csv_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import os\n",
    "import pandas as pd\n",
    "import re\n",
    "import numpy as np\n",
    "from pathlib import Path\n",
    "from datetime import datetime\n",
    "from nltk.tag.stanford import StanfordNERTagger\n",
    "import pylab as pl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv(\"worldnews_0619.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Boarders huh</td>\n",
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       "      <td>[removed]</td>\n",
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       "      <th>2</th>\n",
       "      <td>I think you know less when you think that Stal...</td>\n",
       "      <td>steeritupld</td>\n",
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       "      <th>3</th>\n",
       "      <td>So why are you using it as an argument against...</td>\n",
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       "      <td>eqzooom</td>\n",
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       "      <th>4</th>\n",
       "      <td>There is no round up ready wheat in the commer...</td>\n",
       "      <td>arvada14</td>\n",
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       "      <td>t5_2qh13</td>\n",
       "      <td>t3_aqio89</td>\n",
       "      <td>t1_eghowah</td>\n",
       "      <td>0</td>\n",
       "      <td>1569779899</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>eqzhngv</td>\n",
       "      <td>worldnews</td>\n",
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      ],
      "text/plain": [
       "                                                body       author  \\\n",
       "0                                       Boarders huh    J_Man2743   \n",
       "1                                          [removed]    [deleted]   \n",
       "2  I think you know less when you think that Stal...  steeritupld   \n",
       "3  So why are you using it as an argument against...     arvada14   \n",
       "4  There is no round up ready wheat in the commer...     arvada14   \n",
       "\n",
       "   created_utc subreddit_id    link_id   parent_id  score  retrieved_on  \\\n",
       "0   1559518235     t5_2qh13  t3_a78kyo   t3_a78kyo      0    1568784725   \n",
       "1   1561011745     t5_2qh13  t3_aeu81p  t1_erl6n3x      0    1570329691   \n",
       "2   1560168854     t5_2qh13  t3_andfac  t1_eqmsv60      0    1569348202   \n",
       "3   1560403679     t5_2qh13  t3_aqio89  t1_eggt2jk      0    1569783807   \n",
       "4   1560400159     t5_2qh13  t3_aqio89  t1_eghowah      0    1569779899   \n",
       "\n",
       "   controversiality  gilded       id  subreddit  \n",
       "0                 0       0  epuwwc7  worldnews  \n",
       "1                 0       0  erm9r84  worldnews  \n",
       "2                 0       0  eqmx6le  worldnews  \n",
       "3                 0       0  eqzooom  worldnews  \n",
       "4                 0       0  eqzhngv  worldnews  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"post_date\"]=df[\"created_utc\"].apply(lambda x: datetime.fromtimestamp(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>author</th>\n",
       "      <th>created_utc</th>\n",
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       "    <tr>\n",
       "      <th>796349</th>\n",
       "      <td>Steve Banon\\n\\nFar right \\n\\nPick one</td>\n",
       "      <td>edduvald0</td>\n",
       "      <td>1559347202</td>\n",
       "      <td>t5_2qh13</td>\n",
       "      <td>t3_bva42f</td>\n",
       "      <td>t3_bva42f</td>\n",
       "      <td>-2</td>\n",
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       "      <td>1</td>\n",
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       "      <td>epom0cg</td>\n",
       "      <td>worldnews</td>\n",
       "      <td>2019-05-31 19:00:02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71160</th>\n",
       "      <td>I'd really, really love to know another 2020 c...</td>\n",
       "      <td>Theso</td>\n",
       "      <td>1559347204</td>\n",
       "      <td>t5_2qh13</td>\n",
       "      <td>t3_buzs5f</td>\n",
       "      <td>t1_epol158</td>\n",
       "      <td>1</td>\n",
       "      <td>1568677948</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>epom0h8</td>\n",
       "      <td>worldnews</td>\n",
       "      <td>2019-05-31 19:00:04</td>\n",
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       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>Why there is so many racists post today?\\n\\nBt...</td>\n",
       "      <td>lunetick</td>\n",
       "      <td>1559347205</td>\n",
       "      <td>t5_2qh13</td>\n",
       "      <td>t3_bveiud</td>\n",
       "      <td>t3_bveiud</td>\n",
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       "      <td>0</td>\n",
       "      <td>epom0i0</td>\n",
       "      <td>worldnews</td>\n",
       "      <td>2019-05-31 19:00:05</td>\n",
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       "    <tr>\n",
       "      <th>71258</th>\n",
       "      <td>I don't think such a system could act as a det...</td>\n",
       "      <td>cn_cooling</td>\n",
       "      <td>1559347206</td>\n",
       "      <td>t5_2qh13</td>\n",
       "      <td>t3_bv2vmp</td>\n",
       "      <td>t1_epmkbb1</td>\n",
       "      <td>1</td>\n",
       "      <td>1568677949</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>epom0j1</td>\n",
       "      <td>worldnews</td>\n",
       "      <td>2019-05-31 19:00:06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456707</th>\n",
       "      <td>environmental destruction/pollution and rampan...</td>\n",
       "      <td>Redditaspropaganda</td>\n",
       "      <td>1559347207</td>\n",
       "      <td>t5_2qh13</td>\n",
       "      <td>t3_bvcfi8</td>\n",
       "      <td>t1_epod8zm</td>\n",
       "      <td>3</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>epom0ma</td>\n",
       "      <td>worldnews</td>\n",
       "      <td>2019-05-31 19:00:07</td>\n",
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      ],
      "text/plain": [
       "                                                     body              author  \\\n",
       "796349              Steve Banon\\n\\nFar right \\n\\nPick one           edduvald0   \n",
       "71160   I'd really, really love to know another 2020 c...               Theso   \n",
       "827     Why there is so many racists post today?\\n\\nBt...            lunetick   \n",
       "71258   I don't think such a system could act as a det...          cn_cooling   \n",
       "456707  environmental destruction/pollution and rampan...  Redditaspropaganda   \n",
       "\n",
       "        created_utc subreddit_id    link_id   parent_id  score  retrieved_on  \\\n",
       "796349   1559347202     t5_2qh13  t3_bva42f   t3_bva42f     -2    1568677946   \n",
       "71160    1559347204     t5_2qh13  t3_buzs5f  t1_epol158      1    1568677948   \n",
       "827      1559347205     t5_2qh13  t3_bveiud   t3_bveiud      0    1568677948   \n",
       "71258    1559347206     t5_2qh13  t3_bv2vmp  t1_epmkbb1      1    1568677949   \n",
       "456707   1559347207     t5_2qh13  t3_bvcfi8  t1_epod8zm      3    1568677950   \n",
       "\n",
       "        controversiality  gilded       id  subreddit           post_date  \n",
       "796349                 1       0  epom0cg  worldnews 2019-05-31 19:00:02  \n",
       "71160                  0       0  epom0h8  worldnews 2019-05-31 19:00:04  \n",
       "827                    1       0  epom0i0  worldnews 2019-05-31 19:00:05  \n",
       "71258                  0       0  epom0j1  worldnews 2019-05-31 19:00:06  \n",
       "456707                 0       0  epom0ma  worldnews 2019-05-31 19:00:07  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(\"post_date\").head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Number of comments vs Number of Users Who Have Posted that Many Comment')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt1=df.groupby(\"author\").size().sort_values().value_counts().plot(loglog=True, legend=True, style='o',figsize=(16,9))\n",
    "# pl.axes(xlabel=\"Number of Comments\",ylabel=\"Number of Users Posting x Comments\")\n",
    "pl.suptitle('Number of comments vs Number of Users Who Have Posted that Many Comment')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1      76756\n",
       "11      1228\n",
       "20       388\n",
       "30       155\n",
       "43        79\n",
       "50        53\n",
       "57        28\n",
       "72        21\n",
       "86        17\n",
       "95        12\n",
       "111        8\n",
       "136        6\n",
       "115        4\n",
       "165        3\n",
       "116        3\n",
       "154        2\n",
       "162        2\n",
       "118        2\n",
       "163        2\n",
       "169        2\n",
       "268        1\n",
       "361        1\n",
       "251        1\n",
       "181        1\n",
       "341        1\n",
       "295        1\n",
       "192        1\n",
       "226        1\n",
       "198        1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"author\").size().sort_values().value_counts()[0:-1:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Number of comments vs Day of Month')"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "times=pd.to_datetime(df.post_date)\n",
    "plt2=df.groupby(by=[df.post_date.map(lambda x : (x.month, x.day))]).size().plot(figsize=(16,9))\n",
    "pl.suptitle('Number of comments vs Day of Month')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "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></th>\n",
       "      <th>body</th>\n",
       "      <th>created_utc</th>\n",
       "      <th>subreddit_id</th>\n",
       "      <th>link_id</th>\n",
       "      <th>parent_id</th>\n",
       "      <th>score</th>\n",
       "      <th>retrieved_on</th>\n",
       "      <th>controversiality</th>\n",
       "      <th>gilded</th>\n",
       "      <th>id</th>\n",
       "      <th>subreddit</th>\n",
       "      <th>post_date</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>author</th>\n",
       "      <th>post_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">---Ocelot---</th>\n",
       "      <th>(6, 5)</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 6)</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 8)</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 21)</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>---TheFierceDeity---</th>\n",
       "      <th>(6, 19)</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">--Captain__America--</th>\n",
       "      <th>(6, 6)</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 12)</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 14)</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 15)</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 16)</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 25)</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">--ManBearPig--</th>\n",
       "      <th>(6, 1)</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 11)</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(6, 20)</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                body  created_utc  subreddit_id  link_id  \\\n",
       "author               post_date                                             \n",
       "---Ocelot---         (6, 5)        5            5             5        5   \n",
       "                     (6, 6)        3            3             3        3   \n",
       "                     (6, 8)        3            3             3        3   \n",
       "                     (6, 21)       2            2             2        2   \n",
       "---TheFierceDeity--- (6, 19)       3            3             3        3   \n",
       "--Captain__America-- (6, 6)        2            2             2        2   \n",
       "                     (6, 12)       4            4             4        4   \n",
       "                     (6, 14)       7            7             7        7   \n",
       "                     (6, 15)       6            6             6        6   \n",
       "                     (6, 16)       2            2             2        2   \n",
       "                     (6, 25)       3            3             3        3   \n",
       "--ManBearPig--       (6, 1)        2            2             2        2   \n",
       "                     (6, 11)       5            5             5        5   \n",
       "                     (6, 20)       5            5             5        5   \n",
       "\n",
       "                                parent_id  score  retrieved_on  \\\n",
       "author               post_date                                   \n",
       "---Ocelot---         (6, 5)             5      5             5   \n",
       "                     (6, 6)             3      3             3   \n",
       "                     (6, 8)             3      3             3   \n",
       "                     (6, 21)            2      2             2   \n",
       "---TheFierceDeity--- (6, 19)            3      3             3   \n",
       "--Captain__America-- (6, 6)             2      2             2   \n",
       "                     (6, 12)            4      4             4   \n",
       "                     (6, 14)            7      7             7   \n",
       "                     (6, 15)            6      6             6   \n",
       "                     (6, 16)            2      2             2   \n",
       "                     (6, 25)            3      3             3   \n",
       "--ManBearPig--       (6, 1)             2      2             2   \n",
       "                     (6, 11)            5      5             5   \n",
       "                     (6, 20)            5      5             5   \n",
       "\n",
       "                                controversiality  gilded  id  subreddit  \\\n",
       "author               post_date                                            \n",
       "---Ocelot---         (6, 5)                    5       5   5          5   \n",
       "                     (6, 6)                    3       3   3          3   \n",
       "                     (6, 8)                    3       3   3          3   \n",
       "                     (6, 21)                   2       2   2          2   \n",
       "---TheFierceDeity--- (6, 19)                   3       3   3          3   \n",
       "--Captain__America-- (6, 6)                    2       2   2          2   \n",
       "                     (6, 12)                   4       4   4          4   \n",
       "                     (6, 14)                   7       7   7          7   \n",
       "                     (6, 15)                   6       6   6          6   \n",
       "                     (6, 16)                   2       2   2          2   \n",
       "                     (6, 25)                   3       3   3          3   \n",
       "--ManBearPig--       (6, 1)                    2       2   2          2   \n",
       "                     (6, 11)                   5       5   5          5   \n",
       "                     (6, 20)                   5       5   5          5   \n",
       "\n",
       "                                post_date  \n",
       "author               post_date             \n",
       "---Ocelot---         (6, 5)             5  \n",
       "                     (6, 6)             3  \n",
       "                     (6, 8)             3  \n",
       "                     (6, 21)            2  \n",
       "---TheFierceDeity--- (6, 19)            3  \n",
       "--Captain__America-- (6, 6)             2  \n",
       "                     (6, 12)            4  \n",
       "                     (6, 14)            7  \n",
       "                     (6, 15)            6  \n",
       "                     (6, 16)            2  \n",
       "                     (6, 25)            3  \n",
       "--ManBearPig--       (6, 1)             2  \n",
       "                     (6, 11)            5  \n",
       "                     (6, 20)            5  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frequent_users=df.groupby(by=[df.author,df.post_date.map(lambda x : (x.month, x.day))]).agg('count')[df.groupby([\"author\",df.post_date.map(lambda x : (x.month, x.day))]).agg('count')[\"body\"]>1]\n",
    "frequent_users[1:15]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'Average Number of comments vs Day of Month for Regular Users')"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "frequent_users.body.unstack().mean().plot(figsize=(16,9))\n",
    "pl.suptitle('Average Number of comments vs Day of Month for Regular Users')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}