{
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  "metadata": {
    "colab": {
      "name": "data_cleaning_exploration.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "zOWGGVMF7gY2"
      ]
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QUv-qL5aTlN_"
      },
      "source": [
        "# Data Cleaning"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7Ty2bX21TpE4"
      },
      "source": [
        "Data cleaning is the process of detecting and removing errors and inconsistencies from the data to improve its quality. Improper data cleaning process can lead to errors, faulty analysis, distortion in dataset and eventually incompatible datasets for machine learning purposes. There is no absolute way to prescribe the exact steps in the data cleaning process because the processes will vary from dataset to dataset. My data cleaning process includes:\n",
        "\n",
        "* Check the data types\n",
        "* Check for duplicates - Primary key ('tweets.id')\n",
        "* Check missing values\n",
        "* Make text all lower case\n",
        "* Remove links and images\n",
        "* Remove hashtags\n",
        "* Remove @ mentions\n",
        "* Remove emojis\n",
        "* Remove stop words\n",
        "* Remove punctuation\n",
        "* Get rid of stuff like \"what's\" and making it \"what is'\n",
        "* Stemming / lemmatization\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yRUz0q1mTUkg",
        "outputId": "e1774c13-3ec4-4a34-c282-1ddc302266b2"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d9LbF-SLjH0d",
        "outputId": "d57441cb-7dcf-45fc-9f98-eeb939523849"
      },
      "source": [
        "!pip install -qqq ftfy"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l\r\u001b[K     |█████                           | 10 kB 20.2 MB/s eta 0:00:01\r\u001b[K     |██████████▏                     | 20 kB 24.5 MB/s eta 0:00:01\r\u001b[K     |███████████████▎                | 30 kB 29.9 MB/s eta 0:00:01\r\u001b[K     |████████████████████▍           | 40 kB 19.5 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████▌      | 51 kB 21.9 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▋ | 61 kB 24.7 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 64 kB 2.4 MB/s \n",
            "\u001b[?25h  Building wheel for ftfy (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NuVz70ByXMd1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e874f909-ce9d-4784-9e13-cbaaf892f82b"
      },
      "source": [
        "## Import required libraries\n",
        "\n",
        "## warnings\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "## for data\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "## for plotting\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "## for processing\n",
        "import nltk\n",
        "import re\n",
        "import ftfy\n",
        "from nltk.stem import WordNetLemmatizer \n",
        "from nltk.corpus import stopwords\n",
        "nltk.download('stopwords')\n",
        "nltk.download('punkt')\n",
        "nltk.download('wordnet')\n",
        "nltk.download('averaged_perceptron_tagger')\n",
        "\n",
        "## for opening, manipulating, and saving many different image file f\n",
        "from PIL import Image \n",
        "\n",
        "## WordCloud - Python linrary for creating image wordclouds\n",
        "from wordcloud import WordCloud\n",
        "from nltk import pos_tag ## For Parts of Speech tagging\n",
        "import random ## generating random numbers"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/stopwords.zip.\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n",
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Unzipping corpora/wordnet.zip.\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U4ab5ve6W5YX"
      },
      "source": [
        "## Load the datasets"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bcTpVkZnTa_S"
      },
      "source": [
        "depressive_tweets_df = pd.read_csv(\"/content/drive/MyDrive/NLP/Depression_Detection/Data_fetch_API/output/depressive_tweets.csv\")\n",
        "random_tweets_df = pd.read_csv(\"/content/drive/MyDrive/NLP/Depression_Detection/Depression_tweets_Data/Data1/Sentiment Analysis Dataset 2.csv\", \n",
        "                               encoding = \"ISO-8859-1\", usecols = range(0,4), nrows = 40000)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "-TCfMO6RnZsu",
        "outputId": "2d6df698-6f10-4bd2-b799-d0e3b505320f"
      },
      "source": [
        "depressive_tweets_df"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>tweet.id</th>\n",
              "      <th>created_at</th>\n",
              "      <th>text</th>\n",
              "      <th>location</th>\n",
              "      <th>retweet</th>\n",
              "      <th>favorite</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
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              "      <td>1447537898572574730</td>\n",
              "      <td>2021-10-11 12:21:43</td>\n",
              "      <td>Open discussion. Between the Transfer Portal a...</td>\n",
              "      <td>Cheyenne Wyoming</td>\n",
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              "      <td>1447807717859491842</td>\n",
              "      <td>2021-10-12 06:13:53</td>\n",
              "      <td>I feel a little hopeless. Anyone else? #hopele...</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1448076026219692033</td>\n",
              "      <td>2021-10-13 00:00:03</td>\n",
              "      <td>Which is more healthy? Hope, or hopelessness? ...</td>\n",
              "      <td>Denver, CO</td>\n",
              "      <td>0</td>\n",
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              "      <th>4</th>\n",
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              "      <td>1448382047375040513</td>\n",
              "      <td>2021-10-13 20:16:04</td>\n",
              "      <td>So someone tell me how do I get over #HOPELESS...</td>\n",
              "      <td>Portland Or .</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>2021-11-13 14:00:16</td>\n",
              "      <td>Just got banned from a server F #sad</td>\n",
              "      <td>Jakarta Capital Region</td>\n",
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              "      <th>24143</th>\n",
              "      <td>24143</td>\n",
              "      <td>1459521611997003777</td>\n",
              "      <td>2021-11-13 14:00:43</td>\n",
              "      <td>I literally cried during my exam and the cam i...</td>\n",
              "      <td>بيت أمك</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24144</th>\n",
              "      <td>24144</td>\n",
              "      <td>1459524263946326017</td>\n",
              "      <td>2021-11-13 14:11:15</td>\n",
              "      <td>No one can be happy with a guy like me. That's...</td>\n",
              "      <td>Varanasi, Uttar Pradesh, India</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>24145</th>\n",
              "      <td>24145</td>\n",
              "      <td>1459530315437785095</td>\n",
              "      <td>2021-11-13 14:35:18</td>\n",
              "      <td>arrived at my house but Am I Home? #deep #sad ...</td>\n",
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              "<p>24147 rows × 7 columns</p>\n",
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              "       Unnamed: 0             tweet.id  ... retweet favorite\n",
              "0               0  1447537898572574730  ...       0        0\n",
              "1               1  1447540582490988553  ...       0        0\n",
              "2               2  1447807717859491842  ...       0        0\n",
              "3               3  1448076026219692033  ...       0        0\n",
              "4               4  1448382047375040513  ...       0        2\n",
              "...           ...                  ...  ...     ...      ...\n",
              "24142       24142  1459521498842992642  ...       0        1\n",
              "24143       24143  1459521611997003777  ...       0        0\n",
              "24144       24144  1459524263946326017  ...       0        0\n",
              "24145       24145  1459530315437785095  ...       1        3\n",
              "24146       24146  1459530643591905284  ...       0        0\n",
              "\n",
              "[24147 rows x 7 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "W4mCUxdVtjWv",
        "outputId": "c4c2f790-7054-4d30-bb90-54b18bdf9baa"
      },
      "source": [
        "random_tweets_df"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<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>ItemID</th>\n",
              "      <th>Sentiment</th>\n",
              "      <th>SentimentSource</th>\n",
              "      <th>SentimentText</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>is so sad for my APL frie...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>I missed the New Moon trail...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>omg its already 7:30 :O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>.. Omgaga. Im sooo  im gunna CRy. I'...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>i think mi bf is cheating on me!!!   ...</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>39995</th>\n",
              "      <td>40007</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>@AndreaKidd Ouchies, I hope it isn't anything ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39996</th>\n",
              "      <td>40008</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>@AndreaKobayashi It's the best cafe in Asakusa...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39997</th>\n",
              "      <td>40009</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>@AndreaKoeln heeey! tonight is the night! no s...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39998</th>\n",
              "      <td>40010</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>@AmandaFClark it is when you add the hammock</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39999</th>\n",
              "      <td>40011</td>\n",
              "      <td>0</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>@amandafortier  I am so happy with all the fun...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>40000 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       ItemID  ...                                      SentimentText\n",
              "0              1  ...                       is so sad for my APL frie...\n",
              "1              2  ...                     I missed the New Moon trail...\n",
              "2              3  ...                            omg its already 7:30 :O\n",
              "3              4  ...            .. Omgaga. Im sooo  im gunna CRy. I'...\n",
              "4              5  ...           i think mi bf is cheating on me!!!   ...\n",
              "...          ...  ...                                                ...\n",
              "39995      40007  ...  @AndreaKidd Ouchies, I hope it isn't anything ...\n",
              "39996      40008  ...  @AndreaKobayashi It's the best cafe in Asakusa...\n",
              "39997      40009  ...  @AndreaKoeln heeey! tonight is the night! no s...\n",
              "39998      40010  ...      @AmandaFClark it is when you add the hammock \n",
              "39999      40011  ...  @amandafortier  I am so happy with all the fun...\n",
              "\n",
              "[40000 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0x7Svia3zEhQ"
      },
      "source": [
        "## Slicing the random tweets to have sentiment == 1 \n",
        "new_rand_df = random_tweets_df[random_tweets_df.Sentiment == 1]\n",
        "new_rand_df.reset_index(inplace=True)"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "svpDxeLs2h4g",
        "outputId": "4f75e96a-6832-48b0-ed88-053222683d24"
      },
      "source": [
        "new_rand_df.shape"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(20952, 5)"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "7GI7998x4QRV",
        "outputId": "6978d03f-d064-4788-9a81-f9adae888a5b"
      },
      "source": [
        "new_rand_df.head()"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>ItemID</th>\n",
              "      <th>Sentiment</th>\n",
              "      <th>SentimentSource</th>\n",
              "      <th>SentimentText</th>\n",
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              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>omg its already 7:30 :O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>Juuuuuuuuuuuuuuuuussssst Chillin!!</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>handed in my uniform today . i miss you ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>hmmmm.... i wonder how she my number @-)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>11</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>Sentiment140</td>\n",
              "      <td>thanks to all the haters up in my face a...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   index  ...                                      SentimentText\n",
              "0      2  ...                            omg its already 7:30 :O\n",
              "1      6  ...                 Juuuuuuuuuuuuuuuuussssst Chillin!!\n",
              "2      8  ...        handed in my uniform today . i miss you ...\n",
              "3      9  ...           hmmmm.... i wonder how she my number @-)\n",
              "4     11  ...        thanks to all the haters up in my face a...\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KG29qc_b4GnB"
      },
      "source": [
        "20952 random tweets with sentiment == 1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UitvlZ02qZD7"
      },
      "source": [
        "## Data Cleaning-Processing:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ulH3-xX86jPp",
        "outputId": "6a18d284-77fd-4ea9-8221-444251defa2d"
      },
      "source": [
        "print(depressive_tweets_df.shape)\n",
        "print(new_rand_df.shape)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(24147, 7)\n",
            "(20952, 5)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 263
        },
        "id": "KX5XBnF5pwZ3",
        "outputId": "edb8aa08-b9ea-4828-c01c-ea9a3bff4875"
      },
      "source": [
        "## Check the data type of each column\n",
        "depressive_tweets_df.dtypes.to_frame().rename(columns={0:'data_type'})"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tweet.id</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>created_at</th>\n",
              "      <td>object</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>text</th>\n",
              "      <td>object</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>location</th>\n",
              "      <td>object</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>retweet</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>favorite</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           data_type\n",
              "Unnamed: 0     int64\n",
              "tweet.id       int64\n",
              "created_at    object\n",
              "text          object\n",
              "location      object\n",
              "retweet        int64\n",
              "favorite       int64"
            ]
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "id": "-TigHSsnuLbn",
        "outputId": "dd1f9b0c-cea4-40b0-bf3b-af34023d4de0"
      },
      "source": [
        "## Check the data type of each column\n",
        "new_rand_df.dtypes.to_frame().rename(columns={0:'data_type'})"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>data_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>index</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ItemID</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sentiment</th>\n",
              "      <td>int64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SentimentSource</th>\n",
              "      <td>object</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SentimentText</th>\n",
              "      <td>object</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                data_type\n",
              "index               int64\n",
              "ItemID           int64\n",
              "Sentiment           int64\n",
              "SentimentSource    object\n",
              "SentimentText      object"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZHXvHSCan-7_"
      },
      "source": [
        "## Drop unnecessary columns\n",
        "depressive_tweets_df.drop(columns=['Unnamed: 0'], inplace=True)\n",
        "new_rand_df.drop(columns=['ItemID', 'index','Sentiment', 'SentimentSource'], inplace=True)"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZNQQeuXcq0kp"
      },
      "source": [
        "Since we are mostly dealing with the tweets in our datasets, it is not necessary to change the data types at this stage."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kyiCOEnSqoGT",
        "outputId": "f36a3141-93e7-41d6-a1bc-79852da21581"
      },
      "source": [
        "## Finding unique values in each column\n",
        "for col in depressive_tweets_df:\n",
        "    print(\"There are \", len(depressive_tweets_df[col].unique()), \"unique values in \", col)"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There are  18190 unique values in  tweet.id\n",
            "There are  18071 unique values in  created_at\n",
            "There are  17107 unique values in  text\n",
            "There are  4648 unique values in  location\n",
            "There are  74 unique values in  retweet\n",
            "There are  159 unique values in  favorite\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7ivOCsGzsCJR"
      },
      "source": [
        "By considering **tweet.id** as our primary key, we have **18190** unique tweets, so we need to get rid of the duplicates."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jHMyyyS9u-zm",
        "outputId": "d502e42e-8c34-400d-a6cd-2d1c4e0adabd"
      },
      "source": [
        "## Finding unique values in each column\n",
        "for col in new_rand_df:\n",
        "    print(\"There are \", len(new_rand_df[col].unique()), \"unique values in \", col)"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "There are  20952 unique values in  SentimentText\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F0cHAHxV6tOR"
      },
      "source": [
        "No duplicates in random tweets dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vDHOTp4yrEWh"
      },
      "source": [
        "## drop duplicate values in tweet.id\n",
        "depressive_tweets_df.drop_duplicates(subset=['tweet.id'], inplace=True)"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E8zCo0WYwibg"
      },
      "source": [
        "depressive_tweets_df.reset_index(inplace=True)"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EZ1tY9cgswFs",
        "outputId": "36d59a85-ca66-41c9-9827-d286726532da"
      },
      "source": [
        "depressive_tweets_df.shape"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(18190, 7)"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 263
        },
        "id": "6R_Awmrusz4O",
        "outputId": "c1a95d6b-dc61-4f15-bd38-5d5e29d8bd61"
      },
      "source": [
        "## Find the number of Null values in each columns\n",
        "depressive_tweets_df.isnull().sum().to_frame().rename(columns={0:'Null values'})"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Null values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>index</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tweet.id</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>created_at</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>text</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>location</th>\n",
              "      <td>6384</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>retweet</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>favorite</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            Null values\n",
              "index                 0\n",
              "tweet.id              0\n",
              "created_at            0\n",
              "text                  0\n",
              "location           6384\n",
              "retweet               0\n",
              "favorite              0"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V8c0VrPzu8Up"
      },
      "source": [
        "There are **6384** Null values in the **location** columns but since location will not be used in our analysis or as a feature in our model, we don't need to replace them."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 78
        },
        "id": "cnN6os-fxxNU",
        "outputId": "17740f6c-0cbe-41e8-b27c-be624aa2cce6"
      },
      "source": [
        "## Find the number of Null values in each columns\n",
        "new_rand_df.isnull().sum().to_frame().rename(columns={0:'Null values'})"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Null values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>SentimentText</th>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Null values\n",
              "SentimentText            0"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mZK1ylMTx1Bf"
      },
      "source": [
        "No Null values in random tweets dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TUp4Apyts-ir"
      },
      "source": [
        "## Drop all the columns except index, tweet.id and text\n",
        "new_dep_df = depressive_tweets_df[['text']]"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qFegYxuWqwGZ"
      },
      "source": [
        "## Add label to both datasets (0 is non-depressive and 1 is depressive)\n",
        "new_dep_df['label'] = pd.Series([1 for x in range(len(new_dep_df.index))])\n",
        "new_rand_df['label'] = pd.Series([0 for x in range(len(new_rand_df.index))])"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "SEEbTmOvy1md",
        "outputId": "ccebdc4f-6716-4ea0-ca83-34e0bc02cb89"
      },
      "source": [
        "new_dep_df"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Open discussion. Between the Transfer Portal a...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Plenty of things are changing in my life and t...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>I feel a little hopeless. Anyone else? #hopele...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Which is more healthy? Hope, or hopelessness? ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>So someone tell me how do I get over #HOPELESS...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18185</th>\n",
              "      <td>Just got banned from a server F #sad</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18186</th>\n",
              "      <td>I literally cried during my exam and the cam i...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18187</th>\n",
              "      <td>No one can be happy with a guy like me. That's...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18188</th>\n",
              "      <td>arrived at my house but Am I Home? #deep #sad ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18189</th>\n",
              "      <td>Being spoken down to rn at @starbucks and reme...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>18190 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    text  label\n",
              "0      Open discussion. Between the Transfer Portal a...      1\n",
              "1      Plenty of things are changing in my life and t...      1\n",
              "2      I feel a little hopeless. Anyone else? #hopele...      1\n",
              "3      Which is more healthy? Hope, or hopelessness? ...      1\n",
              "4      So someone tell me how do I get over #HOPELESS...      1\n",
              "...                                                  ...    ...\n",
              "18185               Just got banned from a server F #sad      1\n",
              "18186  I literally cried during my exam and the cam i...      1\n",
              "18187  No one can be happy with a guy like me. That's...      1\n",
              "18188  arrived at my house but Am I Home? #deep #sad ...      1\n",
              "18189  Being spoken down to rn at @starbucks and reme...      1\n",
              "\n",
              "[18190 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IzFLvq0n7NBq"
      },
      "source": [
        "## Change the column name to be aligned with depressive dataset\n",
        "new_rand_df.rename(columns={'SentimentText': 'text'}, inplace=True)"
      ],
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "SlRhCcYDzMX4",
        "outputId": "20b0e9e6-e3e9-4a55-fb61-d84591967712"
      },
      "source": [
        "new_rand_df"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th>label</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>omg its already 7:30 :O</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Juuuuuuuuuuuuuuuuussssst Chillin!!</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>handed in my uniform today . i miss you ...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>hmmmm.... i wonder how she my number @-)</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>thanks to all the haters up in my face a...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20947</th>\n",
              "      <td>@andreaj27 well, cheers. i have a glass of wat...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20948</th>\n",
              "      <td>@AndreaJo84 Is that right? You're over in Palm...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20949</th>\n",
              "      <td>@AndreaKobayashi It's the best cafe in Asakusa...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20950</th>\n",
              "      <td>@AndreaKoeln heeey! tonight is the night! no s...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20951</th>\n",
              "      <td>@AmandaFClark it is when you add the hammock</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20952 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    text  label\n",
              "0                                omg its already 7:30 :O      0\n",
              "1                     Juuuuuuuuuuuuuuuuussssst Chillin!!      0\n",
              "2            handed in my uniform today . i miss you ...      0\n",
              "3               hmmmm.... i wonder how she my number @-)      0\n",
              "4            thanks to all the haters up in my face a...      0\n",
              "...                                                  ...    ...\n",
              "20947  @andreaj27 well, cheers. i have a glass of wat...      0\n",
              "20948  @AndreaJo84 Is that right? You're over in Palm...      0\n",
              "20949  @AndreaKobayashi It's the best cafe in Asakusa...      0\n",
              "20950  @AndreaKoeln heeey! tonight is the night! no s...      0\n",
              "20951      @AmandaFClark it is when you add the hammock       0\n",
              "\n",
              "[20952 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VlUxZVGy0E8i"
      },
      "source": [
        "## Combine two dataframes together\n",
        "df_all = pd.concat([new_dep_df, new_rand_df], ignore_index=True)"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "vpXYWRzq0TM2",
        "outputId": "08e0fede-7370-4762-a23a-32851a7a1a1b"
      },
      "source": [
        "df_all"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
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              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Open discussion. Between the Transfer Portal a...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Plenty of things are changing in my life and t...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>I feel a little hopeless. Anyone else? #hopele...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Which is more healthy? Hope, or hopelessness? ...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>So someone tell me how do I get over #HOPELESS...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39137</th>\n",
              "      <td>@andreaj27 well, cheers. i have a glass of wat...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39138</th>\n",
              "      <td>@AndreaJo84 Is that right? You're over in Palm...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39139</th>\n",
              "      <td>@AndreaKobayashi It's the best cafe in Asakusa...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39140</th>\n",
              "      <td>@AndreaKoeln heeey! tonight is the night! no s...</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39141</th>\n",
              "      <td>@AmandaFClark it is when you add the hammock</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>39142 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    text  label\n",
              "0      Open discussion. Between the Transfer Portal a...      1\n",
              "1      Plenty of things are changing in my life and t...      1\n",
              "2      I feel a little hopeless. Anyone else? #hopele...      1\n",
              "3      Which is more healthy? Hope, or hopelessness? ...      1\n",
              "4      So someone tell me how do I get over #HOPELESS...      1\n",
              "...                                                  ...    ...\n",
              "39137  @andreaj27 well, cheers. i have a glass of wat...      0\n",
              "39138  @AndreaJo84 Is that right? You're over in Palm...      0\n",
              "39139  @AndreaKobayashi It's the best cafe in Asakusa...      0\n",
              "39140  @AndreaKoeln heeey! tonight is the night! no s...      0\n",
              "39141      @AmandaFClark it is when you add the hammock       0\n",
              "\n",
              "[39142 rows x 2 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8W-U8a9MXe7Y"
      },
      "source": [
        "# Expand Contraction\n",
        "cList = {\n",
        "  \"ain't\": \"am not\",\n",
        "  \"aren't\": \"are not\",\n",
        "  \"can't\": \"cannot\",\n",
        "  \"can't've\": \"cannot have\",\n",
        "  \"'cause\": \"because\",\n",
        "  \"could've\": \"could have\",\n",
        "  \"couldn't\": \"could not\",\n",
        "  \"couldn't've\": \"could not have\",\n",
        "  \"didn't\": \"did not\",\n",
        "  \"doesn't\": \"does not\",\n",
        "  \"don't\": \"do not\",\n",
        "  \"hadn't\": \"had not\",\n",
        "  \"hadn't've\": \"had not have\",\n",
        "  \"hasn't\": \"has not\",\n",
        "  \"haven't\": \"have not\",\n",
        "  \"he'd\": \"he would\",\n",
        "  \"he'd've\": \"he would have\",\n",
        "  \"he'll\": \"he will\",\n",
        "  \"he'll've\": \"he will have\",\n",
        "  \"he's\": \"he is\",\n",
        "  \"how'd\": \"how did\",\n",
        "  \"how'd'y\": \"how do you\",\n",
        "  \"how'll\": \"how will\",\n",
        "  \"how's\": \"how is\",\n",
        "  \"I'd\": \"I would\",\n",
        "  \"I'd've\": \"I would have\",\n",
        "  \"I'll\": \"I will\",\n",
        "  \"I'll've\": \"I will have\",\n",
        "  \"I'm\": \"I am\",\n",
        "  \"I've\": \"I have\",\n",
        "  \"isn't\": \"is not\",\n",
        "  \"it'd\": \"it had\",\n",
        "  \"it'd've\": \"it would have\",\n",
        "  \"it'll\": \"it will\",\n",
        "  \"it'll've\": \"it will have\",\n",
        "  \"it's\": \"it is\",\n",
        "  \"let's\": \"let us\",\n",
        "  \"ma'am\": \"madam\",\n",
        "  \"mayn't\": \"may not\",\n",
        "  \"might've\": \"might have\",\n",
        "  \"mightn't\": \"might not\",\n",
        "  \"mightn't've\": \"might not have\",\n",
        "  \"must've\": \"must have\",\n",
        "  \"mustn't\": \"must not\",\n",
        "  \"mustn't've\": \"must not have\",\n",
        "  \"needn't\": \"need not\",\n",
        "  \"needn't've\": \"need not have\",\n",
        "  \"o'clock\": \"of the clock\",\n",
        "  \"oughtn't\": \"ought not\",\n",
        "  \"oughtn't've\": \"ought not have\",\n",
        "  \"shan't\": \"shall not\",\n",
        "  \"sha'n't\": \"shall not\",\n",
        "  \"shan't've\": \"shall not have\",\n",
        "  \"she'd\": \"she would\",\n",
        "  \"she'd've\": \"she would have\",\n",
        "  \"she'll\": \"she will\",\n",
        "  \"she'll've\": \"she will have\",\n",
        "  \"she's\": \"she is\",\n",
        "  \"should've\": \"should have\",\n",
        "  \"shouldn't\": \"should not\",\n",
        "  \"shouldn't've\": \"should not have\",\n",
        "  \"so've\": \"so have\",\n",
        "  \"so's\": \"so is\",\n",
        "  \"that'd\": \"that would\",\n",
        "  \"that'd've\": \"that would have\",\n",
        "  \"that's\": \"that is\",\n",
        "  \"there'd\": \"there had\",\n",
        "  \"there'd've\": \"there would have\",\n",
        "  \"there's\": \"there is\",\n",
        "  \"they'd\": \"they would\",\n",
        "  \"they'd've\": \"they would have\",\n",
        "  \"they'll\": \"they will\",\n",
        "  \"they'll've\": \"they will have\",\n",
        "  \"they're\": \"they are\",\n",
        "  \"they've\": \"they have\",\n",
        "  \"to've\": \"to have\",\n",
        "  \"wasn't\": \"was not\",\n",
        "  \"we'd\": \"we had\",\n",
        "  \"we'd've\": \"we would have\",\n",
        "  \"we'll\": \"we will\",\n",
        "  \"we'll've\": \"we will have\",\n",
        "  \"we're\": \"we are\",\n",
        "  \"we've\": \"we have\",\n",
        "  \"weren't\": \"were not\",\n",
        "  \"what'll\": \"what will\",\n",
        "  \"what'll've\": \"what will have\",\n",
        "  \"what're\": \"what are\",\n",
        "  \"what's\": \"what is\",\n",
        "  \"what've\": \"what have\",\n",
        "  \"when's\": \"when is\",\n",
        "  \"when've\": \"when have\",\n",
        "  \"where'd\": \"where did\",\n",
        "  \"where's\": \"where is\",\n",
        "  \"where've\": \"where have\",\n",
        "  \"who'll\": \"who will\",\n",
        "  \"who'll've\": \"who will have\",\n",
        "  \"who's\": \"who is\",\n",
        "  \"who've\": \"who have\",\n",
        "  \"why's\": \"why is\",\n",
        "  \"why've\": \"why have\",\n",
        "  \"will've\": \"will have\",\n",
        "  \"won't\": \"will not\",\n",
        "  \"won't've\": \"will not have\",\n",
        "  \"would've\": \"would have\",\n",
        "  \"wouldn't\": \"would not\",\n",
        "  \"wouldn't've\": \"would not have\",\n",
        "  \"y'all\": \"you all\",\n",
        "  \"y'alls\": \"you alls\",\n",
        "  \"y'all'd\": \"you all would\",\n",
        "  \"y'all'd've\": \"you all would have\",\n",
        "  \"y'all're\": \"you all are\",\n",
        "  \"y'all've\": \"you all have\",\n",
        "  \"you'd\": \"you had\",\n",
        "  \"you'd've\": \"you would have\",\n",
        "  \"you'll\": \"you you will\",\n",
        "  \"you'll've\": \"you you will have\",\n",
        "  \"you're\": \"you are\",\n",
        "  \"you've\": \"you have\"\n",
        "}\n",
        "\n",
        "c_re = re.compile('(%s)' % '|'.join(cList.keys()))\n",
        "\n",
        "def expandContractions(text, c_re=c_re):\n",
        "    def replace(match):\n",
        "        return cList[match.group(0)]\n",
        "    return c_re.sub(replace, text)"
      ],
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J6aURoUBzYTX"
      },
      "source": [
        "## Function to perform stepwise cleaning process\n",
        "def tweets_cleaner(tweets):\n",
        "  cleaned_tweets = []\n",
        "  for tweet in tweets:\n",
        "    tweet = tweet.lower() #lowercase\n",
        "    \n",
        "    # if url links then don't append to avoid news articles\n",
        "    # also check tweet length, save those > 5 \n",
        "    if re.match(\"(\\w+:\\/\\/\\S+)\", tweet) == None and len(tweet) > 5:\n",
        "    \n",
        "      #remove hashtag, @mention, emoji and image URLs\n",
        "      tweet = ' '.join(re.sub(\"(@[A-Za-z0-9]+)|(\\#[A-Za-z0-9]+)|(<Emoji:.*>)|(pic\\.twitter\\.com\\/.*)\", \" \", tweet).split())\n",
        "\n",
        "      #fix weirdly encoded texts\n",
        "      tweet = ftfy.fix_text(tweet)\n",
        "\n",
        "      #expand contraction\n",
        "      tweet = expandContractions(tweet)\n",
        "\n",
        "\n",
        "      #remove punctuation\n",
        "      tweet = ' '.join(re.sub(\"([^0-9A-Za-z \\t])\", \" \", tweet).split())\n",
        "\n",
        "      #stop words and lemmatization\n",
        "      stop_words = set(stopwords.words('english'))\n",
        "      word_tokens = nltk.word_tokenize(tweet)\n",
        "\n",
        "      lemmatizer=WordNetLemmatizer()\n",
        "      filtered_sentence = [lemmatizer.lemmatize(word) for word in word_tokens if not word in stop_words]\n",
        "      # back to string from list\n",
        "      tweet = ' '.join(filtered_sentence) # join words with a space in between them\n",
        "\n",
        "      cleaned_tweets.append(tweet)\n",
        "\n",
        "  return cleaned_tweets\n"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zOWGGVMF7gY2"
      },
      "source": [
        "## Word Cloud:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0LreQ-h3Fwkm"
      },
      "source": [
        "To get the most common words used in depressive and random datasets, the POS-tag (Parts of Speech tagging) module in the NLTK library was used. Using the WordCloud library, one can generate a Word Cloud based on word frequency and superimpose these words on any image. In this case, I used the Twitter logo and Matplotlib to display the image. The Word Cloud shows the words with higher frequency in bigger text size while the \"not-so\" common words are in smaller text sizes."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4MZO5RsC88pD"
      },
      "source": [
        "depressive_tweets_arr = [x for x in new_dep_df['text']]\n",
        "random_tweets_arr = [x for x in new_rand_df['text']]\n",
        "X_d = tweets_cleaner(depressive_tweets_arr)\n",
        "X_r = tweets_cleaner(random_tweets_arr)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OQwpOceO6vW0"
      },
      "source": [
        "## function to obtain adjectives from tweets\n",
        "def getadjectives(tweet):\n",
        "    tweet = nltk.word_tokenize(tweet)  # convert string to tokens\n",
        "    tweet = [word for (word, tag) in pos_tag(tweet)\n",
        "             if tag == \"JJ\"]  # pos_tag module in NLTK library\n",
        "    return \" \".join(tweet)  # join words with a space in between them"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k_3sVFCf8HpG"
      },
      "source": [
        "### Depressive Tweets Exploration"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "llP3o6gj-0Ap"
      },
      "source": [
        "## Apply getadjectives function to the processed tweets \n",
        "## Extract all tweets into one long string with each word separate with a \"space\"\n",
        "tweets_long_string = [getadjectives(x) for x in X_d]\n",
        "tweets_long_string = \" \".join(tweets_long_string)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "E7fZchNJ2BV3",
        "outputId": "da48ee08-93d4-4ebe-cb5f-25912374188d"
      },
      "source": [
        "# Import Twitter Logo\n",
        "image = np.array(Image.open('/content/drive/MyDrive/NLP/Depression_Detection/data_cleaning/logo.jpeg'))\n",
        "    \n",
        "fig = plt.figure() # Instantiate the figure object\n",
        "fig.set_figwidth(14) # set width\n",
        "fig.set_figheight(18) # set height\n",
        "\n",
        "plt.imshow(image, cmap=plt.cm.gray, interpolation='bilinear') # Display data as an image\n",
        "plt.axis('off') # Remove axis\n",
        "plt.show() # Display image"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GHDleOcT-Nb4"
      },
      "source": [
        "## Create function to generate the blue colour for the Word CLoud\n",
        "\n",
        "def blue_color_func(word, font_size, position, orientation, random_state=None,**kwargs):\n",
        "    return \"hsl(210, 100%%, %d%%)\" % random.randint(50, 70)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "1_G_e_0c89DP",
        "outputId": "5197224d-f678-4bfb-fa5e-6dd9352506c7"
      },
      "source": [
        "## Instantiate the Twitter word cloud object\n",
        "twitter_wc = WordCloud(background_color='white', max_words=1500, mask=image)\n",
        "\n",
        "## generate the word cloud\n",
        "twitter_wc.generate(tweets_long_string)\n",
        "\n",
        "## display the word cloud\n",
        "fig = plt.figure()\n",
        "fig.set_figwidth(14)  # set width\n",
        "fig.set_figheight(18)  # set height\n",
        "\n",
        "plt.imshow(twitter_wc.recolor(color_func=blue_color_func, random_state=3),\n",
        "           interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KLxTVrTDDboh",
        "outputId": "7f3bed2a-a96f-4e3a-c57d-7fce87e46c9c"
      },
      "source": [
        "twitter_wc.to_file(\"/content/drive/MyDrive/NLP/Depression_Detection/data_cleaning/wordcloud.png\") #save to a png file"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<wordcloud.wordcloud.WordCloud at 0x7f12130ba190>"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LLu2I7f3H_tt"
      },
      "source": [
        "**Analyzing Top Words in the Word Cloud for depressive dataset**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YlqKvsg7HT2r"
      },
      "source": [
        "## Combine all words in depressive into a list\n",
        "tweets_long_string = [getadjectives(x) for x in X_d]\n",
        "tweets_list=[]\n",
        "for item in tweets_long_string:\n",
        "    item = item.split()\n",
        "    for i in item:\n",
        "        tweets_list.append(i)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BablBAqDJ0U9"
      },
      "source": [
        "# Use the Built-in Python Collections module to determine Word frequency\n",
        "from collections import Counter\n",
        "counts = Counter(tweets_list)\n",
        "df = pd.DataFrame.from_dict(counts, orient='index').reset_index()\n",
        "df.columns = ['Words', 'Count']\n",
        "df.sort_values(by='Count', ascending=False, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "m0xZ6ESTJ-Xk",
        "outputId": "55972f89-8386-4912-a78e-5f283fa16a54"
      },
      "source": [
        "df.head(10)  # Check dataframe first 10 rows"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Words</th>\n",
              "      <th>Count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>86</th>\n",
              "      <td>mental</td>\n",
              "      <td>906</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>good</td>\n",
              "      <td>483</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>u</td>\n",
              "      <td>477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>much</td>\n",
              "      <td>316</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>179</th>\n",
              "      <td>new</td>\n",
              "      <td>300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>many</td>\n",
              "      <td>272</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>94</th>\n",
              "      <td>last</td>\n",
              "      <td>246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>bad</td>\n",
              "      <td>238</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>hard</td>\n",
              "      <td>209</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>happy</td>\n",
              "      <td>209</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Words  Count\n",
              "86   mental    906\n",
              "88     good    483\n",
              "26        u    477\n",
              "9      much    316\n",
              "179     new    300\n",
              "31     many    272\n",
              "94     last    246\n",
              "19      bad    238\n",
              "41     hard    209\n",
              "50    happy    209"
            ]
          },
          "metadata": {},
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7LTA5EEh8Ngm"
      },
      "source": [
        "### Random Tweets Exploration\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vcSAw5ZE9wnm"
      },
      "source": [
        "## Apply getadjectives function to the processed tweets \n",
        "## Extract all tweets into one long string with each word separate with a \"space\"\n",
        "tweets_long_string_rand = [getadjectives(x) for x in X_r]\n",
        "tweets_long_string_rand = \" \".join(tweets_long_string_rand)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "esVo2URB-MLQ",
        "outputId": "a1bfb7cc-5d47-4682-bf2a-861a4e528245"
      },
      "source": [
        "# Import Twitter Logo\n",
        "image = np.array(Image.open('/content/drive/MyDrive/NLP/Depression_Detection/data_cleaning/logo.jpeg'))\n",
        "    \n",
        "fig = plt.figure() # Instantiate the figure object\n",
        "fig.set_figwidth(14) # set width\n",
        "fig.set_figheight(18) # set height\n",
        "\n",
        "plt.imshow(image, cmap=plt.cm.gray, interpolation='bilinear') # Display data as an image\n",
        "plt.axis('off') # Remove axis\n",
        "plt.show() # Display image"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WyU1k4hR-MO5"
      },
      "source": [
        "## Create function to generate the blue colour for the Word CLoud\n",
        "\n",
        "def blue_color_func(word, font_size, position, orientation, random_state=None,**kwargs):\n",
        "    return \"hsl(210, 100%%, %d%%)\" % random.randint(50, 70)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "2oJfNBd6-MR8",
        "outputId": "7f857978-9f8a-49cf-a748-5da54b341ee2"
      },
      "source": [
        "## Instantiate the Twitter word cloud object\n",
        "twitter_wc = WordCloud(background_color='white', max_words=1500, mask=image)\n",
        "\n",
        "## generate the word cloud\n",
        "twitter_wc.generate(tweets_long_string_rand)\n",
        "\n",
        "## display the word cloud\n",
        "fig = plt.figure()\n",
        "fig.set_figwidth(14)  # set width\n",
        "fig.set_figheight(18)  # set height\n",
        "\n",
        "plt.imshow(twitter_wc.recolor(color_func=blue_color_func, random_state=3),\n",
        "           interpolation=\"bilinear\")\n",
        "plt.axis('off')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x1296 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h6t_q1-4-MUv",
        "outputId": "fb69dfcb-31b0-4957-fcdd-de8fcb8b6ab9"
      },
      "source": [
        "twitter_wc.to_file(\"/content/drive/MyDrive/NLP/Depression_Detection/data_cleaning/wordcloud_rand.png\") #save to a png file"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<wordcloud.wordcloud.WordCloud at 0x7f9e79f80310>"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dkASvS1V_uqv"
      },
      "source": [
        "**Analyzing Top Words in the Word Cloud for random dataset**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ij_xGFme_tVA"
      },
      "source": [
        "## Combine all words in depressive into a list\n",
        "tweets_long_string_rand = [getadjectives(x) for x in X_r]\n",
        "tweets_list_rand=[]\n",
        "for item in tweets_long_string_rand:\n",
        "    item = item.split()\n",
        "    for i in item:\n",
        "        tweets_list_rand.append(i)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HMMr4PEVABYM"
      },
      "source": [
        "## Use the Built-in Python Collections module to determine Word frequency\n",
        "from collections import Counter\n",
        "counts = Counter(tweets_list_rand)\n",
        "df_rand = pd.DataFrame.from_dict(counts, orient='index').reset_index()\n",
        "df_rand.columns = ['Words', 'Count']\n",
        "df_rand.sort_values(by='Count', ascending=False, inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "id": "1X7vo1AUAPUG",
        "outputId": "e8b69f83-1d0a-49ba-c4e1-bcd5dc1dadea"
      },
      "source": [
        "df_rand.head(10)  # Check dataframe first 10 rows"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Words</th>\n",
              "      <th>Count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>88</th>\n",
              "      <td>good</td>\n",
              "      <td>780</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>u</td>\n",
              "      <td>482</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>great</td>\n",
              "      <td>345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>new</td>\n",
              "      <td>332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>happy</td>\n",
              "      <td>290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>ly</td>\n",
              "      <td>201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>89</th>\n",
              "      <td>nice</td>\n",
              "      <td>176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>last</td>\n",
              "      <td>174</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>http</td>\n",
              "      <td>167</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>much</td>\n",
              "      <td>164</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Words  Count\n",
              "88   good    780\n",
              "31      u    482\n",
              "47  great    345\n",
              "8     new    332\n",
              "20  happy    290\n",
              "13     ly    201\n",
              "89   nice    176\n",
              "7    last    174\n",
              "12   http    167\n",
              "96   much    164"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Rw-5ySNYO7QK"
      },
      "source": [
        "## Data Analysis:"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T2CAp53UO9rC"
      },
      "source": [
        "## distribution of classes for prediction\n",
        "def create_distribution(dataFile):\n",
        "  return sns.countplot(x='label', data=dataFile, palette='hls')"
      ],
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "scONzDT7RrRt",
        "outputId": "a76f2695-7050-4deb-d010-1fe10e82d18f"
      },
      "source": [
        "create_distribution(df_all)"
      ],
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6355142390>"
            ]
          },
          "metadata": {},
          "execution_count": 56
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PGUU_n1GSoyl"
      },
      "source": [
        "Depreesive and random (Non-depressive) tweets are almost evenly distributed. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n-Wo3FVTTDmg"
      },
      "source": [
        "**Finding distribution of tweet lengths**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "id": "pyIEaCSvRwet",
        "outputId": "345a7b1f-ef41-49be-c5bb-0d1ecba91e18"
      },
      "source": [
        "dep_line_lengths = [len(statement) for statement in new_dep_df['text']]\n",
        "plt.plot(dep_line_lengths)\n",
        "plt.show()"
      ],
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TSB6hxsBTVsI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        },
        "outputId": "3c30fbdc-a7f4-4f94-c300-27ed432ae6ac"
      },
      "source": [
        "rand_line_lengths = [len(statement) for statement in new_rand_df['text']]\n",
        "plt.plot(dep_line_lengths)\n",
        "plt.show()"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cn6j1nsbk_ZQ"
      },
      "source": [
        "From the distributions above, it is clear that there is no outliers in our depressive and random datasets."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NDsQ0r4c1m4_"
      },
      "source": [
        "## Cleaning combined dataset and save it"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n7xa-eIw200r"
      },
      "source": [
        "tweets_arr = [x for x in df_all['text']]"
      ],
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-u58yHXO3nIc"
      },
      "source": [
        "corpus = tweets_cleaner(tweets_arr)"
      ],
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HTn5gHJqGLty",
        "outputId": "a2d6062a-48b3-4448-fc6d-ff267ffd4067"
      },
      "source": [
        "corpus[:10]"
      ],
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['open discussion transfer portal nil become obsolete organization governing body',\n",
              " 'plenty thing changing life life around one thing change',\n",
              " 'feel little hopeless anyone else',\n",
              " 'healthy hope hopelessness',\n",
              " 'someone tell get live world surrounded people help u much better son inability care would likely give hopelessness darkness',\n",
              " 'parent deserves experience indian legal system',\n",
              " 'also look lot like feel like worse place sometimes',\n",
              " 'glad tackling huge professional shortage facing saddened really living post pandemic world palpable every level department system',\n",
              " 'know someone depressed please resolve never ask straightforward response bad situation depression like weather try understand blackness lethargy loneliness going',\n",
              " 'find every hidden grow calm way go beyond mere others']"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zgMS50Ud04tk"
      },
      "source": [
        "## Adding clean tweets as a new column\n",
        "df_all['clean_text'] = corpus"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hgIt3G9w2vBH"
      },
      "source": [
        "We have to remove those rows with tweets that has been completely deleted in the cleaning process."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UK5ZM4cw2deY"
      },
      "source": [
        "# replace field that's entirely space (or empty) with NaN\n",
        "df_all.replace(r'^\\s*$', np.nan, regex=True, inplace=True)"
      ],
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 414
        },
        "id": "rVEPWTah2pmZ",
        "outputId": "0e193d81-dcbe-4934-ca3b-a5cbe6d2e94d"
      },
      "source": [
        "df_all[df_all['clean_text'].isnull()]"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label</th>\n",
              "      <th>clean_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>You are there for them, but they are not there...</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>881</th>\n",
              "      <td>Why me? \\n\\n#depression #depressed #sad #cry #...</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1142</th>\n",
              "      <td>that’s IT! i’m #depressed</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2037</th>\n",
              "      <td>When your #anxiety has #anxiety 😖</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5073</th>\n",
              "      <td>I have #anxiety</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38624</th>\n",
              "      <td>@amyserrata  i can do that</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38730</th>\n",
              "      <td>@anaggh</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38947</th>\n",
              "      <td>@ancesmulles so. when?</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38949</th>\n",
              "      <td>@AnchMorpork ?? ??? ??????? ???????????? &amp;quot...</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39111</th>\n",
              "      <td>@AmandaChalmers i do</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>233 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    text  label clean_text\n",
              "67     You are there for them, but they are not there...      1        NaN\n",
              "881    Why me? \\n\\n#depression #depressed #sad #cry #...      1        NaN\n",
              "1142                           that’s IT! i’m #depressed      1        NaN\n",
              "2037                   When your #anxiety has #anxiety 😖      1        NaN\n",
              "5073                                     I have #anxiety      1        NaN\n",
              "...                                                  ...    ...        ...\n",
              "38624                        @amyserrata  i can do that       0        NaN\n",
              "38730                                           @anaggh       0        NaN\n",
              "38947                            @ancesmulles so. when?       0        NaN\n",
              "38949  @AnchMorpork ?? ??? ??????? ???????????? &quot...      0        NaN\n",
              "39111                              @AmandaChalmers i do       0        NaN\n",
              "\n",
              "[233 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Vo84LjX25-N"
      },
      "source": [
        "## Deleting the rows with nan \n",
        "df_all.dropna(subset=['clean_text'], inplace=True)"
      ],
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 48
        },
        "id": "z-P04gFb3EmZ",
        "outputId": "6de58956-e3b6-4308-ef92-e833cda8e2bf"
      },
      "source": [
        "## Double_check for nan\n",
        "df_all[df_all['clean_text'].isnull()]"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>text</th>\n",
              "      <th>label</th>\n",
              "      <th>clean_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [text, label, clean_text]\n",
              "Index: []"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AUqtvjn33CTh"
      },
      "source": [
        "## Save cleaned_dataset\n",
        "df_all.to_csv('/content/drive/MyDrive/NLP/Depression_Detection/data_cleaning/processed_data/processed_data.csv',\n",
        "              sep='\\t', encoding='utf-8',index=False)"
      ],
      "execution_count": 67,
      "outputs": []
    }
  ]
}