ACM_EDA.ipynb

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          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n"
          ]
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              "True"
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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from collections import Counter\n",
        "from wordcloud import WordCloud\n",
        "import nltk\n",
        "from nltk.corpus import stopwords\n",
        "from PIL import Image\n",
        "from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n",
        "nltk.download('stopwords')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Load tweet_emotions data set."
      ],
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        "id": "hTLzyX6Gh0aB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv(\"sample_data/tweet_emotions.csv\")"
      ],
      "metadata": {
        "id": "LyOWJL1Af3ss"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print data frame."
      ],
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        "df"
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            "text/plain": [
              "         tweet_id   sentiment  \\\n",
              "0      1956967341       empty   \n",
              "1      1956967666     sadness   \n",
              "2      1956967696     sadness   \n",
              "3      1956967789  enthusiasm   \n",
              "4      1956968416     neutral   \n",
              "...           ...         ...   \n",
              "39995  1753918954     neutral   \n",
              "39996  1753919001        love   \n",
              "39997  1753919005        love   \n",
              "39998  1753919043   happiness   \n",
              "39999  1753919049        love   \n",
              "\n",
              "                                                 content  \n",
              "0      @tiffanylue i know  i was listenin to bad habi...  \n",
              "1      Layin n bed with a headache  ughhhh...waitin o...  \n",
              "2                    Funeral ceremony...gloomy friday...  \n",
              "3                   wants to hang out with friends SOON!  \n",
              "4      @dannycastillo We want to trade with someone w...  \n",
              "...                                                  ...  \n",
              "39995                                   @JohnLloydTaylor  \n",
              "39996                     Happy Mothers Day  All my love  \n",
              "39997  Happy Mother's Day to all the mommies out ther...  \n",
              "39998  @niariley WASSUP BEAUTIFUL!!! FOLLOW ME!!  PEE...  \n",
              "39999  @mopedronin bullet train from tokyo    the gf ...  \n",
              "\n",
              "[40000 rows x 3 columns]"
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>tweet_id</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>content</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1956967341</td>\n",
              "      <td>empty</td>\n",
              "      <td>@tiffanylue i know  i was listenin to bad habi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1956967666</td>\n",
              "      <td>sadness</td>\n",
              "      <td>Layin n bed with a headache  ughhhh...waitin o...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1956967696</td>\n",
              "      <td>sadness</td>\n",
              "      <td>Funeral ceremony...gloomy friday...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1956967789</td>\n",
              "      <td>enthusiasm</td>\n",
              "      <td>wants to hang out with friends SOON!</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1956968416</td>\n",
              "      <td>neutral</td>\n",
              "      <td>@dannycastillo We want to trade with someone w...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <th>39995</th>\n",
              "      <td>1753918954</td>\n",
              "      <td>neutral</td>\n",
              "      <td>@JohnLloydTaylor</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39996</th>\n",
              "      <td>1753919001</td>\n",
              "      <td>love</td>\n",
              "      <td>Happy Mothers Day  All my love</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39997</th>\n",
              "      <td>1753919005</td>\n",
              "      <td>love</td>\n",
              "      <td>Happy Mother's Day to all the mommies out ther...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39998</th>\n",
              "      <td>1753919043</td>\n",
              "      <td>happiness</td>\n",
              "      <td>@niariley WASSUP BEAUTIFUL!!! FOLLOW ME!!  PEE...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39999</th>\n",
              "      <td>1753919049</td>\n",
              "      <td>love</td>\n",
              "      <td>@mopedronin bullet train from tokyo    the gf ...</td>\n",
              "    </tr>\n",
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              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"tweet_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 118857896,\n        \"min\": 1693956175,\n        \"max\": 1966441171,\n        \"num_unique_values\": 40000,\n        \"samples\": [\n          1752414968,\n          1965295852,\n          1696219218\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 13,\n        \"samples\": [\n          \"relief\",\n          \"happiness\",\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39827,\n        \"samples\": [\n          \"the sun is shinning! im off out!!\",\n          \"wow i must have been tired. i fell asleep @ exactly the start of the 10pm news &amp; now up as if its 8am.\",\n          \"@knobzie their loss\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
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    {
      "cell_type": "markdown",
      "source": [
        "Print the first five columns."
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      "metadata": {
        "id": "cXuleqlKh-tc"
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      "cell_type": "code",
      "source": [
        "df.head()"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     tweet_id   sentiment                                            content\n",
              "0  1956967341       empty  @tiffanylue i know  i was listenin to bad habi...\n",
              "1  1956967666     sadness  Layin n bed with a headache  ughhhh...waitin o...\n",
              "2  1956967696     sadness                Funeral ceremony...gloomy friday...\n",
              "3  1956967789  enthusiasm               wants to hang out with friends SOON!\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"tweet_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 118857896,\n        \"min\": 1693956175,\n        \"max\": 1966441171,\n        \"num_unique_values\": 40000,\n        \"samples\": [\n          1752414968,\n          1965295852,\n          1696219218\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 13,\n        \"samples\": [\n          \"relief\",\n          \"happiness\",\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39827,\n        \"samples\": [\n          \"the sun is shinning! im off out!!\",\n          \"wow i must have been tired. i fell asleep @ exactly the start of the 10pm news &amp; now up as if its 8am.\",\n          \"@knobzie their loss\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print all of the columns of the data frame."
      ],
      "metadata": {
        "id": "uoi_Vsh2iCEp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iANReBnCgkOu",
        "outputId": "a08e0cc3-f2a9-4fb7-e06b-3cb2521a214a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['tweet_id', 'sentiment', 'content'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print the number of sentiment words."
      ],
      "metadata": {
        "id": "m_6ZNVEsiDEa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "temp = df.groupby('sentiment').count()['content'].reset_index().sort_values(by='content',ascending=False)\n",
        "temp.style.background_gradient(cmap='Purples')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 457
        },
        "id": "OQOpGbgFgm3G",
        "outputId": "ccfb5cd5-05ba-4065-c7e1-68ba3b6fc5d7"
      },
      "execution_count": null,
      "outputs": [
        {
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              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_82ea3_level0_col0\" class=\"col_heading level0 col0\" >sentiment</th>\n",
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              "      <th id=\"T_82ea3_level0_row0\" class=\"row_heading level0 row0\" >8</th>\n",
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              "      <td id=\"T_82ea3_row0_col1\" class=\"data row0 col1\" >8638</td>\n",
              "    </tr>\n",
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              "      <th id=\"T_82ea3_level0_row1\" class=\"row_heading level0 row1\" >12</th>\n",
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              "      <td id=\"T_82ea3_row1_col1\" class=\"data row1 col1\" >8459</td>\n",
              "    </tr>\n",
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              "      <th id=\"T_82ea3_level0_row2\" class=\"row_heading level0 row2\" >5</th>\n",
              "      <td id=\"T_82ea3_row2_col0\" class=\"data row2 col0\" >happiness</td>\n",
              "      <td id=\"T_82ea3_row2_col1\" class=\"data row2 col1\" >5209</td>\n",
              "    </tr>\n",
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              "      <td id=\"T_82ea3_row3_col1\" class=\"data row3 col1\" >5165</td>\n",
              "    </tr>\n",
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              "      <th id=\"T_82ea3_level0_row4\" class=\"row_heading level0 row4\" >7</th>\n",
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              "      <td id=\"T_82ea3_row4_col1\" class=\"data row4 col1\" >3842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row5\" class=\"row_heading level0 row5\" >11</th>\n",
              "      <td id=\"T_82ea3_row5_col0\" class=\"data row5 col0\" >surprise</td>\n",
              "      <td id=\"T_82ea3_row5_col1\" class=\"data row5 col1\" >2187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row6\" class=\"row_heading level0 row6\" >4</th>\n",
              "      <td id=\"T_82ea3_row6_col0\" class=\"data row6 col0\" >fun</td>\n",
              "      <td id=\"T_82ea3_row6_col1\" class=\"data row6 col1\" >1776</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row7\" class=\"row_heading level0 row7\" >9</th>\n",
              "      <td id=\"T_82ea3_row7_col0\" class=\"data row7 col0\" >relief</td>\n",
              "      <td id=\"T_82ea3_row7_col1\" class=\"data row7 col1\" >1526</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row8\" class=\"row_heading level0 row8\" >6</th>\n",
              "      <td id=\"T_82ea3_row8_col0\" class=\"data row8 col0\" >hate</td>\n",
              "      <td id=\"T_82ea3_row8_col1\" class=\"data row8 col1\" >1323</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row9\" class=\"row_heading level0 row9\" >2</th>\n",
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              "      <td id=\"T_82ea3_row9_col1\" class=\"data row9 col1\" >827</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row10\" class=\"row_heading level0 row10\" >3</th>\n",
              "      <td id=\"T_82ea3_row10_col0\" class=\"data row10 col0\" >enthusiasm</td>\n",
              "      <td id=\"T_82ea3_row10_col1\" class=\"data row10 col1\" >759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row11\" class=\"row_heading level0 row11\" >1</th>\n",
              "      <td id=\"T_82ea3_row11_col0\" class=\"data row11 col0\" >boredom</td>\n",
              "      <td id=\"T_82ea3_row11_col1\" class=\"data row11 col1\" >179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82ea3_level0_row12\" class=\"row_heading level0 row12\" >0</th>\n",
              "      <td id=\"T_82ea3_row12_col0\" class=\"data row12 col0\" >anger</td>\n",
              "      <td id=\"T_82ea3_row12_col1\" class=\"data row12 col1\" >110</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print data above as a bar graph."
      ],
      "metadata": {
        "id": "62q3sDOaiHEN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12,6))\n",
        "sns.countplot(x='sentiment',data=df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 560
        },
        "id": "-EQqE_rZgpHN",
        "outputId": "69ea5253-22b9-42c3-cb98-0fc6a521a0b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: xlabel='sentiment', ylabel='count'>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print common words."
      ],
      "metadata": {
        "id": "qOz_-CjBiJpK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['temp_list'] = df['content'].apply(lambda x:str(x).split())\n",
        "top = Counter([item for sublist in df['temp_list'] for item in sublist])\n",
        "temp = pd.DataFrame(top.most_common(20))\n",
        "temp.columns = ['content','temp_list']\n",
        "temp.style.background_gradient(cmap='Blues')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 677
        },
        "id": "p8KWTWxdgrpB",
        "outputId": "4bd05c86-27d5-493c-bc6a-2db11feb593d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7d499e170160>"
            ],
            "text/html": [
              "<style type=\"text/css\">\n",
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              "  background-color: #f7fbff;\n",
              "  color: #000000;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_20ee6\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_20ee6_level0_col0\" class=\"col_heading level0 col0\" >content</th>\n",
              "      <th id=\"T_20ee6_level0_col1\" class=\"col_heading level0 col1\" >temp_list</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_20ee6_row0_col0\" class=\"data row0 col0\" >to</td>\n",
              "      <td id=\"T_20ee6_row0_col1\" class=\"data row0 col1\" >14039</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_20ee6_row1_col0\" class=\"data row1 col0\" >I</td>\n",
              "      <td id=\"T_20ee6_row1_col1\" class=\"data row1 col1\" >12635</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_20ee6_row2_col0\" class=\"data row2 col0\" >the</td>\n",
              "      <td id=\"T_20ee6_row2_col1\" class=\"data row2 col1\" >12052</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_20ee6_row3_col0\" class=\"data row3 col0\" >a</td>\n",
              "      <td id=\"T_20ee6_row3_col1\" class=\"data row3 col1\" >9352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_20ee6_row4_col0\" class=\"data row4 col0\" >my</td>\n",
              "      <td id=\"T_20ee6_row4_col1\" class=\"data row4 col1\" >7160</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_20ee6_row5_col0\" class=\"data row5 col0\" >and</td>\n",
              "      <td id=\"T_20ee6_row5_col1\" class=\"data row5 col1\" >6750</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_20ee6_row6_col0\" class=\"data row6 col0\" >i</td>\n",
              "      <td id=\"T_20ee6_row6_col1\" class=\"data row6 col1\" >6257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_20ee6_row7_col0\" class=\"data row7 col0\" >you</td>\n",
              "      <td id=\"T_20ee6_row7_col1\" class=\"data row7 col1\" >5535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_20ee6_row8_col0\" class=\"data row8 col0\" >is</td>\n",
              "      <td id=\"T_20ee6_row8_col1\" class=\"data row8 col1\" >5254</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_20ee6_row9_col0\" class=\"data row9 col0\" >for</td>\n",
              "      <td id=\"T_20ee6_row9_col1\" class=\"data row9 col1\" >5146</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_20ee6_row10_col0\" class=\"data row10 col0\" >in</td>\n",
              "      <td id=\"T_20ee6_row10_col1\" class=\"data row10 col1\" >5053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_20ee6_row11_col0\" class=\"data row11 col0\" >of</td>\n",
              "      <td id=\"T_20ee6_row11_col1\" class=\"data row11 col1\" >4419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_20ee6_row12_col0\" class=\"data row12 col0\" >it</td>\n",
              "      <td id=\"T_20ee6_row12_col1\" class=\"data row12 col1\" >4333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_20ee6_row13_col0\" class=\"data row13 col0\" >on</td>\n",
              "      <td id=\"T_20ee6_row13_col1\" class=\"data row13 col1\" >3828</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_20ee6_row14_col0\" class=\"data row14 col0\" >have</td>\n",
              "      <td id=\"T_20ee6_row14_col1\" class=\"data row14 col1\" >3430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_20ee6_row15_col0\" class=\"data row15 col0\" >me</td>\n",
              "      <td id=\"T_20ee6_row15_col1\" class=\"data row15 col1\" >3109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_20ee6_row16_col0\" class=\"data row16 col0\" >that</td>\n",
              "      <td id=\"T_20ee6_row16_col1\" class=\"data row16 col1\" >3063</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_20ee6_row17_col0\" class=\"data row17 col0\" >so</td>\n",
              "      <td id=\"T_20ee6_row17_col1\" class=\"data row17 col1\" >3033</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_20ee6_row18_col0\" class=\"data row18 col0\" >with</td>\n",
              "      <td id=\"T_20ee6_row18_col1\" class=\"data row18 col1\" >2838</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_20ee6_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "      <td id=\"T_20ee6_row19_col0\" class=\"data row19 col0\" >be</td>\n",
              "      <td id=\"T_20ee6_row19_col1\" class=\"data row19 col1\" >2776</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print most common words, ignoring stop words."
      ],
      "metadata": {
        "id": "LT93ZzpJiOjK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def remove_stopword(x):\n",
        "    return [y for y in x if y not in stopwords.words('english')]\n",
        "df['temp_list'] = df['temp_list'].apply(lambda x:remove_stopword(x))"
      ],
      "metadata": {
        "id": "-0-VUdPdgsYD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "top = Counter([item for sublist in df['temp_list'] for item in sublist])\n",
        "temp = pd.DataFrame(top.most_common(100))\n",
        "temp = temp.iloc[1:,:]\n",
        "temp.columns = ['content','temp_list']\n",
        "temp.style.background_gradient(cmap='Purples')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "5VyY4o6tguu-",
        "outputId": "c8e49ce1-a1cc-4639-a653-3caafce1786f"
      },
      "execution_count": null,
      "outputs": [
        {
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              "  color: #000000;\n",
              "}\n",
              "#T_6d1ee_row73_col1, #T_6d1ee_row74_col1, #T_6d1ee_row75_col1, #T_6d1ee_row76_col1 {\n",
              "  background-color: #f9f8fb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6d1ee_row77_col1, #T_6d1ee_row78_col1, #T_6d1ee_row79_col1 {\n",
              "  background-color: #faf8fb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6d1ee_row80_col1, #T_6d1ee_row81_col1, #T_6d1ee_row82_col1, #T_6d1ee_row83_col1, #T_6d1ee_row84_col1, #T_6d1ee_row85_col1, #T_6d1ee_row86_col1 {\n",
              "  background-color: #faf9fc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6d1ee_row87_col1, #T_6d1ee_row88_col1, #T_6d1ee_row89_col1 {\n",
              "  background-color: #fbfafc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6d1ee_row90_col1, #T_6d1ee_row91_col1, #T_6d1ee_row92_col1, #T_6d1ee_row93_col1, #T_6d1ee_row94_col1, #T_6d1ee_row95_col1, #T_6d1ee_row96_col1, #T_6d1ee_row97_col1, #T_6d1ee_row98_col1 {\n",
              "  background-color: #fcfbfd;\n",
              "  color: #000000;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_6d1ee\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th id=\"T_6d1ee_level0_col0\" class=\"col_heading level0 col0\" >content</th>\n",
              "      <th id=\"T_6d1ee_level0_col1\" class=\"col_heading level0 col1\" >temp_list</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row0\" class=\"row_heading level0 row0\" >1</th>\n",
              "      <td id=\"T_6d1ee_row0_col0\" class=\"data row0 col0\" >I'm</td>\n",
              "      <td id=\"T_6d1ee_row0_col1\" class=\"data row0 col1\" >2440</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row1\" class=\"row_heading level0 row1\" >2</th>\n",
              "      <td id=\"T_6d1ee_row1_col0\" class=\"data row1 col0\" >get</td>\n",
              "      <td id=\"T_6d1ee_row1_col1\" class=\"data row1 col1\" >1934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row2\" class=\"row_heading level0 row2\" >3</th>\n",
              "      <td id=\"T_6d1ee_row2_col0\" class=\"data row2 col0\" >like</td>\n",
              "      <td id=\"T_6d1ee_row2_col1\" class=\"data row2 col1\" >1808</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row3\" class=\"row_heading level0 row3\" >4</th>\n",
              "      <td id=\"T_6d1ee_row3_col0\" class=\"data row3 col0\" >day</td>\n",
              "      <td id=\"T_6d1ee_row3_col1\" class=\"data row3 col1\" >1737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row4\" class=\"row_heading level0 row4\" >5</th>\n",
              "      <td id=\"T_6d1ee_row4_col0\" class=\"data row4 col0\" >-</td>\n",
              "      <td id=\"T_6d1ee_row4_col1\" class=\"data row4 col1\" >1730</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row5\" class=\"row_heading level0 row5\" >6</th>\n",
              "      <td id=\"T_6d1ee_row5_col0\" class=\"data row5 col0\" >go</td>\n",
              "      <td id=\"T_6d1ee_row5_col1\" class=\"data row5 col1\" >1558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row6\" class=\"row_heading level0 row6\" >7</th>\n",
              "      <td id=\"T_6d1ee_row6_col0\" class=\"data row6 col0\" >good</td>\n",
              "      <td id=\"T_6d1ee_row6_col1\" class=\"data row6 col1\" >1505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row7\" class=\"row_heading level0 row7\" >8</th>\n",
              "      <td id=\"T_6d1ee_row7_col0\" class=\"data row7 col0\" >got</td>\n",
              "      <td id=\"T_6d1ee_row7_col1\" class=\"data row7 col1\" >1453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row8\" class=\"row_heading level0 row8\" >9</th>\n",
              "      <td id=\"T_6d1ee_row8_col0\" class=\"data row8 col0\" >going</td>\n",
              "      <td id=\"T_6d1ee_row8_col1\" class=\"data row8 col1\" >1305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row9\" class=\"row_heading level0 row9\" >10</th>\n",
              "      <td id=\"T_6d1ee_row9_col0\" class=\"data row9 col0\" >love</td>\n",
              "      <td id=\"T_6d1ee_row9_col1\" class=\"data row9 col1\" >1252</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row10\" class=\"row_heading level0 row10\" >11</th>\n",
              "      <td id=\"T_6d1ee_row10_col0\" class=\"data row10 col0\" >work</td>\n",
              "      <td id=\"T_6d1ee_row10_col1\" class=\"data row10 col1\" >1182</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row11\" class=\"row_heading level0 row11\" >12</th>\n",
              "      <td id=\"T_6d1ee_row11_col0\" class=\"data row11 col0\" >one</td>\n",
              "      <td id=\"T_6d1ee_row11_col1\" class=\"data row11 col1\" >1090</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row12\" class=\"row_heading level0 row12\" >13</th>\n",
              "      <td id=\"T_6d1ee_row12_col0\" class=\"data row12 col0\" >u</td>\n",
              "      <td id=\"T_6d1ee_row12_col1\" class=\"data row12 col1\" >1081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row13\" class=\"row_heading level0 row13\" >14</th>\n",
              "      <td id=\"T_6d1ee_row13_col0\" class=\"data row13 col0\" >know</td>\n",
              "      <td id=\"T_6d1ee_row13_col1\" class=\"data row13 col1\" >1079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row14\" class=\"row_heading level0 row14\" >15</th>\n",
              "      <td id=\"T_6d1ee_row14_col0\" class=\"data row14 col0\" >really</td>\n",
              "      <td id=\"T_6d1ee_row14_col1\" class=\"data row14 col1\" >1073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row15\" class=\"row_heading level0 row15\" >16</th>\n",
              "      <td id=\"T_6d1ee_row15_col0\" class=\"data row15 col0\" >see</td>\n",
              "      <td id=\"T_6d1ee_row15_col1\" class=\"data row15 col1\" >1057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row16\" class=\"row_heading level0 row16\" >17</th>\n",
              "      <td id=\"T_6d1ee_row16_col0\" class=\"data row16 col0\" >back</td>\n",
              "      <td id=\"T_6d1ee_row16_col1\" class=\"data row16 col1\" >1026</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row17\" class=\"row_heading level0 row17\" >18</th>\n",
              "      <td id=\"T_6d1ee_row17_col0\" class=\"data row17 col0\" >&amp;</td>\n",
              "      <td id=\"T_6d1ee_row17_col1\" class=\"data row17 col1\" >967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row18\" class=\"row_heading level0 row18\" >19</th>\n",
              "      <td id=\"T_6d1ee_row18_col0\" class=\"data row18 col0\" >time</td>\n",
              "      <td id=\"T_6d1ee_row18_col1\" class=\"data row18 col1\" >964</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row19\" class=\"row_heading level0 row19\" >20</th>\n",
              "      <td id=\"T_6d1ee_row19_col0\" class=\"data row19 col0\" >im</td>\n",
              "      <td id=\"T_6d1ee_row19_col1\" class=\"data row19 col1\" >949</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row20\" class=\"row_heading level0 row20\" >21</th>\n",
              "      <td id=\"T_6d1ee_row20_col0\" class=\"data row20 col0\" >new</td>\n",
              "      <td id=\"T_6d1ee_row20_col1\" class=\"data row20 col1\" >942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row21\" class=\"row_heading level0 row21\" >22</th>\n",
              "      <td id=\"T_6d1ee_row21_col0\" class=\"data row21 col0\" >think</td>\n",
              "      <td id=\"T_6d1ee_row21_col1\" class=\"data row21 col1\" >934</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row22\" class=\"row_heading level0 row22\" >23</th>\n",
              "      <td id=\"T_6d1ee_row22_col0\" class=\"data row22 col0\" >want</td>\n",
              "      <td id=\"T_6d1ee_row22_col1\" class=\"data row22 col1\" >924</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row23\" class=\"row_heading level0 row23\" >24</th>\n",
              "      <td id=\"T_6d1ee_row23_col0\" class=\"data row23 col0\" >can't</td>\n",
              "      <td id=\"T_6d1ee_row23_col1\" class=\"data row23 col1\" >912</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row24\" class=\"row_heading level0 row24\" >25</th>\n",
              "      <td id=\"T_6d1ee_row24_col0\" class=\"data row24 col0\" >2</td>\n",
              "      <td id=\"T_6d1ee_row24_col1\" class=\"data row24 col1\" >848</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row25\" class=\"row_heading level0 row25\" >26</th>\n",
              "      <td id=\"T_6d1ee_row25_col0\" class=\"data row25 col0\" >still</td>\n",
              "      <td id=\"T_6d1ee_row25_col1\" class=\"data row25 col1\" >816</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row26\" class=\"row_heading level0 row26\" >27</th>\n",
              "      <td id=\"T_6d1ee_row26_col0\" class=\"data row26 col0\" >today</td>\n",
              "      <td id=\"T_6d1ee_row26_col1\" class=\"data row26 col1\" >814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row27\" class=\"row_heading level0 row27\" >28</th>\n",
              "      <td id=\"T_6d1ee_row27_col0\" class=\"data row27 col0\" >miss</td>\n",
              "      <td id=\"T_6d1ee_row27_col1\" class=\"data row27 col1\" >810</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row28\" class=\"row_heading level0 row28\" >29</th>\n",
              "      <td id=\"T_6d1ee_row28_col0\" class=\"data row28 col0\" >last</td>\n",
              "      <td id=\"T_6d1ee_row28_col1\" class=\"data row28 col1\" >768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row29\" class=\"row_heading level0 row29\" >30</th>\n",
              "      <td id=\"T_6d1ee_row29_col0\" class=\"data row29 col0\" >need</td>\n",
              "      <td id=\"T_6d1ee_row29_col1\" class=\"data row29 col1\" >766</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row30\" class=\"row_heading level0 row30\" >31</th>\n",
              "      <td id=\"T_6d1ee_row30_col0\" class=\"data row30 col0\" >much</td>\n",
              "      <td id=\"T_6d1ee_row30_col1\" class=\"data row30 col1\" >756</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row31\" class=\"row_heading level0 row31\" >32</th>\n",
              "      <td id=\"T_6d1ee_row31_col0\" class=\"data row31 col0\" >My</td>\n",
              "      <td id=\"T_6d1ee_row31_col1\" class=\"data row31 col1\" >748</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row32\" class=\"row_heading level0 row32\" >33</th>\n",
              "      <td id=\"T_6d1ee_row32_col0\" class=\"data row32 col0\" >feel</td>\n",
              "      <td id=\"T_6d1ee_row32_col1\" class=\"data row32 col1\" >722</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row33\" class=\"row_heading level0 row33\" >34</th>\n",
              "      <td id=\"T_6d1ee_row33_col0\" class=\"data row33 col0\" >home</td>\n",
              "      <td id=\"T_6d1ee_row33_col1\" class=\"data row33 col1\" >714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row34\" class=\"row_heading level0 row34\" >35</th>\n",
              "      <td id=\"T_6d1ee_row34_col0\" class=\"data row34 col0\" >lol</td>\n",
              "      <td id=\"T_6d1ee_row34_col1\" class=\"data row34 col1\" >691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row35\" class=\"row_heading level0 row35\" >36</th>\n",
              "      <td id=\"T_6d1ee_row35_col0\" class=\"data row35 col0\" >Just</td>\n",
              "      <td id=\"T_6d1ee_row35_col1\" class=\"data row35 col1\" >678</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row36\" class=\"row_heading level0 row36\" >37</th>\n",
              "      <td id=\"T_6d1ee_row36_col0\" class=\"data row36 col0\" >night</td>\n",
              "      <td id=\"T_6d1ee_row36_col1\" class=\"data row36 col1\" >664</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row37\" class=\"row_heading level0 row37\" >38</th>\n",
              "      <td id=\"T_6d1ee_row37_col0\" class=\"data row37 col0\" >Happy</td>\n",
              "      <td id=\"T_6d1ee_row37_col1\" class=\"data row37 col1\" >663</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row38\" class=\"row_heading level0 row38\" >39</th>\n",
              "      <td id=\"T_6d1ee_row38_col0\" class=\"data row38 col0\" >The</td>\n",
              "      <td id=\"T_6d1ee_row38_col1\" class=\"data row38 col1\" >656</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row39\" class=\"row_heading level0 row39\" >40</th>\n",
              "      <td id=\"T_6d1ee_row39_col0\" class=\"data row39 col0\" >would</td>\n",
              "      <td id=\"T_6d1ee_row39_col1\" class=\"data row39 col1\" >651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row40\" class=\"row_heading level0 row40\" >41</th>\n",
              "      <td id=\"T_6d1ee_row40_col0\" class=\"data row40 col0\" >i'm</td>\n",
              "      <td id=\"T_6d1ee_row40_col1\" class=\"data row40 col1\" >646</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row41\" class=\"row_heading level0 row41\" >42</th>\n",
              "      <td id=\"T_6d1ee_row41_col0\" class=\"data row41 col0\" >great</td>\n",
              "      <td id=\"T_6d1ee_row41_col1\" class=\"data row41 col1\" >625</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row42\" class=\"row_heading level0 row42\" >43</th>\n",
              "      <td id=\"T_6d1ee_row42_col0\" class=\"data row42 col0\" >happy</td>\n",
              "      <td id=\"T_6d1ee_row42_col1\" class=\"data row42 col1\" >606</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row43\" class=\"row_heading level0 row43\" >44</th>\n",
              "      <td id=\"T_6d1ee_row43_col0\" class=\"data row43 col0\" >make</td>\n",
              "      <td id=\"T_6d1ee_row43_col1\" class=\"data row43 col1\" >584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row44\" class=\"row_heading level0 row44\" >45</th>\n",
              "      <td id=\"T_6d1ee_row44_col0\" class=\"data row44 col0\" >hope</td>\n",
              "      <td id=\"T_6d1ee_row44_col1\" class=\"data row44 col1\" >569</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row45\" class=\"row_heading level0 row45\" >46</th>\n",
              "      <td id=\"T_6d1ee_row45_col0\" class=\"data row45 col0\" >It's</td>\n",
              "      <td id=\"T_6d1ee_row45_col1\" class=\"data row45 col1\" >564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row46\" class=\"row_heading level0 row46\" >47</th>\n",
              "      <td id=\"T_6d1ee_row46_col0\" class=\"data row46 col0\" >wish</td>\n",
              "      <td id=\"T_6d1ee_row46_col1\" class=\"data row46 col1\" >563</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row47\" class=\"row_heading level0 row47\" >48</th>\n",
              "      <td id=\"T_6d1ee_row47_col0\" class=\"data row47 col0\" >gonna</td>\n",
              "      <td id=\"T_6d1ee_row47_col1\" class=\"data row47 col1\" >535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row48\" class=\"row_heading level0 row48\" >49</th>\n",
              "      <td id=\"T_6d1ee_row48_col0\" class=\"data row48 col0\" >could</td>\n",
              "      <td id=\"T_6d1ee_row48_col1\" class=\"data row48 col1\" >533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row49\" class=\"row_heading level0 row49\" >50</th>\n",
              "      <td id=\"T_6d1ee_row49_col0\" class=\"data row49 col0\" >well</td>\n",
              "      <td id=\"T_6d1ee_row49_col1\" class=\"data row49 col1\" >507</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row50\" class=\"row_heading level0 row50\" >51</th>\n",
              "      <td id=\"T_6d1ee_row50_col0\" class=\"data row50 col0\" >bad</td>\n",
              "      <td id=\"T_6d1ee_row50_col1\" class=\"data row50 col1\" >505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row51\" class=\"row_heading level0 row51\" >52</th>\n",
              "      <td id=\"T_6d1ee_row51_col0\" class=\"data row51 col0\" >fun</td>\n",
              "      <td id=\"T_6d1ee_row51_col1\" class=\"data row51 col1\" >492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row52\" class=\"row_heading level0 row52\" >53</th>\n",
              "      <td id=\"T_6d1ee_row52_col0\" class=\"data row52 col0\" >getting</td>\n",
              "      <td id=\"T_6d1ee_row52_col1\" class=\"data row52 col1\" >487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row53\" class=\"row_heading level0 row53\" >54</th>\n",
              "      <td id=\"T_6d1ee_row53_col0\" class=\"data row53 col0\" >You</td>\n",
              "      <td id=\"T_6d1ee_row53_col1\" class=\"data row53 col1\" >479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row54\" class=\"row_heading level0 row54\" >55</th>\n",
              "      <td id=\"T_6d1ee_row54_col0\" class=\"data row54 col0\" >way</td>\n",
              "      <td id=\"T_6d1ee_row54_col1\" class=\"data row54 col1\" >466</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row55\" class=\"row_heading level0 row55\" >56</th>\n",
              "      <td id=\"T_6d1ee_row55_col0\" class=\"data row55 col0\" >I'll</td>\n",
              "      <td id=\"T_6d1ee_row55_col1\" class=\"data row55 col1\" >464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row56\" class=\"row_heading level0 row56\" >57</th>\n",
              "      <td id=\"T_6d1ee_row56_col0\" class=\"data row56 col0\" >better</td>\n",
              "      <td id=\"T_6d1ee_row56_col1\" class=\"data row56 col1\" >462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row57\" class=\"row_heading level0 row57\" >58</th>\n",
              "      <td id=\"T_6d1ee_row57_col0\" class=\"data row57 col0\" >next</td>\n",
              "      <td id=\"T_6d1ee_row57_col1\" class=\"data row57 col1\" >461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row58\" class=\"row_heading level0 row58\" >59</th>\n",
              "      <td id=\"T_6d1ee_row58_col0\" class=\"data row58 col0\" >right</td>\n",
              "      <td id=\"T_6d1ee_row58_col1\" class=\"data row58 col1\" >459</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row59\" class=\"row_heading level0 row59\" >60</th>\n",
              "      <td id=\"T_6d1ee_row59_col0\" class=\"data row59 col0\" >come</td>\n",
              "      <td id=\"T_6d1ee_row59_col1\" class=\"data row59 col1\" >457</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row60\" class=\"row_heading level0 row60\" >61</th>\n",
              "      <td id=\"T_6d1ee_row60_col0\" class=\"data row60 col0\" >sad</td>\n",
              "      <td id=\"T_6d1ee_row60_col1\" class=\"data row60 col1\" >453</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row61\" class=\"row_heading level0 row61\" >62</th>\n",
              "      <td id=\"T_6d1ee_row61_col0\" class=\"data row61 col0\" >...</td>\n",
              "      <td id=\"T_6d1ee_row61_col1\" class=\"data row61 col1\" >448</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row62\" class=\"row_heading level0 row62\" >63</th>\n",
              "      <td id=\"T_6d1ee_row62_col0\" class=\"data row62 col0\" >nice</td>\n",
              "      <td id=\"T_6d1ee_row62_col1\" class=\"data row62 col1\" >446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row63\" class=\"row_heading level0 row63\" >64</th>\n",
              "      <td id=\"T_6d1ee_row63_col0\" class=\"data row63 col0\" >oh</td>\n",
              "      <td id=\"T_6d1ee_row63_col1\" class=\"data row63 col1\" >444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row64\" class=\"row_heading level0 row64\" >65</th>\n",
              "      <td id=\"T_6d1ee_row64_col0\" class=\"data row64 col0\" >dont</td>\n",
              "      <td id=\"T_6d1ee_row64_col1\" class=\"data row64 col1\" >441</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row65\" class=\"row_heading level0 row65\" >66</th>\n",
              "      <td id=\"T_6d1ee_row65_col0\" class=\"data row65 col0\" >haha</td>\n",
              "      <td id=\"T_6d1ee_row65_col1\" class=\"data row65 col1\" >439</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row66\" class=\"row_heading level0 row66\" >67</th>\n",
              "      <td id=\"T_6d1ee_row66_col0\" class=\"data row66 col0\" >But</td>\n",
              "      <td id=\"T_6d1ee_row66_col1\" class=\"data row66 col1\" >436</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row67\" class=\"row_heading level0 row67\" >68</th>\n",
              "      <td id=\"T_6d1ee_row67_col0\" class=\"data row67 col0\" >morning</td>\n",
              "      <td id=\"T_6d1ee_row67_col1\" class=\"data row67 col1\" >436</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row68\" class=\"row_heading level0 row68\" >69</th>\n",
              "      <td id=\"T_6d1ee_row68_col0\" class=\"data row68 col0\" >Good</td>\n",
              "      <td id=\"T_6d1ee_row68_col1\" class=\"data row68 col1\" >430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row69\" class=\"row_heading level0 row69\" >70</th>\n",
              "      <td id=\"T_6d1ee_row69_col0\" class=\"data row69 col0\" >thanks</td>\n",
              "      <td id=\"T_6d1ee_row69_col1\" class=\"data row69 col1\" >427</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row70\" class=\"row_heading level0 row70\" >71</th>\n",
              "      <td id=\"T_6d1ee_row70_col0\" class=\"data row70 col0\" >It</td>\n",
              "      <td id=\"T_6d1ee_row70_col1\" class=\"data row70 col1\" >424</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row71\" class=\"row_heading level0 row71\" >72</th>\n",
              "      <td id=\"T_6d1ee_row71_col0\" class=\"data row71 col0\" >And</td>\n",
              "      <td id=\"T_6d1ee_row71_col1\" class=\"data row71 col1\" >416</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row72\" class=\"row_heading level0 row72\" >73</th>\n",
              "      <td id=\"T_6d1ee_row72_col0\" class=\"data row72 col0\" >hate</td>\n",
              "      <td id=\"T_6d1ee_row72_col1\" class=\"data row72 col1\" >412</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row73\" class=\"row_heading level0 row73\" >74</th>\n",
              "      <td id=\"T_6d1ee_row73_col0\" class=\"data row73 col0\" >So</td>\n",
              "      <td id=\"T_6d1ee_row73_col1\" class=\"data row73 col1\" >407</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row74\" class=\"row_heading level0 row74\" >75</th>\n",
              "      <td id=\"T_6d1ee_row74_col0\" class=\"data row74 col0\" >even</td>\n",
              "      <td id=\"T_6d1ee_row74_col1\" class=\"data row74 col1\" >407</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row75\" class=\"row_heading level0 row75\" >76</th>\n",
              "      <td id=\"T_6d1ee_row75_col0\" class=\"data row75 col0\" >sorry</td>\n",
              "      <td id=\"T_6d1ee_row75_col1\" class=\"data row75 col1\" >405</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row76\" class=\"row_heading level0 row76\" >77</th>\n",
              "      <td id=\"T_6d1ee_row76_col0\" class=\"data row76 col0\" >people</td>\n",
              "      <td id=\"T_6d1ee_row76_col1\" class=\"data row76 col1\" >403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row77\" class=\"row_heading level0 row77\" >78</th>\n",
              "      <td id=\"T_6d1ee_row77_col0\" class=\"data row77 col0\" >little</td>\n",
              "      <td id=\"T_6d1ee_row77_col1\" class=\"data row77 col1\" >398</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row78\" class=\"row_heading level0 row78\" >79</th>\n",
              "      <td id=\"T_6d1ee_row78_col0\" class=\"data row78 col0\" >that's</td>\n",
              "      <td id=\"T_6d1ee_row78_col1\" class=\"data row78 col1\" >395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row79\" class=\"row_heading level0 row79\" >80</th>\n",
              "      <td id=\"T_6d1ee_row79_col0\" class=\"data row79 col0\" >tomorrow</td>\n",
              "      <td id=\"T_6d1ee_row79_col1\" class=\"data row79 col1\" >392</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row80\" class=\"row_heading level0 row80\" >81</th>\n",
              "      <td id=\"T_6d1ee_row80_col0\" class=\"data row80 col0\" >sleep</td>\n",
              "      <td id=\"T_6d1ee_row80_col1\" class=\"data row80 col1\" >391</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row81\" class=\"row_heading level0 row81\" >82</th>\n",
              "      <td id=\"T_6d1ee_row81_col0\" class=\"data row81 col0\" >never</td>\n",
              "      <td id=\"T_6d1ee_row81_col1\" class=\"data row81 col1\" >389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row82\" class=\"row_heading level0 row82\" >83</th>\n",
              "      <td id=\"T_6d1ee_row82_col0\" class=\"data row82 col0\" >Day</td>\n",
              "      <td id=\"T_6d1ee_row82_col1\" class=\"data row82 col1\" >389</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row83\" class=\"row_heading level0 row83\" >84</th>\n",
              "      <td id=\"T_6d1ee_row83_col0\" class=\"data row83 col0\" >twitter</td>\n",
              "      <td id=\"T_6d1ee_row83_col1\" class=\"data row83 col1\" >384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row84\" class=\"row_heading level0 row84\" >85</th>\n",
              "      <td id=\"T_6d1ee_row84_col0\" class=\"data row84 col0\" >week</td>\n",
              "      <td id=\"T_6d1ee_row84_col1\" class=\"data row84 col1\" >384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row85\" class=\"row_heading level0 row85\" >86</th>\n",
              "      <td id=\"T_6d1ee_row85_col0\" class=\"data row85 col0\" >I've</td>\n",
              "      <td id=\"T_6d1ee_row85_col1\" class=\"data row85 col1\" >381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row86\" class=\"row_heading level0 row86\" >87</th>\n",
              "      <td id=\"T_6d1ee_row86_col0\" class=\"data row86 col0\" >say</td>\n",
              "      <td id=\"T_6d1ee_row86_col1\" class=\"data row86 col1\" >381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row87\" class=\"row_heading level0 row87\" >88</th>\n",
              "      <td id=\"T_6d1ee_row87_col0\" class=\"data row87 col0\" >wait</td>\n",
              "      <td id=\"T_6d1ee_row87_col1\" class=\"data row87 col1\" >368</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row88\" class=\"row_heading level0 row88\" >89</th>\n",
              "      <td id=\"T_6d1ee_row88_col0\" class=\"data row88 col0\" >it.</td>\n",
              "      <td id=\"T_6d1ee_row88_col1\" class=\"data row88 col1\" >366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row89\" class=\"row_heading level0 row89\" >90</th>\n",
              "      <td id=\"T_6d1ee_row89_col0\" class=\"data row89 col0\" >take</td>\n",
              "      <td id=\"T_6d1ee_row89_col1\" class=\"data row89 col1\" >360</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row90\" class=\"row_heading level0 row90\" >91</th>\n",
              "      <td id=\"T_6d1ee_row90_col0\" class=\"data row90 col0\" >4</td>\n",
              "      <td id=\"T_6d1ee_row90_col1\" class=\"data row90 col1\" >355</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row91\" class=\"row_heading level0 row91\" >92</th>\n",
              "      <td id=\"T_6d1ee_row91_col0\" class=\"data row91 col0\" >watching</td>\n",
              "      <td id=\"T_6d1ee_row91_col1\" class=\"data row91 col1\" >353</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row92\" class=\"row_heading level0 row92\" >93</th>\n",
              "      <td id=\"T_6d1ee_row92_col0\" class=\"data row92 col0\" >cant</td>\n",
              "      <td id=\"T_6d1ee_row92_col1\" class=\"data row92 col1\" >352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row93\" class=\"row_heading level0 row93\" >94</th>\n",
              "      <td id=\"T_6d1ee_row93_col0\" class=\"data row93 col0\" >long</td>\n",
              "      <td id=\"T_6d1ee_row93_col1\" class=\"data row93 col1\" >346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row94\" class=\"row_heading level0 row94\" >95</th>\n",
              "      <td id=\"T_6d1ee_row94_col0\" class=\"data row94 col0\" >though</td>\n",
              "      <td id=\"T_6d1ee_row94_col1\" class=\"data row94 col1\" >343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row95\" class=\"row_heading level0 row95\" >96</th>\n",
              "      <td id=\"T_6d1ee_row95_col0\" class=\"data row95 col0\" >days</td>\n",
              "      <td id=\"T_6d1ee_row95_col1\" class=\"data row95 col1\" >343</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row96\" class=\"row_heading level0 row96\" >97</th>\n",
              "      <td id=\"T_6d1ee_row96_col0\" class=\"data row96 col0\" >wanna</td>\n",
              "      <td id=\"T_6d1ee_row96_col1\" class=\"data row96 col1\" >342</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row97\" class=\"row_heading level0 row97\" >98</th>\n",
              "      <td id=\"T_6d1ee_row97_col0\" class=\"data row97 col0\" >find</td>\n",
              "      <td id=\"T_6d1ee_row97_col1\" class=\"data row97 col1\" >342</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6d1ee_level0_row98\" class=\"row_heading level0 row98\" >99</th>\n",
              "      <td id=\"T_6d1ee_row98_col0\" class=\"data row98 col0\" >!</td>\n",
              "      <td id=\"T_6d1ee_row98_col1\" class=\"data row98 col1\" >342</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Print table just for sentiment 'empty'."
      ],
      "metadata": {
        "id": "KbepQ7Y6iPzk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['sentiment']=='empty']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "QdBzb6-DgzQE",
        "outputId": "78ee43f0-0cc8-4185-9e17-2ad665cf530f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         tweet_id sentiment  \\\n",
              "0      1956967341     empty   \n",
              "44     1956978276     empty   \n",
              "52     1956979917     empty   \n",
              "141    1957000336     empty   \n",
              "180    1957007357     empty   \n",
              "...           ...       ...   \n",
              "39702  1753868848     empty   \n",
              "39742  1753870123     empty   \n",
              "39749  1753870555     empty   \n",
              "39845  1753886183     empty   \n",
              "39975  1753904682     empty   \n",
              "\n",
              "                                                 content  \\\n",
              "0      @tiffanylue i know  i was listenin to bad habi...   \n",
              "44     @creyes middle school and elem. High schools w...   \n",
              "52               @djmicdamn hey yu lil fucker i textd yu   \n",
              "141    @softtouchme just answered you- never learned ...   \n",
              "180        Have a headache  I'm going to bed. Goodnight!   \n",
              "...                                                  ...   \n",
              "39702  Here we go again, back to work. Happy Mothers ...   \n",
              "39742  @PhilippaJane the &quot;no pants&quot; idea co...   \n",
              "39749                                  @sloanyxxx Thanks   \n",
              "39845                   @xxxRobyn Yeah *fingers crossed*   \n",
              "39975    @lexia Or even listen to Susan's green policies   \n",
              "\n",
              "                                               temp_list  \n",
              "0      [@tiffanylue, know, listenin, bad, habit, earl...  \n",
              "44     [@creyes, middle, school, elem., High, schools...  \n",
              "52         [@djmicdamn, hey, yu, lil, fucker, textd, yu]  \n",
              "141    [@softtouchme, answered, you-, never, learned,...  \n",
              "180       [Have, headache, I'm, going, bed., Goodnight!]  \n",
              "...                                                  ...  \n",
              "39702  [Here, go, again,, back, work., Happy, Mothers...  \n",
              "39742  [@PhilippaJane, &quot;no, pants&quot;, idea, c...  \n",
              "39749                               [@sloanyxxx, Thanks]  \n",
              "39845              [@xxxRobyn, Yeah, *fingers, crossed*]  \n",
              "39975  [@lexia, Or, even, listen, Susan's, green, pol...  \n",
              "\n",
              "[827 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-78ce05e3-1f08-45d3-a487-e4de4dbf70b2\" class=\"colab-df-container\">\n",
              "    <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>tweet_id</th>\n",
              "      <th>sentiment</th>\n",
              "      <th>content</th>\n",
              "      <th>temp_list</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1956967341</td>\n",
              "      <td>empty</td>\n",
              "      <td>@tiffanylue i know  i was listenin to bad habi...</td>\n",
              "      <td>[@tiffanylue, know, listenin, bad, habit, earl...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>1956978276</td>\n",
              "      <td>empty</td>\n",
              "      <td>@creyes middle school and elem. High schools w...</td>\n",
              "      <td>[@creyes, middle, school, elem., High, schools...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>52</th>\n",
              "      <td>1956979917</td>\n",
              "      <td>empty</td>\n",
              "      <td>@djmicdamn hey yu lil fucker i textd yu</td>\n",
              "      <td>[@djmicdamn, hey, yu, lil, fucker, textd, yu]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>141</th>\n",
              "      <td>1957000336</td>\n",
              "      <td>empty</td>\n",
              "      <td>@softtouchme just answered you- never learned ...</td>\n",
              "      <td>[@softtouchme, answered, you-, never, learned,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>180</th>\n",
              "      <td>1957007357</td>\n",
              "      <td>empty</td>\n",
              "      <td>Have a headache  I'm going to bed. Goodnight!</td>\n",
              "      <td>[Have, headache, I'm, going, bed., Goodnight!]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39702</th>\n",
              "      <td>1753868848</td>\n",
              "      <td>empty</td>\n",
              "      <td>Here we go again, back to work. Happy Mothers ...</td>\n",
              "      <td>[Here, go, again,, back, work., Happy, Mothers...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39742</th>\n",
              "      <td>1753870123</td>\n",
              "      <td>empty</td>\n",
              "      <td>@PhilippaJane the &amp;quot;no pants&amp;quot; idea co...</td>\n",
              "      <td>[@PhilippaJane, &amp;quot;no, pants&amp;quot;, idea, c...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39749</th>\n",
              "      <td>1753870555</td>\n",
              "      <td>empty</td>\n",
              "      <td>@sloanyxxx Thanks</td>\n",
              "      <td>[@sloanyxxx, Thanks]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39845</th>\n",
              "      <td>1753886183</td>\n",
              "      <td>empty</td>\n",
              "      <td>@xxxRobyn Yeah *fingers crossed*</td>\n",
              "      <td>[@xxxRobyn, Yeah, *fingers, crossed*]</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39975</th>\n",
              "      <td>1753904682</td>\n",
              "      <td>empty</td>\n",
              "      <td>@lexia Or even listen to Susan's green policies</td>\n",
              "      <td>[@lexia, Or, even, listen, Susan's, green, pol...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>827 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-78ce05e3-1f08-45d3-a487-e4de4dbf70b2')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-78ce05e3-1f08-45d3-a487-e4de4dbf70b2 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-78ce05e3-1f08-45d3-a487-e4de4dbf70b2');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-6852241b-3fda-4334-89cd-1671a4c8d238\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-6852241b-3fda-4334-89cd-1671a4c8d238')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6852241b-3fda-4334-89cd-1671a4c8d238 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[df['sentiment']=='empty']\",\n  \"rows\": 827,\n  \"fields\": [\n    {\n      \"column\": \"tweet_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 119378699,\n        \"min\": 1693956175,\n        \"max\": 1966428499,\n        \"num_unique_values\": 827,\n        \"samples\": [\n          1962827535,\n          1753254884,\n          1963750715\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 827,\n        \"samples\": [\n          \"gor i am soo bored, man i don't think i could get any more bored\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"temp_list\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Get general info about data frame."
      ],
      "metadata": {
        "id": "_wJmVw8miYTw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.info())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0eUMZlYkg49_",
        "outputId": "8522398f-1fa7-4de7-9f6f-6574a3dc61c5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 40000 entries, 0 to 39999\n",
            "Data columns (total 4 columns):\n",
            " #   Column     Non-Null Count  Dtype \n",
            "---  ------     --------------  ----- \n",
            " 0   tweet_id   40000 non-null  int64 \n",
            " 1   sentiment  40000 non-null  object\n",
            " 2   content    40000 non-null  object\n",
            " 3   temp_list  40000 non-null  object\n",
            "dtypes: int64(1), object(3)\n",
            "memory usage: 1.2+ MB\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Describes the numerics."
      ],
      "metadata": {
        "id": "jdq8fllKich9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df.describe())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7G_jV3E5g7Cm",
        "outputId": "3bacadb8-33be-463b-a8a1-b2a1e63499ee"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "           tweet_id\n",
            "count  4.000000e+04\n",
            "mean   1.845184e+09\n",
            "std    1.188579e+08\n",
            "min    1.693956e+09\n",
            "25%    1.751431e+09\n",
            "50%    1.855443e+09\n",
            "75%    1.962781e+09\n",
            "max    1.966441e+09\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Distribution of sentiments."
      ],
      "metadata": {
        "id": "LNfI_fYJiecE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.countplot(x='sentiment', data=df)\n",
        "plt.title('Distribution of Sentiments')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "IUKItNdug9U6",
        "outputId": "0b60768f-6d90-4105-c403-f2eff9b6f439"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Content length by sentiment."
      ],
      "metadata": {
        "id": "_Go_IBKUigpm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df['content_length'] = df['content'].apply(len)\n",
        "sns.boxplot(x='sentiment', y='content_length', data=df)\n",
        "plt.title('Content Length by Sentiment')\n",
        "plt.xticks(rotation=45)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "zC62261Hg-Iu",
        "outputId": "08217d10-3b3b-418d-f380-fde0f42ced6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Word cloud of most common words."
      ],
      "metadata": {
        "id": "-vliRMWaijf_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "specific_sentiments = df[df['sentiment'].isin(['sadness', 'worry', 'hate', 'fun'])]\n",
        "specific_sentiments = specific_sentiments.copy()"
      ],
      "metadata": {
        "id": "SnNlOzw4hAqX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "all_text = ' '.join(df['content'])\n",
        "words = all_text.split()\n",
        "word_freq = Counter(words)\n",
        "common_words = word_freq.most_common(20)\n",
        "plt.figure(figsize=(10, 8))\n",
        "wordcloud = WordCloud(width=800, height=400, background_color='white').generate_from_frequencies(dict(common_words))\n",
        "plt.imshow(wordcloud, interpolation='bilinear')\n",
        "plt.title('Most Common Words')\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "id": "2p9sPDTohFFA",
        "outputId": "c5c2a698-8b60-4948-945b-5ef1914f0bcf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Word cloud for 4 most dominant sentiments."
      ],
      "metadata": {
        "id": "_zY5ePM5il-M"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['sentiment'].unique())\n",
        "specific_sentiments = df[df['sentiment'].isin(['sadness', 'worry', 'hate', 'fun'])]\n",
        "all_text_specific = ' '.join(specific_sentiments['content'])\n",
        "words_specific = all_text_specific.split()\n",
        "word_freq_specific = Counter(words_specific)\n",
        "common_words_specific = word_freq_specific.most_common(20)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7CpAqfX6hHJK",
        "outputId": "1e5f7927-b0c0-4d0b-8ec1-573ef149838f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['empty' 'sadness' 'enthusiasm' 'neutral' 'worry' 'surprise' 'love' 'fun'\n",
            " 'hate' 'happiness' 'boredom' 'relief' 'anger']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "wordcloud_specific = WordCloud(width=800, height=400, background_color='white').generate_from_frequencies(dict(common_words_specific))\n",
        "plt.figure(figsize=(10, 8))\n",
        "plt.imshow(wordcloud_specific, interpolation='bilinear')\n",
        "plt.title('Most Common Words in Specific Sentiments')\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "id": "rsPQfSC-hHQ7",
        "outputId": "b7803ac7-1d6f-4764-c75a-ed2224db9dc2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Content length comparison for similar sentiments."
      ],
      "metadata": {
        "id": "fES00EfWiqcI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "specific_sentiments = df[df['sentiment'].isin(['sadness', 'worry', 'hate', 'love', 'fun', 'neutral'])]"
      ],
      "metadata": {
        "id": "nxhWwtk5hHYv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(12, 6))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "id": "nH0wufxFhHbO",
        "outputId": "60a0cfa8-523c-496c-ada4-d3abb87c07c2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 0 Axes>"
            ]
          },
          "metadata": {},
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.subplot(1, 3, 1)\n",
        "sns.scatterplot(x='sentiment', y='content_length', data=specific_sentiments[specific_sentiments['sentiment'].isin(['sadness', 'worry'])])\n",
        "plt.title('Sadness vs Worry')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "P6al7_AIhHel",
        "outputId": "16f1216e-20d6-45b7-ae94-c86627600dd2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Sadness vs Worry')"
            ]
          },
          "metadata": {},
          "execution_count": 25
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.subplot(1, 3, 2)\n",
        "sns.scatterplot(x='sentiment', y='content_length', data=specific_sentiments[specific_sentiments['sentiment'].isin(['hate', 'love'])])\n",
        "plt.title('Hate vs Love')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "e5HAz1ilhHg8",
        "outputId": "fd0274b5-3ccf-4386-aca5-1338eac066a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Hate vs Love')"
            ]
          },
          "metadata": {},
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.subplot(1, 3, 3)\n",
        "sns.scatterplot(x='sentiment', y='content_length', data=specific_sentiments[specific_sentiments['sentiment'].isin(['fun', 'neutral'])])\n",
        "plt.title('Fun vs Neutral')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 490
        },
        "id": "5QJhh8yohRjG",
        "outputId": "5fc3faf5-946a-4b74-f300-08a01646ce31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Fun vs Neutral')"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "OJHFsJgLhRqH",
        "outputId": "8aded928-f795-44a9-db80-1eadf3d22121"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    }
  ]
}