got_making_different_outputs_for_IBMcloudSvcs.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "script = pd.read_csv('Game_of_Thrones_Script_count_senti.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "json_script = script.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "json_script.drop(['Tokenize Words', 'Tokenize Words Alphanumeric Only',\n",
    "       'Sentence Word Count', 'Row', 'Family Name', 'Sentiment Scores',\n",
    "       'Polarity', 'Subjectivity'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "json_script.to_json(\"GoTscriptforWD.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_20 = script.groupby(['Name', 'Family Name'])[['Sentence Word Count']].sum().reset_index().sort_values(by=['Sentence Word Count']\n",
    "                                                                                         , ascending=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/ll/tlyhkxyx7qj42_ffkhwd31z00000gn/T/ipykernel_19591/4014958426.py:1: FutureWarning: The behavior of `series[i:j]` with an integer-dtype index is deprecated. In a future version, this will be treated as *label-based* indexing, consistent with e.g. `series[i]` lookups. To retain the old behavior, use `series.iloc[i:j]`. To get the future behavior, use `series.loc[i:j]`.\n",
      "  script = script[script[\"Name\"].isin(top_20[\"Name\"][:20])]\n"
     ]
    }
   ],
   "source": [
    "script = script[script[\"Name\"].isin(top_20[\"Name\"][:20])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12244 entries, 15 to 23908\n",
      "Data columns (total 14 columns):\n",
      " #   Column                            Non-Null Count  Dtype  \n",
      "---  ------                            --------------  -----  \n",
      " 0   Release Date                      12244 non-null  object \n",
      " 1   Season                            12244 non-null  object \n",
      " 2   Episode                           12244 non-null  object \n",
      " 3   Episode Title                     12244 non-null  object \n",
      " 4   Name                              12244 non-null  object \n",
      " 5   Sentence                          12244 non-null  object \n",
      " 6   Tokenize Words                    12244 non-null  object \n",
      " 7   Tokenize Words Alphanumeric Only  12244 non-null  object \n",
      " 8   Sentence Word Count               12244 non-null  int64  \n",
      " 9   Row                               12244 non-null  int64  \n",
      " 10  Family Name                       12244 non-null  object \n",
      " 11  Sentiment Scores                  12244 non-null  object \n",
      " 12  Polarity                          12244 non-null  float64\n",
      " 13  Subjectivity                      12244 non-null  float64\n",
      "dtypes: float64(2), int64(2), object(10)\n",
      "memory usage: 1.4+ MB\n"
     ]
    }
   ],
   "source": [
    "script.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Release Date', 'Season', 'Episode', 'Episode Title', 'Name',\n",
       "       'Sentence', 'Tokenize Words', 'Tokenize Words Alphanumeric Only',\n",
       "       'Sentence Word Count', 'Row', 'Family Name', 'Sentiment Scores',\n",
       "       'Polarity', 'Subjectivity'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "script.drop(['Release Date', 'Season', 'Episode Title', 'Tokenize Words', 'Tokenize Words Alphanumeric Only',\n",
    "       'Sentence Word Count', 'Row', 'Family Name', 'Sentiment Scores',\n",
    "       'Polarity', 'Subjectivity'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>Episode</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>jon snow</td>\n",
       "      <td>Go on. Father's watching.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>jon snow</td>\n",
       "      <td>And your mother.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>sansa stark</td>\n",
       "      <td>Thank you.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>jon snow</td>\n",
       "      <td>Don't think too much, Bran.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>robb stark</td>\n",
       "      <td>Relax your bow arm.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Episode         Name                     Sentence\n",
       "15  Episode 1     jon snow    Go on. Father's watching.\n",
       "16  Episode 1     jon snow             And your mother.\n",
       "18  Episode 1  sansa stark                   Thank you.\n",
       "21  Episode 1     jon snow  Don't think too much, Bran.\n",
       "22  Episode 1   robb stark          Relax your bow arm."
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 12244 entries, 15 to 23908\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   Episode   12244 non-null  object\n",
      " 1   Name      12244 non-null  object\n",
      " 2   Sentence  12244 non-null  object\n",
      "dtypes: object(3)\n",
      "memory usage: 382.6+ KB\n"
     ]
    }
   ],
   "source": [
    "script.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "script.to_csv('GoT-autoAI.csv', encoding='utf-8', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "script = pd.read_csv('GoT-autoAI.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>Episode</th>\n",
       "      <th>Name</th>\n",
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       "      <td>Go on. Father's watching.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>jon snow</td>\n",
       "      <td>And your mother.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>sansa stark</td>\n",
       "      <td>Thank you.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>jon snow</td>\n",
       "      <td>Don't think too much, Bran.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Episode 1</td>\n",
       "      <td>robb stark</td>\n",
       "      <td>Relax your bow arm.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Episode         Name                     Sentence\n",
       "15  Episode 1     jon snow    Go on. Father's watching.\n",
       "16  Episode 1     jon snow             And your mother.\n",
       "18  Episode 1  sansa stark                   Thank you.\n",
       "21  Episode 1     jon snow  Don't think too much, Bran.\n",
       "22  Episode 1   robb stark          Relax your bow arm."
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "script_less_eight = script[script[\"Episode\"]!=\"Episode 8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 11290 entries, 15 to 23908\n",
      "Data columns (total 3 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   Episode   11290 non-null  object\n",
      " 1   Name      11290 non-null  object\n",
      " 2   Sentence  11290 non-null  object\n",
      "dtypes: object(3)\n",
      "memory usage: 352.8+ KB\n"
     ]
    }
   ],
   "source": [
    "script_less_eight.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/ll/tlyhkxyx7qj42_ffkhwd31z00000gn/T/ipykernel_19591/1531792361.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  script_less_eight.drop(['Episode'], axis=1, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "script_less_eight.drop(['Episode'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "script_less_eight.to_csv('GoT-AWScomprehend.csv', encoding='utf-8', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "script_only_eight = script[script[\"Episode\"]==\"Episode 8\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th>Episode</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2349</th>\n",
       "      <td>Episode 8</td>\n",
       "      <td>sansa stark</td>\n",
       "      <td>She didn't forget. She's with her dancing master.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>Episode 8</td>\n",
       "      <td>sansa stark</td>\n",
       "      <td>What is it? What's happening?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>Episode 8</td>\n",
       "      <td>arya stark</td>\n",
       "      <td>You said right, but you went left.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2356</th>\n",
       "      <td>Episode 8</td>\n",
       "      <td>arya stark</td>\n",
       "      <td>Only 'cause you lied.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>Episode 8</td>\n",
       "      <td>arya stark</td>\n",
       "      <td>I was so. I watched, but you...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Episode         Name  \\\n",
       "2349  Episode 8  sansa stark   \n",
       "2351  Episode 8  sansa stark   \n",
       "2354  Episode 8   arya stark   \n",
       "2356  Episode 8   arya stark   \n",
       "2358  Episode 8   arya stark   \n",
       "\n",
       "                                               Sentence  \n",
       "2349  She didn't forget. She's with her dancing master.  \n",
       "2351                      What is it? What's happening?  \n",
       "2354                 You said right, but you went left.  \n",
       "2356                              Only 'cause you lied.  \n",
       "2358                    I was so. I watched, but you...  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script_only_eight.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/ll/tlyhkxyx7qj42_ffkhwd31z00000gn/T/ipykernel_19591/532591304.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  script_only_eight.drop(['Episode'], axis=1, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "script_only_eight.drop(['Episode'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>2349</th>\n",
       "      <td>sansa stark</td>\n",
       "      <td>She didn't forget. She's with her dancing master.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>sansa stark</td>\n",
       "      <td>What is it? What's happening?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>arya stark</td>\n",
       "      <td>You said right, but you went left.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2356</th>\n",
       "      <td>arya stark</td>\n",
       "      <td>Only 'cause you lied.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>arya stark</td>\n",
       "      <td>I was so. I watched, but you...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name                                           Sentence\n",
       "2349  sansa stark  She didn't forget. She's with her dancing master.\n",
       "2351  sansa stark                      What is it? What's happening?\n",
       "2354   arya stark                 You said right, but you went left.\n",
       "2356   arya stark                              Only 'cause you lied.\n",
       "2358   arya stark                    I was so. I watched, but you..."
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script_only_eight.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/ll/tlyhkxyx7qj42_ffkhwd31z00000gn/T/ipykernel_19591/997126856.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  script_only_eight.drop(['Name'], axis=1, inplace=True)\n"
     ]
    }
   ],
   "source": [
    "script_only_eight.drop(['Name'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2349</th>\n",
       "      <td>She didn't forget. She's with her dancing master.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2351</th>\n",
       "      <td>What is it? What's happening?</td>\n",
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       "      <th>2354</th>\n",
       "      <td>You said right, but you went left.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2356</th>\n",
       "      <td>Only 'cause you lied.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2358</th>\n",
       "      <td>I was so. I watched, but you...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               Sentence\n",
       "2349  She didn't forget. She's with her dancing master.\n",
       "2351                      What is it? What's happening?\n",
       "2354                 You said right, but you went left.\n",
       "2356                              Only 'cause you lied.\n",
       "2358                    I was so. I watched, but you..."
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "script_only_eight.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "script_only_eight.to_csv('GoT-AWScomprehend-test-season8.csv', encoding='utf-8', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting boto3\n",
      "  Downloading boto3-1.26.127-py3-none-any.whl (135 kB)\n",
      "\u001b[2K     \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m135.6/135.6 kB\u001b[0m \u001b[31m1.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\n",
      "\u001b[?25hCollecting botocore<1.30.0,>=1.29.127 (from boto3)\n",
      "  Downloading botocore-1.29.127-py3-none-any.whl (10.7 MB)\n",
      "\u001b[2K     \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.7/10.7 MB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0mm eta \u001b[36m0:00:01\u001b[0m[36m0:00:01\u001b[0m\n",
      "\u001b[?25hCollecting jmespath<2.0.0,>=0.7.1 (from boto3)\n",
      "  Downloading jmespath-1.0.1-py3-none-any.whl (20 kB)\n",
      "Collecting s3transfer<0.7.0,>=0.6.0 (from boto3)\n",
      "  Downloading s3transfer-0.6.1-py3-none-any.whl (79 kB)\n",
      "\u001b[2K     \u001b[38;2;114;156;31m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m79.8/79.8 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/local/lib/python3.11/site-packages (from botocore<1.30.0,>=1.29.127->boto3) (2.8.2)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/local/lib/python3.11/site-packages (from botocore<1.30.0,>=1.29.127->boto3) (1.26.15)\n",
      "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.30.0,>=1.29.127->boto3) (1.16.0)\n",
      "Installing collected packages: jmespath, botocore, s3transfer, boto3\n",
      "Successfully installed boto3-1.26.127 botocore-1.29.127 jmespath-1.0.1 s3transfer-0.6.1\n"
     ]
    }
   ],
   "source": [
    "!pip install boto3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'boto3'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[91], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mboto3\u001b[39;00m\n\u001b[1;32m      4\u001b[0m  \u001b[38;5;66;03m# Instantiate Boto3 SDK:\u001b[39;00m\n\u001b[1;32m      5\u001b[0m client \u001b[38;5;241m=\u001b[39m boto3\u001b[38;5;241m.\u001b[39mclient(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcomprehend\u001b[39m\u001b[38;5;124m'\u001b[39m, region_name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mregion\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'boto3'"
     ]
    }
   ],
   "source": [
    "import boto3\n",
    " \n",
    " # Instantiate Boto3 SDK:\n",
    "client = boto3.client('comprehend', region_name='region')\n",
    " \n",
    "start_response = client.start_document_classification_job(\n",
    "     InputDataConfig={\n",
    "         'S3Uri': 's3://srikad-us-west-2-input/docclass/file name',\n",
    "         'InputFormat': 'ONE_DOC_PER_LINE'\n",
    "     },\n",
    "     OutputDataConfig={\n",
    "         'S3Uri': 's3://S3Bucket/output'\n",
    "     },\n",
    "     DataAccessRoleArn='arn:aws:iam::account number:role/resource name',\n",
    "     DocumentClassifierArn=\n",
    "     'arn:aws:comprehend:region:account number:document-classifier/SampleCodeClassifier1'\n",
    " )\n",
    " \n",
    "print(\"Start response: %s\\n\", start_response)\n",
    " \n",
    " # Check the status of the job\n",
    "describe_response = client.describe_document_classification_job(JobId=start_response['JobId'])\n",
    "print(\"Describe response: %s\\n\", describe_response)\n",
    " \n",
    " # List all classification jobs in account\n",
    "list_response = client.list_document_classification_jobs()\n",
    "print(\"List response: %s\\n\", list_response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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