Statistics_analysis_on_WhatsApp_groupchat.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1><b> Statistical Analysis of WhatsApp chat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Importrequired libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/anaconda3/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
      "  import pandas.util.testing as tm\n"
     ]
    }
   ],
   "source": [
    "import numpy as np \n",
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat =  pd.read_csv('/root/Documents/dataset/WhatsApp-Chat/WhatsApp Chat with IS Boys☠.txt',error_bad_lines=False,names=['date','details'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat.drop(0,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat['Info']=chat['details'].apply(lambda x: str(x).split('-')[-1])\n",
    "chat['Time']=chat['details'].apply(lambda x: str(x).split('-')[0])\n",
    "chat['user']=chat['Info'].apply(lambda x: str(x).split(':')[0])\n",
    "chat['msg']=chat['Info'].apply(lambda x: str(x).split(':')[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>date</th>\n",
       "      <th>details</th>\n",
       "      <th>Info</th>\n",
       "      <th>Time</th>\n",
       "      <th>user</th>\n",
       "      <th>msg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>8:34 AM - Mukund Coep: 😂😂😂</td>\n",
       "      <td>Mukund Coep: 😂😂😂</td>\n",
       "      <td>8:34 AM</td>\n",
       "      <td>Mukund Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9/12/19</td>\n",
       "      <td>11:20 AM - Mukund Coep created group \"IS Boys☠\"</td>\n",
       "      <td>Mukund Coep created group \"IS Boys☠\"</td>\n",
       "      <td>11:20 AM</td>\n",
       "      <td>Mukund Coep created group \"IS Boys☠\"</td>\n",
       "      <td>Mukund Coep created group \"IS Boys☠\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>8:34 AM - Mukund Coep added you</td>\n",
       "      <td>Mukund Coep added you</td>\n",
       "      <td>8:34 AM</td>\n",
       "      <td>Mukund Coep added you</td>\n",
       "      <td>Mukund Coep added you</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>9:59 AM - Akash Coep: 😂😂😂</td>\n",
       "      <td>Akash Coep: 😂😂😂</td>\n",
       "      <td>9:59 AM</td>\n",
       "      <td>Akash Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>11:13 AM - Amar Coep: 😂😂😂😂</td>\n",
       "      <td>Amar Coep: 😂😂😂😂</td>\n",
       "      <td>11:13 AM</td>\n",
       "      <td>Amar Coep</td>\n",
       "      <td>😂😂😂😂</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      date                                           details  \\\n",
       "1  9/22/19                        8:34 AM - Mukund Coep: 😂😂😂   \n",
       "2  9/12/19   11:20 AM - Mukund Coep created group \"IS Boys☠\"   \n",
       "3  9/22/19                   8:34 AM - Mukund Coep added you   \n",
       "4  9/22/19                         9:59 AM - Akash Coep: 😂😂😂   \n",
       "5  9/22/19                        11:13 AM - Amar Coep: 😂😂😂😂   \n",
       "\n",
       "                                    Info        Time  \\\n",
       "1                       Mukund Coep: 😂😂😂    8:34 AM    \n",
       "2   Mukund Coep created group \"IS Boys☠\"   11:20 AM    \n",
       "3                  Mukund Coep added you    8:34 AM    \n",
       "4                        Akash Coep: 😂😂😂    9:59 AM    \n",
       "5                        Amar Coep: 😂😂😂😂   11:13 AM    \n",
       "\n",
       "                                    user  \\\n",
       "1                            Mukund Coep   \n",
       "2   Mukund Coep created group \"IS Boys☠\"   \n",
       "3                  Mukund Coep added you   \n",
       "4                             Akash Coep   \n",
       "5                              Amar Coep   \n",
       "\n",
       "                                     msg  \n",
       "1                                    😂😂😂  \n",
       "2   Mukund Coep created group \"IS Boys☠\"  \n",
       "3                  Mukund Coep added you  \n",
       "4                                    😂😂😂  \n",
       "5                                   😂😂😂😂  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat.drop(['details','Info'],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "unusally = []\n",
    "chat.dropna(inplace=True)\n",
    "\n",
    "for i,user in chat['user'].iteritems():\n",
    "    if (user==\" You changed this group's icon\") or (user==\"2 ahe\") or (user==\"E[x]^2\")or(user==' Mukund Coep created group \"IS Boys☠\"')or(user==' 3.5| > 2.5}')or(user==\" Mukund Coep added you\")or(user=='hB1TzoG7M')or(user=='nan'):\n",
    "        unusally.append(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat.drop(unusally,inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unique user presnt in chat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " Ritendra🙂         131\n",
       " Akash Coep         59\n",
       " Amar Coep          55\n",
       " Mukund Coep        33\n",
       " Jayesh IS COEP     26\n",
       " Pushkaraj Coep     16\n",
       " Ashish Coep        16\n",
       " Swapnil Coep       13\n",
       " Atharva Coep       11\n",
       " Shubham Coep        1\n",
       "Name: user, dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat['user'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>date</th>\n",
       "      <th>Time</th>\n",
       "      <th>user</th>\n",
       "      <th>msg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>8:34 AM</td>\n",
       "      <td>Mukund Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>9:59 AM</td>\n",
       "      <td>Akash Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>11:13 AM</td>\n",
       "      <td>Amar Coep</td>\n",
       "      <td>😂😂😂😂</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>12:41 PM</td>\n",
       "      <td>Akash Coep</td>\n",
       "      <td>&lt;Media omitted&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>12:41 PM</td>\n",
       "      <td>Mukund Coep</td>\n",
       "      <td>😂😂</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      date        Time          user               msg\n",
       "1  9/22/19    8:34 AM    Mukund Coep               😂😂😂\n",
       "4  9/22/19    9:59 AM     Akash Coep               😂😂😂\n",
       "5  9/22/19   11:13 AM      Amar Coep              😂😂😂😂\n",
       "6  9/22/19   12:41 PM     Akash Coep   <Media omitted>\n",
       "7  9/22/19   12:41 PM    Mukund Coep                😂😂"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install emot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "convert emoji felling in text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "#emoj explaining in text\n",
    "import re\n",
    "from emot.emo_unicode import UNICODE_EMO,EMOTICONS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'swap face with tears of joy. The feeling of making a sale smiling face with sunglasses, The feeling of actually fulfilling orders unamused face'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def emoToText(text):\n",
    "    for em in UNICODE_EMO:\n",
    "        text = text.replace(em,''.join(UNICODE_EMO[em]).replace(\"_\",\" \").replace(\":\",\"\"))\n",
    "    return text\n",
    "\n",
    "txt=\"swap 😂. The feeling of making a sale 😎, The feeling of actually fulfilling orders 😒\"\n",
    "emoToText(txt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat['Updated_msg'] = chat['msg'].apply(lambda x: emoToText(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>date</th>\n",
       "      <th>Time</th>\n",
       "      <th>user</th>\n",
       "      <th>msg</th>\n",
       "      <th>Updated_msg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>8:34 AM</td>\n",
       "      <td>Mukund Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "      <td>face with tears of joyface with tears of joyf...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>9:59 AM</td>\n",
       "      <td>Akash Coep</td>\n",
       "      <td>😂😂😂</td>\n",
       "      <td>face with tears of joyface with tears of joyf...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>11:13 AM</td>\n",
       "      <td>Amar Coep</td>\n",
       "      <td>😂😂😂😂</td>\n",
       "      <td>face with tears of joyface with tears of joyf...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>12:41 PM</td>\n",
       "      <td>Akash Coep</td>\n",
       "      <td>&lt;Media omitted&gt;</td>\n",
       "      <td>&lt;Media omitted&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9/22/19</td>\n",
       "      <td>12:41 PM</td>\n",
       "      <td>Mukund Coep</td>\n",
       "      <td>😂😂</td>\n",
       "      <td>face with tears of joyface with tears of joy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      date        Time          user               msg  \\\n",
       "1  9/22/19    8:34 AM    Mukund Coep               😂😂😂   \n",
       "4  9/22/19    9:59 AM     Akash Coep               😂😂😂   \n",
       "5  9/22/19   11:13 AM      Amar Coep              😂😂😂😂   \n",
       "6  9/22/19   12:41 PM     Akash Coep   <Media omitted>   \n",
       "7  9/22/19   12:41 PM    Mukund Coep                😂😂   \n",
       "\n",
       "                                         Updated_msg  \n",
       "1   face with tears of joyface with tears of joyf...  \n",
       "4   face with tears of joyface with tears of joyf...  \n",
       "5   face with tears of joyface with tears of joyf...  \n",
       "6                                    <Media omitted>  \n",
       "7       face with tears of joyface with tears of joy  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Chat analysis of each user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 128578 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "/root/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 128578 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,8))\n",
    "sns.countplot(y=chat['user'],orient='h')\n",
    "plt.title('Massage Sent')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dtae statistics\n",
    "date = pd.DataFrame([chat['date'].value_counts().index,chat['date'].value_counts().values],index=['Date','Time'])\n",
    "date = date.transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(y=date['Date'],x=date['Time'])\n",
    "plt.title('By Date')\n",
    "plt.xlabel('Messages')\n",
    "plt.ylabel('Date(MM/DD/YY)')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'8 AM'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat['Time'].iloc[0].split()[0][0] +' '+ chat['Time'].iloc[0].split()[1][:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat['Time'] = chat['Time'].apply(lambda x: (x.split()[0][0] +' '+ x.split()[1][:2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "Time = pd.DataFrame([chat['Time'].value_counts().index,chat['Time'].value_counts().values],index=['time','Msg'])\n",
    "Time = Time.transpose()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(y=Time['time'],x=Time['Msg'])\n",
    "plt.title('By Timing')\n",
    "plt.xlabel('Messages')\n",
    "plt.ylabel('time')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nltk.corpus import stopwords \n",
    "stop = set(stopwords.words('english'))\n",
    "def stopword(text):\n",
    "    flag=0\n",
    "    for i in text.lower().split():\n",
    "        if i in stop:\n",
    "            flag = 1\n",
    "    if flag==1:\n",
    "        return 'present'\n",
    "    else:\n",
    "        return 'absent'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "chat['Stopwords']=chat['Updated_msg'].apply(lambda x:stopword(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def non_stopword(text):\n",
    "    word=[]\n",
    "    for i in text.lower().split():\n",
    "        if i not in stop and i != ' ':\n",
    "            if len(i)<=4:\n",
    "                word.append(i)\n",
    "                break\n",
    "    return ''.join(word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "        104\n",
       "face     56\n",
       "haa       8\n",
       "bhai      7\n",
       "nhi       7\n",
       "       ... \n",
       "use       1\n",
       "mind      1\n",
       "yap       1\n",
       "site      1\n",
       "hi        1\n",
       "Name: Updated_msg, Length: 135, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat['Updated_msg'].apply(lambda x:non_stopword(x)).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "non_stop = pd.DataFrame([chat['Updated_msg'].apply(lambda x:non_stopword(x)).value_counts().index,chat['Updated_msg'].apply(lambda x:non_stopword(x)).value_counts().values],index=['words','count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "non_stop = non_stop.transpose()[1:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(y=non_stop['words'],x=non_stop['count'])\n",
    "plt.title('Most Used non-stop Words')\n",
    "plt.xlabel('Messages')\n",
    "plt.ylabel('time')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 128578 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "/root/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 128578 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "media_sent = chat[chat['Updated_msg'].apply(lambda x:str(x) in ' <Media omitted>')]['user'].value_counts()\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.pie(media_sent.values,labels=media_sent.index,autopct='%1.1f%%')\n",
    "plt.title('Media Sent')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " Ritendra🙂         35\n",
       " Akash Coep        17\n",
       " Amar Coep          9\n",
       " Atharva Coep       4\n",
       " Ashish Coep        2\n",
       " Swapnil Coep       1\n",
       " Jayesh IS COEP     1\n",
       " Pushkaraj Coep     1\n",
       " Mukund Coep        1\n",
       "Name: user, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "media_sent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "        104\n",
       "face     56\n",
       "haa       8\n",
       "bhai      7\n",
       "nhi       7\n",
       "       ... \n",
       "use       1\n",
       "mind      1\n",
       "yap       1\n",
       "site      1\n",
       "hi        1\n",
       "Name: Updated_msg, Length: 135, dtype: int64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat['Updated_msg'].apply(lambda x:non_stopword(x)).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.6.0\n"
     ]
    }
   ],
   "source": [
    "from plotly import __version__\n",
    "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
    "\n",
    "print(__version__) # requires version >= 1.9.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cufflinks as cf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For Notebooks\n",
    "init_notebook_mode(connected=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For offline use\n",
    "cf.go_offline()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": true
       },
       "data": [
        {
         "marker": {
          "color": "rgba(255, 153, 51, 0.6)",
          "line": {
           "color": "rgba(255, 153, 51, 1.0)",
           "width": 1
          }
         },
         "name": "Time",
         "orientation": "h",
         "text": "",
         "type": "bar",
         "x": [
          89,
          36,
          30,
          30,
          28,
          21,
          14,
          13,
          10,
          10,
          9,
          8,
          8,
          7,
          5,
          5,
          5,
          5,
          5,
          4,
          3,
          2,
          2,
          2,
          2,
          2,
          2,
          1,
          1,
          1,
          1
         ],
         "y": [
          "10/16/19",
          "10/29/19",
          "10/9/19",
          "10/30/19",
          "10/2/19",
          "9/22/19",
          "9/27/19",
          "9/25/19",
          "10/6/19",
          "10/11/19",
          "9/26/19",
          "10/19/19",
          "10/4/19",
          "10/15/19",
          "10/7/19",
          "11/1/19",
          "10/24/19",
          "11/4/19",
          "9/24/19",
          "10/13/19",
          "10/18/19",
          "10/26/19",
          "10/20/19",
          "10/10/19",
          "10/31/19",
          "10/17/19",
          "9/23/19",
          "10/21/19",
          "9/28/19",
          "10/14/19",
          "10/27/19"
         ]
        }
       ],
       "layout": {
        "legend": {
         "bgcolor": "#F5F6F9",
         "font": {
          "color": "#4D5663"
         }
        },
        "paper_bgcolor": "#F5F6F9",
        "plot_bgcolor": "#F5F6F9",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "title": {
         "font": {
          "color": "#4D5663"
         },
         "text": "By Date"
        },
        "xaxis": {
         "gridcolor": "#E1E5ED",
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": ""
         },
         "zerolinecolor": "#E1E5ED"
        },
        "yaxis": {
         "gridcolor": "#E1E5ED",
         "showgrid": true,
         "tickfont": {
          "color": "#4D5663"
         },
         "title": {
          "font": {
           "color": "#4D5663"
          },
          "text": ""
         },
         "zerolinecolor": "#E1E5ED"
        }
       }
      },
      "text/html": [
       "<div>\n",
       "        \n",
       "        \n",
       "            <div id=\"2d5832e5-6cb2-471f-ab17-62d321640f0f\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
       "            <script type=\"text/javascript\">\n",
       "                require([\"plotly\"], function(Plotly) {\n",
       "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
       "                    window.PLOTLYENV.BASE_URL='https://plot.ly';\n",
       "                    \n",
       "                if (document.getElementById(\"2d5832e5-6cb2-471f-ab17-62d321640f0f\")) {\n",
       "                    Plotly.newPlot(\n",
       "                        '2d5832e5-6cb2-471f-ab17-62d321640f0f',\n",
       "                        [{\"marker\": {\"color\": \"rgba(255, 153, 51, 0.6)\", \"line\": {\"color\": \"rgba(255, 153, 51, 1.0)\", \"width\": 1}}, \"name\": \"Time\", \"orientation\": \"h\", \"text\": \"\", \"type\": \"bar\", \"x\": [89, 36, 30, 30, 28, 21, 14, 13, 10, 10, 9, 8, 8, 7, 5, 5, 5, 5, 5, 4, 3, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1], \"y\": [\"10/16/19\", \"10/29/19\", \"10/9/19\", \"10/30/19\", \"10/2/19\", \"9/22/19\", \"9/27/19\", \"9/25/19\", \"10/6/19\", \"10/11/19\", \"9/26/19\", \"10/19/19\", \"10/4/19\", \"10/15/19\", \"10/7/19\", \"11/1/19\", \"10/24/19\", \"11/4/19\", \"9/24/19\", \"10/13/19\", \"10/18/19\", \"10/26/19\", \"10/20/19\", \"10/10/19\", \"10/31/19\", \"10/17/19\", \"9/23/19\", \"10/21/19\", \"9/28/19\", \"10/14/19\", \"10/27/19\"]}],\n",
       "                        {\"legend\": {\"bgcolor\": \"#F5F6F9\", \"font\": {\"color\": \"#4D5663\"}}, \"paper_bgcolor\": \"#F5F6F9\", \"plot_bgcolor\": \"#F5F6F9\", \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"By Date\"}, \"xaxis\": {\"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}, \"yaxis\": {\"gridcolor\": \"#E1E5ED\", \"showgrid\": true, \"tickfont\": {\"color\": \"#4D5663\"}, \"title\": {\"font\": {\"color\": \"#4D5663\"}, \"text\": \"\"}, \"zerolinecolor\": \"#E1E5ED\"}},\n",
       "                        {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}\n",
       "                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('2d5832e5-6cb2-471f-ab17-62d321640f0f');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })\n",
       "                };\n",
       "                });\n",
       "            </script>\n",
       "        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "date.iplot(kind='bar',y='Time',x='Date',bins=25,orientation='h',title='By Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#date.iplot(kind='bar',y='Time',x='Date',bins=25,orientation='h',title='By Date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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
}