wrangle_act.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wrangle And Analyze Data.\n",
    "\n",
    "> ## By Ashwani Singh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# WeRateDogs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    " \n",
    "-  The purpose of this project is to apply what I have Learned in Data Wrangling section from Udacity Data Analysis Nano Degree Program. \n",
    "\n",
    "> - The dataset that  will be wrangling (and analyzing and visualizing) is the tweet archive of Twitter user @dog_rates, also known as WeRateDogs. WeRateDogs is a Twitter account that rates people's dogs with a humorous comment about the dog."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Gathering Data -\n",
    "\n",
    "- The WeRateDogs Twitter archive( twitter_archive_enhanced.csv) has provided.\n",
    "- The tweet image predictions, i.e., what breed of dog (or other object, animal, etc.) is present in each tweet according to a neural network. This file (image_predictions.tsv) is hosted on Udacity's servers.\n",
    "-  URL: https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv\n",
    "- Twitter API and Python's Tweepy library to gather each tweet's retweet count and favorite (\"like\") count at minimum, and any additional data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import requests\n",
    "import os\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import tweepy\n",
    "import json\n",
    "import seaborn as sns\n",
    "from timeit import default_timer as timer\n",
    "from tweepy import OAuthHandler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2351</td>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:24:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a 1949 1st generation vulpix. Enj...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666049248...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2352</td>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:04:52 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a purebred Piers Morgan. Loves to Netf...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666044226...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2353</td>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:21:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a very happy pup. Big fan of well-main...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666033412...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2354</td>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:05:30 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a western brown Mitsubishi terrier. Up...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666029285...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2355</td>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666020888...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2356 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0     892420643555336193                    NaN                  NaN   \n",
       "1     892177421306343426                    NaN                  NaN   \n",
       "2     891815181378084864                    NaN                  NaN   \n",
       "3     891689557279858688                    NaN                  NaN   \n",
       "4     891327558926688256                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "2351  666049248165822465                    NaN                  NaN   \n",
       "2352  666044226329800704                    NaN                  NaN   \n",
       "2353  666033412701032449                    NaN                  NaN   \n",
       "2354  666029285002620928                    NaN                  NaN   \n",
       "2355  666020888022790149                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "0     2017-08-01 16:23:56 +0000   \n",
       "1     2017-08-01 00:17:27 +0000   \n",
       "2     2017-07-31 00:18:03 +0000   \n",
       "3     2017-07-30 15:58:51 +0000   \n",
       "4     2017-07-29 16:00:24 +0000   \n",
       "...                         ...   \n",
       "2351  2015-11-16 00:24:50 +0000   \n",
       "2352  2015-11-16 00:04:52 +0000   \n",
       "2353  2015-11-15 23:21:54 +0000   \n",
       "2354  2015-11-15 23:05:30 +0000   \n",
       "2355  2015-11-15 22:32:08 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2351  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2352  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2353  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2354  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "0     This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1     This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2     This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3     This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4     This is Franklin. He would like you to stop ca...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2351  Here we have a 1949 1st generation vulpix. Enj...                  NaN   \n",
       "2352  This is a purebred Piers Morgan. Loves to Netf...                  NaN   \n",
       "2353  Here is a very happy pup. Big fan of well-main...                  NaN   \n",
       "2354  This is a western brown Mitsubishi terrier. Up...                  NaN   \n",
       "2355  Here we have a Japanese Irish Setter. Lost eye...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                          NaN                        NaN   \n",
       "1                          NaN                        NaN   \n",
       "2                          NaN                        NaN   \n",
       "3                          NaN                        NaN   \n",
       "4                          NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2351                       NaN                        NaN   \n",
       "2352                       NaN                        NaN   \n",
       "2353                       NaN                        NaN   \n",
       "2354                       NaN                        NaN   \n",
       "2355                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "0     https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1     https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2     https://twitter.com/dog_rates/status/891815181...                12   \n",
       "3     https://twitter.com/dog_rates/status/891689557...                13   \n",
       "4     https://twitter.com/dog_rates/status/891327558...                12   \n",
       "...                                                 ...               ...   \n",
       "2351  https://twitter.com/dog_rates/status/666049248...                 5   \n",
       "2352  https://twitter.com/dog_rates/status/666044226...                 6   \n",
       "2353  https://twitter.com/dog_rates/status/666033412...                 9   \n",
       "2354  https://twitter.com/dog_rates/status/666029285...                 7   \n",
       "2355  https://twitter.com/dog_rates/status/666020888...                 8   \n",
       "\n",
       "      rating_denominator      name doggo floofer pupper puppo  \n",
       "0                     10   Phineas  None    None   None  None  \n",
       "1                     10     Tilly  None    None   None  None  \n",
       "2                     10    Archie  None    None   None  None  \n",
       "3                     10     Darla  None    None   None  None  \n",
       "4                     10  Franklin  None    None   None  None  \n",
       "...                  ...       ...   ...     ...    ...   ...  \n",
       "2351                  10      None  None    None   None  None  \n",
       "2352                  10         a  None    None   None  None  \n",
       "2353                  10         a  None    None   None  None  \n",
       "2354                  10         a  None    None   None  None  \n",
       "2355                  10      None  None    None   None  None  \n",
       "\n",
       "[2356 rows x 17 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive = pd.read_csv(\"twitter-archive-enhanced.csv\")\n",
    "\n",
    "twitter_archive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      "tweet_id                      2356 non-null int64\n",
      "in_reply_to_status_id         78 non-null float64\n",
      "in_reply_to_user_id           78 non-null float64\n",
      "timestamp                     2356 non-null object\n",
      "source                        2356 non-null object\n",
      "text                          2356 non-null object\n",
      "retweeted_status_id           181 non-null float64\n",
      "retweeted_status_user_id      181 non-null float64\n",
      "retweeted_status_timestamp    181 non-null object\n",
      "expanded_urls                 2297 non-null object\n",
      "rating_numerator              2356 non-null int64\n",
      "rating_denominator            2356 non-null int64\n",
      "name                          2356 non-null object\n",
      "doggo                         2356 non-null object\n",
      "floofer                       2356 non-null object\n",
      "pupper                        2356 non-null object\n",
      "puppo                         2356 non-null object\n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "twitter_archive.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# request for image\n",
    "\n",
    "url = 'https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv'\n",
    "\n",
    "image_requests = requests.get(url, allow_redirects=True)\n",
    "\n",
    "open('image_predictions.tsv', 'wb').write(image_requests.content)\n",
    "\n",
    "images = pd.read_csv('image_predictions.tsv', sep = '\\t')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Twiter Api\n",
    "\n",
    "consumer_key = \"XXXX\"\n",
    "consumer_secret = \"XXXX\"\n",
    "access_token = \"XXXX-XXXX\"\n",
    "access_secret = \"XXXX\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "auth = OAuthHandler(consumer_key, consumer_secret)\n",
    "auth.set_access_token(access_token, access_secret)\n",
    "\n",
    "api = tweepy.API(auth, parser=tweepy.parsers.JSONParser())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2356"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_ids = twitter_archive.tweet_id.values\n",
    "len(tweet_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "888202515573088257\n",
      "873697596434513921\n",
      "872668790621863937\n",
      "872261713294495745\n",
      "869988702071779329\n",
      "866816280283807744\n",
      "861769973181624320\n",
      "856602993587888130\n",
      "851953902622658560\n",
      "845459076796616705\n",
      "844704788403113984\n",
      "842892208864923648\n",
      "837366284874571778\n",
      "837012587749474308\n",
      "829374341691346946\n",
      "827228250799742977\n",
      "812747805718642688\n",
      "802247111496568832\n",
      "793271401113350145\n",
      "779123168116150273\n",
      "775096608509886464\n",
      "771004394259247104\n",
      "770743923962707968\n",
      "759566828574212096\n",
      "754011816964026368\n",
      "704499785726889984\n",
      "680055455951884288\n",
      "3231.9880442619324\n"
     ]
    }
   ],
   "source": [
    "# this starts the timer\n",
    "start = time.time()\n",
    "\n",
    "tweet_ids = twitter_archive.tweet_id.values\n",
    "\n",
    "tweets_data = []\n",
    "tweet_success = []\n",
    "tweet_failure = []\n",
    "\n",
    "for tweet_id in tweet_ids:\n",
    "        try:\n",
    "            data = api.get_status(tweet_id, tweet_mode='extended', \n",
    "                                  wait_on_rate_limit = True, \n",
    "                                  wait_on_rate_limit_notify = True)\n",
    "            tweets_data.append(data)\n",
    "            tweet_success.append(tweet_id)\n",
    "        except:\n",
    "            tweet_failure.append(tweet_id)\n",
    "            print(tweet_id)\n",
    "\n",
    "# this stops the timer            \n",
    "end = time.time()\n",
    "\n",
    "print(end - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('tweet_json.txt', mode = 'w') as file:\n",
    "    json.dump(tweets_data, file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# Loading the Twitter API data\n",
    "twitter_counts_df = pd.read_json('tweet_json.txt')\n",
    "twitter_counts_df['tweet_id'] = tweet_success\n",
    "twitter_counts_df = twitter_counts_df[['tweet_id', 'favorite_count', 'retweet_count']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>tweet_id</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>36239</td>\n",
       "      <td>7712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>31249</td>\n",
       "      <td>5699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>23530</td>\n",
       "      <td>3778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>39521</td>\n",
       "      <td>7868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>37724</td>\n",
       "      <td>8485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  favorite_count  retweet_count\n",
       "0  892420643555336193           36239           7712\n",
       "1  892177421306343426           31249           5699\n",
       "2  891815181378084864           23530           3778\n",
       "3  891689557279858688           39521           7868\n",
       "4  891327558926688256           37724           8485"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_counts_df.head()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Assesing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## for twitter_archive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2351</td>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:24:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a 1949 1st generation vulpix. Enj...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666049248...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2352</td>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:04:52 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a purebred Piers Morgan. Loves to Netf...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666044226...</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2353</td>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:21:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a very happy pup. Big fan of well-main...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666033412...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2354</td>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 23:05:30 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a western brown Mitsubishi terrier. Up...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666029285...</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>a</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2355</td>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-15 22:32:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a Japanese Irish Setter. Lost eye...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666020888...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2356 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0     892420643555336193                    NaN                  NaN   \n",
       "1     892177421306343426                    NaN                  NaN   \n",
       "2     891815181378084864                    NaN                  NaN   \n",
       "3     891689557279858688                    NaN                  NaN   \n",
       "4     891327558926688256                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "2351  666049248165822465                    NaN                  NaN   \n",
       "2352  666044226329800704                    NaN                  NaN   \n",
       "2353  666033412701032449                    NaN                  NaN   \n",
       "2354  666029285002620928                    NaN                  NaN   \n",
       "2355  666020888022790149                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "0     2017-08-01 16:23:56 +0000   \n",
       "1     2017-08-01 00:17:27 +0000   \n",
       "2     2017-07-31 00:18:03 +0000   \n",
       "3     2017-07-30 15:58:51 +0000   \n",
       "4     2017-07-29 16:00:24 +0000   \n",
       "...                         ...   \n",
       "2351  2015-11-16 00:24:50 +0000   \n",
       "2352  2015-11-16 00:04:52 +0000   \n",
       "2353  2015-11-15 23:21:54 +0000   \n",
       "2354  2015-11-15 23:05:30 +0000   \n",
       "2355  2015-11-15 22:32:08 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2351  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2352  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2353  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2354  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2355  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "0     This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1     This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2     This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3     This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4     This is Franklin. He would like you to stop ca...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2351  Here we have a 1949 1st generation vulpix. Enj...                  NaN   \n",
       "2352  This is a purebred Piers Morgan. Loves to Netf...                  NaN   \n",
       "2353  Here is a very happy pup. Big fan of well-main...                  NaN   \n",
       "2354  This is a western brown Mitsubishi terrier. Up...                  NaN   \n",
       "2355  Here we have a Japanese Irish Setter. Lost eye...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                          NaN                        NaN   \n",
       "1                          NaN                        NaN   \n",
       "2                          NaN                        NaN   \n",
       "3                          NaN                        NaN   \n",
       "4                          NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2351                       NaN                        NaN   \n",
       "2352                       NaN                        NaN   \n",
       "2353                       NaN                        NaN   \n",
       "2354                       NaN                        NaN   \n",
       "2355                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "0     https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1     https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2     https://twitter.com/dog_rates/status/891815181...                12   \n",
       "3     https://twitter.com/dog_rates/status/891689557...                13   \n",
       "4     https://twitter.com/dog_rates/status/891327558...                12   \n",
       "...                                                 ...               ...   \n",
       "2351  https://twitter.com/dog_rates/status/666049248...                 5   \n",
       "2352  https://twitter.com/dog_rates/status/666044226...                 6   \n",
       "2353  https://twitter.com/dog_rates/status/666033412...                 9   \n",
       "2354  https://twitter.com/dog_rates/status/666029285...                 7   \n",
       "2355  https://twitter.com/dog_rates/status/666020888...                 8   \n",
       "\n",
       "      rating_denominator      name doggo floofer pupper puppo  \n",
       "0                     10   Phineas  None    None   None  None  \n",
       "1                     10     Tilly  None    None   None  None  \n",
       "2                     10    Archie  None    None   None  None  \n",
       "3                     10     Darla  None    None   None  None  \n",
       "4                     10  Franklin  None    None   None  None  \n",
       "...                  ...       ...   ...     ...    ...   ...  \n",
       "2351                  10      None  None    None   None  None  \n",
       "2352                  10         a  None    None   None  None  \n",
       "2353                  10         a  None    None   None  None  \n",
       "2354                  10         a  None    None   None  None  \n",
       "2355                  10      None  None    None   None  None  \n",
       "\n",
       "[2356 rows x 17 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  twitter_archive \n",
    "\n",
    "twitter_archive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0  892420643555336193                    NaN                  NaN   \n",
       "1  892177421306343426                    NaN                  NaN   \n",
       "2  891815181378084864                    NaN                  NaN   \n",
       "3  891689557279858688                    NaN                  NaN   \n",
       "4  891327558926688256                    NaN                  NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56 +0000   \n",
       "1  2017-08-01 00:17:27 +0000   \n",
       "2  2017-07-31 00:18:03 +0000   \n",
       "3  2017-07-30 15:58:51 +0000   \n",
       "4  2017-07-29 16:00:24 +0000   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text  retweeted_status_id  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1  This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3  This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4  This is Franklin. He would like you to stop ca...                  NaN   \n",
       "\n",
       "   retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                       NaN                        NaN   \n",
       "1                       NaN                        NaN   \n",
       "2                       NaN                        NaN   \n",
       "3                       NaN                        NaN   \n",
       "4                       NaN                        NaN   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1  https://twitter.com/dog_rates/status/892177421...                13   \n",
       "2  https://twitter.com/dog_rates/status/891815181...                12   \n",
       "3  https://twitter.com/dog_rates/status/891689557...                13   \n",
       "4  https://twitter.com/dog_rates/status/891327558...                12   \n",
       "\n",
       "   rating_denominator      name doggo floofer pupper puppo  \n",
       "0                  10   Phineas  None    None   None  None  \n",
       "1                  10     Tilly  None    None   None  None  \n",
       "2                  10    Archie  None    None   None  None  \n",
       "3                  10     Darla  None    None   None  None  \n",
       "4                  10  Franklin  None    None   None  None  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# twitter_archive.head()\n",
    "\n",
    "twitter_archive.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2356 entries, 0 to 2355\n",
      "Data columns (total 17 columns):\n",
      "tweet_id                      2356 non-null int64\n",
      "in_reply_to_status_id         78 non-null float64\n",
      "in_reply_to_user_id           78 non-null float64\n",
      "timestamp                     2356 non-null object\n",
      "source                        2356 non-null object\n",
      "text                          2356 non-null object\n",
      "retweeted_status_id           181 non-null float64\n",
      "retweeted_status_user_id      181 non-null float64\n",
      "retweeted_status_timestamp    181 non-null object\n",
      "expanded_urls                 2297 non-null object\n",
      "rating_numerator              2356 non-null int64\n",
      "rating_denominator            2356 non-null int64\n",
      "name                          2356 non-null object\n",
      "doggo                         2356 non-null object\n",
      "floofer                       2356 non-null object\n",
      "pupper                        2356 non-null object\n",
      "puppo                         2356 non-null object\n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# twitter_archive.info()\n",
    "\n",
    "twitter_archive.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>2.356000e+03</td>\n",
       "      <td>7.800000e+01</td>\n",
       "      <td>7.800000e+01</td>\n",
       "      <td>1.810000e+02</td>\n",
       "      <td>1.810000e+02</td>\n",
       "      <td>2356.000000</td>\n",
       "      <td>2356.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>7.427716e+17</td>\n",
       "      <td>7.455079e+17</td>\n",
       "      <td>2.014171e+16</td>\n",
       "      <td>7.720400e+17</td>\n",
       "      <td>1.241698e+16</td>\n",
       "      <td>13.126486</td>\n",
       "      <td>10.455433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>6.856705e+16</td>\n",
       "      <td>7.582492e+16</td>\n",
       "      <td>1.252797e+17</td>\n",
       "      <td>6.236928e+16</td>\n",
       "      <td>9.599254e+16</td>\n",
       "      <td>45.876648</td>\n",
       "      <td>6.745237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>6.658147e+17</td>\n",
       "      <td>1.185634e+07</td>\n",
       "      <td>6.661041e+17</td>\n",
       "      <td>7.832140e+05</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>6.783989e+17</td>\n",
       "      <td>6.757419e+17</td>\n",
       "      <td>3.086374e+08</td>\n",
       "      <td>7.186315e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>7.196279e+17</td>\n",
       "      <td>7.038708e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>7.804657e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>7.993373e+17</td>\n",
       "      <td>8.257804e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>8.203146e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>10.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>8.405479e+17</td>\n",
       "      <td>8.874740e+17</td>\n",
       "      <td>7.874618e+17</td>\n",
       "      <td>1776.000000</td>\n",
       "      <td>170.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "count  2.356000e+03           7.800000e+01         7.800000e+01   \n",
       "mean   7.427716e+17           7.455079e+17         2.014171e+16   \n",
       "std    6.856705e+16           7.582492e+16         1.252797e+17   \n",
       "min    6.660209e+17           6.658147e+17         1.185634e+07   \n",
       "25%    6.783989e+17           6.757419e+17         3.086374e+08   \n",
       "50%    7.196279e+17           7.038708e+17         4.196984e+09   \n",
       "75%    7.993373e+17           8.257804e+17         4.196984e+09   \n",
       "max    8.924206e+17           8.862664e+17         8.405479e+17   \n",
       "\n",
       "       retweeted_status_id  retweeted_status_user_id  rating_numerator  \\\n",
       "count         1.810000e+02              1.810000e+02       2356.000000   \n",
       "mean          7.720400e+17              1.241698e+16         13.126486   \n",
       "std           6.236928e+16              9.599254e+16         45.876648   \n",
       "min           6.661041e+17              7.832140e+05          0.000000   \n",
       "25%           7.186315e+17              4.196984e+09         10.000000   \n",
       "50%           7.804657e+17              4.196984e+09         11.000000   \n",
       "75%           8.203146e+17              4.196984e+09         12.000000   \n",
       "max           8.874740e+17              7.874618e+17       1776.000000   \n",
       "\n",
       "       rating_denominator  \n",
       "count         2356.000000  \n",
       "mean            10.455433  \n",
       "std              6.745237  \n",
       "min              0.000000  \n",
       "25%             10.000000  \n",
       "50%             10.000000  \n",
       "75%             10.000000  \n",
       "max            170.000000  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# twitter_archive.describe()\n",
    "\n",
    "twitter_archive.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12      558\n",
       "11      464\n",
       "10      461\n",
       "13      351\n",
       "9       158\n",
       "8       102\n",
       "7        55\n",
       "14       54\n",
       "5        37\n",
       "6        32\n",
       "3        19\n",
       "4        17\n",
       "1         9\n",
       "2         9\n",
       "420       2\n",
       "0         2\n",
       "15        2\n",
       "75        2\n",
       "80        1\n",
       "20        1\n",
       "24        1\n",
       "26        1\n",
       "44        1\n",
       "50        1\n",
       "60        1\n",
       "165       1\n",
       "84        1\n",
       "88        1\n",
       "144       1\n",
       "182       1\n",
       "143       1\n",
       "666       1\n",
       "960       1\n",
       "1776      1\n",
       "17        1\n",
       "27        1\n",
       "45        1\n",
       "99        1\n",
       "121       1\n",
       "204       1\n",
       "Name: rating_numerator, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive.rating_numerator.value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numerator rating value are : 40\n"
     ]
    }
   ],
   "source": [
    "print(\"numerator rating value are :\",len(twitter_archive.rating_numerator.value_counts()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10     2333\n",
       "11        3\n",
       "50        3\n",
       "80        2\n",
       "20        2\n",
       "2         1\n",
       "16        1\n",
       "40        1\n",
       "70        1\n",
       "15        1\n",
       "90        1\n",
       "110       1\n",
       "120       1\n",
       "130       1\n",
       "150       1\n",
       "170       1\n",
       "7         1\n",
       "0         1\n",
       "Name: rating_denominator, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive.rating_denominator.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "denominator rating are : 18\n"
     ]
    }
   ],
   "source": [
    "print(\"denominator rating are :\",len(twitter_archive.rating_denominator.value_counts()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None        745\n",
       "a            55\n",
       "Charlie      12\n",
       "Oliver       11\n",
       "Cooper       11\n",
       "           ... \n",
       "Pubert        1\n",
       "Bertson       1\n",
       "Colin         1\n",
       "Jessifer      1\n",
       "Cheryl        1\n",
       "Name: name, Length: 957, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name value are :  957\n"
     ]
    }
   ],
   "source": [
    "print(\"name value are : \",len(twitter_archive.name.value_counts()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>     2221\n",
       "<a href=\"http://vine.co\" rel=\"nofollow\">Vine - Make a Scene</a>                          91\n",
       "<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>                       33\n",
       "<a href=\"https://about.twitter.com/products/tweetdeck\" rel=\"nofollow\">TweetDeck</a>      11\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_archive.source.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "source value are : 4\n"
     ]
    }
   ],
   "source": [
    "print(\"source value are :\",len(twitter_archive.source.value_counts()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## for images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>tweet_id</th>\n",
       "      <th>jpg_url</th>\n",
       "      <th>img_num</th>\n",
       "      <th>p1</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Welsh_springer_spaniel</td>\n",
       "      <td>0.465074</td>\n",
       "      <td>True</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.156665</td>\n",
       "      <td>True</td>\n",
       "      <td>Shetland_sheepdog</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.506826</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.074192</td>\n",
       "      <td>True</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>German_shepherd</td>\n",
       "      <td>0.596461</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.138584</td>\n",
       "      <td>True</td>\n",
       "      <td>bloodhound</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Rhodesian_ridgeback</td>\n",
       "      <td>0.408143</td>\n",
       "      <td>True</td>\n",
       "      <td>redbone</td>\n",
       "      <td>0.360687</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.560311</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.243682</td>\n",
       "      <td>True</td>\n",
       "      <td>Doberman</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                                          jpg_url  \\\n",
       "0  666020888022790149  https://pbs.twimg.com/media/CT4udn0WwAA0aMy.jpg   \n",
       "1  666029285002620928  https://pbs.twimg.com/media/CT42GRgUYAA5iDo.jpg   \n",
       "2  666033412701032449  https://pbs.twimg.com/media/CT4521TWwAEvMyu.jpg   \n",
       "3  666044226329800704  https://pbs.twimg.com/media/CT5Dr8HUEAA-lEu.jpg   \n",
       "4  666049248165822465  https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "\n",
       "   img_num                      p1   p1_conf  p1_dog                  p2  \\\n",
       "0        1  Welsh_springer_spaniel  0.465074    True              collie   \n",
       "1        1                 redbone  0.506826    True  miniature_pinscher   \n",
       "2        1         German_shepherd  0.596461    True            malinois   \n",
       "3        1     Rhodesian_ridgeback  0.408143    True             redbone   \n",
       "4        1      miniature_pinscher  0.560311    True          Rottweiler   \n",
       "\n",
       "    p2_conf  p2_dog                   p3   p3_conf  p3_dog  \n",
       "0  0.156665    True    Shetland_sheepdog  0.061428    True  \n",
       "1  0.074192    True  Rhodesian_ridgeback  0.072010    True  \n",
       "2  0.138584    True           bloodhound  0.116197    True  \n",
       "3  0.360687    True   miniature_pinscher  0.222752    True  \n",
       "4  0.243682    True             Doberman  0.154629    True  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "https://pbs.twimg.com/media/CvJCabcWgAIoUxW.jpg    2\n",
       "https://pbs.twimg.com/media/C3nygbBWQAAjwcW.jpg    2\n",
       "https://pbs.twimg.com/media/CsrjryzWgAAZY00.jpg    2\n",
       "https://pbs.twimg.com/media/CZhn-QAWwAASQan.jpg    2\n",
       "https://pbs.twimg.com/media/CsGnz64WYAEIDHJ.jpg    2\n",
       "                                                  ..\n",
       "https://pbs.twimg.com/media/CU8tOJZWUAAlNoF.jpg    1\n",
       "https://pbs.twimg.com/media/CVg6L2hWIAAYuEb.jpg    1\n",
       "https://pbs.twimg.com/media/CUTdvAJXIAAMS4q.jpg    1\n",
       "https://pbs.twimg.com/media/Cj6O1G9UYAAIU-1.jpg    1\n",
       "https://pbs.twimg.com/media/CVgbIobUYAEaeI3.jpg    1\n",
       "Name: jpg_url, Length: 2009, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.jpg_url.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "images url are :  2009\n"
     ]
    }
   ],
   "source": [
    "print(\"images url are : \",len(images.jpg_url.value_counts()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://pbs.twimg.com/media/CsGnz64WYAEIDHJ.jpg\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# importing image python\n",
    "\n",
    "from IPython.display import Image\n",
    "\n",
    "Image(url= \"https://pbs.twimg.com/media/CsGnz64WYAEIDHJ.jpg\" )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1532\n",
       "False     543\n",
       "Name: p1_dog, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.p1_dog.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     1553\n",
       "False     522\n",
       "Name: p2_dog, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.p2_dog.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "golden_retriever      150\n",
       "Labrador_retriever    100\n",
       "Pembroke               89\n",
       "Chihuahua              83\n",
       "pug                    57\n",
       "                     ... \n",
       "hammer                  1\n",
       "minibus                 1\n",
       "clumber                 1\n",
       "mailbox                 1\n",
       "cougar                  1\n",
       "Name: p1, Length: 378, dtype: int64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.p1.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p1 value are : 378\n"
     ]
    }
   ],
   "source": [
    "print(\"p1 value are :\",len(images.p1.value_counts()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Labrador_retriever    104\n",
       "golden_retriever       92\n",
       "Cardigan               73\n",
       "Chihuahua              44\n",
       "Pomeranian             42\n",
       "                     ... \n",
       "computer_keyboard       1\n",
       "triceratops             1\n",
       "rifle                   1\n",
       "brown_bear              1\n",
       "cougar                  1\n",
       "Name: p2, Length: 405, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "images.p2.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p2 value are : 405\n"
     ]
    }
   ],
   "source": [
    "print(\"p2 value are :\",len(images.p2.value_counts()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## for twitter_counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>tweet_id</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>36239</td>\n",
       "      <td>7712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>31249</td>\n",
       "      <td>5699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>23530</td>\n",
       "      <td>3778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>39521</td>\n",
       "      <td>7868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>37724</td>\n",
       "      <td>8485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2324</td>\n",
       "      <td>666049248165822465</td>\n",
       "      <td>96</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2325</td>\n",
       "      <td>666044226329800704</td>\n",
       "      <td>273</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2326</td>\n",
       "      <td>666033412701032449</td>\n",
       "      <td>112</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2327</td>\n",
       "      <td>666029285002620928</td>\n",
       "      <td>121</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2328</td>\n",
       "      <td>666020888022790149</td>\n",
       "      <td>2413</td>\n",
       "      <td>462</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2329 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  favorite_count  retweet_count\n",
       "0     892420643555336193           36239           7712\n",
       "1     892177421306343426           31249           5699\n",
       "2     891815181378084864           23530           3778\n",
       "3     891689557279858688           39521           7868\n",
       "4     891327558926688256           37724           8485\n",
       "...                  ...             ...            ...\n",
       "2324  666049248165822465              96             39\n",
       "2325  666044226329800704             273            132\n",
       "2326  666033412701032449             112             41\n",
       "2327  666029285002620928             121             42\n",
       "2328  666020888022790149            2413            462\n",
       "\n",
       "[2329 rows x 3 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_counts_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>tweet_id</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>36239</td>\n",
       "      <td>7712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>31249</td>\n",
       "      <td>5699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>23530</td>\n",
       "      <td>3778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>39521</td>\n",
       "      <td>7868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>37724</td>\n",
       "      <td>8485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  favorite_count  retweet_count\n",
       "0  892420643555336193           36239           7712\n",
       "1  892177421306343426           31249           5699\n",
       "2  891815181378084864           23530           3778\n",
       "3  891689557279858688           39521           7868\n",
       "4  891327558926688256           37724           8485"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_counts_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2329 entries, 0 to 2328\n",
      "Data columns (total 3 columns):\n",
      "tweet_id          2329 non-null int64\n",
      "favorite_count    2329 non-null int64\n",
      "retweet_count     2329 non-null int64\n",
      "dtypes: int64(3)\n",
      "memory usage: 54.7 KB\n"
     ]
    }
   ],
   "source": [
    "twitter_counts_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>tweet_id</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>2.329000e+03</td>\n",
       "      <td>2329.000000</td>\n",
       "      <td>2329.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>7.419019e+17</td>\n",
       "      <td>7566.601546</td>\n",
       "      <td>2706.563332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>6.824830e+16</td>\n",
       "      <td>11746.215613</td>\n",
       "      <td>4577.102475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>6.660209e+17</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>6.782555e+17</td>\n",
       "      <td>1316.000000</td>\n",
       "      <td>548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>7.182469e+17</td>\n",
       "      <td>3289.000000</td>\n",
       "      <td>1268.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>7.986731e+17</td>\n",
       "      <td>9261.000000</td>\n",
       "      <td>3150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>8.924206e+17</td>\n",
       "      <td>156287.000000</td>\n",
       "      <td>77861.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           tweet_id  favorite_count  retweet_count\n",
       "count  2.329000e+03     2329.000000    2329.000000\n",
       "mean   7.419019e+17     7566.601546    2706.563332\n",
       "std    6.824830e+16    11746.215613    4577.102475\n",
       "min    6.660209e+17        0.000000       1.000000\n",
       "25%    6.782555e+17     1316.000000     548.000000\n",
       "50%    7.182469e+17     3289.000000    1268.000000\n",
       "75%    7.986731e+17     9261.000000    3150.000000\n",
       "max    8.924206e+17   156287.000000   77861.000000"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitter_counts_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now make a copy of each dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "twitter_archive_copy = twitter_archive.copy()\n",
    "images_copy = images.copy()\n",
    "twitter_counts_df_copy = twitter_counts_df.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# cleaning data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ol>\n",
    "    <li>Merge the clean version of twitter_archive, images, twitter_counts_df into a DataFrame.</li>\n",
    "    <li>Create a column for various dog type.</li>\n",
    "    <li>Delete Retweets.</li>\n",
    "    <li>Remove the column no longer uses.</li>\n",
    "    <li>Change tweet_id from integer to a String.</li>\n",
    "    <li>Change the timestamp to correct datetime format.</li>\n",
    "    <li>Correct the naming issue.</li>\n",
    "    <li>Standardize the Dog ratings.</li>\n",
    "    <li>Create new dog_breed column using the image prediction.</li>\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Merge the clean version of twitter_archive, images, twitter_counts_df into a DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "store = [twitter_archive_copy, images_copy, twitter_counts_df_copy]\n",
    "tweet_datas = pd.concat(store, sort=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0  892420643555336193                    NaN                  NaN   \n",
       "1  892177421306343426                    NaN                  NaN   \n",
       "2  891815181378084864                    NaN                  NaN   \n",
       "3  891689557279858688                    NaN                  NaN   \n",
       "4  891327558926688256                    NaN                  NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56 +0000   \n",
       "1  2017-08-01 00:17:27 +0000   \n",
       "2  2017-07-31 00:18:03 +0000   \n",
       "3  2017-07-30 15:58:51 +0000   \n",
       "4  2017-07-29 16:00:24 +0000   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text  retweeted_status_id  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1  This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3  This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4  This is Franklin. He would like you to stop ca...                  NaN   \n",
       "\n",
       "   retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                       NaN                        NaN   \n",
       "1                       NaN                        NaN   \n",
       "2                       NaN                        NaN   \n",
       "3                       NaN                        NaN   \n",
       "4                       NaN                        NaN   \n",
       "\n",
       "                                       expanded_urls  ...  p1_conf  p1_dog  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...  ...      NaN     NaN   \n",
       "1  https://twitter.com/dog_rates/status/892177421...  ...      NaN     NaN   \n",
       "2  https://twitter.com/dog_rates/status/891815181...  ...      NaN     NaN   \n",
       "3  https://twitter.com/dog_rates/status/891689557...  ...      NaN     NaN   \n",
       "4  https://twitter.com/dog_rates/status/891327558...  ...      NaN     NaN   \n",
       "\n",
       "    p2 p2_conf p2_dog   p3 p3_conf p3_dog  favorite_count retweet_count  \n",
       "0  NaN     NaN    NaN  NaN     NaN    NaN             NaN           NaN  \n",
       "1  NaN     NaN    NaN  NaN     NaN    NaN             NaN           NaN  \n",
       "2  NaN     NaN    NaN  NaN     NaN    NaN             NaN           NaN  \n",
       "3  NaN     NaN    NaN  NaN     NaN    NaN             NaN           NaN  \n",
       "4  NaN     NaN    NaN  NaN     NaN    NaN             NaN           NaN  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6760 entries, 0 to 2328\n",
      "Data columns (total 30 columns):\n",
      "tweet_id                      6760 non-null int64\n",
      "in_reply_to_status_id         78 non-null float64\n",
      "in_reply_to_user_id           78 non-null float64\n",
      "timestamp                     2356 non-null object\n",
      "source                        2356 non-null object\n",
      "text                          2356 non-null object\n",
      "retweeted_status_id           181 non-null float64\n",
      "retweeted_status_user_id      181 non-null float64\n",
      "retweeted_status_timestamp    181 non-null object\n",
      "expanded_urls                 2297 non-null object\n",
      "rating_numerator              2356 non-null float64\n",
      "rating_denominator            2356 non-null float64\n",
      "name                          2356 non-null object\n",
      "doggo                         2356 non-null object\n",
      "floofer                       2356 non-null object\n",
      "pupper                        2356 non-null object\n",
      "puppo                         2356 non-null object\n",
      "jpg_url                       2075 non-null object\n",
      "img_num                       2075 non-null float64\n",
      "p1                            2075 non-null object\n",
      "p1_conf                       2075 non-null float64\n",
      "p1_dog                        2075 non-null object\n",
      "p2                            2075 non-null object\n",
      "p2_conf                       2075 non-null float64\n",
      "p2_dog                        2075 non-null object\n",
      "p3                            2075 non-null object\n",
      "p3_conf                       2075 non-null float64\n",
      "p3_dog                        2075 non-null object\n",
      "favorite_count                2329 non-null float64\n",
      "retweet_count                 2329 non-null float64\n",
      "dtypes: float64(12), int64(1), object(17)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Create a column for various dog type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas['dog_type'] = tweet_datas['text'].str.extract('(doggo|floofer|pupper|puppo)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dog_type</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>200</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <td>884</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1643</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>717</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <td>2320</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <td>243</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <td>1084</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>764</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>364</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1676</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     dog_type doggo floofer pupper puppo\n",
       "200       NaN   NaN     NaN    NaN   NaN\n",
       "884       NaN   NaN     NaN    NaN   NaN\n",
       "1643   pupper  None    None   None  None\n",
       "717       NaN  None    None   None  None\n",
       "2320      NaN  None    None   None  None\n",
       "243       NaN  None    None   None  None\n",
       "1084      NaN  None    None   None  None\n",
       "764       NaN   NaN     NaN    NaN   NaN\n",
       "364       NaN  None    None   None  None\n",
       "1676      NaN  None    None   None  None"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas[['dog_type', 'doggo', 'floofer', 'pupper', 'puppo']].sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>dog_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0  892420643555336193                    NaN                  NaN   \n",
       "1  892177421306343426                    NaN                  NaN   \n",
       "2  891815181378084864                    NaN                  NaN   \n",
       "3  891689557279858688                    NaN                  NaN   \n",
       "4  891327558926688256                    NaN                  NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56 +0000   \n",
       "1  2017-08-01 00:17:27 +0000   \n",
       "2  2017-07-31 00:18:03 +0000   \n",
       "3  2017-07-30 15:58:51 +0000   \n",
       "4  2017-07-29 16:00:24 +0000   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text  retweeted_status_id  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1  This is Tilly. She's just checking pup on you....                  NaN   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...                  NaN   \n",
       "3  This is Darla. She commenced a snooze mid meal...                  NaN   \n",
       "4  This is Franklin. He would like you to stop ca...                  NaN   \n",
       "\n",
       "   retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                       NaN                        NaN   \n",
       "1                       NaN                        NaN   \n",
       "2                       NaN                        NaN   \n",
       "3                       NaN                        NaN   \n",
       "4                       NaN                        NaN   \n",
       "\n",
       "                                       expanded_urls  ...  p1_dog   p2  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...  ...     NaN  NaN   \n",
       "1  https://twitter.com/dog_rates/status/892177421...  ...     NaN  NaN   \n",
       "2  https://twitter.com/dog_rates/status/891815181...  ...     NaN  NaN   \n",
       "3  https://twitter.com/dog_rates/status/891689557...  ...     NaN  NaN   \n",
       "4  https://twitter.com/dog_rates/status/891327558...  ...     NaN  NaN   \n",
       "\n",
       "  p2_conf p2_dog   p3 p3_conf p3_dog favorite_count  retweet_count dog_type  \n",
       "0     NaN    NaN  NaN     NaN    NaN            NaN            NaN      NaN  \n",
       "1     NaN    NaN  NaN     NaN    NaN            NaN            NaN      NaN  \n",
       "2     NaN    NaN  NaN     NaN    NaN            NaN            NaN      NaN  \n",
       "3     NaN    NaN  NaN     NaN    NaN            NaN            NaN      NaN  \n",
       "4     NaN    NaN  NaN     NaN    NaN            NaN            NaN      NaN  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>dog_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>191</td>\n",
       "      <td>855851453814013952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-22 18:31:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo participating in the #ScienceMa...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/855851453...</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1919</td>\n",
       "      <td>855851453814013952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.115138</td>\n",
       "      <td>True</td>\n",
       "      <td>groenendael</td>\n",
       "      <td>0.0961</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>183</td>\n",
       "      <td>855851453814013952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44443.0</td>\n",
       "      <td>17363.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "191   855851453814013952                    NaN                  NaN   \n",
       "1919  855851453814013952                    NaN                  NaN   \n",
       "183   855851453814013952                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "191   2017-04-22 18:31:02 +0000   \n",
       "1919                        NaN   \n",
       "183                         NaN   \n",
       "\n",
       "                                                 source  \\\n",
       "191   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1919                                                NaN   \n",
       "183                                                 NaN   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "191   Here's a puppo participating in the #ScienceMa...                  NaN   \n",
       "1919                                                NaN                  NaN   \n",
       "183                                                 NaN                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "191                        NaN                        NaN   \n",
       "1919                       NaN                        NaN   \n",
       "183                        NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  ...  p1_dog  \\\n",
       "191   https://twitter.com/dog_rates/status/855851453...  ...     NaN   \n",
       "1919                                                NaN  ...    True   \n",
       "183                                                 NaN  ...     NaN   \n",
       "\n",
       "                      p2   p2_conf p2_dog           p3 p3_conf p3_dog  \\\n",
       "191                  NaN       NaN    NaN          NaN     NaN    NaN   \n",
       "1919  Labrador_retriever  0.115138   True  groenendael  0.0961   True   \n",
       "183                  NaN       NaN    NaN          NaN     NaN    NaN   \n",
       "\n",
       "     favorite_count  retweet_count dog_type  \n",
       "191             NaN            NaN    puppo  \n",
       "1919            NaN            NaN      NaN  \n",
       "183         44443.0        17363.0      NaN  \n",
       "\n",
       "[3 rows x 31 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas[tweet_datas.tweet_id==855851453814013952]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pupper     265\n",
       "doggo       93\n",
       "puppo       37\n",
       "floofer      4\n",
       "Name: dog_type, dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.dog_type.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Delete Retweets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas = tweet_datas[np.isnan(tweet_datas.retweeted_status_id)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 31 columns):\n",
      "tweet_id                      6579 non-null int64\n",
      "in_reply_to_status_id         78 non-null float64\n",
      "in_reply_to_user_id           78 non-null float64\n",
      "timestamp                     2175 non-null object\n",
      "source                        2175 non-null object\n",
      "text                          2175 non-null object\n",
      "retweeted_status_id           0 non-null float64\n",
      "retweeted_status_user_id      0 non-null float64\n",
      "retweeted_status_timestamp    0 non-null object\n",
      "expanded_urls                 2117 non-null object\n",
      "rating_numerator              2175 non-null float64\n",
      "rating_denominator            2175 non-null float64\n",
      "name                          2175 non-null object\n",
      "doggo                         2175 non-null object\n",
      "floofer                       2175 non-null object\n",
      "pupper                        2175 non-null object\n",
      "puppo                         2175 non-null object\n",
      "jpg_url                       2075 non-null object\n",
      "img_num                       2075 non-null float64\n",
      "p1                            2075 non-null object\n",
      "p1_conf                       2075 non-null float64\n",
      "p1_dog                        2075 non-null object\n",
      "p2                            2075 non-null object\n",
      "p2_conf                       2075 non-null float64\n",
      "p2_dog                        2075 non-null object\n",
      "p3                            2075 non-null object\n",
      "p3_conf                       2075 non-null float64\n",
      "p3_dog                        2075 non-null object\n",
      "favorite_count                2329 non-null float64\n",
      "retweet_count                 2329 non-null float64\n",
      "dog_type                      364 non-null object\n",
      "dtypes: float64(12), int64(1), object(18)\n",
      "memory usage: 1.6+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# remove the column retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp\n",
    "\n",
    "tweet_datas = tweet_datas.drop(['retweeted_status_id', 'retweeted_status_user_id', 'retweeted_status_timestamp'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>dog_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Archie</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Darla</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "0  892420643555336193                    NaN                  NaN   \n",
       "1  892177421306343426                    NaN                  NaN   \n",
       "2  891815181378084864                    NaN                  NaN   \n",
       "3  891689557279858688                    NaN                  NaN   \n",
       "4  891327558926688256                    NaN                  NaN   \n",
       "\n",
       "                   timestamp  \\\n",
       "0  2017-08-01 16:23:56 +0000   \n",
       "1  2017-08-01 00:17:27 +0000   \n",
       "2  2017-07-31 00:18:03 +0000   \n",
       "3  2017-07-30 15:58:51 +0000   \n",
       "4  2017-07-29 16:00:24 +0000   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                text  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...   \n",
       "1  This is Tilly. She's just checking pup on you....   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...   \n",
       "3  This is Darla. She commenced a snooze mid meal...   \n",
       "4  This is Franklin. He would like you to stop ca...   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...              13.0   \n",
       "1  https://twitter.com/dog_rates/status/892177421...              13.0   \n",
       "2  https://twitter.com/dog_rates/status/891815181...              12.0   \n",
       "3  https://twitter.com/dog_rates/status/891689557...              13.0   \n",
       "4  https://twitter.com/dog_rates/status/891327558...              12.0   \n",
       "\n",
       "   rating_denominator      name  ... p1_dog   p2 p2_conf p2_dog   p3  p3_conf  \\\n",
       "0                10.0   Phineas  ...    NaN  NaN     NaN    NaN  NaN      NaN   \n",
       "1                10.0     Tilly  ...    NaN  NaN     NaN    NaN  NaN      NaN   \n",
       "2                10.0    Archie  ...    NaN  NaN     NaN    NaN  NaN      NaN   \n",
       "3                10.0     Darla  ...    NaN  NaN     NaN    NaN  NaN      NaN   \n",
       "4                10.0  Franklin  ...    NaN  NaN     NaN    NaN  NaN      NaN   \n",
       "\n",
       "  p3_dog  favorite_count retweet_count dog_type  \n",
       "0    NaN             NaN           NaN      NaN  \n",
       "1    NaN             NaN           NaN      NaN  \n",
       "2    NaN             NaN           NaN      NaN  \n",
       "3    NaN             NaN           NaN      NaN  \n",
       "4    NaN             NaN           NaN      NaN  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 28 columns):\n",
      "tweet_id                 6579 non-null int64\n",
      "in_reply_to_status_id    78 non-null float64\n",
      "in_reply_to_user_id      78 non-null float64\n",
      "timestamp                2175 non-null object\n",
      "source                   2175 non-null object\n",
      "text                     2175 non-null object\n",
      "expanded_urls            2117 non-null object\n",
      "rating_numerator         2175 non-null float64\n",
      "rating_denominator       2175 non-null float64\n",
      "name                     2175 non-null object\n",
      "doggo                    2175 non-null object\n",
      "floofer                  2175 non-null object\n",
      "pupper                   2175 non-null object\n",
      "puppo                    2175 non-null object\n",
      "jpg_url                  2075 non-null object\n",
      "img_num                  2075 non-null float64\n",
      "p1                       2075 non-null object\n",
      "p1_conf                  2075 non-null float64\n",
      "p1_dog                   2075 non-null object\n",
      "p2                       2075 non-null object\n",
      "p2_conf                  2075 non-null float64\n",
      "p2_dog                   2075 non-null object\n",
      "p3                       2075 non-null object\n",
      "p3_conf                  2075 non-null float64\n",
      "p3_dog                   2075 non-null object\n",
      "favorite_count           2329 non-null float64\n",
      "retweet_count            2329 non-null float64\n",
      "dog_type                 364 non-null object\n",
      "dtypes: float64(10), int64(1), object(17)\n",
      "memory usage: 1.5+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Remove the column no longer uses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas = tweet_datas.drop(['in_reply_to_status_id', 'in_reply_to_user_id', 'source', 'img_num'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>dog_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>2017-08-01 16:23:56 +0000</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>2017-08-01 00:17:27 +0000</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>2017-07-31 00:18:03 +0000</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>2017-07-30 15:58:51 +0000</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>2017-07-29 16:00:24 +0000</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id                  timestamp  \\\n",
       "0  892420643555336193  2017-08-01 16:23:56 +0000   \n",
       "1  892177421306343426  2017-08-01 00:17:27 +0000   \n",
       "2  891815181378084864  2017-07-31 00:18:03 +0000   \n",
       "3  891689557279858688  2017-07-30 15:58:51 +0000   \n",
       "4  891327558926688256  2017-07-29 16:00:24 +0000   \n",
       "\n",
       "                                                text  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...   \n",
       "1  This is Tilly. She's just checking pup on you....   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...   \n",
       "3  This is Darla. She commenced a snooze mid meal...   \n",
       "4  This is Franklin. He would like you to stop ca...   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...              13.0   \n",
       "1  https://twitter.com/dog_rates/status/892177421...              13.0   \n",
       "2  https://twitter.com/dog_rates/status/891815181...              12.0   \n",
       "3  https://twitter.com/dog_rates/status/891689557...              13.0   \n",
       "4  https://twitter.com/dog_rates/status/891327558...              12.0   \n",
       "\n",
       "   rating_denominator      name doggo floofer pupper  ... p1_dog   p2 p2_conf  \\\n",
       "0                10.0   Phineas  None    None   None  ...    NaN  NaN     NaN   \n",
       "1                10.0     Tilly  None    None   None  ...    NaN  NaN     NaN   \n",
       "2                10.0    Archie  None    None   None  ...    NaN  NaN     NaN   \n",
       "3                10.0     Darla  None    None   None  ...    NaN  NaN     NaN   \n",
       "4                10.0  Franklin  None    None   None  ...    NaN  NaN     NaN   \n",
       "\n",
       "   p2_dog   p3 p3_conf  p3_dog favorite_count retweet_count  dog_type  \n",
       "0     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "1     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "2     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "3     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "4     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 24 columns):\n",
      "tweet_id              6579 non-null int64\n",
      "timestamp             2175 non-null object\n",
      "text                  2175 non-null object\n",
      "expanded_urls         2117 non-null object\n",
      "rating_numerator      2175 non-null float64\n",
      "rating_denominator    2175 non-null float64\n",
      "name                  2175 non-null object\n",
      "doggo                 2175 non-null object\n",
      "floofer               2175 non-null object\n",
      "pupper                2175 non-null object\n",
      "puppo                 2175 non-null object\n",
      "jpg_url               2075 non-null object\n",
      "p1                    2075 non-null object\n",
      "p1_conf               2075 non-null float64\n",
      "p1_dog                2075 non-null object\n",
      "p2                    2075 non-null object\n",
      "p2_conf               2075 non-null float64\n",
      "p2_dog                2075 non-null object\n",
      "p3                    2075 non-null object\n",
      "p3_conf               2075 non-null float64\n",
      "p3_dog                2075 non-null object\n",
      "favorite_count        2329 non-null float64\n",
      "retweet_count         2329 non-null float64\n",
      "dog_type              364 non-null object\n",
      "dtypes: float64(7), int64(1), object(16)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Change tweet_id from integer to a String."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "#using astype(str)\n",
    "\n",
    "tweet_datas['tweet_id'] = tweet_datas['tweet_id'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 24 columns):\n",
      "tweet_id              6579 non-null object\n",
      "timestamp             2175 non-null object\n",
      "text                  2175 non-null object\n",
      "expanded_urls         2117 non-null object\n",
      "rating_numerator      2175 non-null float64\n",
      "rating_denominator    2175 non-null float64\n",
      "name                  2175 non-null object\n",
      "doggo                 2175 non-null object\n",
      "floofer               2175 non-null object\n",
      "pupper                2175 non-null object\n",
      "puppo                 2175 non-null object\n",
      "jpg_url               2075 non-null object\n",
      "p1                    2075 non-null object\n",
      "p1_conf               2075 non-null float64\n",
      "p1_dog                2075 non-null object\n",
      "p2                    2075 non-null object\n",
      "p2_conf               2075 non-null float64\n",
      "p2_dog                2075 non-null object\n",
      "p3                    2075 non-null object\n",
      "p3_conf               2075 non-null float64\n",
      "p3_dog                2075 non-null object\n",
      "favorite_count        2329 non-null float64\n",
      "retweet_count         2329 non-null float64\n",
      "dog_type              364 non-null object\n",
      "dtypes: float64(7), object(17)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Change the timestamp to correct datetime format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fisrt remove the timezone from timestamp\n",
    "tweet_datas['timestamp'] = tweet_datas['timestamp'].str.slice(start =0, stop= -6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# now convert it into datetime\n",
    "\n",
    "tweet_datas['timestamp'] =  pd.to_datetime(tweet_datas['timestamp'], format=\"%Y-%m-%d %H:%M:%S\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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>tweet_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>...</th>\n",
       "      <th>p1_dog</th>\n",
       "      <th>p2</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_dog</th>\n",
       "      <th>p3</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_dog</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>dog_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>2017-08-01 16:23:56</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Phineas</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>2017-08-01 00:17:27</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Tilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>2017-07-31 00:18:03</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Archie</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>2017-07-30 15:58:51</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891689557...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Darla</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>2017-07-29 16:00:24</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891327558...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>Franklin</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             tweet_id           timestamp  \\\n",
       "0  892420643555336193 2017-08-01 16:23:56   \n",
       "1  892177421306343426 2017-08-01 00:17:27   \n",
       "2  891815181378084864 2017-07-31 00:18:03   \n",
       "3  891689557279858688 2017-07-30 15:58:51   \n",
       "4  891327558926688256 2017-07-29 16:00:24   \n",
       "\n",
       "                                                text  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...   \n",
       "1  This is Tilly. She's just checking pup on you....   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...   \n",
       "3  This is Darla. She commenced a snooze mid meal...   \n",
       "4  This is Franklin. He would like you to stop ca...   \n",
       "\n",
       "                                       expanded_urls  rating_numerator  \\\n",
       "0  https://twitter.com/dog_rates/status/892420643...              13.0   \n",
       "1  https://twitter.com/dog_rates/status/892177421...              13.0   \n",
       "2  https://twitter.com/dog_rates/status/891815181...              12.0   \n",
       "3  https://twitter.com/dog_rates/status/891689557...              13.0   \n",
       "4  https://twitter.com/dog_rates/status/891327558...              12.0   \n",
       "\n",
       "   rating_denominator      name doggo floofer pupper  ... p1_dog   p2 p2_conf  \\\n",
       "0                10.0   Phineas  None    None   None  ...    NaN  NaN     NaN   \n",
       "1                10.0     Tilly  None    None   None  ...    NaN  NaN     NaN   \n",
       "2                10.0    Archie  None    None   None  ...    NaN  NaN     NaN   \n",
       "3                10.0     Darla  None    None   None  ...    NaN  NaN     NaN   \n",
       "4                10.0  Franklin  None    None   None  ...    NaN  NaN     NaN   \n",
       "\n",
       "   p2_dog   p3 p3_conf  p3_dog favorite_count retweet_count  dog_type  \n",
       "0     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "1     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "2     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "3     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "4     NaN  NaN     NaN     NaN            NaN           NaN       NaN  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 24 columns):\n",
      "tweet_id              6579 non-null object\n",
      "timestamp             2175 non-null datetime64[ns]\n",
      "text                  2175 non-null object\n",
      "expanded_urls         2117 non-null object\n",
      "rating_numerator      2175 non-null float64\n",
      "rating_denominator    2175 non-null float64\n",
      "name                  2175 non-null object\n",
      "doggo                 2175 non-null object\n",
      "floofer               2175 non-null object\n",
      "pupper                2175 non-null object\n",
      "puppo                 2175 non-null object\n",
      "jpg_url               2075 non-null object\n",
      "p1                    2075 non-null object\n",
      "p1_conf               2075 non-null float64\n",
      "p1_dog                2075 non-null object\n",
      "p2                    2075 non-null object\n",
      "p2_conf               2075 non-null float64\n",
      "p2_dog                2075 non-null object\n",
      "p3                    2075 non-null object\n",
      "p3_conf               2075 non-null float64\n",
      "p3_dog                2075 non-null object\n",
      "favorite_count        2329 non-null float64\n",
      "retweet_count         2329 non-null float64\n",
      "dog_type              364 non-null object\n",
      "dtypes: datetime64[ns](1), float64(7), object(16)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Correct the naming issue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas['name'] = tweet_datas['name'].str.replace('^[a-z]+', 'None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None       784\n",
       "Lucy        11\n",
       "Charlie     11\n",
       "Oliver      10\n",
       "Cooper      10\n",
       "          ... \n",
       "Kawhi        1\n",
       "Noosh        1\n",
       "Pavlov       1\n",
       "Jarod        1\n",
       "Pipsy        1\n",
       "Name: name, Length: 931, dtype: int64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25         NaN\n",
       "870       None\n",
       "842        NaN\n",
       "510        Moe\n",
       "0          NaN\n",
       "301     Oliver\n",
       "612        NaN\n",
       "657        NaN\n",
       "730       None\n",
       "1714      None\n",
       "Name: name, dtype: object"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.name.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code And Test : Standardize the Dog ratings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas['rating_numerator'] = tweet_datas['rating_numerator'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas['rating_denominator'] = tweet_datas['rating_denominator'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 6579 entries, 0 to 2328\n",
      "Data columns (total 24 columns):\n",
      "tweet_id              6579 non-null object\n",
      "timestamp             2175 non-null datetime64[ns]\n",
      "text                  2175 non-null object\n",
      "expanded_urls         2117 non-null object\n",
      "rating_numerator      2175 non-null float64\n",
      "rating_denominator    2175 non-null float64\n",
      "name                  2175 non-null object\n",
      "doggo                 2175 non-null object\n",
      "floofer               2175 non-null object\n",
      "pupper                2175 non-null object\n",
      "puppo                 2175 non-null object\n",
      "jpg_url               2075 non-null object\n",
      "p1                    2075 non-null object\n",
      "p1_conf               2075 non-null float64\n",
      "p1_dog                2075 non-null object\n",
      "p2                    2075 non-null object\n",
      "p2_conf               2075 non-null float64\n",
      "p2_dog                2075 non-null object\n",
      "p3                    2075 non-null object\n",
      "p3_conf               2075 non-null float64\n",
      "p3_dog                2075 non-null object\n",
      "favorite_count        2329 non-null float64\n",
      "retweet_count         2329 non-null float64\n",
      "dog_type              364 non-null object\n",
      "dtypes: datetime64[ns](1), float64(7), object(16)\n",
      "memory usage: 1.3+ MB\n"
     ]
    }
   ],
   "source": [
    "tweet_datas.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "search() missing 1 required positional argument: 'string'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-68-652fe9c2be7e>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtext\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtweet_datas\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'text'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0miteritems\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m     \u001b[0mrating_decimal\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mre\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msearch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'\\d+\\.\\d+'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: search() missing 1 required positional argument: 'string'"
     ]
    }
   ],
   "source": [
    "# For loop to gather all the indices, text and rating for the tweet that contain decimal in numerator\n",
    "\n",
    "import re\n",
    "\n",
    "\n",
    "rating_decimal = []\n",
    "\n",
    "for i, text in tweet_datas['text'].iteritems():\n",
    "\n",
    "    rating_decimal.append(re.search('\\d+\\.\\d+'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas.loc[40]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "\n",
    "Image(url='https://pbs.twimg.com/media/CUCQTpEWEAA7EDz.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "####  This is Kevin. He's just so happy with the ratings !"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas.loc[248]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "248                                                NaN\n",
       "248    https://pbs.twimg.com/media/CU64WOlWcAA37TV.jpg\n",
       "248                                                NaN\n",
       "Name: jpg_url, dtype: object"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.loc[248]['jpg_url']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"https://pbs.twimg.com/media/CU64WOlWcAA37TV.jpg\"/>"
      ],
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(url='https://pbs.twimg.com/media/CU64WOlWcAA37TV.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas['rating'] = 10*(tweet_datas['rating_numerator']/tweet_datas['rating_denominator'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2175.0\n",
       "mean        inf\n",
       "std         NaN\n",
       "min         0.0\n",
       "25%        10.0\n",
       "50%        11.0\n",
       "75%        12.0\n",
       "max         inf\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.rating.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    13.0\n",
       "1    13.0\n",
       "2    12.0\n",
       "3    13.0\n",
       "4    12.0\n",
       "Name: rating, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\AppData\\Roaming\\Python\\Python37\\site-packages\\ipykernel_launcher.py:7: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "  import sys\n",
      "C:\\Users\\Lenovo\\AppData\\Roaming\\Python\\Python37\\site-packages\\ipykernel_launcher.py:13: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "  del sys.path[0]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# 9 - Code\n",
    "tweet_datas['dog_breed'] = 'None'\n",
    "\n",
    "for i, row in tweet_datas.iterrows():\n",
    "\n",
    "    if row.p1_dog:\n",
    "        tweet_datas.set_value(i, 'dog_breed', row.p1)\n",
    "    elif row.p2_dog and row.rating_numerator >= 10:\n",
    "        tweet_datas.set_value(i, 'dog_breed', row.p2)\n",
    "    elif row.p3_dog and row.rating_numerator >= 10:\n",
    "        tweet_datas.set_value(i, 'dog_breed', row.p3)\n",
    "    else:\n",
    "        tweet_datas.set_value(i, 'dog_breed', 'None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    NaN\n",
       "1    NaN\n",
       "2    NaN\n",
       "3    NaN\n",
       "4    NaN\n",
       "Name: dog_breed, dtype: object"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.dog_breed.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# storing, Analyzing and Vizualizing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<ol>\n",
    "    <li>Vizualizing the total number of tweets overtime to observe the change in it.</li>\n",
    "    <li>Vizualizing retweet count and favourite count comparision over time.</li>\n",
    "    <li>Vizualizing the most popular Dog breed</li>\n",
    "    <li>Vizualizing the most popular dog namw.</li>\n",
    "</ol>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "tweet_datas.to_csv('twitter_archive_master.csv', encoding= 'utf-8', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vizualizing the total number of tweets overtime to observe the change in it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id    2175\n",
       "dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.timestamp = pd.to_datetime(tweet_datas['timestamp'], format='%Y-%m-%d %H:%M:%S.%f')\n",
    "\n",
    "monthly_tweets = tweet_datas.groupby(pd.Grouper(key = 'timestamp', freq=  'M')).count().reset_index()\n",
    "\n",
    "monthly_tweets = monthly_tweets[['timestamp', 'tweet_id']]\n",
    "\n",
    "monthly_tweets.head()\n",
    "\n",
    "monthly_tweets.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\Anaconda3\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\converter.py:103: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
      "\n",
      "To register the converters:\n",
      "\t>>> from pandas.plotting import register_matplotlib_converters\n",
      "\t>>> register_matplotlib_converters()\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot time vs tweet\n",
    "\n",
    "plt.figure(figsize=(10,8))\n",
    "\n",
    "# plt.xlim([datetime.date(2015,11,30), datetime(2017,7,30)])\n",
    "\n",
    "plt.xlabel('Year and Month')\n",
    "\n",
    "plt.ylabel('Tweets Count')\n",
    "\n",
    "plt.plot(monthly_tweets.timestamp, monthly_tweets.tweet_id)\n",
    "\n",
    "plt.title('WeRateDogs Tweets over Time');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> over the time the graph decreases rapidly. its no peak on 2016-01 and then decreasaes rapidly to 2017-10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Analyze and Visualize: Visualizing the retweet counts, and favorite counts comparison over time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 468x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatterplot of retweets vs favorite count\n",
    "\n",
    "sns.lmplot(x= 'retweet_count', y = 'favorite_count', data= tweet_datas, size = 5, \n",
    "           aspect = 1.3, scatter_kws = {'alpha':1/5})\n",
    "\n",
    "plt.title('Favorite Count vs. Retweet Count');\n",
    "plt.xlabel('Retweet Count');\n",
    "plt.ylabel('Favorite Count');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> favourite count are co related with retweet count. This is a positive co relation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Analyze and Visualize: Visualizing the most popular dog breed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pupper     244\n",
       "doggo       84\n",
       "puppo       32\n",
       "floofer      4\n",
       "Name: dog_type, dtype: int64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_datas.dog_type.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "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": [
    "# dog_breed = tweet_datas.groupby('dog_breed').filter(lambda x: len(x)>=25)\n",
    "\n",
    "tweet_datas.dog_type.value_counts().plot(kind = 'barh')\n",
    "\n",
    "plt.title('Most Rated Dog Breed')\n",
    "plt.xlabel('Count')\n",
    "plt.ylabel('Breed of dog');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> pupper is the most popular dog breed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Analyze and Visualize: Visualizing the most popular dog names¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Lenovo\\AppData\\Roaming\\Python\\Python37\\site-packages\\ipykernel_launcher.py:1: FutureWarning: `Series.plot()` should not be called with positional arguments, only keyword arguments. The order of positional arguments will change in the future. Use `Series.plot(kind='barh')` instead of `Series.plot('barh',)`.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "image/png": 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AgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADCwNYsuYKVsPH9T1h5/yjb7nbd+3W6oBgAAYHWw0gcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwLYr9FXVz1bVq6vq3Kr6RFX9W1XdZFcXBwAAwM7ZZuirqkryxiTv6u4bdffNk/xxkuvs6uKW1LHP7hwPAABgBNuz0vdrSS7p7hdvbujus5K8r6r+qqo+XlUbq+qYZBYSt9B+16p6T1W9cVotfHFVXWnad8+q+kBVfbiqXldVB0zt51XVn1TV+5I8eKWfPAAAwOjWbEefWyQ5c5n2ByU5Ismtkhyc5Iyqek+SO26hPUlum+TmSb6Q5K1JHlRV70rytCT36O4fVNX/k+RJSf5sOuaH3X2n5QqrquOSHJck+1zjkO14KgAAAHuX7Ql9W3KnJCd392VJvlZV705ym620fzfJ6d39uSSpqpOnvj/MLAj+x+xK0lw5yQfmxnnNlgro7hOTnJgk+x16eO/EcwEAABjS9oS+s5McvUx7baH/ltqTZGkw66n/27v7oVs45gdbLw8AAIAt2Z57+t6ZZL+qeszmhqq6TZJvJzmmqvapqkOS3DnJ6Unes4X2JLltVf38dC/fMUnel+SDSX6lqm48nXt/7wwKAACwMra50tfdXVUPTPLcqjo+s8sxz0vyhCQHJPloZit2T+nur1bVG5PcYZn2m2Z22eb6JLfMLBy+sbt/XFWPSHJyVe03Dfu0JJ9euacJAACwd9que/q6+ytJfnOZXX80fc337eXaJxd19zHLnP+dmd33t7R97fbUBwAAwPK268PZAQAA2DPtzLt3XiHd/a4k79pd4wEAAGClDwAAYGhCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADCw3fbh7LvaLQ87MBvWr1t0GQAAAKuKlT4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwsDWLLmClbDx/U9Yef8o2+523ft1uqAYAAGB1sNIHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMB2OPRV1fWq6l+q6jNVdW5VPa+qrlxVd62qt0x97ldVx69cuQAAAFwROxT6qqqSvCHJm7r78CQ3SXJAkmfM9+vuN3f3+p0tsqrW7Ow5AAAA9kY7utJ3tyQ/7O6XJUl3X5bkiUkelWT/zZ2q6hFV9cKqOrCqzquqK03t+1fVl6pq36q6UVW9tarOrKr3VtVNpz4nVdVzquq0JM/amScJAACwt9rRFbRfTHLmfEN3f7eqvpjkxks7d/emqvpokrskOS3JfZO8rbsvqaoTkzy2uz9TVbdL8qLMQmUyW0G8xxQqL6eqjktyXJLsc41DdvCpAAAAjGtHQ18l6SvQniSvSXJMZqHvIUleVFUHJLljktfNrhhNkuw3d8zrthT4kqS7T0xyYpLsd+jhWxoXAABgr7Wjoe/sJP99vqGqrpHk55Kcu4Vj3pzkmVV17SRHJnlnkqsl+U53H7GFY36wg/UBAACQHb+n7x1J9q+qhyVJVe2T5NlJTkpy0XIHdPf3k5ye5HlJ3tLdl3X3d5N8vqoePJ2nqupWO1gTAAAAS+xQ6OvuTvLAJA+uqs8k+XSSHyb5420c+pokvzV93+zYJI+e7vk7O8n9d6QmAAAALq9m+W3Pt9+hh/ehD3/uNvudt37dbqgGAABg96qqM7v7qKXtO/zh7AAAAKx+Qh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwNYsuoCVcsvDDsyG9esWXQYAAMCqYqUPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADGzNogtYKRvP35S1x5+yXX3PW79uF1cDAACwOljpAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBg2xX6qupnq+rVVXVuVX2iqv6tqo6rqrfszOBVdUJVPXna/rOqusfOnA8AAICftmZbHaqqkrwxyT9190OmtiOS3HdnBq6qnxq7u/9kZ84HAADA5W3PSt+vJbmku1+8uaG7z0ry3iQHVNXrq+qTVfXKKSCmqv6kqs6oqo9X1Ylz7e+qqr+oqncnefz8IFV1UlUdPW0fWVXvrqozq+ptVXXoCj1fAACAvcr2hL5bJDlzC/tuneQJSW6e5IZJfmVqf2F336a7b5HkqknuM3fMNbv7Lt397OVOWFX7JnlBkqO7+8gkL03yjC30Pa6qNlTVhssu2rQdTwUAAGDvss3LO7fh9O7+cpJU1VlJ1iZ5X5Jfq6qnJNk/ybWTnJ3kX6djXrONc/5CZkHz7dMC4T5JLliuY3efmOTEJNnv0MN7Z54IAADAiLYn9J2d5Ogt7Lt4bvuyJGuq6ipJXpTkqO7+UlWdkOQqc/1+sI3xKsnZ3X2H7agNAACArdieyzvfmWS/qnrM5oaquk2Su2yh/+aA982qOiBbDoxb8qkkh1TVHaax9q2qX7yC5wAAACDbEfq6u5M8MMmvTx/ZcHaSE5J8ZQv9v5PkH5JsTPKmJGdckYK6+0eZBcVnVdVHk5yV5I5X5BwAAADM1CzT7fn2O/TwPvThz92uvuetX7eLqwEAANi9qurM7j5qaft2fTg7AAAAeyahDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgaxZdwEq55WEHZsP6dYsuAwAAYFWx0gcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGtmbRBayUjedvytrjT9muvuetX7eLqwEAAFgdrPQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMLAVD31V9f2VPicAAAA7xkofAADAwHZL6Kuqk6rq6LnH35/bfkpVbayqj1bV+qq6UVV9eG7/4VV15u6oEwAAYDRrFjl4Vd07yQOS3K67L6qqa3f3hVW1qaqO6O6zkjwyyUmLrBMAAGBPtejLO++R5GXdfVGSdPeFU/tLkjyyqvZJckySVy13cFUdV1UbqmrDZRdt2i0FAwAA7El2V+i7dPNYVVVJrjy1V5Jepv8/J7l3kvskObO7v7XcSbv7xO4+qruP2mf/A1e+agAAgD3c7gp95yU5ctq+f5J9p+1TkzyqqvZPkqq6dpJ09w+TvC3J3yV52W6qEQAAYDi7IvTtX1Vfnvt6UpJ/SHKXqjo9ye2S/CBJuvutSd6cZENVnZXkyXPneWVmq4Cn7oIaAQAA9gor/kYu3b2lIHn7ue2nzvVfn2T9Mv3vlOSl3X3ZCpYHAACwV1nou3duSVW9McmNktxt0bUAAADsyVZl6OvuBy66BgAAgBEs+iMbAAAA2IWEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgq/LD2XfELQ87MBvWr1t0GQAAAKuKlT4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwsDWLLmClbDx/U9Yef8qiywAAAAZ13vp1iy5hh1jpAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAxM6AMAABiY0AcAADAwoQ8AAGBgKxb6qqqr6tlzj59cVSes1PkBAAC44lZype/iJA+qqoNX8JwAAADshJUMfZcmOTHJE5fuqKobVNU7qupj0/frT+0nVdXzq+r9VfW5qjp67pg/qqozpmOevoJ1AgAA7DVW+p6+v01ybFUduKT9hUle3t2/lOSVSZ4/t+/QJHdKcp8k65Okqu6Z5PAkt01yRJIjq+rOK1wrAADA8FY09HX3d5O8PMnjluy6Q5JXTduvyCzkbfam7v5xd38iyXWmtntOXx9J8uEkN80sBP6UqjquqjZU1YbLLtq0ck8EAABgEGt2wTmfm1lQe9lW+vTc9sVz2zX3/Znd/fdbG6i7T8zsktLsd+jhvbW+AAAAe6MV/8iG7r4wyWuTPHqu+f1JHjJtH5vkfds4zduSPKqqDkiSqjqsqn5mpWsFAAAY3a76nL5nJ5l/F8/HJXlkVX0syf9M8vitHdzdp2Z2OegHqmpjktcnufouqhUAAGBYK3Z5Z3cfMLf9tST7zz0+L8ndljnmEVs5x/OSPG+l6gMAANgb7aqVPgAAAFYBoQ8AAGBgQh8AAMDAhD4AAICBCX0AAAADE/oAAAAGJvQBAAAMTOgDAAAYmNAHAAAwMKEPAABgYGsWXcBKueVhB2bD+nWLLgMAAGBVsdIHAAAwMKEPAABgYEIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AQAADEzoAwAAGJjQBwAAMDChDwAAYGBCHwAAwMCEPgAAgIEJfQAAAAMT+gAAAAYm9AEAAAysunvRNayIqvpekk8tug5+ysFJvrnoIrgc87I6mZfVx5ysTuZldTIvq485WZ129bzcoLsPWdq4ZhcOuLt9qruPWnQR/ERVbTAnq495WZ3My+pjTlYn87I6mZfVx5ysTouaF5d3AgAADEzoAwAAGNhIoe/ERRfA5ZiT1cm8rE7mZfUxJ6uTeVmdzMvqY05Wp4XMyzBv5AIAAMDljbTSBwAAwBJ7fOirqntV1aeq6rNVdfyi69mbVNVLq+rrVfXxubZrV9Xbq+oz0/drTe1VVc+f5uljVfXLi6t8XFX1c1V1WlWdU1VnV9Xjp3bzskBVdZWqOr2qPjrNy9On9p+vqg9N8/Kaqrry1L7f9Piz0/61i6x/ZFW1T1V9pKreMj02JwtWVedV1caqOquqNkxtfoYtWFVds6peX1WfnH7H3MG8LFZV/cL092Tz13er6gnmZbGq6onT7/qPV9XJ078BFv67ZY8OfVW1T5K/TXLvJDdP8tCquvliq3oLDOoAAAiiSURBVNqrnJTkXkvajk/yju4+PMk7psfJbI4On76OS/J3u6nGvc2lSf6wu2+W5PZJfn/6O2FeFuviJHfr7lslOSLJvarq9kmeleRvpnn5dpJHT/0fneTb3X3jJH8z9WPXeHySc+Yem5PV4de6+4i5tzX3M2zxnpfkrd190yS3yuzvjXlZoO7+1PT35IgkRya5KMkbY14WpqoOS/K4JEd19y2S7JPkIVkFv1v26NCX5LZJPtvdn+vuHyV5dZL7L7imvUZ3vyfJhUua75/kn6btf0rygLn2l/fMB5Ncs6oO3T2V7j26+4Lu/vC0/b3MfikfFvOyUNPr+/3p4b7TVye5W5LXT+1L52XzfL0+yd2rqnZTuXuNqrpeknVJXjI9rpiT1crPsAWqqmskuXOSf0yS7v5Rd38n5mU1uXuSc7v7CzEvi7YmyVWrak2S/ZNckFXwu2VPD32HJfnS3OMvT20sznW6+4JkFkCS/MzUbq52s+kSgVsn+VDMy8JNlxGeleTrSd6e5Nwk3+nuS6cu86/9f83LtH9TkoN2b8V7hecmeUqSH0+PD4o5WQ06yalVdWZVHTe1+Rm2WDdM8o0kL5suh35JVV0t5mU1eUiSk6dt87Ig3X1+kr9O8sXMwt6mJGdmFfxu2dND33JJ2NuRrk7majeqqgOS/HOSJ3T3d7fWdZk287ILdPdl0yU418vsKoWbLddt+m5edrGquk+Sr3f3mfPNy3Q1J7vfr3T3L2d2KdrvV9Wdt9LXvOwea5L8cpK/6+5bJ/lBfnLJ4HLMy2403R92vySv21bXZdrMywqa7p+8f5KfT3LdJFfL7GfZUrv9d8ueHvq+nOTn5h5fL8lXFlQLM1/bfKnA9P3rU7u52k2qat/MAt8ru/sNU7N5WSWmS6Leldk9l9ecLv9Ifvq1/695mfYfmMtfSs3O+ZUk96uq8zK7NeBuma38mZMF6+6vTN+/ntn9SbeNn2GL9uUkX+7uD02PX59ZCDQvq8O9k3y4u782PTYvi3OPJJ/v7m909yVJ3pDkjlkFv1v29NB3RpLDp3fEuXJmS9tvXnBNe7s3J3n4tP3wJP8y1/6w6Z2jbp9k0+ZLD1g503Xg/5jknO5+ztwu87JAVXVIVV1z2r5qZr8UzklyWpKjp25L52XzfB2d5J3tQ1VXVHc/tbuv191rM/vd8c7uPjbmZKGq6mpVdfXN20numeTj8TNsobr7q0m+VFW/MDXdPcknYl5Wi4fmJ5d2JuZlkb6Y5PZVtf/0b7LNf1cW/rtlj/9w9qr6jcz+d3afJC/t7mcsuKS9RlWdnOSuSQ5O8rUkf5rkTUlem+T6mf3Bf3B3Xzj9wX9hZu/2eVGSR3b3hkXUPbKqulOS9ybZmJ/cp/THmd3XZ14WpKp+KbMbtffJ7D/bXtvdf1ZVN8xslenaST6S5Le6++KqukqSV2R2T+aFSR7S3Z9bTPXjq6q7Jnlyd9/HnCzW9Pq/cXq4JsmruvsZVXVQ/AxbqKo6IrM3Pbpyks8leWSmn2cxLwtTVftndk/YDbt709Tm78sC1exjmY7J7B3VP5LktzO7d2+hv1v2+NAHAADAlu3pl3cCAACwFUIfAADAwIQ+AACAgQl9AAAAAxP6AAAABib0AbBHqKquqmfPPX5yVZ2wQuc+qaqO3nbPnR7nwVV1TlWdtqR9bVX9Z1V9ZNp/elU9fEvnAYArQugDYE9xcZIHVdXBiy5kXlXtcwW6PzrJ73X3ry2z79zuvnV33yyzD4x/YlU9ckWKBGCvJvQBsKe4NMmJSZ64dMfSlbqq+v70/a5V9e6qem1Vfbqq1lfVsdNK2saqutHcae5RVe+d+t1nOn6fqvqrqjqjqj5WVb8zd97TqupVSTYuU89Dp/N/vKqeNbX9SZI7JXlxVf3V1p7o9OG8T0ryuOnYa1fVm6YaPlhVvzS1H1JVb6+qD1fV31fVF6rq4Kq6WlWdUlUfnWo4ZvtfZgBGs2bRBQDAFfC3ST5WVX95BY65VZKbJbkwyeeSvKS7b1tVj0/yB0meMPVbm+QuSW6U5LSqunGShyXZ1N23qar9kvxHVZ069b9tklt09+fnB6uq6yZ5VpIjk3w7yalV9YDu/rOquluSJ3f3hu2o+8NJbjptPz3JR7r7AdM5Xp7kiCR/muSd3f3MqrpXkuOm/vdK8pXuXjfVdOD2vVQAjMhKHwB7jO7+bmaB53FX4LAzuvuC7r44yblJNoe2jZkFvc1e290/7u7PZBYOb5rknkkeVlVnJflQkoOSHD71P31p4JvcJsm7uvsb3X1pklcmufMVqHezmtu+U5JXJEl3vzPJQVOQu1OSV0/tb80sZG5+bveoqmdV1a9296YdGB+AQQh9AOxpnpvZvXFXm2u7NNPvtKqqJFee23fx3PaP5x7/OD99xUsvGaczC15/0N1HTF8/392bQ+MPtlBfbaH9irp1knO2cs7eQnu6+9OZrTRuTPLM6dJSAPZSQh8Ae5TuvjDJazMLfpudl1nISZL7J9l3B0794Kq60nSf3w2TfCrJ25L8blXtmyRVdZOqutrWTpLZiuBdpnvr9kny0CTvviKFVNXaJH+d5AVT03uSHDvtu2uSb06rnu9L8ptT+z2TXGvavm6Si7r7/0zn+eUrMj4AY3FPHwB7omcn+V9zj/8hyb9U1elJ3pEtr8JtzacyC2fXSfLY7v5hVb0ks0tAPzytIH4jyQO2dpLuvqCqnprktMxW4v6tu/9lO8a/UVV9JMlVknwvyQu6+2XTvhOSvKyqPpbkoiSbP87h6UlOnt6o5d1JLpiOvWuSv6qqHye5JMnvbsf4AAyqupdezQIA7AmmN5e5rLsvrao7JPm77j5i0XUBsLpY6QOAPdf1k7y2qq6U5EdJHrPgegBYhaz0AQAADMwbuQAAAAxM6AMAABiY0AcAADAwoQ8AAGBgQh8AAMDAhD4AAICB/f/AvXdVvqVn/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "tweet_datas.name.value_counts()[0:7].plot('barh', figsize=(15,8), title='Most Common Dog Names').set_xlabel(\"Number of Dogs\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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