wuthering2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ed1d2cea-6d9a-4bf5-82ce-e0306553bc07",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import pandas as pd\n",
    "from transformers import pipeline\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d4fca172-6d75-44b4-8a24-471b8e2514a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "frenchdf.to_csv(\"hurlevent.csv\", index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "63e9f337-6ed1-4ab3-b3a0-d276fcc69b0a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Text</th>\n",
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       "    <tr>\n",
       "      <th>He took a seat opposite Catherine</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>who kept her gaze fixed on him</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>as if she feared he would vanish were she to remove it</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He did not raise his to her often:</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>a quick glance now and then sufficed</th>\n",
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       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [He took a seat opposite Catherine, who kept her gaze fixed on him , as if she feared he would vanish were she to remove it, He did not raise his to her often:, a quick glance now and then sufficed]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "edf = pd.read_csv(\"bronte/linton_en.csv\", index_col = 0)\n",
    "edf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9ee3af46-f546-4d93-9daf-48413554fd1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "enresults = []\n",
    "# for sentences in df:\n",
    "for index, row in edf.iterrows():\n",
    "    dict = {}\n",
    "    sentiment_pipeline = pipeline(\"sentiment-analysis\", model=\"cardiffnlp/twitter-xlm-roberta-base-sentiment\")\n",
    "    data = index \n",
    "    rating = sentiment_pipeline(data)\n",
    "    # print(index)\n",
    "    # print(rating)\n",
    "    #df['score'] = rating\n",
    "    # print(df['score'])\n",
    "    dict['text'] = index\n",
    "    dict['label'] = rating[0]['label']\n",
    "    dict['score'] = rating[0]['score']\n",
    "    enresults.append(dict)\n",
    "# print(results) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c2244c74-5260-49de-91da-c1521a5447fd",
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>He took a seat opposite Catherine</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.522261</td>\n",
       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>who kept her gaze fixed on him</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.492833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>as if she feared he would vanish were she to r...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.721657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>He did not raise his to her often:</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.573433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a quick glance now and then sufficed</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.432435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>but it flashed back</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.520420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>each time more confidently</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.592306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>the undisguised delight he drank from hers</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.531873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>They were too much absorbed in their mutual joy</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.388671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>to suffer embarrassment.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.933410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Not so Mr. Edgar</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.520566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>he grew pale with pure annoyance:</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.880579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>a feeling that reached its climax</td>\n",
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       "      <td>0.372927</td>\n",
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       "      <th>13</th>\n",
       "      <td>when his lady rose,</td>\n",
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       "      <td>0.493878</td>\n",
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       "      <th>14</th>\n",
       "      <td>and stepping across the rug</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.536243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>seized Heathcliff’s hands again,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.640792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>and laughed like one beside herself.</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.352033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>“I shall think it a dream to-morrow!” she cried</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.546600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>I shall not be able to believe</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.861976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>that I have seen, and touched, and spoken to y...</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.771640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>And yet, cruel Heathcliff!</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.952251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>you don’t deserve this welcome.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.888623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>to be absent and silent for three years,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.559199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>and never to think of me!”</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.512595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>A little more than you have thought of me,” he...</td>\n",
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       "      <td>0.490105</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>“I heard of your marriage, Cathy, not long sin...</td>\n",
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       "      <td>0.723653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>; and, while waiting in the yard below,</td>\n",
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       "      <td>0.564331</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>I meditated this plan</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.586790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>just to have one glimpse of your face</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.468848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>a stare of surprise, perhaps</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.509321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>and pretended pleasure;</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.386152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>afterwards settle my score with Hindley;</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.693387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>and then prevent the law by doing execution on...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.701327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Your welcome has put these ideas out of my mind;</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.472241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>but beware of meeting me with another aspect n...</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.478341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Nay, you’ll not drive me off again.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.575289</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>You were really sorry for me, were you?</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.866053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Well, there was cause.</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.594909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>I’ve fought through a bitter life</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.815367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>since I last heard your voice;</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.543911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>and you must forgive me,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.596205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>for I struggled only for you!”</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.500223</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text     label     score\n",
       "0                   He took a seat opposite Catherine   neutral  0.522261\n",
       "1                     who kept her gaze fixed on him    neutral  0.492833\n",
       "2   as if she feared he would vanish were she to r...  negative  0.721657\n",
       "3                  He did not raise his to her often:   neutral  0.573433\n",
       "4                a quick glance now and then sufficed   neutral  0.432435\n",
       "5                                 but it flashed back   neutral  0.520420\n",
       "6                          each time more confidently  positive  0.592306\n",
       "7          the undisguised delight he drank from hers  positive  0.531873\n",
       "8     They were too much absorbed in their mutual joy  negative  0.388671\n",
       "9                            to suffer embarrassment.  negative  0.933410\n",
       "10                                   Not so Mr. Edgar  negative  0.520566\n",
       "11                  he grew pale with pure annoyance:  negative  0.880579\n",
       "12                  a feeling that reached its climax   neutral  0.372927\n",
       "13                                when his lady rose,   neutral  0.493878\n",
       "14                        and stepping across the rug   neutral  0.536243\n",
       "15                   seized Heathcliff’s hands again,  negative  0.640792\n",
       "16               and laughed like one beside herself.   neutral  0.352033\n",
       "17    “I shall think it a dream to-morrow!” she cried  positive  0.546600\n",
       "18                     I shall not be able to believe  negative  0.861976\n",
       "19  that I have seen, and touched, and spoken to y...  positive  0.771640\n",
       "20                         And yet, cruel Heathcliff!  negative  0.952251\n",
       "21                    you don’t deserve this welcome.  negative  0.888623\n",
       "22           to be absent and silent for three years,  negative  0.559199\n",
       "23                         and never to think of me!”   neutral  0.512595\n",
       "24  A little more than you have thought of me,” he...   neutral  0.490105\n",
       "25  “I heard of your marriage, Cathy, not long sin...   neutral  0.723653\n",
       "26           ; and, while waiting in the yard below,    neutral  0.564331\n",
       "27                              I meditated this plan   neutral  0.586790\n",
       "28              just to have one glimpse of your face   neutral  0.468848\n",
       "29                       a stare of surprise, perhaps   neutral  0.509321\n",
       "30                            and pretended pleasure;  negative  0.386152\n",
       "31          afterwards settle my score with Hindley;    neutral  0.693387\n",
       "32  and then prevent the law by doing execution on...  negative  0.701327\n",
       "33  Your welcome has put these ideas out of my mind;   negative  0.472241\n",
       "34  but beware of meeting me with another aspect n...   neutral  0.478341\n",
       "35               Nay, you’ll not drive me off again.   negative  0.575289\n",
       "36           You were really sorry for me, were you?   negative  0.866053\n",
       "37                             Well, there was cause.   neutral  0.594909\n",
       "38                 I’ve fought through a bitter life   negative  0.815367\n",
       "39                    since I last heard your voice;    neutral  0.543911\n",
       "40                           and you must forgive me,  negative  0.596205\n",
       "41                     for I struggled only for you!”   neutral  0.500223"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf = pd.DataFrame(enresults)\n",
    "engdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "51ad09f2-b44b-435b-92a2-ad7f8b64f2a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "neutral     21\n",
       "negative    17\n",
       "positive     4\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf['label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "279e665b-effb-4987-b261-e47d863ba7cf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "negative    0.691786\n",
       "neutral     0.522042\n",
       "positive    0.610605\n",
       "Name: score, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf.groupby(['label'])['score'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "00fc5ad6-1b3f-4300-9609-df9567af401f",
   "metadata": {},
   "outputs": [],
   "source": [
    "engdf.to_csv(\"bronte/linton_en_scored.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65116101-abd8-40e6-9eae-9a99a479932b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "6f766f2b-49e8-4649-a628-6c3aa7cbe0e1",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Il s’assit en face de Catherine</th>\n",
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       "      <th>qui tenait les yeux fixes sur lui ;</th>\n",
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       "      <th>elle semblait craindre qu’il ne disparût si elle les détournait un instant.</th>\n",
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       "      <th>Lui ne leva pas souvent les yeux sur elle.</th>\n",
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       "      <th>Un rapide regard de temps à autre suffisait</th>\n",
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       "                                                    Unnamed: 1\n",
       "Texte                                                         \n",
       "Il s’assit en face de Catherine                            NaN\n",
       "qui tenait les yeux fixes sur lui ;                        NaN\n",
       "elle semblait craindre qu’il ne disparût si ell...         NaN\n",
       "Lui ne leva pas souvent les yeux sur elle.                 NaN\n",
       "Un rapide regard de temps à autre suffisait                NaN"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "fdf = pd.read_csv(\"bronte/linton_fr.csv\", index_col = 0)\n",
    "fdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4c127e6d-b07f-4a1d-a341-9f38d9e2b12f",
   "metadata": {},
   "outputs": [],
   "source": [
    "fresults = []\n",
    "# for sentences in df:\n",
    "for index, row in fdf.iterrows():\n",
    "    dict = {}\n",
    "    sentiment_pipeline = pipeline(\"sentiment-analysis\", model=\"cardiffnlp/twitter-xlm-roberta-base-sentiment\")\n",
    "    data = index \n",
    "    rating = sentiment_pipeline(data)\n",
    "    # print(index)\n",
    "    # print(rating)\n",
    "    #df['score'] = rating\n",
    "    # print(df['score'])\n",
    "    dict['text'] = index\n",
    "    dict['label'] = rating[0]['label']\n",
    "    dict['score'] = rating[0]['score']\n",
    "    fresults.append(dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c17ec547-dcb6-4676-874d-4576bd0b8bae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .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>text</th>\n",
       "      <th>label</th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Il s’assit en face de Catherine</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.787971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>qui tenait les yeux fixes sur lui ;</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.493397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>elle semblait craindre qu’il ne disparût si el...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.905929</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lui ne leva pas souvent les yeux sur elle.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.441555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Un rapide regard de temps à autre suffisait</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.473813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mais ce regard reflétait,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.452555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>chaque fois avec plus d’assurance,</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.628510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>le délice dissimulé qu’il buvait dans le sien.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.420714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Ils étaient trop absorbés dans leur joie mutuelle</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.847978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>pour se sentir embarrassés.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.877373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Il n’en était pas de même de Mr. Edgar</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.538110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>il pâlissait de contrariété.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.876112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ce sentiment atteignit le comble</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.480427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>quand sa femme se leva et,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.578888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>s’approchant de Heathcliff,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.452029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>lui saisit de nouveau les mains,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.498429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>en riant d’un air égaré.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.790459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Demain, je m’imaginerai avoir rêvé, s’écria- t...</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.474488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Je ne pourrai pas croire</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.586161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>que je vous ai vu, que je vous ai touché, que ...</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.781497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Et pourtant, cruel Heathcliff,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.944651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>vous ne méritez pas cet accueil.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.946809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Rester trois ans absent, sans donner signe de vie</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.907845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>et sans jamais penser à moi !</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.376132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Un peu plus que vous n’avez pensé à moi, murmu...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.579227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>J’ai appris votre mariage, Cathy, il n’y a pas...</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.581446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Pendant que j’attendais en bas, dans la cour,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.534994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>je méditais ce projet</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.897901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>entrevoir simplement votre visage,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.593154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>recevoir en retour un regard de surprise, peut...</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.466751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>et de plaisir affecté</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.586515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>puis régler mon compte avec Hindley,</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.564010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>et enfin prévenir la loi en me faisant justic...</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.754096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Votre accueil m’a fait sortir ces idées de l’e...</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.855174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>mais prenez garde de ne pas me recevoir d’un a...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.782245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Non, vous ne me chasserez plus.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.724057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Vous étiez réellement inquiète de moi, n’est-...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.857927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Eh bien ! il y avait de quoi.</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.530495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>J’ai mené un dur combat dans la vie,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.775802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>depuis le jour que j’ai cessé d’entendre votre...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.468151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>il faut me pardonner,</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.930229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>car c’est uniquement pour vous que je luttais !</td>\n",
       "      <td>positive</td>\n",
       "      <td>0.620993</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text     label     score\n",
       "0                     Il s’assit en face de Catherine  negative  0.787971\n",
       "1                 qui tenait les yeux fixes sur lui ;   neutral  0.493397\n",
       "2   elle semblait craindre qu’il ne disparût si el...  negative  0.905929\n",
       "3         Lui ne leva pas souvent les yeux sur elle.   negative  0.441555\n",
       "4        Un rapide regard de temps à autre suffisait    neutral  0.473813\n",
       "5                           mais ce regard reflétait,  negative  0.452555\n",
       "6                  chaque fois avec plus d’assurance,  positive  0.628510\n",
       "7      le délice dissimulé qu’il buvait dans le sien.  negative  0.420714\n",
       "8   Ils étaient trop absorbés dans leur joie mutuelle  positive  0.847978\n",
       "9                         pour se sentir embarrassés.  negative  0.877373\n",
       "10             Il n’en était pas de même de Mr. Edgar  negative  0.538110\n",
       "11                      il pâlissait de contrariété.   negative  0.876112\n",
       "12                   Ce sentiment atteignit le comble  positive  0.480427\n",
       "13                         quand sa femme se leva et,   neutral  0.578888\n",
       "14                       s’approchant de Heathcliff,    neutral  0.452029\n",
       "15                   lui saisit de nouveau les mains,   neutral  0.498429\n",
       "16                           en riant d’un air égaré.  negative  0.790459\n",
       "17  Demain, je m’imaginerai avoir rêvé, s’écria- t...   neutral  0.474488\n",
       "18                           Je ne pourrai pas croire  negative  0.586161\n",
       "19  que je vous ai vu, que je vous ai touché, que ...  positive  0.781497\n",
       "20                     Et pourtant, cruel Heathcliff,  negative  0.944651\n",
       "21                   vous ne méritez pas cet accueil.  negative  0.946809\n",
       "22  Rester trois ans absent, sans donner signe de vie  negative  0.907845\n",
       "23                      et sans jamais penser à moi !   neutral  0.376132\n",
       "24  Un peu plus que vous n’avez pensé à moi, murmu...  negative  0.579227\n",
       "25  J’ai appris votre mariage, Cathy, il n’y a pas...   neutral  0.581446\n",
       "26      Pendant que j’attendais en bas, dans la cour,   neutral  0.534994\n",
       "27                              je méditais ce projet  positive  0.897901\n",
       "28                entrevoir simplement votre visage,    neutral  0.593154\n",
       "29  recevoir en retour un regard de surprise, peut...  positive  0.466751\n",
       "30                              et de plaisir affecté  negative  0.586515\n",
       "31              puis régler mon compte avec Hindley,    neutral  0.564010\n",
       "32   et enfin prévenir la loi en me faisant justic...  positive  0.754096\n",
       "33  Votre accueil m’a fait sortir ces idées de l’e...  positive  0.855174\n",
       "34  mais prenez garde de ne pas me recevoir d’un a...  negative  0.782245\n",
       "35                   Non, vous ne me chasserez plus.   negative  0.724057\n",
       "36   Vous étiez réellement inquiète de moi, n’est-...  negative  0.857927\n",
       "37                      Eh bien ! il y avait de quoi.  positive  0.530495\n",
       "38              J’ai mené un dur combat dans la vie,   negative  0.775802\n",
       "39  depuis le jour que j’ai cessé d’entendre votre...  negative  0.468151\n",
       "40                              il faut me pardonner,  negative  0.930229\n",
       "41    car c’est uniquement pour vous que je luttais !  positive  0.620993"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frdf = pd.DataFrame(fresults)\n",
    "frdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "13e6525c-4d96-40ab-98c6-393600f511d3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "negative    21\n",
       "neutral     11\n",
       "positive    10\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frdf['label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "73ec17e4-e152-4989-a71f-3ee9354ebac5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "neutral     21\n",
       "negative    17\n",
       "positive     4\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf['label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "03e44bbc-b326-4318-b70b-d205e38172b9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "negative    21\n",
       "neutral     11\n",
       "positive    10\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frdf['label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "92dbb4c0-b985-4693-a294-de5a74bb3c13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "neutral     21\n",
       "negative    17\n",
       "positive     4\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf['label'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0897431b-9743-4e27-869f-c0c32ee89296",
   "metadata": {},
   "source": [
    "### French translation has stronger \"positive\" and \"negative\" scores "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "33483ab0-a08a-4d2e-baaa-a3d5d96ed0ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "negative    0.722876\n",
       "neutral     0.510980\n",
       "positive    0.686382\n",
       "Name: score, dtype: float64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frdf.groupby(['label'])['score'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c84ad5b-6484-434f-b247-f010ecfb4604",
   "metadata": {},
   "source": [
    "### English original has slightly stronger \"neutral\" scores "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ce18fe88-d379-4c32-8c9e-d457c3dda9c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "label\n",
       "negative    0.691786\n",
       "neutral     0.522042\n",
       "positive    0.610605\n",
       "Name: score, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engdf.groupby(['label'])['score'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c86e7d1b-2df2-4f17-a0d7-650ef31c4d43",
   "metadata": {},
   "outputs": [],
   "source": [
    "frdf.to_csv(\"bronte/linton_fr_scored.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "ba673045-ec95-4757-824a-d4b5cfda32f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'text': 'Il s’assit en face de Catherine', 'label': 'negative', 'score': 0.7879713773727417, 'categ_score': -2}\n"
     ]
    }
   ],
   "source": [
    "for row in fresults: \n",
    "    if row['label'] == 'negative':\n",
    "        if row['score'] > 0.5:\n",
    "            row['categ_score'] = -2\n",
    "        else: \n",
    "            row['categ_score'] = -1\n",
    "    elif row['label'] == 'positive':\n",
    "        if row['score'] > 0.5:\n",
    "            row['categ_score'] = 2\n",
    "        else:\n",
    "            row['categ_score'] = 1\n",
    "    else:\n",
    "        row['categ_score'] = 0\n",
    "print(fresults[0])                        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "80c1f482-9538-42fb-ac70-3471cb3880e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>text</th>\n",
       "      <th>label</th>\n",
       "      <th>score</th>\n",
       "      <th>categ_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Il s’assit en face de Catherine</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.787971</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>qui tenait les yeux fixes sur lui ;</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.493397</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>elle semblait craindre qu’il ne disparût si el...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.905929</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lui ne leva pas souvent les yeux sur elle.</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.441555</td>\n",
       "      <td>-1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Un rapide regard de temps à autre suffisait</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.473813</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text     label     score  \\\n",
       "0                    Il s’assit en face de Catherine  negative  0.787971   \n",
       "1                qui tenait les yeux fixes sur lui ;   neutral  0.493397   \n",
       "2  elle semblait craindre qu’il ne disparût si el...  negative  0.905929   \n",
       "3        Lui ne leva pas souvent les yeux sur elle.   negative  0.441555   \n",
       "4       Un rapide regard de temps à autre suffisait    neutral  0.473813   \n",
       "\n",
       "   categ_score  \n",
       "0           -2  \n",
       "1            0  \n",
       "2           -2  \n",
       "3           -1  \n",
       "4            0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fr_categ = pd.DataFrame(fresults)\n",
    "fr_categ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7516840e-f38f-4b2d-9390-f7ebedb7e98f",
   "metadata": {},
   "outputs": [],
   "source": [
    "fr_categ.to_csv(\"linton_fr_categ.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "981c12cf-5c6c-4926-adaf-f15bd69c63fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'text': 'He took a seat opposite Catherine', 'label': 'neutral', 'score': 0.5222605466842651, 'categ_score': 0}\n"
     ]
    }
   ],
   "source": [
    "for row in enresults: \n",
    "    if row['label'] == 'negative':\n",
    "        if row['score'] > 0.5:\n",
    "            row['categ_score'] = -2\n",
    "        else: \n",
    "            row['categ_score'] = -1\n",
    "    elif row['label'] == 'positive':\n",
    "        if row['score'] > 0.5:\n",
    "            row['categ_score'] = 2\n",
    "        else:\n",
    "            row['categ_score'] = 1\n",
    "    else:\n",
    "        row['categ_score'] = 0\n",
    "print(enresults[0])     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fe82ee92-d3a9-48ba-9cb9-18ab510afe31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "      <th>score</th>\n",
       "      <th>categ_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>He took a seat opposite Catherine</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.522261</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>who kept her gaze fixed on him</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.492833</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>as if she feared he would vanish were she to r...</td>\n",
       "      <td>negative</td>\n",
       "      <td>0.721657</td>\n",
       "      <td>-2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>He did not raise his to her often:</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.573433</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a quick glance now and then sufficed</td>\n",
       "      <td>neutral</td>\n",
       "      <td>0.432435</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text     label     score  \\\n",
       "0                  He took a seat opposite Catherine   neutral  0.522261   \n",
       "1                    who kept her gaze fixed on him    neutral  0.492833   \n",
       "2  as if she feared he would vanish were she to r...  negative  0.721657   \n",
       "3                 He did not raise his to her often:   neutral  0.573433   \n",
       "4               a quick glance now and then sufficed   neutral  0.432435   \n",
       "\n",
       "   categ_score  \n",
       "0            0  \n",
       "1            0  \n",
       "2           -2  \n",
       "3            0  \n",
       "4            0  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "en_categ = pd.DataFrame(enresults)\n",
    "en_categ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "56ca3fd2-5a58-45b1-b22d-4aabfba9b1c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "en_categ.to_csv(\"bronte/linton_en_categ.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51fa64aa-90cd-4c65-9c57-3b165eb6ae84",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "68a4d4da-c95d-4f16-ab53-4c6bce390c56",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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