nlp-lab/Project/advanced_approach/Evaluation_sentiment_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package punkt to /home/jonas/nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n",
      "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
      "[nltk_data]     /home/jonas/nltk_data...\n",
      "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
      "[nltk_data]       date!\n",
      "[nltk_data] Downloading package wordnet to /home/jonas/nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import twitter_learning as twl\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "matplotlib.rc('font', family='symbola', size=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* download data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dataset already downloaded\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "\n",
    "if [ ! -e 'dataset_sentiment.csv' ]\n",
    "then\n",
    "    echo \"downloading dataset\"\n",
    "    wget https://raw.githubusercontent.com/SmartDataAnalytics/MA-INF-4222-NLP-Lab/master/2018_SoSe/exercises/dataset_sentiment.csv\n",
    "else\n",
    "    echo \"dataset already downloaded\"\n",
    "fi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sentiment_score(s):\n",
    "    #(pos, neg, neu)^T\n",
    "    return s[0] - s[1]\n",
    "\n",
    "def plot_sentiment_space(predicted_sentiment_vectors_list, top_sentiments, top_emojis, style=['bo']):\n",
    "    # sentiment score axis\n",
    "    top_X = np.array([sentiment_score(x) for x in top_sentiments])\n",
    "    \n",
    "\n",
    "    # neutral axis:\n",
    "    top_Y = np.array([x[2] for x in top_sentiments])\n",
    "    \n",
    "\n",
    "    fig_1, ax_1 = plt.subplots(figsize=(7.5,5))\n",
    "    plt.title(\"sentiment-score-plot\")\n",
    "    plt.xlabel(\"sentiment score\")\n",
    "    plt.ylabel(\"neutrality\")\n",
    "    plt.xlim([np.min(top_X),np.max(top_X)])\n",
    "    plt.ylim([np.min(top_Y),np.max(top_Y)])\n",
    "    for i in range(len(top_X)):\n",
    "        plt.text(top_X[i], top_Y[i], top_emojis[i])\n",
    "    for i in range(len(predicted_sentiment_vectors_list)):\n",
    "        pred_X = np.array([sentiment_score(x) for x in predicted_sentiment_vectors_list[i]])\n",
    "        pred_Y = np.array([x[2] for x in predicted_sentiment_vectors_list[i]])\n",
    "        plt.plot(pred_X, pred_Y, style[i], alpha=0.5)\n",
    "    #plt.savefig(\"val-error_sentiment-plot\" + str(datetime.datetime.now()) +  \".png\", bbox_inches='tight')\n",
    "\n",
    "    # sentiment score axis\n",
    "    top_X = np.array([x[0] for x in top_sentiments])\n",
    "    \n",
    "\n",
    "    # neutral axis:\n",
    "    top_Y = np.array([x[1] for x in top_sentiments])\n",
    "    \n",
    "\n",
    "    fig_2, ax_2 = plt.subplots(figsize=(7.5,5))\n",
    "    plt.title(\"positive-negative-plot\")\n",
    "    plt.xlabel(\"positive\")\n",
    "    plt.ylabel(\"negative\")\n",
    "    plt.xlim([np.min(top_X),np.max(top_X)])\n",
    "    plt.ylim([np.min(top_Y),np.max(top_Y)])\n",
    "    for i in range(len(top_X)):\n",
    "        plt.text(top_X[i], top_Y[i], top_emojis[i])\n",
    "    for i in range(len(predicted_sentiment_vectors_list)):\n",
    "        pred_X = np.array([x[0] for x in predicted_sentiment_vectors_list[i]])\n",
    "        pred_Y = np.array([x[1] for x in predicted_sentiment_vectors_list[i]])\n",
    "        plt.plot(pred_X, pred_Y, style[i], alpha=0.5)\n",
    "    #'plt.savefig(\"val-error_positive-negative-plot\" + str(datetime.datetime.now()) + \".png\", bbox_inches='tight')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* read data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('dataset_sentiment.csv')\n",
    "df = df[['text','sentiment']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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",
       "    }\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>sentiment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>nancyleegrahn how did everyone feel about th...</td>\n",
       "      <td>Neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>scottwalker didnt catch the full gopdebate l...</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>tjmshow no mention of tamir rice and the gop...</td>\n",
       "      <td>Neutral</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>robgeorge that carly fiorina is trending  ho...</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>danscavino gopdebate w realdonaldtrump deliv...</td>\n",
       "      <td>Positive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text sentiment\n",
       "0    nancyleegrahn how did everyone feel about th...   Neutral\n",
       "1    scottwalker didnt catch the full gopdebate l...  Positive\n",
       "2    tjmshow no mention of tamir rice and the gop...   Neutral\n",
       "3    robgeorge that carly fiorina is trending  ho...  Positive\n",
       "4    danscavino gopdebate w realdonaldtrump deliv...  Positive"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['text'] = df['text'].apply(lambda x: x.lower())\n",
    "df['text'] = df['text'].apply(lambda x: x.replace('rt',' '))\n",
    "df['text'] = df['text'].apply((lambda x: re.sub('[^a-zA-Z0-9\\s]','',x)))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "neg = np.array([df['sentiment'][i] == 'Negative' for i in range(df.shape[0])])\n",
    "pos = np.array([df['sentiment'][i] == 'Positive' for i in range(df.shape[0])])\n",
    "neu = np.array([df['sentiment'][i] == 'Neutral' for i in range(df.shape[0])])\n",
    "\n",
    "text = np.array(df['text'].tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* load pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipeline_file = \"/home/jonas/Dokumente/NLP_DATA/python_dumps/pipelines/tfidf_final/final_epoch01.pipeline\"\n",
    "pm = twl.pipeline_manager.load_from_pipeline_file(pipeline_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* plot statements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_20 = list(\"😳😋😀😌😏😔😒😎😢😅😁😉🙌🙏😘😊😩😍😭😂\")\n",
    "top_20_sents = twl.emoji2sent(top_20)\n",
    "\n",
    "pred_pos = pm.predict(text[pos])\n",
    "pred_neg = pm.predict(text[neg])\n",
    "pred_neu = pm.predict(text[neu])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 540x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#twl.plot_sentiment_space(predicted_sentiment_vectors=pred_pos, top_sentiments=top_20_sents, top_emojis=top_20, style='go')\n",
    "#twl.plot_sentiment_space(predicted_sentiment_vectors=pred_neg, top_sentiments=top_20_sents, top_emojis=top_20, style='ro')\n",
    "#twl.plot_sentiment_space(predicted_sentiment_vectors=pred_neu, top_sentiments=top_20_sents, top_emojis=top_20, style='bo')\n",
    "plot_sentiment_space(predicted_sentiment_vectors_list=[pred_pos,pred_neg,pred_neu], top_sentiments=top_20_sents, top_emojis=top_20, style=['g+','b+','r+'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## user labeled sentiment dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('../sentiment_sentences.csv', delimiter=';')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "neg = np.array([df['sent'][i] == 'n' for i in range(df.shape[0])])\n",
    "pos = np.array([df['sent'][i] == 'p' for i in range(df.shape[0])])\n",
    "\n",
    "text = np.array(df['text'].tolist())\n",
    "\n",
    "pred_pos = pm.predict(text[pos])\n",
    "pred_neg = pm.predict(text[neg])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_sentiment_space(predicted_sentiment_vectors_list=[pred_pos,pred_neg], top_sentiments=top_20_sents, top_emojis=top_20, style=['go','ro'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<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",
       "    }\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>sent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>I am so happy</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>i love my life</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>i really like this sunshine</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>while doing sport i feel free</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>i is terrible to learn when the weather is thi...</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>i am almost crying when i run out of ice cream</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>fuck off</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>you are my best friend ever</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>i love my mommy</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>i prefer oral exams</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>best cocktail is the mojito especial</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>you got a beautiful wedding</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>you husband is this handsome</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>this is such a sneaky bitch</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>you're kidding</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>you are really too drunk</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>you start being annoying</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>i love my mac</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>but it would be better if they are less expensive</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>you are a bad friend</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>I am in love with my new laptop</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>You piss me off</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>I hate school</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>I'm so mad at you</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Seeing you cry, makes me sad</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>You are so lovely</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Fish is disgusting</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>At times I feel so depressed</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Summer makes me happy</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>I want to dance and sing aloud</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Everything will be ok</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>why are you upset?</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>I dont like it when it rains</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>I dont care at all</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>you are such a bitch</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>I dont understand what this is all about</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>give me a break, idiot!</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>please dont leave me</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>I love cuddling with my dog</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>I want to die</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>that is really sad!</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>why are you saying that, you moron!</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>OMG! i love that cat soo much!</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>can you feel the love tonight</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>i get so emotional when i watch lion king</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>i really hate you</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>that is disgusting</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>my heart is broken</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>i love these sunny days</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>this gave me positive feelings</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>i am sick</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>i am tired</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>are you sick or tired?</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>you are so cute and sweet</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>i just lost my mind</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>i hate all people</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>you are just dumb</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>i will get lucky</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>i like ice cream</td>\n",
       "      <td>p</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>go home you idiot</td>\n",
       "      <td>n</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 text sent\n",
       "0                                       I am so happy    p\n",
       "1                                      i love my life    p\n",
       "2                         i really like this sunshine    p\n",
       "3                       while doing sport i feel free    p\n",
       "4   i is terrible to learn when the weather is thi...    n\n",
       "5      i am almost crying when i run out of ice cream    n\n",
       "6                                            fuck off    n\n",
       "7                         you are my best friend ever    p\n",
       "8                                     i love my mommy    p\n",
       "9                                 i prefer oral exams    p\n",
       "10               best cocktail is the mojito especial    p\n",
       "11                        you got a beautiful wedding    p\n",
       "12                       you husband is this handsome    p\n",
       "13                        this is such a sneaky bitch    n\n",
       "14                                     you're kidding    n\n",
       "15                           you are really too drunk    n\n",
       "16                           you start being annoying    n\n",
       "17                                      i love my mac    p\n",
       "18  but it would be better if they are less expensive    n\n",
       "19                               you are a bad friend    n\n",
       "20                    I am in love with my new laptop    p\n",
       "21                                    You piss me off    n\n",
       "22                                      I hate school    n\n",
       "23                                  I'm so mad at you    n\n",
       "24                       Seeing you cry, makes me sad    n\n",
       "25                                  You are so lovely    p\n",
       "26                                 Fish is disgusting    n\n",
       "27                       At times I feel so depressed    n\n",
       "28                              Summer makes me happy    p\n",
       "29                     I want to dance and sing aloud    p\n",
       "30                              Everything will be ok    p\n",
       "31                                 why are you upset?    n\n",
       "32                       I dont like it when it rains    n\n",
       "33                                 I dont care at all    n\n",
       "34                               you are such a bitch    n\n",
       "35           I dont understand what this is all about    n\n",
       "36                            give me a break, idiot!    n\n",
       "37                               please dont leave me    n\n",
       "38                        I love cuddling with my dog    p\n",
       "39                                      I want to die    n\n",
       "40                                that is really sad!    n\n",
       "41                why are you saying that, you moron!    n\n",
       "42                     OMG! i love that cat soo much!    p\n",
       "43                      can you feel the love tonight    p\n",
       "44          i get so emotional when i watch lion king    p\n",
       "45                                  i really hate you    n\n",
       "46                                 that is disgusting    n\n",
       "47                                 my heart is broken    n\n",
       "48                            i love these sunny days    p\n",
       "49                     this gave me positive feelings    p\n",
       "50                                          i am sick    n\n",
       "51                                         i am tired    n\n",
       "52                             are you sick or tired?    n\n",
       "53                          you are so cute and sweet    p\n",
       "54                                i just lost my mind    n\n",
       "55                                  i hate all people    n\n",
       "56                                  you are just dumb    n\n",
       "57                                   i will get lucky    p\n",
       "58                                   i like ice cream    p\n",
       "59                                  go home you idiot    n"
      ]
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