Ordinal_numbering_encoding_or_Label_Encoding.ipynb

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      "cell_type": "markdown",
      "source": [
        "e.g:\n",
        "\n",
        " 1. Student's grade in an exam (A,B,C,D,E)\n",
        " 2. Educational level, with the categories: Elementary school, high school, college graduate, PHD ranked from 1 to 4\n",
        "\n",
        " When the categorical variables are ordinal , the most strightforward best approach is to replace the labels by some ordinal number based on the rank."
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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import datetime"
      ]
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      "source": [
        "# create a variable with dates, and from that extract the weekday\n",
        "# create a list of dates with 20 days difference from today\n",
        "# and then transform it into dataframe\n",
        "\n",
        "df_base=datetime.datetime.today()\n",
        "df_date_list=[df_base - datetime.timedelta(days=x) for x in range(0,20)]\n",
        "df=pd.DataFrame(df_date_list)\n",
        "df.columns=['day']\n",
        "df"
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              "                          day\n",
              "0  2024-03-26 06:01:20.292130\n",
              "1  2024-03-25 06:01:20.292130\n",
              "2  2024-03-24 06:01:20.292130\n",
              "3  2024-03-23 06:01:20.292130\n",
              "4  2024-03-22 06:01:20.292130\n",
              "5  2024-03-21 06:01:20.292130\n",
              "6  2024-03-20 06:01:20.292130\n",
              "7  2024-03-19 06:01:20.292130\n",
              "8  2024-03-18 06:01:20.292130\n",
              "9  2024-03-17 06:01:20.292130\n",
              "10 2024-03-16 06:01:20.292130\n",
              "11 2024-03-15 06:01:20.292130\n",
              "12 2024-03-14 06:01:20.292130\n",
              "13 2024-03-13 06:01:20.292130\n",
              "14 2024-03-12 06:01:20.292130\n",
              "15 2024-03-11 06:01:20.292130\n",
              "16 2024-03-10 06:01:20.292130\n",
              "17 2024-03-09 06:01:20.292130\n",
              "18 2024-03-08 06:01:20.292130\n",
              "19 2024-03-07 06:01:20.292130"
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      "source": [
        "# extract the week day name\n",
        "\n",
        "\n",
        "df['day_ordinal']=df['day'].dt.weekday\n",
        "df.head(20)  # 0 is Monday"
      ],
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            "text/plain": [
              "                          day  day_ordinal\n",
              "0  2024-03-26 06:01:20.292130            1\n",
              "1  2024-03-25 06:01:20.292130            0\n",
              "2  2024-03-24 06:01:20.292130            6\n",
              "3  2024-03-23 06:01:20.292130            5\n",
              "4  2024-03-22 06:01:20.292130            4\n",
              "5  2024-03-21 06:01:20.292130            3\n",
              "6  2024-03-20 06:01:20.292130            2\n",
              "7  2024-03-19 06:01:20.292130            1\n",
              "8  2024-03-18 06:01:20.292130            0\n",
              "9  2024-03-17 06:01:20.292130            6\n",
              "10 2024-03-16 06:01:20.292130            5\n",
              "11 2024-03-15 06:01:20.292130            4\n",
              "12 2024-03-14 06:01:20.292130            3\n",
              "13 2024-03-13 06:01:20.292130            2\n",
              "14 2024-03-12 06:01:20.292130            1\n",
              "15 2024-03-11 06:01:20.292130            0\n",
              "16 2024-03-10 06:01:20.292130            6\n",
              "17 2024-03-09 06:01:20.292130            5\n",
              "18 2024-03-08 06:01:20.292130            4\n",
              "19 2024-03-07 06:01:20.292130            3"
            ],
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              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
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              "        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>day</th>\n",
              "      <th>day_ordinal</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2024-03-26 06:01:20.292130</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2024-03-25 06:01:20.292130</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2024-03-24 06:01:20.292130</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2024-03-23 06:01:20.292130</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2024-03-22 06:01:20.292130</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2024-03-21 06:01:20.292130</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2024-03-20 06:01:20.292130</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2024-03-19 06:01:20.292130</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2024-03-18 06:01:20.292130</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2024-03-17 06:01:20.292130</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2024-03-16 06:01:20.292130</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2024-03-15 06:01:20.292130</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2024-03-14 06:01:20.292130</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2024-03-13 06:01:20.292130</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2024-03-12 06:01:20.292130</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2024-03-11 06:01:20.292130</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2024-03-10 06:01:20.292130</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2024-03-09 06:01:20.292130</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2024-03-08 06:01:20.292130</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2024-03-07 06:01:20.292130</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
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              "        document.querySelector('#' + key + ' button');\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 20,\n  \"fields\": [\n    {\n      \"column\": \"day\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-03-07 06:01:20.292130\",\n        \"max\": \"2024-03-26 06:01:20.292130\",\n        \"num_unique_values\": 20,\n        \"samples\": [\n          \"2024-03-26 06:01:20.292130\",\n          \"2024-03-09 06:01:20.292130\",\n          \"2024-03-11 06:01:20.292130\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"day_ordinal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2,\n        \"min\": 0,\n        \"max\": 6,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          1,\n          0,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    }
  ]
}