     2019-2020      3.0   \n",
              "64          16+  TV-14           2001     2001-2020      9.0   \n",
              "6686        16+  TV-14           2005     2005-2020      6.0   \n",
              "1730         7+  TV-PG           2007     2007-2020      5.0   \n",
              "8638        18+  TV-MA           2013     2013-2020      3.0   \n",
              "10406       16+  TV-14           2009     2009-2020      6.0   \n",
              "9508        18+  TV-MA           2010     2010-2020     10.0   \n",
              "5204        16+  TV-14           2016     2016-2020      5.0   \n",
              "6320        18+  TV-MA           2013     2013-2020      7.0   \n",
              "5418        18+  TV-MA           2015     2015-2020      3.0   \n",
              "5408        16+  TV-14           2013     2013-2020      7.0   \n",
              "\n",
              "                                         What it's about  \\\n",
              "1336   When Walter White, a New Mexico chemistry teac...   \n",
              "1920   Famed astrophysicist Neil deGrasse Tyson provi...   \n",
              "3969   Every gearhead wants power and this show revea...   \n",
              "7003   Rick is a mentally-unbalanced but scientifical...   \n",
              "7483   A modern update finds the famous sleuth and hi...   \n",
              "3515   Twin brother and sister Dipper and Mabel Pines...   \n",
              "6475   A gangster family epic set in 1919 Birmingham,...   \n",
              "7914   When a young boy vanishes, a small town uncove...   \n",
              "1156   A contemporary British re-working of The Twili...   \n",
              "6032   A gritty chronicle of the war against Colombia...   \n",
              "9526   The West Wing provides a glimpse into presiden...   \n",
              "2128   A missing child causes four families to help e...   \n",
              "4361   Four egocentric friends who run a neighborhood...   \n",
              "709    Several hundred years ago, humans were nearly ...   \n",
              "9007   It’s 1958 Manhattan and Miriam “Midge” Maisel ...   \n",
              "9342   Set in Springfield, the average American town,...   \n",
              "7699   Follows the misadventures of four irreverent g...   \n",
              "8519   The gripping, decades-spanning inside story of...   \n",
              "4002   Dr. Gregory House, a drug-addicted, unconventi...   \n",
              "1241   Meet the most beloved sitcom horse of the 90s ...   \n",
              "9619   Follows the lives and families of three adults...   \n",
              "6448   Hilarious ensemble comedy that follows Leslie ...   \n",
              "2339   Dexter Morgan, a blood spatter pattern analyst...   \n",
              "5412   Lawyer-by-day Matt Murdock uses his heightened...   \n",
              "9576   The exploits of FBI Special Agents Fox Mulder ...   \n",
              "4556   A character drama based on the 2001 Elmore Leo...   \n",
              "275    Hook up with Finn and Jake as they travel the ...   \n",
              "8763   Set in a dystopian future, a woman is forced t...   \n",
              "5900   In a world where eighty percent of the populat...   \n",
              "10366  A documentary-style look into the daily (or ra...   \n",
              "5782   A contemporary and culturally resonant drama a...   \n",
              "8626   A thriller set two hundred years in the future...   \n",
              "3663   Both a gift and a curse, Graham has the extrao...   \n",
              "8923   A show of heroic deeds and epic battles with a...   \n",
              "1377   The murder of a young boy in a small coastal t...   \n",
              "1389   A single-camera ensemble comedy following the ...   \n",
              "8295   Set during the Cold War period in the 1980s, T...   \n",
              "8018   When they were boys, Sam and Dean Winchester l...   \n",
              "8944   Avatar Korra, a headstrong, rebellious, feisty...   \n",
              "473    An anthology series centered around some of hi...   \n",
              "5682   To carry out the biggest heist in history, a m...   \n",
              "6388   A financial adviser drags his family from Chic...   \n",
              "4675   A security consultant hunts for a ruthless ass...   \n",
              "4916   David Haller, AKA Legion, is a troubled young ...   \n",
              "7401   One gunshot, one death, one moment out of time...   \n",
              "4028   A father recounts to his children - through a ...   \n",
              "7425   Inexperienced Otis channels his sex therapist ...   \n",
              "64     24 is an American television series produced f...   \n",
              "6686   Due to a political conspiracy, an innocent man...   \n",
              "1730   When Buy More computer geek Chuck Bartowski un...   \n",
              "8638   When the Police Service of Northern Ireland ar...   \n",
              "10406  Neal Caffrey, a con man, forger and thief, is ...   \n",
              "9508   Sheriff's deputy Rick Grimes awakens from a co...   \n",
              "5204   Bored and unhappy as the Lord of Hell, Lucifer...   \n",
              "6320   A crime she committed in her youthful past sen...   \n",
              "5418   After a tragic ending to her short-lived super...   \n",
              "5408   Agent Phil Coulson of S.H.I.E.L.D. (Strategic ...   \n",
              "\n",
              "                                          Where to Watch  \\\n",
              "1336   62 episodes (100%) are available to stream on ...   \n",
              "1920   2 episodes (7%) are available to watch free on...   \n",
              "3969   14 episodes (8%) are available to stream on a ...   \n",
              "7003   5 episodes (12%) are available to watch free o...   \n",
              "7483   12 episodes (92%) are available to stream on a...   \n",
              "3515   2 episodes (5%) are available to watch free on...   \n",
              "6475   30 episodes (100%) are available to stream on ...   \n",
              "7914   25 episodes (100%) are available to stream on ...   \n",
              "1156   21 episodes (95%) are available to stream on a...   \n",
              "6032   30 episodes (100%) are available to stream on ...   \n",
              "9526   155 episodes (100%) are available to stream on...   \n",
              "2128   26 episodes (100%) are available to stream on ...   \n",
              "4361   146 episodes (95%) are available to stream on ...   \n",
              "709    59 episodes (98%) are available to watch free ...   \n",
              "9007   26 episodes (100%) are available to stream on ...   \n",
              "9342   4 episodes (1%) are available to watch free on...   \n",
              "7699   44 episodes (14%) are available to watch free ...   \n",
              "8519   30 episodes (100%) are available to stream on ...   \n",
              "4002   10 episodes (6%) are available to watch free o...   \n",
              "1241                                                None   \n",
              "9619   11 episodes (15%) are available to watch free ...   \n",
              "6448   124 episodes (98%) are available to watch free...   \n",
              "2339   1 episodes (1%) are available to watch free on...   \n",
              "5412   39 episodes (100%) are available to stream on ...   \n",
              "9576   3 episodes (1%) are available to watch free on...   \n",
              "4556                                                None   \n",
              "275    1 episodes (0%) are available to watch free on...   \n",
              "8763   37 episodes (100%) are available to stream on ...   \n",
              "5900   86 episodes (92%) are available to watch free ...   \n",
              "10366  20 episodes (100%) are available to stream on ...   \n",
              "5782   45 episodes (100%) are available to stream on ...   \n",
              "8626   46 episodes (100%) are available to stream on ...   \n",
              "3663   39 episodes (100%) are available to stream on ...   \n",
              "8923   40 episodes (100%) are available to stream on ...   \n",
              "1377   24 episodes (100%) are available to stream on ...   \n",
              "1389   5 episodes (3%) are available to watch free on...   \n",
              "8295   75 episodes (100%) are available to stream on ...   \n",
              "8018   5 episodes (2%) are available to watch free on...   \n",
              "8944   1 episodes (2%) are available to watch free on...   \n",
              "473    19 episodes (95%) are available to stream on a...   \n",
              "5682   38 episodes (100%) are available to stream on ...   \n",
              "6388   30 episodes (100%) are available to stream on ...   \n",
              "4675   16 episodes (67%) are available to stream on a...   \n",
              "4916   27 episodes (100%) are available to stream on ...   \n",
              "7401                                                None   \n",
              "4028   208 episodes (100%) are available to stream on...   \n",
              "7425   16 episodes (100%) are available to stream on ...   \n",
              "64     205 episodes (100%) are available to stream on...   \n",
              "6686   87 episodes (98%) are available to stream on a...   \n",
              "1730   90 episodes (99%) are available to stream on a...   \n",
              "8638   27 episodes (93%) are available to watch free ...   \n",
              "10406  81 episodes (100%) are available to watch free...   \n",
              "9508   146 episodes (100%) are available to stream on...   \n",
              "5204   75 episodes (100%) are available to stream on ...   \n",
              "6320   91 episodes (99%) are available to stream on a...   \n",
              "5418   39 episodes (100%) are available to stream on ...   \n",
              "5408   123 episodes (90%) are available to stream on ...   \n",
              "\n",
              "       Rent or Buy Available  Exclusive Service  Has Tag  \n",
              "1336                       1                  0        1  \n",
              "1920                       1                  0        1  \n",
              "3969                       1                  0        1  \n",
              "7003                       1                  0        1  \n",
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              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Title</th>\n",
              "      <th>URL</th>\n",
              "      <th>Type</th>\n",
              "      <th>Service</th>\n",
              "      <th>Genre</th>\n",
              "      <th>Tag</th>\n",
              "      <th>IMDB</th>\n",
              "      <th>ReelGood</th>\n",
              "      <th>AgeRating</th>\n",
              "      <th>Rated</th>\n",
              "      <th>Released Year</th>\n",
              "      <th>Duration Year</th>\n",
              "      <th>Seasons</th>\n",
              "      <th>What it's about</th>\n",
              "      <th>Where to Watch</th>\n",
              "      <th>Rent or Buy Available</th>\n",
              "      <th>Exclusive Service</th>\n",
              "      <th>Has Tag</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1336</th>\n",
              "      <td>Breaking Bad</td>\n",
              "      <td>/show/breaking-bad-2008</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama, Crime]</td>\n",
              "      <td>[Gangster, High School, Doctor, Drug, Teacher]</td>\n",
              "      <td>9.5</td>\n",
              "      <td>100.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2008</td>\n",
              "      <td>2008-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>When Walter White, a New Mexico chemistry teac...</td>\n",
              "      <td>62 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1920</th>\n",
              "      <td>Cosmos</td>\n",
              "      <td>/show/cosmos-a-spacetime-odyssey-2014</td>\n",
              "      <td>tv</td>\n",
              "      <td>[natgeo, free, tubi_tv, fox, fox_tveverywhere,...</td>\n",
              "      <td>[Documentary]</td>\n",
              "      <td>[Space, Science]</td>\n",
              "      <td>9.3</td>\n",
              "      <td>82.0</td>\n",
              "      <td>all</td>\n",
              "      <td>TV-G</td>\n",
              "      <td>2014</td>\n",
              "      <td>2014-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Famed astrophysicist Neil deGrasse Tyson provi...</td>\n",
              "      <td>2 episodes (7%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3969</th>\n",
              "      <td>Horsepower TV</td>\n",
              "      <td>/show/horsepower-2006</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Sport]</td>\n",
              "      <td>[Racing]</td>\n",
              "      <td>9.2</td>\n",
              "      <td>38.0</td>\n",
              "      <td>all</td>\n",
              "      <td>TV-G</td>\n",
              "      <td>2006</td>\n",
              "      <td>2006-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>Every gearhead wants power and this show revea...</td>\n",
              "      <td>14 episodes (8%) are available to stream on a ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7003</th>\n",
              "      <td>Rick and Morty</td>\n",
              "      <td>/show/rick-and-morty-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hulu_plus, hoopla, fubo_tv, adult_swim_...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Animation, Scienc...</td>\n",
              "      <td>[Time Travel, Space, Science, Alien]</td>\n",
              "      <td>9.2</td>\n",
              "      <td>96.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Rick is a mentally-unbalanced but scientifical...</td>\n",
              "      <td>5 episodes (12%) are available to watch free o...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7483</th>\n",
              "      <td>Sherlock</td>\n",
              "      <td>/show/sherlock-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Based on Books, Adaptation, Serial Killer]</td>\n",
              "      <td>9.1</td>\n",
              "      <td>94.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A modern update finds the famous sleuth and hi...</td>\n",
              "      <td>12 episodes (92%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3515</th>\n",
              "      <td>Gravity Falls</td>\n",
              "      <td>/show/gravity-falls-2012</td>\n",
              "      <td>tv</td>\n",
              "      <td>[disneynow, free, disneynow_free, hulu_plus, d...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Fantasy, Animation]</td>\n",
              "      <td>[Supernatural, Disney]</td>\n",
              "      <td>8.9</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2012</td>\n",
              "      <td>2012-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Twin brother and sister Dipper and Mabel Pines...</td>\n",
              "      <td>2 episodes (5%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6475</th>\n",
              "      <td>Peaky Blinders</td>\n",
              "      <td>/show/peaky-blinders-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama, Crime]</td>\n",
              "      <td>[Gangster, War, Drug, World War II, Racing]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>A gangster family epic set in 1919 Birmingham,...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7914</th>\n",
              "      <td>Stranger Things</td>\n",
              "      <td>/show/stranger-things-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Horror, Fantasy, Drama]</td>\n",
              "      <td>[Space, Science, Supernatural, Monster, Friend...</td>\n",
              "      <td>8.8</td>\n",
              "      <td>96.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>When a young boy vanishes, a small town uncove...</td>\n",
              "      <td>25 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1156</th>\n",
              "      <td>Black Mirror</td>\n",
              "      <td>/show/black-mirror-2011</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Science-Fiction, Fantasy, Drama]</td>\n",
              "      <td>[Dystopia, Space, Technology]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>92.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2011</td>\n",
              "      <td>2011-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>A contemporary British re-working of The Twili...</td>\n",
              "      <td>21 episodes (95%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6032</th>\n",
              "      <td>Narcos</td>\n",
              "      <td>/show/narcos-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Biography, Drama, Crime]</td>\n",
              "      <td>[Based On True Story, Gangster, Drug]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A gritty chronicle of the war against Colombia...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9526</th>\n",
              "      <td>The West Wing</td>\n",
              "      <td>/show/the-west-wing-1999</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Drama]</td>\n",
              "      <td>[Political, Spy]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>1999</td>\n",
              "      <td>1999-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>The West Wing provides a glimpse into presiden...</td>\n",
              "      <td>155 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2128</th>\n",
              "      <td>Dark</td>\n",
              "      <td>/show/dark-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Time Travel, Police]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>94.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A missing child causes four families to help e...</td>\n",
              "      <td>26 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4361</th>\n",
              "      <td>It's Always Sunny in Philadelphia</td>\n",
              "      <td>/show/its-always-sunny-in-philadelphia-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[philo, fx_tveverywhere, fox_tveverywhere, vic...</td>\n",
              "      <td>[Comedy]</td>\n",
              "      <td>[Friendship, Political]</td>\n",
              "      <td>8.8</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>15.0</td>\n",
              "      <td>Four egocentric friends who run a neighborhood...</td>\n",
              "      <td>146 episodes (95%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>709</th>\n",
              "      <td>Attack on Titan</td>\n",
              "      <td>/show/attack-on-titan-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[adult_swim_tveverywhere, crunchyroll_premium,...</td>\n",
              "      <td>[Action &amp; Adventure, Animation, Anime]</td>\n",
              "      <td>[Supernatural, Dystopia, Monster, Political, A...</td>\n",
              "      <td>8.8</td>\n",
              "      <td>92.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Several hundred years ago, humans were nearly ...</td>\n",
              "      <td>59 episodes (98%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9007</th>\n",
              "      <td>The Marvelous Mrs. Maisel</td>\n",
              "      <td>/show/the-marvelous-mrs-maisel-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Stand-up &amp; Talk, Comedy, Drama]</td>\n",
              "      <td>[New York, Feel-good]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>It’s 1958 Manhattan and Miriam “Midge” Maisel ...</td>\n",
              "      <td>26 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9342</th>\n",
              "      <td>The Simpsons</td>\n",
              "      <td>/show/the-simpsons-1989</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, fox, fx_tveverywhere, fubo_tv, hulu_plu...</td>\n",
              "      <td>[Comedy, Animation, Family]</td>\n",
              "      <td>[Vampire, Cartoon, Supernatural, Parody, Frien...</td>\n",
              "      <td>8.7</td>\n",
              "      <td>91.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>1989</td>\n",
              "      <td>1989-2020</td>\n",
              "      <td>32.0</td>\n",
              "      <td>Set in Springfield, the average American town,...</td>\n",
              "      <td>4 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7699</th>\n",
              "      <td>South Park</td>\n",
              "      <td>/show/south-park-1997</td>\n",
              "      <td>tv</td>\n",
              "      <td>[comedy, free, hulu_plus, philo, fubo_tv, come...</td>\n",
              "      <td>[Comedy, Animation]</td>\n",
              "      <td>[Mature, Political, Feel-good, Time Travel, Pa...</td>\n",
              "      <td>8.7</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1997</td>\n",
              "      <td>1997-2020</td>\n",
              "      <td>24.0</td>\n",
              "      <td>Follows the misadventures of four irreverent g...</td>\n",
              "      <td>44 episodes (14%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8519</th>\n",
              "      <td>The Crown</td>\n",
              "      <td>/show/the-crown-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[History, Drama]</td>\n",
              "      <td>[Political, Princess, Royalty]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>88.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>The gripping, decades-spanning inside story of...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4002</th>\n",
              "      <td>House</td>\n",
              "      <td>/show/house-2004</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, peacock, nbc_tveverywhere, amazon_...</td>\n",
              "      <td>[Comedy, Mystery, Drama]</td>\n",
              "      <td>[Doctor, Drug]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>92.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2004</td>\n",
              "      <td>2004-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Dr. Gregory House, a drug-addicted, unconventi...</td>\n",
              "      <td>10 episodes (6%) are available to watch free o...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1241</th>\n",
              "      <td>BoJack Horseman</td>\n",
              "      <td>/show/bojack-horseman-2014</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Animation, Comedy, Drama]</td>\n",
              "      <td>[Mature, Space, Psychology, Genius, Animal, Drug]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2014</td>\n",
              "      <td>2014-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Meet the most beloved sitcom horse of the 90s ...</td>\n",
              "      <td>None</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9619</th>\n",
              "      <td>This Is Us</td>\n",
              "      <td>/show/this-is-us-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, nbc_tveverywhere, fubo_tv, hulu_pl...</td>\n",
              "      <td>[Comedy, Drama]</td>\n",
              "      <td>[Feel-good]</td>\n",
              "      <td>8.7</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Follows the lives and families of three adults...</td>\n",
              "      <td>11 episodes (15%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6448</th>\n",
              "      <td>Parks and Recreation</td>\n",
              "      <td>/show/parks-and-recreation-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, philo, nbc_tveverywhere, amazon_prime, ...</td>\n",
              "      <td>[Comedy]</td>\n",
              "      <td>[Political]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>90.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Hilarious ensemble comedy that follows Leslie ...</td>\n",
              "      <td>124 episodes (98%) are available to watch free...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2339</th>\n",
              "      <td>Dexter</td>\n",
              "      <td>/show/dexter-2006</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, showtime, netflix, fubo_tv, showtime_free]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Based on Books, Adaptation, Serial Killer]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2006</td>\n",
              "      <td>2006-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>Dexter Morgan, a blood spatter pattern analyst...</td>\n",
              "      <td>1 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5412</th>\n",
              "      <td>Marvel's Daredevil</td>\n",
              "      <td>/show/marvels-daredevil-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Supernatural, Disney, Superhero, Comic Book, ...</td>\n",
              "      <td>8.6</td>\n",
              "      <td>90.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Lawyer-by-day Matt Murdock uses his heightened...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9576</th>\n",
              "      <td>The X-Files</td>\n",
              "      <td>/show/the-x-files-1993</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, philo, fox, bbc_america_tve, hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Mystery, Drama]</td>\n",
              "      <td>[Space, Vampire, Science, Alien, Supernatural,...</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>1993</td>\n",
              "      <td>1993-2020</td>\n",
              "      <td>11.0</td>\n",
              "      <td>The exploits of FBI Special Agents Fox Mulder ...</td>\n",
              "      <td>3 episodes (1%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4556</th>\n",
              "      <td>Justified</td>\n",
              "      <td>/show/justified-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Military, Gangster]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>A character drama based on the 2001 Elmore Leo...</td>\n",
              "      <td>None</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>275</th>\n",
              "      <td>Adventure Time</td>\n",
              "      <td>/show/adventure-time-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, cartoon_network_free, hulu_plus, hoopla...</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Animation, Child...</td>\n",
              "      <td>[Magic, Princess, Cartoon, Royalty]</td>\n",
              "      <td>8.6</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>11.0</td>\n",
              "      <td>Hook up with Finn and Jake as they travel the ...</td>\n",
              "      <td>1 episodes (0%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8763</th>\n",
              "      <td>The Handmaid's Tale</td>\n",
              "      <td>/show/the-handmaids-tale-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Drama]</td>\n",
              "      <td>[Dystopia, Political, Based on Books, Doctor, ...</td>\n",
              "      <td>8.5</td>\n",
              "      <td>88.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Set in a dystopian future, a woman is forced t...</td>\n",
              "      <td>37 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5900</th>\n",
              "      <td>My Hero Academia</td>\n",
              "      <td>/show/my-hero-academia-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[adult_swim_tveverywhere, crunchyroll_premium,...</td>\n",
              "      <td>[Action &amp; Adventure, Animation, Anime]</td>\n",
              "      <td>[Revenge, Supernatural, High School, Superhero...</td>\n",
              "      <td>8.5</td>\n",
              "      <td>88.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>In a world where eighty percent of the populat...</td>\n",
              "      <td>86 episodes (92%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10366</th>\n",
              "      <td>What We Do in the Shadows</td>\n",
              "      <td>/show/what-we-do-in-the-shadows-2019</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Horror, Comedy, Fantasy]</td>\n",
              "      <td>[Vampire, Supernatural]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>85.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2019</td>\n",
              "      <td>2019-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A documentary-style look into the daily (or ra...</td>\n",
              "      <td>20 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5782</th>\n",
              "      <td>Mr. Robot</td>\n",
              "      <td>/show/mr-robot-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Robot, Suspense, Science]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>92.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A contemporary and culturally resonant drama a...</td>\n",
              "      <td>45 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8626</th>\n",
              "      <td>The Expanse</td>\n",
              "      <td>/show/the-expanse-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Drama]</td>\n",
              "      <td>[Dystopia, Science, Space, Futuristic]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>89.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>A thriller set two hundred years in the future...</td>\n",
              "      <td>46 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3663</th>\n",
              "      <td>Hannibal</td>\n",
              "      <td>/show/hannibal-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Horror, Drama, Crime]</td>\n",
              "      <td>[Serial Killer]</td>\n",
              "      <td>8.5</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Both a gift and a curse, Graham has the extrao...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8923</th>\n",
              "      <td>The Last Kingdom</td>\n",
              "      <td>/show/the-last-kingdom-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Romance, Action &amp; Adventure, History]</td>\n",
              "      <td>[Political, Royalty]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A show of heroic deeds and epic battles with a...</td>\n",
              "      <td>40 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1377</th>\n",
              "      <td>Broadchurch</td>\n",
              "      <td>/show/broadchurch-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Police, Serial Killer, Religion]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>The murder of a young boy in a small coastal t...</td>\n",
              "      <td>24 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1389</th>\n",
              "      <td>Brooklyn Nine-Nine</td>\n",
              "      <td>/show/brooklyn-nine-nine-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[nbc, free, peacock, nbc_tveverywhere, fubo_tv...</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Crime]</td>\n",
              "      <td>[New York, Police, War]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>8.0</td>\n",
              "      <td>A single-camera ensemble comedy following the ...</td>\n",
              "      <td>5 episodes (3%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8295</th>\n",
              "      <td>The Americans</td>\n",
              "      <td>/show/the-americans-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Mystery, Drama, Crime]</td>\n",
              "      <td>[Political, War, Spy]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Set during the Cold War period in the 1980s, T...</td>\n",
              "      <td>75 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8018</th>\n",
              "      <td>Supernatural</td>\n",
              "      <td>/show/supernatural-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, thecw, netflix, tnt, fubo_tv]</td>\n",
              "      <td>[Horror, Fantasy, Drama]</td>\n",
              "      <td>[Vampire, Supernatural, Monster, Time Travel, ...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>93.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>16.0</td>\n",
              "      <td>When they were boys, Sam and Dean Winchester l...</td>\n",
              "      <td>5 episodes (2%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8944</th>\n",
              "      <td>The Legend of Korra</td>\n",
              "      <td>/show/the-legend-of-korra-2012</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hoopla, abc_news, netflix, cbs_all_access]</td>\n",
              "      <td>[Action &amp; Adventure, Animation]</td>\n",
              "      <td>[Supernatural, Political, Martial Arts, Feel-g...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>87.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2012</td>\n",
              "      <td>2012-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>Avatar Korra, a headstrong, rebellious, feisty...</td>\n",
              "      <td>1 episodes (2%) are available to watch free on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>473</th>\n",
              "      <td>American Crime Story</td>\n",
              "      <td>/show/american-crime-story-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Biography, Drama, Crime]</td>\n",
              "      <td>[Based On True Story, Police, Adaptation, Seri...</td>\n",
              "      <td>8.4</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>An anthology series centered around some of hi...</td>\n",
              "      <td>19 episodes (95%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5682</th>\n",
              "      <td>Money Heist</td>\n",
              "      <td>/show/money-heist-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Thriller, Crime]</td>\n",
              "      <td>[Mature]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>To carry out the biggest heist in history, a m...</td>\n",
              "      <td>38 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6388</th>\n",
              "      <td>Ozark</td>\n",
              "      <td>/show/ozark-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Gangster, Drug]</td>\n",
              "      <td>8.4</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>A financial adviser drags his family from Chic...</td>\n",
              "      <td>30 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4675</th>\n",
              "      <td>Killing Eve</td>\n",
              "      <td>/show/killing-eve-2018</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amc_premiere, philo, bbc_america_tve, fubo_tv...</td>\n",
              "      <td>[LGBTQ, Action &amp; Adventure, Thriller]</td>\n",
              "      <td>[Based on Books, Psychology, Adaptation]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-2020</td>\n",
              "      <td>4.0</td>\n",
              "      <td>A security consultant hunts for a ruthless ass...</td>\n",
              "      <td>16 episodes (67%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4916</th>\n",
              "      <td>Legion</td>\n",
              "      <td>/show/legion-2017</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Science-Fiction, Action &amp; Adventure, Drama]</td>\n",
              "      <td>[Science, Supernatural, Psychology, Superhero,...</td>\n",
              "      <td>8.3</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2017</td>\n",
              "      <td>2017-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>David Haller, AKA Legion, is a troubled young ...</td>\n",
              "      <td>27 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7401</th>\n",
              "      <td>Sense8</td>\n",
              "      <td>/show/sense8-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Mystery, Drama]</td>\n",
              "      <td>[Mature, Space, Supernatural]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>86.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>One gunshot, one death, one moment out of time...</td>\n",
              "      <td>None</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4028</th>\n",
              "      <td>How I Met Your Mother</td>\n",
              "      <td>/show/how-i-met-your-mother-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Romance, Comedy]</td>\n",
              "      <td>[Friendship, College]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>89.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>A father recounts to his children - through a ...</td>\n",
              "      <td>208 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7425</th>\n",
              "      <td>Sex Education</td>\n",
              "      <td>/show/sex-education-2019</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Comedy, Drama]</td>\n",
              "      <td>[Mature, Teen, Feel-good]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2019</td>\n",
              "      <td>2019-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>Inexperienced Otis channels his sex therapist ...</td>\n",
              "      <td>16 episodes (100%) are available to stream on ...</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>24</td>\n",
              "      <td>/show/24-2001</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Thriller, Drama]</td>\n",
              "      <td>[Revenge, Political, Spy, Prison]</td>\n",
              "      <td>8.3</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2001</td>\n",
              "      <td>2001-2020</td>\n",
              "      <td>9.0</td>\n",
              "      <td>24 is an American television series produced f...</td>\n",
              "      <td>205 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6686</th>\n",
              "      <td>Prison Break</td>\n",
              "      <td>/show/prison-break-2005</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Gangster, Psychology, Escape, Prison, Suspens...</td>\n",
              "      <td>8.3</td>\n",
              "      <td>88.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2005</td>\n",
              "      <td>2005-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Due to a political conspiracy, an innocent man...</td>\n",
              "      <td>87 episodes (98%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1730</th>\n",
              "      <td>Chuck</td>\n",
              "      <td>/show/chuck-2007</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amazon_prime]</td>\n",
              "      <td>[Comedy, Action &amp; Adventure, Drama]</td>\n",
              "      <td>[Space, Police, Spy, Technology]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>85.0</td>\n",
              "      <td>7+</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>2007</td>\n",
              "      <td>2007-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>When Buy More computer geek Chuck Bartowski un...</td>\n",
              "      <td>90 episodes (99%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8638</th>\n",
              "      <td>The Fall</td>\n",
              "      <td>/show/the-fall-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[free, hoopla, tubi_tv, plex_free, sundancenow...</td>\n",
              "      <td>[Thriller, Drama, Crime]</td>\n",
              "      <td>[Suspense, Police, Serial Killer]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>89.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>When the Police Service of Northern Ireland ar...</td>\n",
              "      <td>27 episodes (93%) are available to watch free ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10406</th>\n",
              "      <td>White Collar</td>\n",
              "      <td>/show/white-collar-2009</td>\n",
              "      <td>tv</td>\n",
              "      <td>[hulu_plus]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[New York]</td>\n",
              "      <td>8.2</td>\n",
              "      <td>85.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2009</td>\n",
              "      <td>2009-2020</td>\n",
              "      <td>6.0</td>\n",
              "      <td>Neal Caffrey, a con man, forger and thief, is ...</td>\n",
              "      <td>81 episodes (100%) are available to watch free...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9508</th>\n",
              "      <td>The Walking Dead</td>\n",
              "      <td>/show/the-walking-dead-2010</td>\n",
              "      <td>tv</td>\n",
              "      <td>[amc_premiere, philo, netflix, fubo_tv, amc]</td>\n",
              "      <td>[Horror, Drama]</td>\n",
              "      <td>[Zombie, Dystopia, Survival, Comic Book, Adapt...</td>\n",
              "      <td>8.2</td>\n",
              "      <td>91.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2010</td>\n",
              "      <td>2010-2020</td>\n",
              "      <td>10.0</td>\n",
              "      <td>Sheriff's deputy Rick Grimes awakens from a co...</td>\n",
              "      <td>146 episodes (100%) are available to stream on...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5204</th>\n",
              "      <td>Lucifer</td>\n",
              "      <td>/show/lucifer-2016</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Science-Fiction, Fantasy, Crime]</td>\n",
              "      <td>[Supernatural, Police, Superhero, Comic Book, ...</td>\n",
              "      <td>8.2</td>\n",
              "      <td>91.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2016</td>\n",
              "      <td>2016-2020</td>\n",
              "      <td>5.0</td>\n",
              "      <td>Bored and unhappy as the Lord of Hell, Lucifer...</td>\n",
              "      <td>75 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6320</th>\n",
              "      <td>Orange Is the New Black</td>\n",
              "      <td>/show/orange-is-the-new-black-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[LGBTQ, Comedy, Crime]</td>\n",
              "      <td>[Based On True Story, Prison]</td>\n",
              "      <td>8.1</td>\n",
              "      <td>87.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>A crime she committed in her youthful past sen...</td>\n",
              "      <td>91 episodes (99%) are available to stream on a...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5418</th>\n",
              "      <td>Marvel's Jessica Jones</td>\n",
              "      <td>/show/marvels-jessica-jones-2015</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Drama, Crime]</td>\n",
              "      <td>[Supernatural, Psychology, Disney, Superhero, ...</td>\n",
              "      <td>7.9</td>\n",
              "      <td>85.0</td>\n",
              "      <td>18+</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>2015</td>\n",
              "      <td>2015-2020</td>\n",
              "      <td>3.0</td>\n",
              "      <td>After a tragic ending to her short-lived super...</td>\n",
              "      <td>39 episodes (100%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5408</th>\n",
              "      <td>Marvel's Agents of S.H.I.E.L.D.</td>\n",
              "      <td>/show/marvels-agents-of-shield-2013</td>\n",
              "      <td>tv</td>\n",
              "      <td>[netflix]</td>\n",
              "      <td>[Action &amp; Adventure, Fantasy, Drama]</td>\n",
              "      <td>[Supernatural, Disney, Superhero, Comic Book, ...</td>\n",
              "      <td>7.5</td>\n",
              "      <td>87.0</td>\n",
              "      <td>16+</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>2013</td>\n",
              "      <td>2013-2020</td>\n",
              "      <td>7.0</td>\n",
              "      <td>Agent Phil Coulson of S.H.I.E.L.D. (Strategic ...</td>\n",
              "      <td>123 episodes (90%) are available to stream on ...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c8e00b53-a792-4df0-852f-3970854669e7')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c8e00b53-a792-4df0-852f-3970854669e7 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c8e00b53-a792-4df0-852f-3970854669e7');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
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              "\n",
              "\n",
              "<div id=\"df-b3781a4f-e373-4cc4-b548-c4d9a4ab4438\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b3781a4f-e373-4cc4-b548-c4d9a4ab4438')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b3781a4f-e373-4cc4-b548-c4d9a4ab4438 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"# (by='Service', key=lambda x: x\",\n  \"rows\": 57,\n  \"fields\": [\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"Breaking Bad\",\n          \"Gravity Falls\",\n          \"Mr. Robot\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"URL\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"/show/breaking-bad-2008\",\n          \"/show/gravity-falls-2012\",\n          \"/show/mr-robot-2015\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Type\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"tv\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Service\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Genre\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tag\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IMDB\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3381265649647141,\n        \"min\": 7.5,\n        \"max\": 9.5,\n        \"num_unique_values\": 15,\n        \"samples\": [\n          8.4\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ReelGood\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7.511811918288379,\n        \"min\": 38.0,\n        \"max\": 100.0,\n        \"num_unique_values\": 14,\n        \"samples\": [\n          85.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"AgeRating\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"all\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rated\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"TV-G\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Released Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 6,\n        \"min\": 1989,\n        \"max\": 2019,\n        \"num_unique_values\": 21,\n        \"samples\": [\n          2008\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration Year\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 21,\n        \"samples\": [\n          \"2008-2020\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Seasons\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.129158866392396,\n        \"min\": 3.0,\n        \"max\": 32.0,\n        \"num_unique_values\": 13,\n        \"samples\": [\n          16.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"What it's about\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 57,\n        \"samples\": [\n          \"When Walter White, a New Mexico chemistry teacher, is diagnosed with Stage III cancer and given a prognosis of only two years left to live. He becomes filled with a sense of fearlessness and an unrelenting desire to secure his family's financial future at any cost as he enters the dangerous world of drugs and crime\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Where to Watch\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 52,\n        \"samples\": [\n          \"124 episodes (98%) are available to watch free online (Peacock). 124 episodes (98%) are available to stream on a popular subscription service (Netflix, Hulu & 2 others). 11 episodes (9%) are available to stream on a TV everywhere service (NBC & Comedy Central). 124 episodes (98%) are available to rent or buy from $1.99 on 6 services (iTunes, Google Play, Prime Video & 4 others).\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Rent or Buy Available\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Exclusive Service\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Has Tag\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 1,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Appendix: Exploration of Question 1"
      ],
      "metadata": {
        "id": "29K0v8cPOIgn"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Genre Percentage"
      ],
      "metadata": {
        "id": "mJDheHZpQ9PE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Some titles can be similar, so it's good to group by Tag as well! (since the tags are the same under a certain title)\n",
        "df_unique_genre_tag = top_20_platform_df.drop_duplicates(subset=['Title', 'Genre', 'Tag'])"
      ],
      "metadata": {
        "id": "Ysh7BnkGOb-J"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the total number of unique titles (TV shows)\n",
        "total_unique_titles = df_unique_genre_tag['Title'].nunique()\n",
        "\n",
        "# Calculate the frequency of each genre\n",
        "genre_counts = df_unique_genre_tag['Genre'].value_counts()\n",
        "\n",
        "# Calculate the percentage of each genre based on the total number of unique titles\n",
        "genre_percentage = (genre_counts / total_unique_titles) * 100\n",
        "\n",
        "# Print the results\n",
        "print(\"Total Number of Unique Titles (TV Shows):\", total_unique_titles)\n",
        "print(\"\\nGenre Counts:\")\n",
        "print(genre_counts)\n",
        "print(\"\\nGenre Percentage based on Total Unique Titles (TV Shows):\")\n",
        "print(genre_percentage)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WcGNZV_4Q0-5",
        "outputId": "d49d2de6-5082-4556-a091-399f67673fef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total Number of Unique Titles (TV Shows): 8271\n",
            "\n",
            "Genre Counts:\n",
            "Genre\n",
            "Drama                 2668\n",
            "Comedy                2302\n",
            "Animation             1881\n",
            "Action & Adventure    1877\n",
            "Documentary           1877\n",
            "Reality               1473\n",
            "Crime                 1213\n",
            "Family                 978\n",
            "Anime                  648\n",
            "Children               567\n",
            "Mystery                513\n",
            "Fantasy                463\n",
            "Romance                460\n",
            "Science-Fiction        384\n",
            "Thriller               307\n",
            "History                282\n",
            "Food                   249\n",
            "Game Show              211\n",
            "Home & Garden          211\n",
            "Horror                 190\n",
            "Sport                  154\n",
            "Travel                 143\n",
            "Biography              127\n",
            "Musical                 60\n",
            "LGBTQ                   56\n",
            "Stand-up & Talk         28\n",
            "Cult                     9\n",
            "Name: count, dtype: int64\n",
            "\n",
            "Genre Percentage based on Total Unique Titles (TV Shows):\n",
            "Genre\n",
            "Drama                 32.257284\n",
            "Comedy                27.832185\n",
            "Animation             22.742111\n",
            "Action & Adventure    22.693749\n",
            "Documentary           22.693749\n",
            "Reality               17.809213\n",
            "Crime                 14.665699\n",
            "Family                11.824447\n",
            "Anime                  7.834603\n",
            "Children               6.855277\n",
            "Mystery                6.202394\n",
            "Fantasy                5.597872\n",
            "Romance                5.561601\n",
            "Science-Fiction        4.642728\n",
            "Thriller               3.711764\n",
            "History                3.409503\n",
            "Food                   3.010519\n",
            "Game Show              2.551082\n",
            "Home & Garden          2.551082\n",
            "Horror                 2.297183\n",
            "Sport                  1.861927\n",
            "Travel                 1.728932\n",
            "Biography              1.535485\n",
            "Musical                0.725426\n",
            "LGBTQ                  0.677064\n",
            "Stand-up & Talk        0.338532\n",
            "Cult                   0.108814\n",
            "Name: count, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Sort the genre_percentage DataFrame by percentage in descending order and select the top 10 genres\n",
        "top_10_genres = genre_percentage.sort_values(ascending=False).head(10)\n",
        "\n",
        "# Set plot style\n",
        "plt.figure(figsize=(10, 6))\n",
        "sns.set_style(\"whitegrid\")\n",
        "\n",
        "# Plot the bar chart using seaborn\n",
        "ax = sns.barplot(x=top_10_genres.index, y=top_10_genres.values, palette='summer')  # Use 'summer' palette\n",
        "\n",
        "# Set titles and labels\n",
        "plt.title('Genre Percentage for Unique TV Shows (Top 10)', fontsize=16)\n",
        "plt.xlabel('Genre', fontsize=14)\n",
        "plt.ylabel('Percentage (%)', fontsize=14)\n",
        "\n",
        "# Rotate x-axis labels\n",
        "plt.xticks(rotation=45, ha='right')\n",
        "\n",
        "# Add grid lines\n",
        "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
        "\n",
        "# Add labels on top of each bar\n",
        "for bar, value in zip(ax.patches, top_10_genres.values):\n",
        "    height = bar.get_height()\n",
        "    plt.text(bar.get_x() + bar.get_width() / 2, height + 1, f'{value:.2f}%', ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "# Show plot\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 716
        },
        "id": "N0yfELWlOb3Y",
        "outputId": "153f133d-c277-46d5-96eb-0a156a11f11c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-40-18ac74b32247>:9: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  ax = sns.barplot(x=top_10_genres.index, y=top_10_genres.values, palette='summer')  # Use 'summer' palette\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Tag Percentage"
      ],
      "metadata": {
        "id": "8LXOB--lShcA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Check the unique tags on each platform\n",
        "df_unique_tag = top_20_platform_df.drop_duplicates(subset=['Title', 'Tag'])"
      ],
      "metadata": {
        "id": "yulRyE-LSk7E"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Flatten the lists in the 'Tag' column and extract individual tags\n",
        "tags = [set(re.findall(r\"'([^']*)'\", str(tag))) for tag in df_unique_tag['Tag']]\n",
        "\n",
        "# Flatten the list of sets and remove empty strings\n",
        "flattened_tags = [tag for sublist in tags for tag in sublist if tag.strip()]\n",
        "\n",
        "# Count the occurrences of each tag\n",
        "tag_counts = pd.Series(Counter(flattened_tags)).reset_index()\n",
        "tag_counts.columns = ['Tag', 'Count']\n",
        "\n",
        "# Calculate the total unique count of titles\n",
        "total_unique_titles = df_unique_tag['Title'].nunique()\n",
        "\n",
        "# Calculate the percentage of each tag\n",
        "tag_counts['Percentage'] = (tag_counts['Count'] / total_unique_titles) * 100\n",
        "\n",
        "# Print the results\n",
        "print(tag_counts)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZICxZCAjSk5A",
        "outputId": "e17146dd-da40-4a85-f33a-9613c52e6a10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "            Tag  Count  Percentage\n",
            "0       Teacher     23    0.278080\n",
            "1          Drug     71    0.858421\n",
            "2        Doctor    199    2.405997\n",
            "3      Gangster     55    0.664974\n",
            "4   High School    148    1.789385\n",
            "..          ...    ...         ...\n",
            "86       Jungle      5    0.060452\n",
            "87      Hunting      5    0.060452\n",
            "88        Short      9    0.108814\n",
            "89    Christmas      5    0.060452\n",
            "90        Egypt      4    0.048362\n",
            "\n",
            "[91 rows x 3 columns]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Sort the tag counts by frequency and select the top 10\n",
        "top_tags = tag_counts.sort_values(by='Count', ascending=False).head(10)\n",
        "\n",
        "# Set the style\n",
        "plt.figure(figsize=(10, 5))\n",
        "sns.set_style(\"whitegrid\")\n",
        "\n",
        "# Plot the bar chart for percentages\n",
        "ax = sns.barplot(x='Tag', y='Percentage', data=top_tags, palette='summer')\n",
        "ax.set_xlabel('Tag', fontsize=14)  # Increase font size\n",
        "ax.set_ylabel('Percentage (%)', fontsize=14)  # Increase font size\n",
        "ax.set_title('Top 10 Most Frequent Tags (Percentage)', fontsize=16)  # Increase font size\n",
        "\n",
        "# Rotate x-axis labels\n",
        "plt.xticks(rotation=45)  # Rotate xticks by 45 degrees\n",
        "\n",
        "# Add labels on top of each bar\n",
        "for bar, value in zip(ax.patches, top_tags['Percentage']):\n",
        "    height = bar.get_height()\n",
        "    ax.text(bar.get_x() + bar.get_width() / 2, height + 0.5, f'{value:.2f}%', ha='center', va='bottom', fontsize=10)\n",
        "\n",
        "# Show the plot\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 616
        },
        "id": "AJNTqiY9Sk27",
        "outputId": "973fb62d-8609-4513-9c3a-5af5592fb650"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-43-a5037559702c>:9: FutureWarning: \n",
            "\n",
            "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n",
            "\n",
            "  ax = sns.barplot(x='Tag', y='Percentage', data=top_tags, palette='summer')\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Netflix Data - Production Country"
      ],
      "metadata": {
        "id": "I1e8UXxZRLmc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix = pd.read_csv('/content/drive/MyDrive/DSO 574/Assignment 3/Database/Netflix catalogue USA 2016-2020.csv')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GFoKP07gRLUI",
        "outputId": "10ba5614-a66b-4352-a206-bf8f7d9aaed5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-44-aff3c48addc7>:1: DtypeWarning: Columns (5) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df_netflix = pd.read_csv('/content/drive/MyDrive/DSO 574/Assignment 3/Database/Netflix catalogue USA 2016-2020.csv')\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix = df_netflix.loc[df_netflix['Content Type'] == 'TVSeason']"
      ],
      "metadata": {
        "id": "DtQf3t5nRXe5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix['YearMonth'] = pd.to_datetime(df_netflix['YearMonth'], format = '%b-%Y', errors = 'coerce')"
      ],
      "metadata": {
        "id": "VW8p8fM_RXcf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix['Year'] = df_netflix['YearMonth'].dt.year"
      ],
      "metadata": {
        "id": "tKa4hCzHRXaP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix = df_netflix.drop_duplicates(subset = ['YearMonth', 'Title'])"
      ],
      "metadata": {
        "id": "ML4cOsnfRXXt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_netflix.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "C8aN_ZbdRpTv",
        "outputId": "d3926ee5-4043-4b67-e516-b6eb06060356"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    YearMonth Platform Country Content Type  \\\n",
              "3  2016-01-01  Netflix     USA     TVSeason   \n",
              "16 2016-01-01  Netflix     USA     TVSeason   \n",
              "17 2016-01-01  Netflix     USA     TVSeason   \n",
              "18 2016-01-01  Netflix     USA     TVSeason   \n",
              "19 2016-01-01  Netflix     USA     TVSeason   \n",
              "\n",
              "                                           Title First Release Year  \\\n",
              "3   #deathtoselfie With Steven Furtick: Season 1               2014   \n",
              "16               3rd Rock From the Sun: Season 1               1996   \n",
              "17               3rd Rock From the Sun: Season 2               1996   \n",
              "18               3rd Rock From the Sun: Season 3               1997   \n",
              "19               3rd Rock From the Sun: Season 4               1998   \n",
              "\n",
              "       Primary Genre SecondaryGenre                          Genre Duration  \\\n",
              "3      Miscellaneous  Miscellaneous  Miscellaneous - Miscellaneous      520   \n",
              "16  Sci-Fi & Fantasy         Comedy      Sci-Fi & Fantasy - Comedy      420   \n",
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              "19  Sci-Fi & Fantasy         Comedy      Sci-Fi & Fantasy - Comedy      504   \n",
              "\n",
              "     Duration Group Number of Episodes Primary Production Country  \\\n",
              "3   45 - 60 minutes                 10                        USA   \n",
              "16  15 - 30 minutes                 20                        USA   \n",
              "17  15 - 30 minutes                 26                        USA   \n",
              "18  15 - 30 minutes                 27                        USA   \n",
              "19  15 - 30 minutes                 24                        USA   \n",
              "\n",
              "   Primary Production Company  Year  \n",
              "3         No Company Assigned  2016  \n",
              "16      Carsey-Werner Company  2016  \n",
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              "      <td>TVSeason</td>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_netflix"
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          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "production_country = df_netflix.groupby(['Year', 'Primary Production Country']).size().unstack(fill_value=0)\n",
        "production_country = round(production_country / 12)\n",
        "production_country"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 322
        },
        "id": "a4eKKwzERpRT",
        "outputId": "74e6fe87-bdcc-4345-ee88-b961f9cf3724"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Primary Production Country  Argentina  Australia  Bahrain  Belgium  Brazil  \\\n",
              "Year                                                                         \n",
              "2016                              7.0       55.0      0.0      1.0     6.0   \n",
              "2017                              8.0       81.0      1.0      3.0     7.0   \n",
              "2018                              6.0       91.0      1.0      3.0     9.0   \n",
              "2019                             16.0       98.0      1.0      6.0    20.0   \n",
              "2020                             20.0       90.0      1.0     10.0    31.0   \n",
              "\n",
              "Primary Production Country  Canada  Chile  China  Colombia  Croatia  ...  \\\n",
              "Year                                                                 ...   \n",
              "2016                         138.0    4.0    8.0      22.0      0.0  ...   \n",
              "2017                         171.0    8.0   27.0      18.0      0.0  ...   \n",
              "2018                         184.0    4.0   34.0      14.0      0.0  ...   \n",
              "2019                         175.0    5.0   69.0      21.0      2.0  ...   \n",
              "2020                         163.0    4.0   86.0      24.0      2.0  ...   \n",
              "\n",
              "Primary Production Country  Spain  Sweden  Switzerland  Taiwan  Thailand  \\\n",
              "Year                                                                       \n",
              "2016                         19.0     4.0          0.0     2.0       0.0   \n",
              "2017                         27.0     4.0          1.0     6.0       1.0   \n",
              "2018                         42.0     4.0          0.0     7.0      10.0   \n",
              "2019                         59.0     5.0          1.0    28.0      60.0   \n",
              "2020                         69.0     8.0          1.0    38.0      74.0   \n",
              "\n",
              "Primary Production Country  Turkey  UAE     UK     USA  Ukraine  \n",
              "Year                                                             \n",
              "2016                           3.0  0.0  353.0  1474.0      0.0  \n",
              "2017                          28.0  0.0  413.0  1328.0      2.0  \n",
              "2018                          28.0  0.0  488.0  1293.0      3.0  \n",
              "2019                          34.0  1.0  435.0  1434.0      5.0  \n",
              "2020                          34.0  1.0  340.0  1552.0      3.0  \n",
              "\n",
              "[5 rows x 58 columns]"
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              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>8.0</td>\n",
              "      <td>81.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>171.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>27.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>413.0</td>\n",
              "      <td>1328.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>6.0</td>\n",
              "      <td>91.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>184.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>42.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>488.0</td>\n",
              "      <td>1293.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>16.0</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>175.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>69.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>...</td>\n",
              "      <td>59.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>60.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>435.0</td>\n",
              "      <td>1434.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>20.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>163.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>86.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>...</td>\n",
              "      <td>69.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>38.0</td>\n",
              "      <td>74.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>340.0</td>\n",
              "      <td>1552.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 58 columns</p>\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "production_country"
            }
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Sum the occurrences for each country across all years\n",
        "total_occurrences_by_country = production_country.sum()\n",
        "\n",
        "# Get the top 10 countries with the highest total occurrences\n",
        "top_countries_all_time = total_occurrences_by_country.nlargest(20)\n",
        "\n",
        "# Print or use top_countries_all_time as needed\n",
        "print(top_countries_all_time)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LUNF1rd8RpJe",
        "outputId": "a807f250-11e1-4d19-c243-df9c233ca84e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Primary Production Country\n",
            "USA            7081.0\n",
            "UK             2029.0\n",
            "Canada          831.0\n",
            "Japan           723.0\n",
            "South Korea     428.0\n",
            "Australia       415.0\n",
            "France          258.0\n",
            "India           226.0\n",
            "China           224.0\n",
            "Spain           216.0\n",
            "Mexico          209.0\n",
            "Thailand        145.0\n",
            "Turkey          127.0\n",
            "Colombia         99.0\n",
            "Germany          99.0\n",
            "Malaysia         82.0\n",
            "Taiwan           81.0\n",
            "Italy            75.0\n",
            "Brazil           73.0\n",
            "Denmark          73.0\n",
            "dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the percentage of value in each cell relative to the total count for each year (row)\n",
        "marketshare_by_country = (production_country.div(production_country.sum(axis=1), axis=0) * 100).round(1).astype(str) + '%'\n",
        "\n",
        "# Reorder the columns in the DataFrame based on the order of top countries\n",
        "marketshare_by_country = marketshare_by_country[top_countries_all_time.index]\n",
        "\n",
        "marketshare_by_country"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        },
        "id": "sFi2x7lQRXVS",
        "outputId": "c00882c6-ab86-4363-940b-a35da1a8b511"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Primary Production Country    USA     UK Canada Japan South Korea Australia  \\\n",
              "Year                                                                          \n",
              "2016                        62.2%  14.9%   5.8%  3.7%        1.1%      2.3%   \n",
              "2017                        53.1%  16.5%   6.8%  3.6%        2.7%      3.2%   \n",
              "2018                        48.5%  18.3%   6.9%  4.6%        2.9%      3.4%   \n",
              "2019                        45.5%  13.8%   5.5%  5.7%        3.0%      3.1%   \n",
              "2020                        45.4%   9.9%   4.8%  7.1%        4.7%      2.6%   \n",
              "\n",
              "Primary Production Country France India China Spain Mexico Thailand Turkey  \\\n",
              "Year                                                                         \n",
              "2016                         1.7%  0.4%  0.3%  0.8%   1.6%     0.0%   0.1%   \n",
              "2017                         1.7%  0.9%  1.1%  1.1%   1.3%     0.0%   1.1%   \n",
              "2018                         1.7%  1.4%  1.3%  1.6%   1.5%     0.4%   1.0%   \n",
              "2019                         1.8%  2.4%  2.2%  1.9%   1.6%     1.9%   1.1%   \n",
              "2020                         2.1%  2.4%  2.5%  2.0%   1.4%     2.2%   1.0%   \n",
              "\n",
              "Primary Production Country Colombia Germany Malaysia Taiwan Italy Brazil  \\\n",
              "Year                                                                       \n",
              "2016                           0.9%    0.5%     0.0%   0.1%  0.4%   0.3%   \n",
              "2017                           0.7%    0.7%     0.1%   0.2%  0.6%   0.3%   \n",
              "2018                           0.5%    0.6%     0.1%   0.3%  0.6%   0.3%   \n",
              "2019                           0.7%    0.7%     1.2%   0.9%  0.5%   0.6%   \n",
              "2020                           0.7%    1.0%     1.2%   1.1%  0.5%   0.9%   \n",
              "\n",
              "Primary Production Country Denmark  \n",
              "Year                                \n",
              "2016                          0.4%  \n",
              "2017                          0.6%  \n",
              "2018                          0.6%  \n",
              "2019                          0.5%  \n",
              "2020                          0.5%  "
            ],
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>Primary Production Country</th>\n",
              "      <th>USA</th>\n",
              "      <th>UK</th>\n",
              "      <th>Canada</th>\n",
              "      <th>Japan</th>\n",
              "      <th>South Korea</th>\n",
              "      <th>Australia</th>\n",
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              "      <th>India</th>\n",
              "      <th>China</th>\n",
              "      <th>Spain</th>\n",
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              "      <th>Thailand</th>\n",
              "      <th>Turkey</th>\n",
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              "      <th>Germany</th>\n",
              "      <th>Malaysia</th>\n",
              "      <th>Taiwan</th>\n",
              "      <th>Italy</th>\n",
              "      <th>Brazil</th>\n",
              "      <th>Denmark</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Year</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016</th>\n",
              "      <td>62.2%</td>\n",
              "      <td>14.9%</td>\n",
              "      <td>5.8%</td>\n",
              "      <td>3.7%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>2.3%</td>\n",
              "      <td>1.7%</td>\n",
              "      <td>0.4%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.8%</td>\n",
              "      <td>1.6%</td>\n",
              "      <td>0.0%</td>\n",
              "      <td>0.1%</td>\n",
              "      <td>0.9%</td>\n",
              "      <td>0.5%</td>\n",
              "      <td>0.0%</td>\n",
              "      <td>0.1%</td>\n",
              "      <td>0.4%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.4%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>53.1%</td>\n",
              "      <td>16.5%</td>\n",
              "      <td>6.8%</td>\n",
              "      <td>3.6%</td>\n",
              "      <td>2.7%</td>\n",
              "      <td>3.2%</td>\n",
              "      <td>1.7%</td>\n",
              "      <td>0.9%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>1.3%</td>\n",
              "      <td>0.0%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>0.7%</td>\n",
              "      <td>0.7%</td>\n",
              "      <td>0.1%</td>\n",
              "      <td>0.2%</td>\n",
              "      <td>0.6%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.6%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018</th>\n",
              "      <td>48.5%</td>\n",
              "      <td>18.3%</td>\n",
              "      <td>6.9%</td>\n",
              "      <td>4.6%</td>\n",
              "      <td>2.9%</td>\n",
              "      <td>3.4%</td>\n",
              "      <td>1.7%</td>\n",
              "      <td>1.4%</td>\n",
              "      <td>1.3%</td>\n",
              "      <td>1.6%</td>\n",
              "      <td>1.5%</td>\n",
              "      <td>0.4%</td>\n",
              "      <td>1.0%</td>\n",
              "      <td>0.5%</td>\n",
              "      <td>0.6%</td>\n",
              "      <td>0.1%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.6%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.6%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019</th>\n",
              "      <td>45.5%</td>\n",
              "      <td>13.8%</td>\n",
              "      <td>5.5%</td>\n",
              "      <td>5.7%</td>\n",
              "      <td>3.0%</td>\n",
              "      <td>3.1%</td>\n",
              "      <td>1.8%</td>\n",
              "      <td>2.4%</td>\n",
              "      <td>2.2%</td>\n",
              "      <td>1.9%</td>\n",
              "      <td>1.6%</td>\n",
              "      <td>1.9%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>0.7%</td>\n",
              "      <td>0.7%</td>\n",
              "      <td>1.2%</td>\n",
              "      <td>0.9%</td>\n",
              "      <td>0.5%</td>\n",
              "      <td>0.6%</td>\n",
              "      <td>0.5%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020</th>\n",
              "      <td>45.4%</td>\n",
              "      <td>9.9%</td>\n",
              "      <td>4.8%</td>\n",
              "      <td>7.1%</td>\n",
              "      <td>4.7%</td>\n",
              "      <td>2.6%</td>\n",
              "      <td>2.1%</td>\n",
              "      <td>2.4%</td>\n",
              "      <td>2.5%</td>\n",
              "      <td>2.0%</td>\n",
              "      <td>1.4%</td>\n",
              "      <td>2.2%</td>\n",
              "      <td>1.0%</td>\n",
              "      <td>0.7%</td>\n",
              "      <td>1.0%</td>\n",
              "      <td>1.2%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>0.5%</td>\n",
              "      <td>0.9%</td>\n",
              "      <td>0.5%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "marketshare_by_country",
              "summary": "{\n  \"name\": \"marketshare_by_country\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Year\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2017,\n          2020,\n          2018\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"USA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"53.1%\",\n          \"45.4%\",\n          \"48.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"UK\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"16.5%\",\n          \"9.9%\",\n          \"18.3%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Canada\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"6.8%\",\n          \"4.8%\",\n          \"6.9%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Japan\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"3.6%\",\n          \"7.1%\",\n          \"4.6%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"South Korea\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2.7%\",\n          \"4.7%\",\n          \"2.9%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Australia\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"3.2%\",\n          \"2.6%\",\n          \"3.4%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"France\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"1.7%\",\n          \"1.8%\",\n          \"2.1%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"India\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"0.9%\",\n          \"2.4%\",\n          \"0.4%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"China\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"1.1%\",\n          \"2.5%\",\n          \"1.3%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Spain\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"1.1%\",\n          \"2.0%\",\n          \"1.6%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Mexico\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"1.3%\",\n          \"1.4%\",\n          \"1.6%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Thailand\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"0.4%\",\n          \"2.2%\",\n          \"0.0%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Turkey\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.1%\",\n          \"1.1%\",\n          \"1.0%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Colombia\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.9%\",\n          \"0.7%\",\n          \"0.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Germany\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"0.7%\",\n          \"1.0%\",\n          \"0.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Malaysia\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.0%\",\n          \"0.1%\",\n          \"1.2%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Taiwan\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"0.2%\",\n          \"1.1%\",\n          \"0.3%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Italy\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.4%\",\n          \"0.6%\",\n          \"0.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Brazil\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.3%\",\n          \"0.6%\",\n          \"0.9%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Denmark\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.4%\",\n          \"0.6%\",\n          \"0.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Calculate the percentage of value in each cell relative to the total count for each year\n",
        "average_production_country_by_year_percentage = (production_country.div(production_country.sum(axis=1), axis=0) * 100).round(1).astype(str) + '%'\n",
        "\n",
        "# Extract percentage values for 2016 and 2020\n",
        "percentage_values_2016 = average_production_country_by_year_percentage.loc[2016].str.rstrip('%').astype(float)\n",
        "percentage_values_2020 = average_production_country_by_year_percentage.loc[2020].str.rstrip('%').astype(float)\n",
        "\n",
        "# Calculate the differences between 2020 and 2016 for each country\n",
        "differences_by_country_percentage = percentage_values_2020 - percentage_values_2016\n",
        "\n",
        "# Get the highest positive and negative differences for each country\n",
        "highest_positive_difference_by_country = differences_by_country_percentage[differences_by_country_percentage > 0].sort_values(ascending=False)\n",
        "highest_negative_difference_by_country = differences_by_country_percentage[differences_by_country_percentage < 0].sort_values(ascending=True)\n",
        "\n",
        "# Print the results\n",
        "print(\"Highest positive difference by country:\")\n",
        "print(highest_positive_difference_by_country)\n",
        "print(\"\\nHighest negative difference by country:\")\n",
        "print(highest_negative_difference_by_country)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mu1j3ycHSApn",
        "outputId": "185fbe89-72a0-4a9b-b7bd-ebc83cd33148"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Highest positive difference by country:\n",
            "Primary Production Country\n",
            "South Korea            3.6\n",
            "Japan                  3.4\n",
            "China                  2.2\n",
            "Thailand               2.2\n",
            "India                  2.0\n",
            "Spain                  1.2\n",
            "Malaysia               1.2\n",
            "Taiwan                 1.0\n",
            "Turkey                 0.9\n",
            "Brazil                 0.6\n",
            "Singapore              0.6\n",
            "Germany                0.5\n",
            "France                 0.4\n",
            "Australia              0.3\n",
            "Israel                 0.3\n",
            "Argentina              0.3\n",
            "Belgium                0.3\n",
            "Egypt                  0.3\n",
            "Finland                0.2\n",
            "Hong Kong              0.2\n",
            "Nigeria                0.2\n",
            "No Country Assigned    0.2\n",
            "Russia                 0.2\n",
            "Norway                 0.1\n",
            "Poland                 0.1\n",
            "Croatia                0.1\n",
            "Czech Republic         0.1\n",
            "Ukraine                0.1\n",
            "Saudi Arabia           0.1\n",
            "Pakistan               0.1\n",
            "Lebanon                0.1\n",
            "Kuwait                 0.1\n",
            "Ireland                0.1\n",
            "Denmark                0.1\n",
            "Italy                  0.1\n",
            "dtype: float64\n",
            "\n",
            "Highest negative difference by country:\n",
            "Primary Production Country\n",
            "USA           -16.8\n",
            "UK             -5.0\n",
            "Canada         -1.0\n",
            "Mexico         -0.2\n",
            "Colombia       -0.2\n",
            "Netherlands    -0.2\n",
            "Chile          -0.1\n",
            "Hungary        -0.1\n",
            "New Zealand    -0.1\n",
            "dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "growth_positive_by_country = marketshare_by_country[highest_positive_difference_by_country.nlargest(5).index]\n",
        "growth_negtive_by_country = marketshare_by_country[highest_negative_difference_by_country.nsmallest(5).index]"
      ],
      "metadata": {
        "id": "4FElZiN-SAni"
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      "execution_count": null,
      "outputs": []
    },
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        "growth_positive_by_country"
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              "Primary Production Country South Korea Japan China Thailand India\n",
              "Year                                                             \n",
              "2016                              1.1%  3.7%  0.3%     0.0%  0.4%\n",
              "2017                              2.7%  3.6%  1.1%     0.0%  0.9%\n",
              "2018                              2.9%  4.6%  1.3%     0.4%  1.4%\n",
              "2019                              3.0%  5.7%  2.2%     1.9%  2.4%\n",
              "2020                              4.7%  7.1%  2.5%     2.2%  2.4%"
            ],
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              "      <th>2016</th>\n",
              "      <td>1.1%</td>\n",
              "      <td>3.7%</td>\n",
              "      <td>0.3%</td>\n",
              "      <td>0.0%</td>\n",
              "      <td>0.4%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017</th>\n",
              "      <td>2.7%</td>\n",
              "      <td>3.6%</td>\n",
              "      <td>1.1%</td>\n",
              "      <td>0.0%</td>\n",
              "      <td>0.9%</td>\n",
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              "      <th>2018</th>\n",
              "      <td>2.9%</td>\n",
              "      <td>4.6%</td>\n",
              "      <td>1.3%</td>\n",
              "      <td>0.4%</td>\n",
              "      <td>1.4%</td>\n",
              "    </tr>\n",
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              "      <th>2019</th>\n",
              "      <td>3.0%</td>\n",
              "      <td>5.7%</td>\n",
              "      <td>2.2%</td>\n",
              "      <td>1.9%</td>\n",
              "      <td>2.4%</td>\n",
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              "      <th>2020</th>\n",
              "      <td>4.7%</td>\n",
              "      <td>7.1%</td>\n",
              "      <td>2.5%</td>\n",
              "      <td>2.2%</td>\n",
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              "type": "dataframe",
              "variable_name": "growth_positive_by_country",
              "summary": "{\n  \"name\": \"growth_positive_by_country\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Year\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2017,\n          2020,\n          2018\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"South Korea\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2.7%\",\n          \"4.7%\",\n          \"2.9%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Japan\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"3.6%\",\n          \"7.1%\",\n          \"4.6%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"China\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"1.1%\",\n          \"2.5%\",\n          \"1.3%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Thailand\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"0.4%\",\n          \"2.2%\",\n          \"0.0%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"India\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"0.9%\",\n          \"2.4%\",\n          \"0.4%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
          "execution_count": 55
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    {
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            "text/plain": [
              "Primary Production Country    USA     UK Canada Mexico Colombia\n",
              "Year                                                           \n",
              "2016                        62.2%  14.9%   5.8%   1.6%     0.9%\n",
              "2017                        53.1%  16.5%   6.8%   1.3%     0.7%\n",
              "2018                        48.5%  18.3%   6.9%   1.5%     0.5%\n",
              "2019                        45.5%  13.8%   5.5%   1.6%     0.7%\n",
              "2020                        45.4%   9.9%   4.8%   1.4%     0.7%"
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              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-087b51dc-2a93-4904-b818-5da2ec0c393b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-087b51dc-2a93-4904-b818-5da2ec0c393b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-cd7718ef-f9e9-4dee-a8e2-9b5f97abf883\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cd7718ef-f9e9-4dee-a8e2-9b5f97abf883')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cd7718ef-f9e9-4dee-a8e2-9b5f97abf883 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "growth_negtive_by_country",
              "summary": "{\n  \"name\": \"growth_negtive_by_country\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Year\",\n      \"properties\": {\n        \"dtype\": \"int32\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2017,\n          2020,\n          2018\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"USA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"53.1%\",\n          \"45.4%\",\n          \"48.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"UK\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"16.5%\",\n          \"9.9%\",\n          \"18.3%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Canada\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"6.8%\",\n          \"4.8%\",\n          \"6.9%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Mexico\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"1.3%\",\n          \"1.4%\",\n          \"1.6%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Colombia\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"0.9%\",\n          \"0.7%\",\n          \"0.5%\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    }
  ]
}