EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "pd.set_option('display.precision', 2)\n",
    "pd.set_option('display.max.columns', 40)\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv(\"inputs/Train.csv\")\n",
    "test = pd.read_csv(\"inputs/Test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SUAVK39Z</td>\n",
       "      <td>I feel that it was better I dieAm happy</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9JDAGUV3</td>\n",
       "      <td>Why do I get hallucinations?</td>\n",
       "      <td>Drugs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>419WR1LQ</td>\n",
       "      <td>I am stresseed due to lack of financial suppor...</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6UY7DX6Q</td>\n",
       "      <td>Why is life important?</td>\n",
       "      <td>Suicide</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FYC0FTFB</td>\n",
       "      <td>How could I be helped to go through the depres...</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>611</th>\n",
       "      <td>BOHSNXCN</td>\n",
       "      <td>What should I do to stop alcoholism?</td>\n",
       "      <td>Alcohol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>612</th>\n",
       "      <td>GVDXRQPY</td>\n",
       "      <td>How to become my oldself again</td>\n",
       "      <td>Suicide</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>613</th>\n",
       "      <td>IO4JHIQS</td>\n",
       "      <td>How can someone stop it?</td>\n",
       "      <td>Alcohol</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>614</th>\n",
       "      <td>1DS3P1XO</td>\n",
       "      <td>I feel unworthy</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>615</th>\n",
       "      <td>ORF71PVQ</td>\n",
       "      <td>I feel so discouraged with life</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>616 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ID                                               text       label\n",
       "0    SUAVK39Z            I feel that it was better I dieAm happy  Depression\n",
       "1    9JDAGUV3                       Why do I get hallucinations?       Drugs\n",
       "2    419WR1LQ  I am stresseed due to lack of financial suppor...  Depression\n",
       "3    6UY7DX6Q                             Why is life important?     Suicide\n",
       "4    FYC0FTFB  How could I be helped to go through the depres...  Depression\n",
       "..        ...                                                ...         ...\n",
       "611  BOHSNXCN               What should I do to stop alcoholism?     Alcohol\n",
       "612  GVDXRQPY                     How to become my oldself again     Suicide\n",
       "613  IO4JHIQS                           How can someone stop it?     Alcohol\n",
       "614  1DS3P1XO                                   I feel unworthy   Depression\n",
       "615  ORF71PVQ                    I feel so discouraged with life  Depression\n",
       "\n",
       "[616 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.label.value_counts().plot(kind='barh');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02V56KMO</td>\n",
       "      <td>How to overcome bad feelings and emotions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>03BMGTOK</td>\n",
       "      <td>I feel like giving up in life</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>03LZVFM6</td>\n",
       "      <td>I was so depressed feel like got no strength t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0EPULUM5</td>\n",
       "      <td>I feel so low especially since I had no one to...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0GM4C5GD</td>\n",
       "      <td>can i be successful when I am a drug addict?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>Z9A6ACLK</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>305</th>\n",
       "      <td>ZDUOIGKN</td>\n",
       "      <td>My girlfriend dumped me</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>ZHQ60CCH</td>\n",
       "      <td>How can I go back to being my old self?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>307</th>\n",
       "      <td>ZVIJMA4O</td>\n",
       "      <td>Is it true bhang is  medicinal?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>ZYIFAY98</td>\n",
       "      <td>how can I overcome the problem?</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>309 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ID                                               text\n",
       "0    02V56KMO          How to overcome bad feelings and emotions\n",
       "1    03BMGTOK                     I feel like giving up in life \n",
       "2    03LZVFM6  I was so depressed feel like got no strength t...\n",
       "3    0EPULUM5  I feel so low especially since I had no one to...\n",
       "4    0GM4C5GD       can i be successful when I am a drug addict?\n",
       "..        ...                                                ...\n",
       "304  Z9A6ACLK                                                Yes\n",
       "305  ZDUOIGKN                            My girlfriend dumped me\n",
       "306  ZHQ60CCH            How can I go back to being my old self?\n",
       "307  ZVIJMA4O                    Is it true bhang is  medicinal?\n",
       "308  ZYIFAY98                    how can I overcome the problem?\n",
       "\n",
       "[309 rows x 2 columns]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>Z9A6ACLK</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           ID text\n",
       "304  Z9A6ACLK  Yes"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test[test.text.str.match(\"Yes\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "min      1.00\n",
       "mean     7.83\n",
       "max     36.00\n",
       "Name: text, dtype: float64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_len = train.text.apply(lambda x: len(x.split(' ')))\n",
    "train_len.agg(['min', 'mean', 'max'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "min      1.0\n",
       "mean     8.1\n",
       "max     31.0\n",
       "Name: text, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.text.apply(lambda x: len(x.split(' '))).agg(['min', 'mean', 'max'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Challenging', 'Dissappointed', 'Sad,lonely'], dtype=object)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[train.text.apply(lambda x: len(x.split(' '))) == train.text.apply(lambda x: len(x.split(' '))).min()].text.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(pd.crosstab(train.label, train_len), annot=True, cbar=False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>text</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SUAVK39Z</td>\n",
       "      <td>I feel that it was better I dieAm happy</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9JDAGUV3</td>\n",
       "      <td>Why do I get hallucinations?</td>\n",
       "      <td>Drugs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>419WR1LQ</td>\n",
       "      <td>I am stresseed due to lack of financial suppor...</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         ID                                               text       label\n",
       "0  SUAVK39Z            I feel that it was better I dieAm happy  Depression\n",
       "1  9JDAGUV3                       Why do I get hallucinations?       Drugs\n",
       "2  419WR1LQ  I am stresseed due to lack of financial suppor...  Depression"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>Depression</th>\n",
       "      <th>Alcohol</th>\n",
       "      <th>Suicide</th>\n",
       "      <th>Drugs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>I feel that it was better I dieAm happy</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Why do I get hallucinations?</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>I am stresseed due to lack of financial suppor...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  Depression  Alcohol  \\\n",
       "0            I feel that it was better I dieAm happy           1        0   \n",
       "1                       Why do I get hallucinations?           0        0   \n",
       "2  I am stresseed due to lack of financial suppor...           1        0   \n",
       "\n",
       "   Suicide  Drugs  \n",
       "0        0      0  \n",
       "1        0      1  \n",
       "2        0      0  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train = pd.concat([train.text, pd.get_dummies(train['label']).reindex(columns=[\"Depression\", \"Alcohol\", \"Suicide\", \"Drugs\"])], axis=1)\n",
    "train[:3]"
   ]
  }
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