p7/project/wrangle_act.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wrangle and Analyze Data Project"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "import tweepy as tweepy\n",
    "import json\n",
    "from tweepy.parsers import JSONParser\n",
    "import time\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import re"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gather Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>0</th>\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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "      <th>3</th>\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",
       "      <th>4</th>\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": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in the twitter archive enhanced csv given to us\n",
    "df_twitter_archive = pd.read_csv('twitter-archive-enhanced.csv')\n",
    "df_twitter_archive.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Gather image predictions from Udacity's servers\n",
    "url = 'https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv'\n",
    "response = requests.get(url)\n",
    "\n",
    "# check response code\n",
    "response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the provided image predictions\n",
    "with open(url.split('/')[-1], mode='wb') as file:\n",
    "    file.write(response.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>0</th>\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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "      <th>3</th>\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",
       "      <th>4</th>\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": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the image predictions tsv file into a dataframe\n",
    "image_predictions = pd.read_csv('image-predictions.tsv', sep='\\t')\n",
    "image_predictions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Access the twitter archives using your unique keys and tokens\n",
    "consumer_key = '##########'\n",
    "consumer_secret = '##########'\n",
    "access_token = '##########'\n",
    "access_secret = '##########'\n",
    "\n",
    "auth = tweepy.OAuthHandler(consumer_key, consumer_secret)\n",
    "auth.set_access_token(access_token, access_secret)\n",
    "\n",
    "api = tweepy.API(auth, parser=JSONParser(), wait_on_rate_limit=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Do a test run of the api\n",
    "tweet = api.get_status(887473957103951883,tweet_mode='extended')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "887473957103951883\n",
      "17792\n"
     ]
    }
   ],
   "source": [
    "# Testing\n",
    "print(tweet['id'])\n",
    "print(tweet['retweet_count'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading Tweet 1/2356. (0.0%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2/2356. (0.1%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 3/2356. (0.1%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 4/2356. (0.2%) complete. Elapsed Time = 0.23\n",
      "Reading Tweet 5/2356. (0.2%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 6/2356. (0.3%) complete. Elapsed Time = 0.23\n",
      "Reading Tweet 7/2356. (0.3%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 8/2356. (0.3%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 9/2356. (0.4%) complete. Elapsed Time = 0.38\n",
      "Reading Tweet 10/2356. (0.4%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 11/2356. (0.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 12/2356. (0.5%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 13/2356. (0.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 14/2356. (0.6%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 15/2356. (0.6%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 16/2356. (0.7%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 17/2356. (0.7%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 18/2356. (0.8%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 19/2356. (0.8%) complete. Elapsed Time = 0.19\n",
      "888202515573088257[{'code': 144, 'message': 'No status found with that ID.'}]\n",
      "Reading Tweet 21/2356. (0.9%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 22/2356. (0.9%) complete. Elapsed Time = 0.3\n",
      "Reading Tweet 23/2356. (1.0%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 24/2356. (1.0%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 25/2356. (1.1%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 26/2356. (1.1%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 27/2356. (1.1%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 28/2356. (1.2%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 29/2356. (1.2%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 30/2356. (1.3%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 31/2356. (1.3%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 32/2356. (1.4%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 33/2356. (1.4%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 34/2356. (1.4%) complete. Elapsed Time = 0.18\n",
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      "Reading Tweet 2226/2356. (94.5%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2227/2356. (94.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2228/2356. (94.6%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2229/2356. (94.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2230/2356. (94.7%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2231/2356. (94.7%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2232/2356. (94.7%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2233/2356. (94.8%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2234/2356. (94.8%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2235/2356. (94.9%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2236/2356. (94.9%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2237/2356. (94.9%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2238/2356. (95.0%) complete. Elapsed Time = 0.26\n",
      "Reading Tweet 2239/2356. (95.0%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2240/2356. (95.1%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2241/2356. (95.1%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2242/2356. (95.2%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2243/2356. (95.2%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2244/2356. (95.2%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 2245/2356. (95.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2246/2356. (95.3%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2247/2356. (95.4%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2248/2356. (95.4%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2249/2356. (95.5%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 2250/2356. (95.5%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2251/2356. (95.5%) complete. Elapsed Time = 0.3\n",
      "Reading Tweet 2252/2356. (95.6%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2253/2356. (95.6%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2254/2356. (95.7%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2255/2356. (95.7%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2256/2356. (95.8%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2257/2356. (95.8%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2258/2356. (95.8%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2259/2356. (95.9%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2260/2356. (95.9%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2261/2356. (96.0%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2262/2356. (96.0%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2263/2356. (96.1%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2264/2356. (96.1%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2265/2356. (96.1%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2266/2356. (96.2%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2267/2356. (96.2%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2268/2356. (96.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2269/2356. (96.3%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2270/2356. (96.3%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2271/2356. (96.4%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2272/2356. (96.4%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2273/2356. (96.5%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2274/2356. (96.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2275/2356. (96.6%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2276/2356. (96.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2277/2356. (96.6%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2278/2356. (96.7%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2279/2356. (96.7%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 2280/2356. (96.8%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2281/2356. (96.8%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2282/2356. (96.9%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2283/2356. (96.9%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2284/2356. (96.9%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2285/2356. (97.0%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2286/2356. (97.0%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2287/2356. (97.1%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2288/2356. (97.1%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2289/2356. (97.2%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2290/2356. (97.2%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2291/2356. (97.2%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2292/2356. (97.3%) complete. Elapsed Time = 0.24\n",
      "Reading Tweet 2293/2356. (97.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2294/2356. (97.4%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2295/2356. (97.4%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2296/2356. (97.5%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2297/2356. (97.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2298/2356. (97.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2299/2356. (97.6%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2300/2356. (97.6%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2301/2356. (97.7%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2302/2356. (97.7%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2303/2356. (97.8%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2304/2356. (97.8%) complete. Elapsed Time = 0.23\n",
      "Reading Tweet 2305/2356. (97.8%) complete. Elapsed Time = 0.23\n",
      "Reading Tweet 2306/2356. (97.9%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2307/2356. (97.9%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2308/2356. (98.0%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2309/2356. (98.0%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 2310/2356. (98.0%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2311/2356. (98.1%) complete. Elapsed Time = 0.38\n",
      "Reading Tweet 2312/2356. (98.1%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2313/2356. (98.2%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2314/2356. (98.2%) complete. Elapsed Time = 0.33\n",
      "Reading Tweet 2315/2356. (98.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2316/2356. (98.3%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2317/2356. (98.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2318/2356. (98.4%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2319/2356. (98.4%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2320/2356. (98.5%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2321/2356. (98.5%) complete. Elapsed Time = 0.24\n",
      "Reading Tweet 2322/2356. (98.6%) complete. Elapsed Time = 0.28\n",
      "Reading Tweet 2323/2356. (98.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2324/2356. (98.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2325/2356. (98.7%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2326/2356. (98.7%) complete. Elapsed Time = 0.21\n",
      "Reading Tweet 2327/2356. (98.8%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2328/2356. (98.8%) complete. Elapsed Time = 0.16\n",
      "Reading Tweet 2329/2356. (98.9%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2330/2356. (98.9%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2331/2356. (98.9%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2332/2356. (99.0%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2333/2356. (99.0%) complete. Elapsed Time = 0.16\n",
      "Reading Tweet 2334/2356. (99.1%) complete. Elapsed Time = 0.24\n",
      "Reading Tweet 2335/2356. (99.1%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2336/2356. (99.2%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2337/2356. (99.2%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2338/2356. (99.2%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2339/2356. (99.3%) complete. Elapsed Time = 0.22\n",
      "Reading Tweet 2340/2356. (99.3%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2341/2356. (99.4%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2342/2356. (99.4%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2343/2356. (99.4%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2344/2356. (99.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2345/2356. (99.5%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2346/2356. (99.6%) complete. Elapsed Time = 0.17\n",
      "Reading Tweet 2347/2356. (99.6%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2348/2356. (99.7%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2349/2356. (99.7%) complete. Elapsed Time = 0.19\n",
      "Reading Tweet 2350/2356. (99.7%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2351/2356. (99.8%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2352/2356. (99.8%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2353/2356. (99.9%) complete. Elapsed Time = 0.18\n",
      "Reading Tweet 2354/2356. (99.9%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2355/2356. (100.0%) complete. Elapsed Time = 0.2\n",
      "Reading Tweet 2356/2356. (100.0%) complete. Elapsed Time = 0.19\n",
      "Reading Process Completed. Elapsed Time is 28:51\n"
     ]
    }
   ],
   "source": [
    "# Query the api and get erroneous tweets. Track timing of tweet completion as well.\n",
    "df_list = []\n",
    "errors_list = []\n",
    "\n",
    "tweets = df_twitter_archive['tweet_id']\n",
    "\n",
    "now = time.time()\n",
    "\n",
    "for index, t in enumerate(tweets):\n",
    "\n",
    "    try:\n",
    "        start = time.time()\n",
    "        tweet = api.get_status(t,tweet_mode='extended')\n",
    "        end = time.time()\n",
    "        print(\"Reading Tweet {}/{}. ({}%) complete. Elapsed Time = {}\".format((index+1),len(tweets), round(((index+1)/len(tweets)) * 100,1), round((end - start),2)))\n",
    "        retweet_count = tweet['retweet_count']\n",
    "        favorite_count = tweet['favorite_count']\n",
    "        df_list.append({'tweet_id':int(t),\n",
    "                        'retweet_count':int(retweet_count),\n",
    "                        'favorite_count':int(favorite_count)\n",
    "                       })\n",
    "\n",
    "    \n",
    "    \n",
    "    except Exception as e:\n",
    "        print(str(t) + str(e))\n",
    "        errors_list.append(t)\n",
    "\n",
    "then = time.time()\n",
    "diff = round(then - now)\n",
    "minutes = diff // 60\n",
    "seconds = diff % 60\n",
    "print(\"Reading Process Completed. Elapsed Time is {}:{}\".format(minutes, seconds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[888202515573088257,\n",
       " 873697596434513921,\n",
       " 872668790621863937,\n",
       " 869988702071779329,\n",
       " 866816280283807744,\n",
       " 861769973181624320,\n",
       " 845459076796616705,\n",
       " 842892208864923648,\n",
       " 837012587749474308,\n",
       " 827228250799742977,\n",
       " 812747805718642688,\n",
       " 802247111496568832,\n",
       " 775096608509886464,\n",
       " 770743923962707968,\n",
       " 754011816964026368,\n",
       " 680055455951884288]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "errors_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>tweet_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38044</td>\n",
       "      <td>8321</td>\n",
       "      <td>892420643555336193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32670</td>\n",
       "      <td>6148</td>\n",
       "      <td>892177421306343426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>30108</td>\n",
       "      <td>7178</td>\n",
       "      <td>890006608113172480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>40160</td>\n",
       "      <td>8939</td>\n",
       "      <td>872486979161796608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>10070</td>\n",
       "      <td>4280</td>\n",
       "      <td>747103485104099331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      favorite_count  retweet_count            tweet_id\n",
       "0              38044           8321  892420643555336193\n",
       "1              32670           6148  892177421306343426\n",
       "10             30108           7178  890006608113172480\n",
       "100            40160           8939  872486979161796608\n",
       "1000           10070           4280  747103485104099331"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# save df of queried tweets to JSON and then convert to a dataframe\n",
    "df_json = pd.DataFrame(df_list, columns = ['tweet_id', 'retweet_count', 'favorite_count'])\n",
    "df_json.to_json('tweet_json.txt')\n",
    "df_json = pd.read_json('tweet_json.txt')\n",
    "df_json.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assess Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **df_twitter_archive assessments**<br />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>0</th>\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",
       "      <th>1</th>\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",
       "      <th>2</th>\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",
       "      <th>3</th>\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",
       "      <th>4</th>\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",
       "      <th>5</th>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 00:08:17 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a majestic great white breaching ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891087950...</td>\n",
       "      <td>13</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",
       "      <th>6</th>\n",
       "      <td>890971913173991426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 16:27:12 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Jax. He enjoys ice cream so much he gets ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://gofundme.com/ydvmve-surgery-for-jax,ht...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Jax</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>890729181411237888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-28 00:22:40 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>When you watch your owner call another dog a g...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890729181...</td>\n",
       "      <td>13</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",
       "      <th>8</th>\n",
       "      <td>890609185150312448</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-27 16:25:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Zoey. She doesn't want to be one of th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890609185...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Zoey</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>890240255349198849</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 15:59:51 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Cassie. She is a college pup. Studying...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890240255...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>Cassie</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>890006608113172480</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-26 00:31:25 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Koda. He is a South Australian decksha...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/890006608...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Koda</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>889880896479866881</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 16:11:53 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Bruno. He is a service shark. Only get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889880896...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Bruno</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>889665388333682689</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 01:55:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a puppo that seems to be on the fence a...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889665388...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>889638837579907072</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-25 00:10:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Ted. He does his best. Sometimes that'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889638837...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Ted</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>889531135344209921</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 17:02:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Stuart. He's sporting his favorite fan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889531135...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Stuart</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>puppo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>889278841981685760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-24 00:19:32 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Oliver. You're witnessing one of his m...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/889278841...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Oliver</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>888917238123831296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-23 00:22:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Jim. He found a fren. Taught him how t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888917238...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Jim</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>888804989199671297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 16:56:37 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Zeke. He has a new stick. Very proud o...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888804989...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Zeke</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>888554962724278272</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-22 00:23:06 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Ralphus. He's powering up. Attempting ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888554962...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Ralphus</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>888202515573088257</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 01:02:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Canela. She attempted s...</td>\n",
       "      <td>8.874740e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-07-19 00:47:34 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887473957...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Canela</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>888078434458587136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-20 16:49:33 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Gerald. He was just told he didn't get...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/888078434...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Gerald</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>887705289381826560</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 16:06:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Jeffrey. He has a monopoly on the pool...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887705289...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>887517139158093824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 03:39:09 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>I've yet to rate a Venezuelan Hover Wiener. Th...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887517139...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>such</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>887473957103951883</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-19 00:47:34 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Canela. She attempted some fancy porch...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887473957...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Canela</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>887343217045368832</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 16:08:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>You may not have known you needed to see this ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887343217...</td>\n",
       "      <td>13</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",
       "      <th>25</th>\n",
       "      <td>887101392804085760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-18 00:07:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This... is a Jubilant Antarctic House Bear. We...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/887101392...</td>\n",
       "      <td>12</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",
       "      <th>26</th>\n",
       "      <td>886983233522544640</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-17 16:17:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Maya. She's very shy. Rarely leaves he...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886983233...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Maya</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>886736880519319552</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 23:58:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Mingus. He's a wonderful father to his...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.gofundme.com/mingusneedsus,https:/...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Mingus</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>886680336477933568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-16 20:14:00 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Derek. He's late for a dog meeting. 13...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886680336...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Derek</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>886366144734445568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 23:25:31 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Roscoe. Another pupper fallen victim t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886366144...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Roscoe</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\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",
       "      <th>2326</th>\n",
       "      <td>666411507551481857</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:24:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is quite the dog. Gets really excited whe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666411507...</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>quite</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2327</th>\n",
       "      <td>666407126856765440</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-17 00:06:54 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a southern Vesuvius bumblegruff. Can d...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666407126...</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",
       "      <th>2328</th>\n",
       "      <td>666396247373291520</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 23:23:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh goodness. A super rare northeast Qdoba kang...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666396247...</td>\n",
       "      <td>9</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",
       "      <th>2329</th>\n",
       "      <td>666373753744588802</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:54:18 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Those are sunglasses and a jean jacket. 11/10 ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666373753...</td>\n",
       "      <td>11</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",
       "      <th>2330</th>\n",
       "      <td>666362758909284353</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 21:10:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Unique dog here. Very small. Lives in containe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666362758...</td>\n",
       "      <td>6</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",
       "      <th>2331</th>\n",
       "      <td>666353288456101888</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:32:58 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a mixed Asiago from the Galápagos...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666353288...</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",
       "    <tr>\n",
       "      <th>2332</th>\n",
       "      <td>666345417576210432</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 20:01:42 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Look at this jokester thinking seat belt laws ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666345417...</td>\n",
       "      <td>10</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",
       "      <th>2333</th>\n",
       "      <td>666337882303524864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 19:31:45 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an extremely rare horned Parthenon. No...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666337882...</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2334</th>\n",
       "      <td>666293911632134144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:37:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a funny dog. Weird toes. Won't come do...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666293911...</td>\n",
       "      <td>3</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",
       "      <th>2335</th>\n",
       "      <td>666287406224695296</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 16:11:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an Albanian 3 1/2 legged  Episcopalian...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666287406...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2336</th>\n",
       "      <td>666273097616637952</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 15:14:19 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can take selfies 11/10 https://t.co/ws2AMaNwPW</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666273097...</td>\n",
       "      <td>11</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",
       "      <th>2337</th>\n",
       "      <td>666268910803644416</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 14:57:41 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Very concerned about fellow dog trapped in com...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666268910...</td>\n",
       "      <td>10</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",
       "      <th>2338</th>\n",
       "      <td>666104133288665088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 04:02:55 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Not familiar with this breed. No tail (weird)....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666104133...</td>\n",
       "      <td>1</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",
       "      <th>2339</th>\n",
       "      <td>666102155909144576</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:55:04 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Oh my. Here you are seeing an Adobe Setter giv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666102155...</td>\n",
       "      <td>11</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",
       "      <th>2340</th>\n",
       "      <td>666099513787052032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:44:34 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Can stand on stump for what seems like a while...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666099513...</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",
       "    <tr>\n",
       "      <th>2341</th>\n",
       "      <td>666094000022159362</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 03:22:39 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This appears to be a Mongolian Presbyterian mi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666094000...</td>\n",
       "      <td>9</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",
       "      <th>2342</th>\n",
       "      <td>666082916733198337</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 02:38:37 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a well-established sunblockerspan...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666082916...</td>\n",
       "      <td>6</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",
       "      <th>2343</th>\n",
       "      <td>666073100786774016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:59:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Let's hope this flight isn't Malaysian (lol). ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666073100...</td>\n",
       "      <td>10</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",
       "      <th>2344</th>\n",
       "      <td>666071193221509120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:52:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have a northern speckled Rhododendron....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666071193...</td>\n",
       "      <td>9</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",
       "      <th>2345</th>\n",
       "      <td>666063827256086533</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:22:45 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is the happiest dog you will ever see. Ve...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666063827...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>the</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2346</th>\n",
       "      <td>666058600524156928</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 01:01:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is the Rand Paul of retrievers folks! He'...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666058600...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>the</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2347</th>\n",
       "      <td>666057090499244032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:55:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>My oh my. This is a rare blond Canadian terrie...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666057090...</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",
       "      <th>2348</th>\n",
       "      <td>666055525042405380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:49:46 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here is a Siberian heavily armored polar bear ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666055525...</td>\n",
       "      <td>10</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",
       "      <th>2349</th>\n",
       "      <td>666051853826850816</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:35:11 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is an odd dog. Hard on the outside but lo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666051853...</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>an</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2350</th>\n",
       "      <td>666050758794694657</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-16 00:30:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is a truly beautiful English Wilson Staff...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666050758...</td>\n",
       "      <td>10</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",
       "      <th>2351</th>\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",
       "      <th>2352</th>\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",
       "      <th>2353</th>\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",
       "      <th>2354</th>\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",
       "      <th>2355</th>\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",
       "5     891087950875897856                    NaN                  NaN   \n",
       "6     890971913173991426                    NaN                  NaN   \n",
       "7     890729181411237888                    NaN                  NaN   \n",
       "8     890609185150312448                    NaN                  NaN   \n",
       "9     890240255349198849                    NaN                  NaN   \n",
       "10    890006608113172480                    NaN                  NaN   \n",
       "11    889880896479866881                    NaN                  NaN   \n",
       "12    889665388333682689                    NaN                  NaN   \n",
       "13    889638837579907072                    NaN                  NaN   \n",
       "14    889531135344209921                    NaN                  NaN   \n",
       "15    889278841981685760                    NaN                  NaN   \n",
       "16    888917238123831296                    NaN                  NaN   \n",
       "17    888804989199671297                    NaN                  NaN   \n",
       "18    888554962724278272                    NaN                  NaN   \n",
       "19    888202515573088257                    NaN                  NaN   \n",
       "20    888078434458587136                    NaN                  NaN   \n",
       "21    887705289381826560                    NaN                  NaN   \n",
       "22    887517139158093824                    NaN                  NaN   \n",
       "23    887473957103951883                    NaN                  NaN   \n",
       "24    887343217045368832                    NaN                  NaN   \n",
       "25    887101392804085760                    NaN                  NaN   \n",
       "26    886983233522544640                    NaN                  NaN   \n",
       "27    886736880519319552                    NaN                  NaN   \n",
       "28    886680336477933568                    NaN                  NaN   \n",
       "29    886366144734445568                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "2326  666411507551481857                    NaN                  NaN   \n",
       "2327  666407126856765440                    NaN                  NaN   \n",
       "2328  666396247373291520                    NaN                  NaN   \n",
       "2329  666373753744588802                    NaN                  NaN   \n",
       "2330  666362758909284353                    NaN                  NaN   \n",
       "2331  666353288456101888                    NaN                  NaN   \n",
       "2332  666345417576210432                    NaN                  NaN   \n",
       "2333  666337882303524864                    NaN                  NaN   \n",
       "2334  666293911632134144                    NaN                  NaN   \n",
       "2335  666287406224695296                    NaN                  NaN   \n",
       "2336  666273097616637952                    NaN                  NaN   \n",
       "2337  666268910803644416                    NaN                  NaN   \n",
       "2338  666104133288665088                    NaN                  NaN   \n",
       "2339  666102155909144576                    NaN                  NaN   \n",
       "2340  666099513787052032                    NaN                  NaN   \n",
       "2341  666094000022159362                    NaN                  NaN   \n",
       "2342  666082916733198337                    NaN                  NaN   \n",
       "2343  666073100786774016                    NaN                  NaN   \n",
       "2344  666071193221509120                    NaN                  NaN   \n",
       "2345  666063827256086533                    NaN                  NaN   \n",
       "2346  666058600524156928                    NaN                  NaN   \n",
       "2347  666057090499244032                    NaN                  NaN   \n",
       "2348  666055525042405380                    NaN                  NaN   \n",
       "2349  666051853826850816                    NaN                  NaN   \n",
       "2350  666050758794694657                    NaN                  NaN   \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",
       "5     2017-07-29 00:08:17 +0000   \n",
       "6     2017-07-28 16:27:12 +0000   \n",
       "7     2017-07-28 00:22:40 +0000   \n",
       "8     2017-07-27 16:25:51 +0000   \n",
       "9     2017-07-26 15:59:51 +0000   \n",
       "10    2017-07-26 00:31:25 +0000   \n",
       "11    2017-07-25 16:11:53 +0000   \n",
       "12    2017-07-25 01:55:32 +0000   \n",
       "13    2017-07-25 00:10:02 +0000   \n",
       "14    2017-07-24 17:02:04 +0000   \n",
       "15    2017-07-24 00:19:32 +0000   \n",
       "16    2017-07-23 00:22:39 +0000   \n",
       "17    2017-07-22 16:56:37 +0000   \n",
       "18    2017-07-22 00:23:06 +0000   \n",
       "19    2017-07-21 01:02:36 +0000   \n",
       "20    2017-07-20 16:49:33 +0000   \n",
       "21    2017-07-19 16:06:48 +0000   \n",
       "22    2017-07-19 03:39:09 +0000   \n",
       "23    2017-07-19 00:47:34 +0000   \n",
       "24    2017-07-18 16:08:03 +0000   \n",
       "25    2017-07-18 00:07:08 +0000   \n",
       "26    2017-07-17 16:17:36 +0000   \n",
       "27    2017-07-16 23:58:41 +0000   \n",
       "28    2017-07-16 20:14:00 +0000   \n",
       "29    2017-07-15 23:25:31 +0000   \n",
       "...                         ...   \n",
       "2326  2015-11-17 00:24:19 +0000   \n",
       "2327  2015-11-17 00:06:54 +0000   \n",
       "2328  2015-11-16 23:23:41 +0000   \n",
       "2329  2015-11-16 21:54:18 +0000   \n",
       "2330  2015-11-16 21:10:36 +0000   \n",
       "2331  2015-11-16 20:32:58 +0000   \n",
       "2332  2015-11-16 20:01:42 +0000   \n",
       "2333  2015-11-16 19:31:45 +0000   \n",
       "2334  2015-11-16 16:37:02 +0000   \n",
       "2335  2015-11-16 16:11:11 +0000   \n",
       "2336  2015-11-16 15:14:19 +0000   \n",
       "2337  2015-11-16 14:57:41 +0000   \n",
       "2338  2015-11-16 04:02:55 +0000   \n",
       "2339  2015-11-16 03:55:04 +0000   \n",
       "2340  2015-11-16 03:44:34 +0000   \n",
       "2341  2015-11-16 03:22:39 +0000   \n",
       "2342  2015-11-16 02:38:37 +0000   \n",
       "2343  2015-11-16 01:59:36 +0000   \n",
       "2344  2015-11-16 01:52:02 +0000   \n",
       "2345  2015-11-16 01:22:45 +0000   \n",
       "2346  2015-11-16 01:01:59 +0000   \n",
       "2347  2015-11-16 00:55:59 +0000   \n",
       "2348  2015-11-16 00:49:46 +0000   \n",
       "2349  2015-11-16 00:35:11 +0000   \n",
       "2350  2015-11-16 00:30:50 +0000   \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",
       "5     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "6     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "7     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "8     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "9     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "10    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "11    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "12    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "13    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "14    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "15    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "16    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "17    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "18    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "19    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "20    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "21    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "22    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "23    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "24    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "25    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "26    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "27    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "28    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "29    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "2326  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2327  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2328  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2329  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2330  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2331  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2332  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2333  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2334  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2335  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2336  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2337  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2338  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2339  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2340  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2341  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2342  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2343  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2344  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2345  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2346  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2347  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2348  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2349  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2350  <a href=\"http://twitter.com/download/iphone\" r...   \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",
       "5     Here we have a majestic great white breaching ...                  NaN   \n",
       "6     Meet Jax. He enjoys ice cream so much he gets ...                  NaN   \n",
       "7     When you watch your owner call another dog a g...                  NaN   \n",
       "8     This is Zoey. She doesn't want to be one of th...                  NaN   \n",
       "9     This is Cassie. She is a college pup. Studying...                  NaN   \n",
       "10    This is Koda. He is a South Australian decksha...                  NaN   \n",
       "11    This is Bruno. He is a service shark. Only get...                  NaN   \n",
       "12    Here's a puppo that seems to be on the fence a...                  NaN   \n",
       "13    This is Ted. He does his best. Sometimes that'...                  NaN   \n",
       "14    This is Stuart. He's sporting his favorite fan...                  NaN   \n",
       "15    This is Oliver. You're witnessing one of his m...                  NaN   \n",
       "16    This is Jim. He found a fren. Taught him how t...                  NaN   \n",
       "17    This is Zeke. He has a new stick. Very proud o...                  NaN   \n",
       "18    This is Ralphus. He's powering up. Attempting ...                  NaN   \n",
       "19    RT @dog_rates: This is Canela. She attempted s...         8.874740e+17   \n",
       "20    This is Gerald. He was just told he didn't get...                  NaN   \n",
       "21    This is Jeffrey. He has a monopoly on the pool...                  NaN   \n",
       "22    I've yet to rate a Venezuelan Hover Wiener. Th...                  NaN   \n",
       "23    This is Canela. She attempted some fancy porch...                  NaN   \n",
       "24    You may not have known you needed to see this ...                  NaN   \n",
       "25    This... is a Jubilant Antarctic House Bear. We...                  NaN   \n",
       "26    This is Maya. She's very shy. Rarely leaves he...                  NaN   \n",
       "27    This is Mingus. He's a wonderful father to his...                  NaN   \n",
       "28    This is Derek. He's late for a dog meeting. 13...                  NaN   \n",
       "29    This is Roscoe. Another pupper fallen victim t...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2326  This is quite the dog. Gets really excited whe...                  NaN   \n",
       "2327  This is a southern Vesuvius bumblegruff. Can d...                  NaN   \n",
       "2328  Oh goodness. A super rare northeast Qdoba kang...                  NaN   \n",
       "2329  Those are sunglasses and a jean jacket. 11/10 ...                  NaN   \n",
       "2330  Unique dog here. Very small. Lives in containe...                  NaN   \n",
       "2331  Here we have a mixed Asiago from the Galápagos...                  NaN   \n",
       "2332  Look at this jokester thinking seat belt laws ...                  NaN   \n",
       "2333  This is an extremely rare horned Parthenon. No...                  NaN   \n",
       "2334  This is a funny dog. Weird toes. Won't come do...                  NaN   \n",
       "2335  This is an Albanian 3 1/2 legged  Episcopalian...                  NaN   \n",
       "2336     Can take selfies 11/10 https://t.co/ws2AMaNwPW                  NaN   \n",
       "2337  Very concerned about fellow dog trapped in com...                  NaN   \n",
       "2338  Not familiar with this breed. No tail (weird)....                  NaN   \n",
       "2339  Oh my. Here you are seeing an Adobe Setter giv...                  NaN   \n",
       "2340  Can stand on stump for what seems like a while...                  NaN   \n",
       "2341  This appears to be a Mongolian Presbyterian mi...                  NaN   \n",
       "2342  Here we have a well-established sunblockerspan...                  NaN   \n",
       "2343  Let's hope this flight isn't Malaysian (lol). ...                  NaN   \n",
       "2344  Here we have a northern speckled Rhododendron....                  NaN   \n",
       "2345  This is the happiest dog you will ever see. Ve...                  NaN   \n",
       "2346  Here is the Rand Paul of retrievers folks! He'...                  NaN   \n",
       "2347  My oh my. This is a rare blond Canadian terrie...                  NaN   \n",
       "2348  Here is a Siberian heavily armored polar bear ...                  NaN   \n",
       "2349  This is an odd dog. Hard on the outside but lo...                  NaN   \n",
       "2350  This is a truly beautiful English Wilson Staff...                  NaN   \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",
       "5                          NaN                        NaN   \n",
       "6                          NaN                        NaN   \n",
       "7                          NaN                        NaN   \n",
       "8                          NaN                        NaN   \n",
       "9                          NaN                        NaN   \n",
       "10                         NaN                        NaN   \n",
       "11                         NaN                        NaN   \n",
       "12                         NaN                        NaN   \n",
       "13                         NaN                        NaN   \n",
       "14                         NaN                        NaN   \n",
       "15                         NaN                        NaN   \n",
       "16                         NaN                        NaN   \n",
       "17                         NaN                        NaN   \n",
       "18                         NaN                        NaN   \n",
       "19                4.196984e+09  2017-07-19 00:47:34 +0000   \n",
       "20                         NaN                        NaN   \n",
       "21                         NaN                        NaN   \n",
       "22                         NaN                        NaN   \n",
       "23                         NaN                        NaN   \n",
       "24                         NaN                        NaN   \n",
       "25                         NaN                        NaN   \n",
       "26                         NaN                        NaN   \n",
       "27                         NaN                        NaN   \n",
       "28                         NaN                        NaN   \n",
       "29                         NaN                        NaN   \n",
       "...                        ...                        ...   \n",
       "2326                       NaN                        NaN   \n",
       "2327                       NaN                        NaN   \n",
       "2328                       NaN                        NaN   \n",
       "2329                       NaN                        NaN   \n",
       "2330                       NaN                        NaN   \n",
       "2331                       NaN                        NaN   \n",
       "2332                       NaN                        NaN   \n",
       "2333                       NaN                        NaN   \n",
       "2334                       NaN                        NaN   \n",
       "2335                       NaN                        NaN   \n",
       "2336                       NaN                        NaN   \n",
       "2337                       NaN                        NaN   \n",
       "2338                       NaN                        NaN   \n",
       "2339                       NaN                        NaN   \n",
       "2340                       NaN                        NaN   \n",
       "2341                       NaN                        NaN   \n",
       "2342                       NaN                        NaN   \n",
       "2343                       NaN                        NaN   \n",
       "2344                       NaN                        NaN   \n",
       "2345                       NaN                        NaN   \n",
       "2346                       NaN                        NaN   \n",
       "2347                       NaN                        NaN   \n",
       "2348                       NaN                        NaN   \n",
       "2349                       NaN                        NaN   \n",
       "2350                       NaN                        NaN   \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",
       "5     https://twitter.com/dog_rates/status/891087950...                13   \n",
       "6     https://gofundme.com/ydvmve-surgery-for-jax,ht...                13   \n",
       "7     https://twitter.com/dog_rates/status/890729181...                13   \n",
       "8     https://twitter.com/dog_rates/status/890609185...                13   \n",
       "9     https://twitter.com/dog_rates/status/890240255...                14   \n",
       "10    https://twitter.com/dog_rates/status/890006608...                13   \n",
       "11    https://twitter.com/dog_rates/status/889880896...                13   \n",
       "12    https://twitter.com/dog_rates/status/889665388...                13   \n",
       "13    https://twitter.com/dog_rates/status/889638837...                12   \n",
       "14    https://twitter.com/dog_rates/status/889531135...                13   \n",
       "15    https://twitter.com/dog_rates/status/889278841...                13   \n",
       "16    https://twitter.com/dog_rates/status/888917238...                12   \n",
       "17    https://twitter.com/dog_rates/status/888804989...                13   \n",
       "18    https://twitter.com/dog_rates/status/888554962...                13   \n",
       "19    https://twitter.com/dog_rates/status/887473957...                13   \n",
       "20    https://twitter.com/dog_rates/status/888078434...                12   \n",
       "21    https://twitter.com/dog_rates/status/887705289...                13   \n",
       "22    https://twitter.com/dog_rates/status/887517139...                14   \n",
       "23    https://twitter.com/dog_rates/status/887473957...                13   \n",
       "24    https://twitter.com/dog_rates/status/887343217...                13   \n",
       "25    https://twitter.com/dog_rates/status/887101392...                12   \n",
       "26    https://twitter.com/dog_rates/status/886983233...                13   \n",
       "27    https://www.gofundme.com/mingusneedsus,https:/...                13   \n",
       "28    https://twitter.com/dog_rates/status/886680336...                13   \n",
       "29    https://twitter.com/dog_rates/status/886366144...                12   \n",
       "...                                                 ...               ...   \n",
       "2326  https://twitter.com/dog_rates/status/666411507...                 2   \n",
       "2327  https://twitter.com/dog_rates/status/666407126...                 7   \n",
       "2328  https://twitter.com/dog_rates/status/666396247...                 9   \n",
       "2329  https://twitter.com/dog_rates/status/666373753...                11   \n",
       "2330  https://twitter.com/dog_rates/status/666362758...                 6   \n",
       "2331  https://twitter.com/dog_rates/status/666353288...                 8   \n",
       "2332  https://twitter.com/dog_rates/status/666345417...                10   \n",
       "2333  https://twitter.com/dog_rates/status/666337882...                 9   \n",
       "2334  https://twitter.com/dog_rates/status/666293911...                 3   \n",
       "2335  https://twitter.com/dog_rates/status/666287406...                 1   \n",
       "2336  https://twitter.com/dog_rates/status/666273097...                11   \n",
       "2337  https://twitter.com/dog_rates/status/666268910...                10   \n",
       "2338  https://twitter.com/dog_rates/status/666104133...                 1   \n",
       "2339  https://twitter.com/dog_rates/status/666102155...                11   \n",
       "2340  https://twitter.com/dog_rates/status/666099513...                 8   \n",
       "2341  https://twitter.com/dog_rates/status/666094000...                 9   \n",
       "2342  https://twitter.com/dog_rates/status/666082916...                 6   \n",
       "2343  https://twitter.com/dog_rates/status/666073100...                10   \n",
       "2344  https://twitter.com/dog_rates/status/666071193...                 9   \n",
       "2345  https://twitter.com/dog_rates/status/666063827...                10   \n",
       "2346  https://twitter.com/dog_rates/status/666058600...                 8   \n",
       "2347  https://twitter.com/dog_rates/status/666057090...                 9   \n",
       "2348  https://twitter.com/dog_rates/status/666055525...                10   \n",
       "2349  https://twitter.com/dog_rates/status/666051853...                 2   \n",
       "2350  https://twitter.com/dog_rates/status/666050758...                10   \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",
       "5                     10      None   None    None    None   None  \n",
       "6                     10       Jax   None    None    None   None  \n",
       "7                     10      None   None    None    None   None  \n",
       "8                     10      Zoey   None    None    None   None  \n",
       "9                     10    Cassie  doggo    None    None   None  \n",
       "10                    10      Koda   None    None    None   None  \n",
       "11                    10     Bruno   None    None    None   None  \n",
       "12                    10      None   None    None    None  puppo  \n",
       "13                    10       Ted   None    None    None   None  \n",
       "14                    10    Stuart   None    None    None  puppo  \n",
       "15                    10    Oliver   None    None    None   None  \n",
       "16                    10       Jim   None    None    None   None  \n",
       "17                    10      Zeke   None    None    None   None  \n",
       "18                    10   Ralphus   None    None    None   None  \n",
       "19                    10    Canela   None    None    None   None  \n",
       "20                    10    Gerald   None    None    None   None  \n",
       "21                    10   Jeffrey   None    None    None   None  \n",
       "22                    10      such   None    None    None   None  \n",
       "23                    10    Canela   None    None    None   None  \n",
       "24                    10      None   None    None    None   None  \n",
       "25                    10      None   None    None    None   None  \n",
       "26                    10      Maya   None    None    None   None  \n",
       "27                    10    Mingus   None    None    None   None  \n",
       "28                    10     Derek   None    None    None   None  \n",
       "29                    10    Roscoe   None    None  pupper   None  \n",
       "...                  ...       ...    ...     ...     ...    ...  \n",
       "2326                  10     quite   None    None    None   None  \n",
       "2327                  10         a   None    None    None   None  \n",
       "2328                  10      None   None    None    None   None  \n",
       "2329                  10      None   None    None    None   None  \n",
       "2330                  10      None   None    None    None   None  \n",
       "2331                  10      None   None    None    None   None  \n",
       "2332                  10      None   None    None    None   None  \n",
       "2333                  10        an   None    None    None   None  \n",
       "2334                  10         a   None    None    None   None  \n",
       "2335                   2        an   None    None    None   None  \n",
       "2336                  10      None   None    None    None   None  \n",
       "2337                  10      None   None    None    None   None  \n",
       "2338                  10      None   None    None    None   None  \n",
       "2339                  10      None   None    None    None   None  \n",
       "2340                  10      None   None    None    None   None  \n",
       "2341                  10      None   None    None    None   None  \n",
       "2342                  10      None   None    None    None   None  \n",
       "2343                  10      None   None    None    None   None  \n",
       "2344                  10      None   None    None    None   None  \n",
       "2345                  10       the   None    None    None   None  \n",
       "2346                  10       the   None    None    None   None  \n",
       "2347                  10         a   None    None    None   None  \n",
       "2348                  10         a   None    None    None   None  \n",
       "2349                  10        an   None    None    None   None  \n",
       "2350                  10         a   None    None    None   None  \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": [
    "df_twitter_archive"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>803</th>\n",
       "      <td>772152991789019136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-03 19:23:13 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here's a couple rufferees making sure all the ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/772152991...</td>\n",
       "      <td>10</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",
       "      <th>0</th>\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",
       "      <th>1154</th>\n",
       "      <td>725458796924002305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-04-27 22:57:10 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Pup had to be removed cuz it wouldn't have bee...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/foxdeportes/status/7251360...</td>\n",
       "      <td>13</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",
       "      <th>2229</th>\n",
       "      <td>668248472370458624</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-22 02:03:45 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Say hello to Bisquick. He is a Brown Douglass ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/668248472...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>Bisquick</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>308</th>\n",
       "      <td>835574547218894849</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-25 19:37:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Eli. He works backstage at Bone Jovi c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/835574547...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Eli</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>815</th>\n",
       "      <td>771004394259247104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-08-31 15:19:06 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @katieornah: @dog_rates learning a lot at c...</td>\n",
       "      <td>7.710021e+17</td>\n",
       "      <td>1.732729e+09</td>\n",
       "      <td>2016-08-31 15:10:07 +0000</td>\n",
       "      <td>https://twitter.com/katieornah/status/77100213...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2080</th>\n",
       "      <td>670823764196741120</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-29 04:37:03 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Remington. He's a man dime. 12/10 http...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/670823764...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Remington</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>317</th>\n",
       "      <td>834786237630337024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-23 15:25:23 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Tobi. She is properly fetching her sho...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/834786237...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tobi</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>695074328191332352</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-02-04 02:40:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Lorenzo. He's educated af. Just gradua...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/695074328...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Lorenzo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pupper</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1572</th>\n",
       "      <td>687664829264453632</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-01-14 15:57:26 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Opal. He's a Belgian Dijon Poofster. Upse...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/687664829...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Opal</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",
       "803   772152991789019136                    NaN                  NaN   \n",
       "0     892420643555336193                    NaN                  NaN   \n",
       "1154  725458796924002305                    NaN                  NaN   \n",
       "2229  668248472370458624                    NaN                  NaN   \n",
       "308   835574547218894849                    NaN                  NaN   \n",
       "815   771004394259247104                    NaN                  NaN   \n",
       "2080  670823764196741120                    NaN                  NaN   \n",
       "317   834786237630337024                    NaN                  NaN   \n",
       "1458  695074328191332352                    NaN                  NaN   \n",
       "1572  687664829264453632                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "803   2016-09-03 19:23:13 +0000   \n",
       "0     2017-08-01 16:23:56 +0000   \n",
       "1154  2016-04-27 22:57:10 +0000   \n",
       "2229  2015-11-22 02:03:45 +0000   \n",
       "308   2017-02-25 19:37:50 +0000   \n",
       "815   2016-08-31 15:19:06 +0000   \n",
       "2080  2015-11-29 04:37:03 +0000   \n",
       "317   2017-02-23 15:25:23 +0000   \n",
       "1458  2016-02-04 02:40:08 +0000   \n",
       "1572  2016-01-14 15:57:26 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "803   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "0     <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1154  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2229  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "308   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "815   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2080  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "317   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1458  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1572  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "803   Here's a couple rufferees making sure all the ...                  NaN   \n",
       "0     This is Phineas. He's a mystical boy. Only eve...                  NaN   \n",
       "1154  Pup had to be removed cuz it wouldn't have bee...                  NaN   \n",
       "2229  Say hello to Bisquick. He is a Brown Douglass ...                  NaN   \n",
       "308   This is Eli. He works backstage at Bone Jovi c...                  NaN   \n",
       "815   RT @katieornah: @dog_rates learning a lot at c...         7.710021e+17   \n",
       "2080  This is Remington. He's a man dime. 12/10 http...                  NaN   \n",
       "317   This is Tobi. She is properly fetching her sho...                  NaN   \n",
       "1458  This is Lorenzo. He's educated af. Just gradua...                  NaN   \n",
       "1572  Meet Opal. He's a Belgian Dijon Poofster. Upse...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "803                        NaN                        NaN   \n",
       "0                          NaN                        NaN   \n",
       "1154                       NaN                        NaN   \n",
       "2229                       NaN                        NaN   \n",
       "308                        NaN                        NaN   \n",
       "815               1.732729e+09  2016-08-31 15:10:07 +0000   \n",
       "2080                       NaN                        NaN   \n",
       "317                        NaN                        NaN   \n",
       "1458                       NaN                        NaN   \n",
       "1572                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "803   https://twitter.com/dog_rates/status/772152991...                10   \n",
       "0     https://twitter.com/dog_rates/status/892420643...                13   \n",
       "1154  https://twitter.com/foxdeportes/status/7251360...                13   \n",
       "2229  https://twitter.com/dog_rates/status/668248472...                 8   \n",
       "308   https://twitter.com/dog_rates/status/835574547...                11   \n",
       "815   https://twitter.com/katieornah/status/77100213...                12   \n",
       "2080  https://twitter.com/dog_rates/status/670823764...                12   \n",
       "317   https://twitter.com/dog_rates/status/834786237...                13   \n",
       "1458  https://twitter.com/dog_rates/status/695074328...                11   \n",
       "1572  https://twitter.com/dog_rates/status/687664829...                11   \n",
       "\n",
       "      rating_denominator       name doggo floofer  pupper puppo  \n",
       "803                   10       None  None    None    None  None  \n",
       "0                     10    Phineas  None    None    None  None  \n",
       "1154                  10       None  None    None    None  None  \n",
       "2229                  10   Bisquick  None    None    None  None  \n",
       "308                   10        Eli  None    None    None  None  \n",
       "815                   10       None  None    None  pupper  None  \n",
       "2080                  10  Remington  None    None    None  None  \n",
       "317                   10       Tobi  None    None    None  None  \n",
       "1458                  10    Lorenzo  None    None  pupper  None  \n",
       "1572                  10       Opal  None    None    None  None  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "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": [
    "df_twitter_archive.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "59"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive['expanded_urls'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None         745\n",
       "a             55\n",
       "Charlie       12\n",
       "Cooper        11\n",
       "Oliver        11\n",
       "Lucy          11\n",
       "Penny         10\n",
       "Tucker        10\n",
       "Lola          10\n",
       "Bo             9\n",
       "Winston        9\n",
       "Sadie          8\n",
       "the            8\n",
       "an             7\n",
       "Bailey         7\n",
       "Daisy          7\n",
       "Buddy          7\n",
       "Toby           7\n",
       "Scout          6\n",
       "Oscar          6\n",
       "Leo            6\n",
       "Koda           6\n",
       "Jack           6\n",
       "Rusty          6\n",
       "Dave           6\n",
       "Jax            6\n",
       "Milo           6\n",
       "Stanley        6\n",
       "Bella          6\n",
       "George         5\n",
       "            ... \n",
       "Shadoe         1\n",
       "Ronnie         1\n",
       "Marty          1\n",
       "Hubertson      1\n",
       "Meatball       1\n",
       "Rumble         1\n",
       "Samsom         1\n",
       "light          1\n",
       "Grizzwald      1\n",
       "Sprout         1\n",
       "Pupcasso       1\n",
       "Pherb          1\n",
       "Striker        1\n",
       "Fabio          1\n",
       "Tessa          1\n",
       "Jangle         1\n",
       "Maxwell        1\n",
       "Noah           1\n",
       "Geno           1\n",
       "Mya            1\n",
       "Rilo           1\n",
       "Pip            1\n",
       "Herb           1\n",
       "Bauer          1\n",
       "Ebby           1\n",
       "Godzilla       1\n",
       "Lugan          1\n",
       "Barney         1\n",
       "Kallie         1\n",
       "Ben            1\n",
       "Name: name, Length: 957, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive['name'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive['rating_denominator'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive['rating_numerator'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive['rating_denominator'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**observations**\n",
    "\n",
    "quality issues:\n",
    "- Name column has \"None\", \"a\", \"the\", and \"an\" names that are not real names\n",
    "- timestamp date is incorrect format(unecessary +0000 in date). The timestamp data type is wrong; object should be changed to time\n",
    "- data type of tweet_id should be string instead of object\n",
    "- there are 59 null entries in the expanded_urls column\n",
    "- rating_denominator column should only have one denominator value - 10 \n",
    "- rating_numerator have values lower than 10 that should be removed.\n",
    "- some ratings can be extracted from the text of the tweet and be used to fill in the rating_numerator column<br />\n",
    "\n",
    "tidiness issues:<br />\n",
    "- in_reply_to_status_id, in_reply_to_user_id, retweeted_status_id, retweeted_status_user_id, and retweeted_status_timestamp columns have null values in them. This is an issue because we want only the original tweets. We will drop these columns later in the project."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **image_predictions assessments**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2075 entries, 0 to 2074\n",
      "Data columns (total 12 columns):\n",
      "tweet_id    2075 non-null int64\n",
      "jpg_url     2075 non-null object\n",
      "img_num     2075 non-null int64\n",
      "p1          2075 non-null object\n",
      "p1_conf     2075 non-null float64\n",
      "p1_dog      2075 non-null bool\n",
      "p2          2075 non-null object\n",
      "p2_conf     2075 non-null float64\n",
      "p2_dog      2075 non-null bool\n",
      "p3          2075 non-null object\n",
      "p3_conf     2075 non-null float64\n",
      "p3_dog      2075 non-null bool\n",
      "dtypes: bool(3), float64(3), int64(2), object(4)\n",
      "memory usage: 152.1+ KB\n"
     ]
    }
   ],
   "source": [
    "image_predictions.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>192</th>\n",
       "      <td>669567591774625800</td>\n",
       "      <td>https://pbs.twimg.com/media/CUrIK1DWoAAhECq.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.980511</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.009166</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_pinscher</td>\n",
       "      <td>0.002659</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1507</th>\n",
       "      <td>785639753186217984</td>\n",
       "      <td>https://pbs.twimg.com/media/CucnLmeWAAALOSC.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>porcupine</td>\n",
       "      <td>0.978042</td>\n",
       "      <td>False</td>\n",
       "      <td>sea_urchin</td>\n",
       "      <td>0.006106</td>\n",
       "      <td>False</td>\n",
       "      <td>echidna</td>\n",
       "      <td>0.005442</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>448</th>\n",
       "      <td>674690135443775488</td>\n",
       "      <td>https://pbs.twimg.com/media/CVz7FxXWUAAlTRP.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>tick</td>\n",
       "      <td>0.242538</td>\n",
       "      <td>False</td>\n",
       "      <td>nail</td>\n",
       "      <td>0.212589</td>\n",
       "      <td>False</td>\n",
       "      <td>screw</td>\n",
       "      <td>0.172838</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>417</th>\n",
       "      <td>674024893172875264</td>\n",
       "      <td>https://pbs.twimg.com/media/CVqeEKLW4AA1wXH.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Pomeranian</td>\n",
       "      <td>0.648500</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.339835</td>\n",
       "      <td>True</td>\n",
       "      <td>Persian_cat</td>\n",
       "      <td>0.006448</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>707059547140169728</td>\n",
       "      <td>https://pbs.twimg.com/media/Cc_64zVWEAAeXs7.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Samoyed</td>\n",
       "      <td>0.897312</td>\n",
       "      <td>True</td>\n",
       "      <td>Great_Pyrenees</td>\n",
       "      <td>0.039180</td>\n",
       "      <td>True</td>\n",
       "      <td>kuvasz</td>\n",
       "      <td>0.019516</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>645</th>\n",
       "      <td>681610798867845120</td>\n",
       "      <td>https://pbs.twimg.com/media/CXWRZBgWkAEHMea.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>toy_poodle</td>\n",
       "      <td>0.821704</td>\n",
       "      <td>True</td>\n",
       "      <td>miniature_poodle</td>\n",
       "      <td>0.116042</td>\n",
       "      <td>True</td>\n",
       "      <td>Yorkshire_terrier</td>\n",
       "      <td>0.014847</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1792</th>\n",
       "      <td>830956169170665475</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/83095...</td>\n",
       "      <td>1</td>\n",
       "      <td>kuvasz</td>\n",
       "      <td>0.451516</td>\n",
       "      <td>True</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.317196</td>\n",
       "      <td>True</td>\n",
       "      <td>English_setter</td>\n",
       "      <td>0.132759</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>671561002136281088</td>\n",
       "      <td>https://pbs.twimg.com/media/CVHdK-7WwAAsuyc.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Gordon_setter</td>\n",
       "      <td>0.469373</td>\n",
       "      <td>True</td>\n",
       "      <td>black-and-tan_coonhound</td>\n",
       "      <td>0.270893</td>\n",
       "      <td>True</td>\n",
       "      <td>Rottweiler</td>\n",
       "      <td>0.153233</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>584</th>\n",
       "      <td>678969228704284672</td>\n",
       "      <td>https://pbs.twimg.com/media/CWwu6OLUkAEo3gq.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.680251</td>\n",
       "      <td>True</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.201697</td>\n",
       "      <td>True</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.019676</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\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",
       "192   669567591774625800    https://pbs.twimg.com/media/CUrIK1DWoAAhECq.jpg   \n",
       "1507  785639753186217984    https://pbs.twimg.com/media/CucnLmeWAAALOSC.jpg   \n",
       "448   674690135443775488    https://pbs.twimg.com/media/CVz7FxXWUAAlTRP.jpg   \n",
       "417   674024893172875264    https://pbs.twimg.com/media/CVqeEKLW4AA1wXH.jpg   \n",
       "978   707059547140169728    https://pbs.twimg.com/media/Cc_64zVWEAAeXs7.jpg   \n",
       "645   681610798867845120    https://pbs.twimg.com/media/CXWRZBgWkAEHMea.jpg   \n",
       "1792  830956169170665475  https://pbs.twimg.com/ext_tw_video_thumb/83095...   \n",
       "313   671561002136281088    https://pbs.twimg.com/media/CVHdK-7WwAAsuyc.jpg   \n",
       "584   678969228704284672    https://pbs.twimg.com/media/CWwu6OLUkAEo3gq.jpg   \n",
       "4     666049248165822465    https://pbs.twimg.com/media/CT5IQmsXIAAKY4A.jpg   \n",
       "\n",
       "      img_num                  p1   p1_conf  p1_dog                        p2  \\\n",
       "192         1           Chihuahua  0.980511    True               toy_terrier   \n",
       "1507        1           porcupine  0.978042   False                sea_urchin   \n",
       "448         1                tick  0.242538   False                      nail   \n",
       "417         1          Pomeranian  0.648500    True                  Pekinese   \n",
       "978         1             Samoyed  0.897312    True            Great_Pyrenees   \n",
       "645         1          toy_poodle  0.821704    True          miniature_poodle   \n",
       "1792        1              kuvasz  0.451516    True          golden_retriever   \n",
       "313         1       Gordon_setter  0.469373    True   black-and-tan_coonhound   \n",
       "584         1  Labrador_retriever  0.680251    True  Chesapeake_Bay_retriever   \n",
       "4           1  miniature_pinscher  0.560311    True                Rottweiler   \n",
       "\n",
       "       p2_conf  p2_dog                  p3   p3_conf  p3_dog  \n",
       "192   0.009166    True  miniature_pinscher  0.002659    True  \n",
       "1507  0.006106   False             echidna  0.005442   False  \n",
       "448   0.212589   False               screw  0.172838   False  \n",
       "417   0.339835    True         Persian_cat  0.006448   False  \n",
       "978   0.039180    True              kuvasz  0.019516    True  \n",
       "645   0.116042    True   Yorkshire_terrier  0.014847    True  \n",
       "1792  0.317196    True      English_setter  0.132759    True  \n",
       "313   0.270893    True          Rottweiler  0.153233    True  \n",
       "584   0.201697    True    golden_retriever  0.019676    True  \n",
       "4     0.243682    True            Doberman  0.154629    True  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_predictions.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**observations** <br />\n",
    "\n",
    "quality issues:<br />\n",
    "- some names of dogs are capitalized and some are not in the p1, p2, and p3 columns\n",
    "\n",
    "tidiness issues: <br />\n",
    "- df_twitter_archive, image predictions, and df_json can be combined into one table since they all describe one tweet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **df_json assessments**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>tweet_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38044</td>\n",
       "      <td>8321</td>\n",
       "      <td>892420643555336193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>32670</td>\n",
       "      <td>6148</td>\n",
       "      <td>892177421306343426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>30108</td>\n",
       "      <td>7178</td>\n",
       "      <td>890006608113172480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>40160</td>\n",
       "      <td>8939</td>\n",
       "      <td>872486979161796608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>10070</td>\n",
       "      <td>4280</td>\n",
       "      <td>747103485104099331</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      favorite_count  retweet_count            tweet_id\n",
       "0              38044           8321  892420643555336193\n",
       "1              32670           6148  892177421306343426\n",
       "10             30108           7178  890006608113172480\n",
       "100            40160           8939  872486979161796608\n",
       "1000           10070           4280  747103485104099331"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_json.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2340 entries, 0 to 2339\n",
      "Data columns (total 4 columns):\n",
      "Unnamed: 0        2340 non-null int64\n",
      "tweet_id          2340 non-null int64\n",
      "retweet_count     2340 non-null int64\n",
      "favorite_count    2340 non-null int64\n",
      "dtypes: int64(4)\n",
      "memory usage: 73.2 KB\n"
     ]
    }
   ],
   "source": [
    "df_json.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**observations**<br />\n",
    "\n",
    "tidiness issues: <br />\n",
    "- \"Unamed: 0\" column should be dropped since it is only an index column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clean Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a copy of the dataframes before starting the cleaning process\n",
    "df_twitter_archive_clean = df_twitter_archive.copy()\n",
    "image_predictions_clean = image_predictions.copy()\n",
    "df_json_clean = df_json.copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean 8 Quality Issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #1:**<br />\n",
    "\n",
    "**Define** <br />\n",
    "Dog names \"None\", \"a\", \"the\" and \"an\" should be replaced"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replace the dog names that are not names to NaN. There are many more dog names that are not really dog names \n",
    "# but for this example, we will only clean the ones found in the value_counts listing from the assessments above\n",
    "df_twitter_archive_clean['name'].replace(\"None\", \"NaN\", inplace= True)\n",
    "df_twitter_archive_clean['name'].replace(\"a\", \"NaN\", inplace= True)\n",
    "df_twitter_archive_clean['name'].replace(\"the\", \"NaN\", inplace= True)\n",
    "df_twitter_archive_clean['name'].replace(\"an\", \"NaN\", inplace= True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'None' in df_twitter_archive_clean['name']\n",
    "'a' in df_twitter_archive_clean['name']\n",
    "'the' in df_twitter_archive_clean['name']\n",
    "'an' in df_twitter_archive_clean['name']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #2:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "Timestamp format is incorrect. Change timestamp data type from object to datetime. The +0000 will drop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_archive_clean['timestamp'] = pd.to_datetime(df_twitter_archive_clean['timestamp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56</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",
       "      <th>1</th>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27</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",
       "      <th>2</th>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03</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",
       "      <th>3</th>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51</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",
       "      <th>4</th>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24</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                                             source  \\\n",
       "0 2017-08-01 16:23:56  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1 2017-08-01 00:17:27  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2 2017-07-31 00:18:03  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "3 2017-07-30 15:58:51  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "4 2017-07-29 16:00:24  <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": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive_clean.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #3:**<br />\n",
    "\n",
    "**Define** <br />\n",
    "Data type of tweet_id should be string, not object. We need to change the tweet_id of image_predictions_clean dataframe and df_json_clean dataframe to string as well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_archive_clean.tweet_id = df_twitter_archive_clean.tweet_id.astype(str)\n",
    "image_predictions_clean.tweet_id = image_predictions_clean.tweet_id.astype(str)\n",
    "df_json_clean.tweet_id = df_json_clean.tweet_id.astype(str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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 object\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 datetime64[ns]\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: datetime64[ns](1), float64(4), int64(2), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_archive_clean.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #4:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "The expanded_urls column has null values that need to be dropped. There are 59 total that we observed from the assessments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Drop the null values in the expanded_urls column\n",
    "df_twitter_archive_clean[\"expanded_urls\"].dropna(inplace= True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"NaN\" in df_twitter_archive_clean[\"expanded_urls\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #5:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "The rating_denominator column should only have the denominator 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_archive_clean[\"rating_denominator\"] = 10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10    2356\n",
       "Name: rating_denominator, dtype: int64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive_clean.rating_denominator.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #6:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "The numerator column should exclude numbers less than 10 but just for an example, we will only exclude the values 0, 1, and 2. There should be 20 entries excluded based on the assessments we have done but because we have already started cleaning and dropping columns and rows, there are only 15 entries to be excluded now."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Recreate the dataframe by excluding the rating_numerator that are equal to 0, 1, and 2\n",
    "df_twitter_archive_clean = df_twitter_archive_clean[df_twitter_archive_clean.rating_numerator != 0]\n",
    "df_twitter_archive_clean = df_twitter_archive_clean[df_twitter_archive_clean.rating_numerator != 1]\n",
    "df_twitter_archive_clean = df_twitter_archive_clean[df_twitter_archive_clean.rating_numerator != 2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "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",
       "420       2\n",
       "15        2\n",
       "75        2\n",
       "17        1\n",
       "121       1\n",
       "99        1\n",
       "45        1\n",
       "27        1\n",
       "20        1\n",
       "24        1\n",
       "26        1\n",
       "44        1\n",
       "50        1\n",
       "60        1\n",
       "80        1\n",
       "84        1\n",
       "88        1\n",
       "144       1\n",
       "182       1\n",
       "204       1\n",
       "143       1\n",
       "666       1\n",
       "960       1\n",
       "1776      1\n",
       "165       1\n",
       "Name: rating_numerator, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive_clean['rating_numerator'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #7:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "We can extract numerator ratings from the tweet text and fill the missing values in rating_numerator column by finding the pattern ##.##"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_archive_clean['rating_numerator'] = df_twitter_archive_clean.text.str.extract('(\\d?\\d*\\.?\\d\\d*/)', expand=False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    }\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",
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       "      <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",
       "      <th>1712</th>\n",
       "      <td>680494726643068929</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-25 21:06:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Here we have uncovered an entire battalion of ...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/680494726...</td>\n",
       "      <td>11.26/</td>\n",
       "      <td>10</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": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "1712  680494726643068929                    NaN                  NaN   \n",
       "\n",
       "               timestamp                                             source  \\\n",
       "1712 2015-12-25 21:06:00  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "1712  Here we have uncovered an entire battalion of ...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "1712                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls rating_numerator  \\\n",
       "1712  https://twitter.com/dog_rates/status/680494726...           11.26/   \n",
       "\n",
       "      rating_denominator name doggo floofer pupper puppo  \n",
       "1712                  10  NaN  None    None   None  None  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive_clean[df_twitter_archive_clean['tweet_id']=='680494726643068929']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Define**<br />\n",
    "\n",
    "Replace the / character from the rating_numerator column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_archive_clean['rating_numerator'].replace('/','', regex=True, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
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       "      <th>rating_denominator</th>\n",
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       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
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       "      <td>10</td>\n",
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       "      <td>None</td>\n",
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       "      <td>None</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "1712  680494726643068929                    NaN                  NaN   \n",
       "\n",
       "               timestamp                                             source  \\\n",
       "1712 2015-12-25 21:06:00  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "1712  Here we have uncovered an entire battalion of ...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "1712                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls rating_numerator  \\\n",
       "1712  https://twitter.com/dog_rates/status/680494726...            11.26   \n",
       "\n",
       "      rating_denominator name doggo floofer pupper puppo  \n",
       "1712                  10  NaN  None    None   None  None  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_archive_clean[df_twitter_archive_clean['tweet_id']=='680494726643068929']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #8:** <br />\n",
    "\n",
    "**Define**<br />\n",
    "There are capitalized and lower cased names in the p1, p2, and p3 columns. Replace all dog names in these columns with a lower case letter."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_predictions_clean['p1'] = image_predictions_clean['p1'].str.lower()\n",
    "image_predictions_clean['p2'] = image_predictions_clean['p2'].str.lower()\n",
    "image_predictions_clean['p3'] = image_predictions_clean['p3'].str.lower()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>218</th>\n",
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       "      <td>https://pbs.twimg.com/media/CUyUSuWXIAAZKYF.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.601886</td>\n",
       "      <td>True</td>\n",
       "      <td>siberian_husky</td>\n",
       "      <td>0.340106</td>\n",
       "      <td>True</td>\n",
       "      <td>eskimo_dog</td>\n",
       "      <td>0.050041</td>\n",
       "      <td>True</td>\n",
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       "      <td>https://pbs.twimg.com/media/CUoFZTyW4AE70iD.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>teddy</td>\n",
       "      <td>0.379656</td>\n",
       "      <td>False</td>\n",
       "      <td>pembroke</td>\n",
       "      <td>0.212343</td>\n",
       "      <td>True</td>\n",
       "      <td>chow</td>\n",
       "      <td>0.096995</td>\n",
       "      <td>True</td>\n",
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       "      <td>minivan</td>\n",
       "      <td>0.789376</td>\n",
       "      <td>False</td>\n",
       "      <td>beach_wagon</td>\n",
       "      <td>0.081125</td>\n",
       "      <td>False</td>\n",
       "      <td>convertible</td>\n",
       "      <td>0.064534</td>\n",
       "      <td>False</td>\n",
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       "      <th>182</th>\n",
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       "      <td>https://pbs.twimg.com/media/CUoDk8mWsAAMyBL.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>cuirass</td>\n",
       "      <td>0.756829</td>\n",
       "      <td>False</td>\n",
       "      <td>breastplate</td>\n",
       "      <td>0.233520</td>\n",
       "      <td>False</td>\n",
       "      <td>bulletproof_vest</td>\n",
       "      <td>0.003812</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1728</th>\n",
       "      <td>820690176645140481</td>\n",
       "      <td>https://pbs.twimg.com/media/C2OtWr0VQAEnS9r.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>west_highland_white_terrier</td>\n",
       "      <td>0.872064</td>\n",
       "      <td>True</td>\n",
       "      <td>kuvasz</td>\n",
       "      <td>0.059526</td>\n",
       "      <td>True</td>\n",
       "      <td>samoyed</td>\n",
       "      <td>0.037400</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>675878199931371520</td>\n",
       "      <td>https://pbs.twimg.com/media/CWEzo19WoAEiOCj.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>wood_rabbit</td>\n",
       "      <td>0.785756</td>\n",
       "      <td>False</td>\n",
       "      <td>hare</td>\n",
       "      <td>0.118181</td>\n",
       "      <td>False</td>\n",
       "      <td>cardigan</td>\n",
       "      <td>0.043627</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>708119489313951744</td>\n",
       "      <td>https://pbs.twimg.com/media/CdO-6x5W8AENSBJ.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>norwich_terrier</td>\n",
       "      <td>0.264483</td>\n",
       "      <td>True</td>\n",
       "      <td>norfolk_terrier</td>\n",
       "      <td>0.258786</td>\n",
       "      <td>True</td>\n",
       "      <td>chow</td>\n",
       "      <td>0.096899</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>718613305783398402</td>\n",
       "      <td>https://pbs.twimg.com/media/CfkG_PMWsAAH0MZ.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>labrador_retriever</td>\n",
       "      <td>0.584580</td>\n",
       "      <td>True</td>\n",
       "      <td>german_short-haired_pointer</td>\n",
       "      <td>0.340657</td>\n",
       "      <td>True</td>\n",
       "      <td>chesapeake_bay_retriever</td>\n",
       "      <td>0.031975</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1466</th>\n",
       "      <td>778650543019483137</td>\n",
       "      <td>https://pbs.twimg.com/media/Cs5ShihWEAAH2ti.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>german_shepherd</td>\n",
       "      <td>0.515699</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.300292</td>\n",
       "      <td>True</td>\n",
       "      <td>kelpie</td>\n",
       "      <td>0.087022</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>668826086256599040</td>\n",
       "      <td>https://pbs.twimg.com/media/CUglxbFXAAA5O0d.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.640185</td>\n",
       "      <td>True</td>\n",
       "      <td>irish_terrier</td>\n",
       "      <td>0.153700</td>\n",
       "      <td>True</td>\n",
       "      <td>rhodesian_ridgeback</td>\n",
       "      <td>0.068457</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                          jpg_url  \\\n",
       "218   670073503555706880  https://pbs.twimg.com/media/CUyUSuWXIAAZKYF.jpg   \n",
       "183   669353438988365824  https://pbs.twimg.com/media/CUoFZTyW4AE70iD.jpg   \n",
       "1611  801285448605831168  https://pbs.twimg.com/media/Cx683NPUAAAjyU4.jpg   \n",
       "182   669351434509529089  https://pbs.twimg.com/media/CUoDk8mWsAAMyBL.jpg   \n",
       "1728  820690176645140481  https://pbs.twimg.com/media/C2OtWr0VQAEnS9r.jpg   \n",
       "503   675878199931371520  https://pbs.twimg.com/media/CWEzo19WoAEiOCj.jpg   \n",
       "993   708119489313951744  https://pbs.twimg.com/media/CdO-6x5W8AENSBJ.jpg   \n",
       "1085  718613305783398402  https://pbs.twimg.com/media/CfkG_PMWsAAH0MZ.jpg   \n",
       "1466  778650543019483137  https://pbs.twimg.com/media/Cs5ShihWEAAH2ti.jpg   \n",
       "156   668826086256599040  https://pbs.twimg.com/media/CUglxbFXAAA5O0d.jpg   \n",
       "\n",
       "      img_num                           p1   p1_conf  p1_dog  \\\n",
       "218         1                     malamute  0.601886    True   \n",
       "183         1                        teddy  0.379656   False   \n",
       "1611        1                      minivan  0.789376   False   \n",
       "182         1                      cuirass  0.756829   False   \n",
       "1728        2  west_highland_white_terrier  0.872064    True   \n",
       "503         1                  wood_rabbit  0.785756   False   \n",
       "993         1              norwich_terrier  0.264483    True   \n",
       "1085        1           labrador_retriever  0.584580    True   \n",
       "1466        1              german_shepherd  0.515699    True   \n",
       "156         1                     malinois  0.640185    True   \n",
       "\n",
       "                               p2   p2_conf  p2_dog                        p3  \\\n",
       "218                siberian_husky  0.340106    True                eskimo_dog   \n",
       "183                      pembroke  0.212343    True                      chow   \n",
       "1611                  beach_wagon  0.081125   False               convertible   \n",
       "182                   breastplate  0.233520   False          bulletproof_vest   \n",
       "1728                       kuvasz  0.059526    True                   samoyed   \n",
       "503                          hare  0.118181   False                  cardigan   \n",
       "993               norfolk_terrier  0.258786    True                      chow   \n",
       "1085  german_short-haired_pointer  0.340657    True  chesapeake_bay_retriever   \n",
       "1466                     malinois  0.300292    True                    kelpie   \n",
       "156                 irish_terrier  0.153700    True       rhodesian_ridgeback   \n",
       "\n",
       "       p3_conf  p3_dog  \n",
       "218   0.050041    True  \n",
       "183   0.096995    True  \n",
       "1611  0.064534   False  \n",
       "182   0.003812   False  \n",
       "1728  0.037400    True  \n",
       "503   0.043627    True  \n",
       "993   0.096899    True  \n",
       "1085  0.031975    True  \n",
       "1466  0.087022    True  \n",
       "156   0.068457    True  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image_predictions_clean.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean 2 Tidiness Issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #1:**<br />\n",
    "\n",
    "**Define** <br />\n",
    "Remove the retweeted images because we only want original tweets. We will drop the columns in_reply_to_status_id, in_reply_to_user_id, retweeted_status_id, retweeted_status_user_id, and retweeted_status_timestamp. From the df_json_clean dataset we can drop the \"Unnamed: 0\" column."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Drop the \"in-reply\", \"retweeted\", and \"Unnamed: 0\" columns \n",
    "df_twitter_archive_clean.drop(['in_reply_to_status_id'], axis=1, inplace = True)\n",
    "df_twitter_archive_clean.drop(['in_reply_to_user_id'], axis=1, inplace = True)\n",
    "df_twitter_archive_clean.drop(['retweeted_status_id'], axis=1, inplace = True)\n",
    "df_twitter_archive_clean.drop(['retweeted_status_user_id'], axis=1, inplace = True)\n",
    "df_twitter_archive_clean.drop(['retweeted_status_timestamp'], axis=1, inplace = True)\n",
    "df_json_clean.drop(['Unnamed: 0'], axis = 1, inplace= True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2336 entries, 0 to 2355\n",
      "Data columns (total 12 columns):\n",
      "tweet_id              2336 non-null object\n",
      "timestamp             2336 non-null datetime64[ns]\n",
      "source                2336 non-null object\n",
      "text                  2336 non-null object\n",
      "expanded_urls         2280 non-null object\n",
      "rating_numerator      2336 non-null object\n",
      "rating_denominator    2336 non-null int64\n",
      "name                  2336 non-null object\n",
      "doggo                 2336 non-null object\n",
      "floofer               2336 non-null object\n",
      "pupper                2336 non-null object\n",
      "puppo                 2336 non-null object\n",
      "dtypes: datetime64[ns](1), int64(1), object(10)\n",
      "memory usage: 237.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_archive_clean.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2340 entries, 0 to 2339\n",
      "Data columns (total 3 columns):\n",
      "tweet_id          2340 non-null object\n",
      "retweet_count     2340 non-null int64\n",
      "favorite_count    2340 non-null int64\n",
      "dtypes: int64(2), object(1)\n",
      "memory usage: 54.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df_json_clean.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #2:**<br />\n",
    "\n",
    "**Define** <br />\n",
    "We can combine all three datasets into one dataset called twitter_master_df. First we will combine the df_twitter_archive_clean dataset with image_predictions_clean dataset. Then we will combine that dataset with the df_json_clean dataset to make one master dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "archive_predictions = pd.merge(df_twitter_archive_clean, image_predictions_clean, how='left', on='tweet_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2336 entries, 0 to 2335\n",
      "Data columns (total 23 columns):\n",
      "tweet_id              2336 non-null object\n",
      "timestamp             2336 non-null datetime64[ns]\n",
      "source                2336 non-null object\n",
      "text                  2336 non-null object\n",
      "expanded_urls         2280 non-null object\n",
      "rating_numerator      2336 non-null object\n",
      "rating_denominator    2336 non-null int64\n",
      "name                  2336 non-null object\n",
      "doggo                 2336 non-null object\n",
      "floofer               2336 non-null object\n",
      "pupper                2336 non-null object\n",
      "puppo                 2336 non-null object\n",
      "jpg_url               2059 non-null object\n",
      "img_num               2059 non-null float64\n",
      "p1                    2059 non-null object\n",
      "p1_conf               2059 non-null float64\n",
      "p1_dog                2059 non-null object\n",
      "p2                    2059 non-null object\n",
      "p2_conf               2059 non-null float64\n",
      "p2_dog                2059 non-null object\n",
      "p3                    2059 non-null object\n",
      "p3_conf               2059 non-null float64\n",
      "p3_dog                2059 non-null object\n",
      "dtypes: datetime64[ns](1), float64(4), int64(1), object(17)\n",
      "memory usage: 438.0+ KB\n"
     ]
    }
   ],
   "source": [
    "archive_predictions.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Define**<br />\n",
    "Combine the archive_predictions dataset with the df_json_clean dataset to make a master dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master = pd.merge(archive_predictions, df_json_clean, how='left', on='tweet_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2336 entries, 0 to 2335\n",
      "Data columns (total 25 columns):\n",
      "tweet_id              2336 non-null object\n",
      "timestamp             2336 non-null datetime64[ns]\n",
      "source                2336 non-null object\n",
      "text                  2336 non-null object\n",
      "expanded_urls         2280 non-null object\n",
      "rating_numerator      2336 non-null object\n",
      "rating_denominator    2336 non-null int64\n",
      "name                  2336 non-null object\n",
      "doggo                 2336 non-null object\n",
      "floofer               2336 non-null object\n",
      "pupper                2336 non-null object\n",
      "puppo                 2336 non-null object\n",
      "jpg_url               2059 non-null object\n",
      "img_num               2059 non-null float64\n",
      "p1                    2059 non-null object\n",
      "p1_conf               2059 non-null float64\n",
      "p1_dog                2059 non-null object\n",
      "p2                    2059 non-null object\n",
      "p2_conf               2059 non-null float64\n",
      "p2_dog                2059 non-null object\n",
      "p3                    2059 non-null object\n",
      "p3_conf               2059 non-null float64\n",
      "p3_dog                2059 non-null object\n",
      "retweet_count         2320 non-null float64\n",
      "favorite_count        2320 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(6), int64(1), object(17)\n",
      "memory usage: 474.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_master.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Define**<br />\n",
    "Drop any rows that do not contain a jpg_url. This will enable easier analyses later on."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master = df_twitter_master[df_twitter_master['jpg_url'].notnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2059 entries, 0 to 2335\n",
      "Data columns (total 25 columns):\n",
      "tweet_id              2059 non-null object\n",
      "timestamp             2059 non-null datetime64[ns]\n",
      "source                2059 non-null object\n",
      "text                  2059 non-null object\n",
      "expanded_urls         2059 non-null object\n",
      "rating_numerator      2059 non-null object\n",
      "rating_denominator    2059 non-null int64\n",
      "name                  2059 non-null object\n",
      "doggo                 2059 non-null object\n",
      "floofer               2059 non-null object\n",
      "pupper                2059 non-null object\n",
      "puppo                 2059 non-null object\n",
      "jpg_url               2059 non-null object\n",
      "img_num               2059 non-null float64\n",
      "p1                    2059 non-null object\n",
      "p1_conf               2059 non-null float64\n",
      "p1_dog                2059 non-null object\n",
      "p2                    2059 non-null object\n",
      "p2_conf               2059 non-null float64\n",
      "p2_dog                2059 non-null object\n",
      "p3                    2059 non-null object\n",
      "p3_conf               2059 non-null float64\n",
      "p3_dog                2059 non-null object\n",
      "retweet_count         2051 non-null float64\n",
      "favorite_count        2051 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(6), int64(1), object(17)\n",
      "memory usage: 418.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_master.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Define**<br />\n",
    "Set the following columns to the correct data type:<br />\n",
    "p1_dog, p2_dog, p3_dog --> bool<br />\n",
    "rating_numerator --> float<br />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master['p1_dog'] = df_twitter_master['p1_dog'].astype(bool)\n",
    "df_twitter_master['p2_dog'] = df_twitter_master['p2_dog'].astype(bool)\n",
    "df_twitter_master['p3_dog'] = df_twitter_master['p3_dog'].astype(bool)\n",
    "df_twitter_master['rating_numerator'] = df_twitter_master['rating_numerator'].astype(float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Test**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2059 entries, 0 to 2335\n",
      "Data columns (total 25 columns):\n",
      "tweet_id              2059 non-null object\n",
      "timestamp             2059 non-null datetime64[ns]\n",
      "source                2059 non-null object\n",
      "text                  2059 non-null object\n",
      "expanded_urls         2059 non-null object\n",
      "rating_numerator      2059 non-null float64\n",
      "rating_denominator    2059 non-null int64\n",
      "name                  2059 non-null object\n",
      "doggo                 2059 non-null object\n",
      "floofer               2059 non-null object\n",
      "pupper                2059 non-null object\n",
      "puppo                 2059 non-null object\n",
      "jpg_url               2059 non-null object\n",
      "img_num               2059 non-null float64\n",
      "p1                    2059 non-null object\n",
      "p1_conf               2059 non-null float64\n",
      "p1_dog                2059 non-null bool\n",
      "p2                    2059 non-null object\n",
      "p2_conf               2059 non-null float64\n",
      "p2_dog                2059 non-null bool\n",
      "p3                    2059 non-null object\n",
      "p3_conf               2059 non-null float64\n",
      "p3_dog                2059 non-null bool\n",
      "retweet_count         2051 non-null float64\n",
      "favorite_count        2051 non-null float64\n",
      "dtypes: bool(3), datetime64[ns](1), float64(7), int64(1), object(13)\n",
      "memory usage: 376.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_master.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Issue #3(for fun):**<br />\n",
    "\n",
    "**Define** <br />\n",
    "The columns doggo, floofer, pupper, and puppo can be condensed into one column called Stage with the possible variables as doggo, floofer, pupper, and puppo. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First, we will substitute all the NaN for null values. \n",
    "df_twitter_master['doggo'].replace(np.nan,'', inplace=True)\n",
    "df_twitter_master['floofer'].replace(np.nan,'', inplace=True)\n",
    "df_twitter_master['pupper'].replace(np.nan,'', inplace=True)\n",
    "df_twitter_master['puppo'].replace(np.nan, '', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master['stage'] = 'None'\n",
    "\n",
    "def get_dog_stage(row):\n",
    "    stage = []\n",
    "    if row['doggo'] == 'doggo':\n",
    "        stage.append('doggo')\n",
    "    if row['floofer'] == 'floofer':\n",
    "        stage.append('floofer')\n",
    "    if row['pupper'] == 'pupper':\n",
    "        stage.append('pupper')\n",
    "    if row['puppo'] == 'puppo':\n",
    "        stage.append('puppo')\n",
    "    \n",
    "    if len(stage) < 1:\n",
    "        row['stage'] = 'None'\n",
    "    else:\n",
    "        row['stage'] = ','.join(stage)\n",
    "        \n",
    "    return row\n",
    "\n",
    "df_twitter_master = df_twitter_master.apply(get_dog_stage, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None             1738\n",
       "pupper            211\n",
       "doggo              67\n",
       "puppo              23\n",
       "doggo,pupper       11\n",
       "floofer             7\n",
       "doggo,floofer       1\n",
       "doggo,puppo         1\n",
       "Name: stage, dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_master.stage.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master['stage'].replace('doggo,pupper','doggo-pupper', inplace=True)\n",
    "df_twitter_master['stage'].replace('doggo,floofer','doggo-floofer', inplace=True)\n",
    "df_twitter_master['stage'].replace('doggo,puppo','doggo-puppo', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None             1738\n",
       "pupper            211\n",
       "doggo              67\n",
       "puppo              23\n",
       "doggo-pupper       11\n",
       "floofer             7\n",
       "doggo-floofer       1\n",
       "doggo-puppo         1\n",
       "Name: stage, dtype: int64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_master.stage.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_twitter_master = df_twitter_master.drop(['doggo', 'floofer', 'pupper', 'puppo'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2059 entries, 0 to 2335\n",
      "Data columns (total 22 columns):\n",
      "tweet_id              2059 non-null object\n",
      "timestamp             2059 non-null datetime64[ns]\n",
      "source                2059 non-null object\n",
      "text                  2059 non-null object\n",
      "expanded_urls         2059 non-null object\n",
      "rating_numerator      2059 non-null float64\n",
      "rating_denominator    2059 non-null int64\n",
      "name                  2059 non-null object\n",
      "jpg_url               2059 non-null object\n",
      "img_num               2059 non-null float64\n",
      "p1                    2059 non-null object\n",
      "p1_conf               2059 non-null float64\n",
      "p1_dog                2059 non-null bool\n",
      "p2                    2059 non-null object\n",
      "p2_conf               2059 non-null float64\n",
      "p2_dog                2059 non-null bool\n",
      "p3                    2059 non-null object\n",
      "p3_conf               2059 non-null float64\n",
      "p3_dog                2059 non-null bool\n",
      "retweet_count         2051 non-null float64\n",
      "favorite_count        2051 non-null float64\n",
      "stage                 2059 non-null object\n",
      "dtypes: bool(3), datetime64[ns](1), float64(7), int64(1), object(10)\n",
      "memory usage: 327.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df_twitter_master.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Storing and Acting on Wrangled Data ##"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Store Data ##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Store the clean dataframe in a CSV file with the main one named twitter_archive_master.csv. \n",
    "df_twitter_master.to_csv('twitter_archive_master.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Act on Data ###\n",
    "### Insight #1: Top rated and lowest rated dogs <br />\n",
    "Because these ratings are subjective, I will show the top 3 rated dogs and the 3 lowest rated dogs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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>jpg_url</th>\n",
       "      <th>img_num</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>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>stage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1068</th>\n",
       "      <td>740214038584557568</td>\n",
       "      <td>2016-06-07 16:09:13</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>This is getting incredibly frustrating. This is a Mexican Golden Beaver. We only rate dogs. Only send dogs ...10/10 https://t.co/0yolOOyD3X</td>\n",
       "      <td>https://twitter.com/dog_rates/status/740214038584557568/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>getting</td>\n",
       "      <td>https://pbs.twimg.com/media/CkXEu2OUoAAs8yU.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>labrador_retriever</td>\n",
       "      <td>0.189782</td>\n",
       "      <td>True</td>\n",
       "      <td>vizsla</td>\n",
       "      <td>0.067607</td>\n",
       "      <td>True</td>\n",
       "      <td>2102.0</td>\n",
       "      <td>7004.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1074</th>\n",
       "      <td>739544079319588864</td>\n",
       "      <td>2016-06-05 19:47:03</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>This... is a Tyrannosaurus rex. We only rate dogs. Please only send in dogs. Thank you ...10/10 https://t.co/zxw8d5g94P</td>\n",
       "      <td>https://twitter.com/dog_rates/status/739544079319588864/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CkNjahBXAAQ2kWo.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.016641</td>\n",
       "      <td>True</td>\n",
       "      <td>ice_bear</td>\n",
       "      <td>0.014858</td>\n",
       "      <td>False</td>\n",
       "      <td>22841.0</td>\n",
       "      <td>41575.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1007</th>\n",
       "      <td>747512671126323200</td>\n",
       "      <td>2016-06-27 19:31:23</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Guys pls stop sending actual sharks. It's too dangerous for me and the people taking the photos. Thank you ...10/10 https://t.co/12lICZN2SP</td>\n",
       "      <td>https://twitter.com/dog_rates/status/747512671126323200/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cl-yykwWkAAqUCE.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.095089</td>\n",
       "      <td>True</td>\n",
       "      <td>german_shepherd</td>\n",
       "      <td>0.080146</td>\n",
       "      <td>True</td>\n",
       "      <td>1701.0</td>\n",
       "      <td>5837.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>772114945936949249</td>\n",
       "      <td>2016-09-03 16:52:02</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>This is Finn. He's very nervous for the game. Has a lot of money riding on it.10/10 would attempt to comfort https://t.co/CbtNfecWiT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/772114945936949249/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>Finn</td>\n",
       "      <td>https://pbs.twimg.com/media/Crcacf9WgAEcrMh.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.052980</td>\n",
       "      <td>True</td>\n",
       "      <td>italian_greyhound</td>\n",
       "      <td>0.037239</td>\n",
       "      <td>True</td>\n",
       "      <td>512.0</td>\n",
       "      <td>2885.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>748977405889503236</td>\n",
       "      <td>2016-07-01 20:31:43</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>What jokester sent in a pic without a dog in it? This is not @rock_rates. This is @dog_rates. Thank you ...10/10 https://t.co/nDPaYHrtNX</td>\n",
       "      <td>https://twitter.com/dog_rates/status/748977405889503236/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>not</td>\n",
       "      <td>https://pbs.twimg.com/media/CmTm-XQXEAAEyN6.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>bluetick</td>\n",
       "      <td>0.152810</td>\n",
       "      <td>True</td>\n",
       "      <td>english_setter</td>\n",
       "      <td>0.051835</td>\n",
       "      <td>True</td>\n",
       "      <td>3654.0</td>\n",
       "      <td>11286.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1108</th>\n",
       "      <td>733482008106668032</td>\n",
       "      <td>2016-05-20 02:18:32</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>\"Ello this is dog how may I assist\" ...10/10 https://t.co/jeAENpjH7L</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733482008106668032/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Ci3Z_idUkAA8RUh.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>computer_keyboard</td>\n",
       "      <td>0.142274</td>\n",
       "      <td>False</td>\n",
       "      <td>mouse</td>\n",
       "      <td>0.058505</td>\n",
       "      <td>False</td>\n",
       "      <td>1012.0</td>\n",
       "      <td>3287.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>738402415918125056</td>\n",
       "      <td>2016-06-02 16:10:29</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>\"Don't talk to me or my son ever again\" ...10/10 for both https://t.co/s96OYXZIfK</td>\n",
       "      <td>https://twitter.com/dog_rates/status/738402415918125056/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cj9VEs_XAAAlTai.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>blenheim_spaniel</td>\n",
       "      <td>0.193905</td>\n",
       "      <td>True</td>\n",
       "      <td>chihuahua</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>True</td>\n",
       "      <td>901.0</td>\n",
       "      <td>3412.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>759566828574212096</td>\n",
       "      <td>2016-07-31 01:50:18</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>RT @dog_rates: This... is a Tyrannosaurus rex. We only rate dogs. Please only send in dogs. Thank you ...10/10 https://t.co/zxw8d5g94P</td>\n",
       "      <td>https://twitter.com/dog_rates/status/739544079319588864/photo/1,https://twitter.com/dog_rates/status/739544079319588864/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CkNjahBXAAQ2kWo.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.016641</td>\n",
       "      <td>True</td>\n",
       "      <td>ice_bear</td>\n",
       "      <td>0.014858</td>\n",
       "      <td>False</td>\n",
       "      <td>22841.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1095</th>\n",
       "      <td>736010884653420544</td>\n",
       "      <td>2016-05-27 01:47:23</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Right after you graduate vs when you remember you're on your own now and can barely work a washing machine ...10/10 https://t.co/O1TLuYjsNS</td>\n",
       "      <td>https://twitter.com/dog_rates/status/736010884653420544/photo/1,https://twitter.com/dog_rates/status/736010884653420544/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CjbV-lEWgAAr6WY.jpg</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>labrador_retriever</td>\n",
       "      <td>0.119475</td>\n",
       "      <td>True</td>\n",
       "      <td>bluetick</td>\n",
       "      <td>0.077475</td>\n",
       "      <td>True</td>\n",
       "      <td>3171.0</td>\n",
       "      <td>8258.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1623</th>\n",
       "      <td>684594889858887680</td>\n",
       "      <td>2016-01-06 04:38:35</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>\"FOR THE LAST TIME I DON'T WANNA PLAY TWISTER ALL THE SPOTS ARE GREY DAMN IT CINDY\" ...10/10 https://t.co/uhQNehTpIu</td>\n",
       "      <td>https://twitter.com/dog_rates/status/684594889858887680/photo/1</td>\n",
       "      <td>0.10</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CYAra7JWsAACPZH.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>english_setter</td>\n",
       "      <td>0.035352</td>\n",
       "      <td>True</td>\n",
       "      <td>brittany_spaniel</td>\n",
       "      <td>0.003879</td>\n",
       "      <td>True</td>\n",
       "      <td>3785.0</td>\n",
       "      <td>9372.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>706291001778950144</td>\n",
       "      <td>2016-03-06 01:31:11</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>When you're just relaxin and having a swell time but then remember you have to fill out the FAFSA ...11/10 https://t.co/qy33OBcexg</td>\n",
       "      <td>https://twitter.com/dog_rates/status/706291001778950144/photo/1,https://twitter.com/dog_rates/status/706291001778950144/photo/1</td>\n",
       "      <td>0.11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cc0_2tXXEAA2iTY.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>bull_mastiff</td>\n",
       "      <td>0.164087</td>\n",
       "      <td>True</td>\n",
       "      <td>staffordshire_bullterrier</td>\n",
       "      <td>0.105011</td>\n",
       "      <td>True</td>\n",
       "      <td>499.0</td>\n",
       "      <td>1779.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1014</th>\n",
       "      <td>746872823977771008</td>\n",
       "      <td>2016-06-26 01:08:52</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>This is a carrot. We only rate dogs. Please only send in dogs. You all really should know this by now ...11/10 https://t.co/9e48aPrBm2</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746872823977771008/photo/1,https://twitter.com/dog_rates/status/746872823977771008/photo/1</td>\n",
       "      <td>0.11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cl1s1p7WMAA44Vk.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>beagle</td>\n",
       "      <td>0.207835</td>\n",
       "      <td>True</td>\n",
       "      <td>italian_greyhound</td>\n",
       "      <td>0.043565</td>\n",
       "      <td>True</td>\n",
       "      <td>2304.0</td>\n",
       "      <td>6304.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1006</th>\n",
       "      <td>747594051852075008</td>\n",
       "      <td>2016-06-28 00:54:46</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Again w the sharks guys. This week is about dogs ACTING or DRESSING like sharks. NOT actual sharks. Thank u ...11/10 https://t.co/Ie2mWXWjpr</td>\n",
       "      <td>https://twitter.com/dog_rates/status/747594051852075008/photo/1</td>\n",
       "      <td>0.11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cl_80k5WkAEbo9m.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>dingo</td>\n",
       "      <td>0.270226</td>\n",
       "      <td>False</td>\n",
       "      <td>chihuahua</td>\n",
       "      <td>0.098939</td>\n",
       "      <td>True</td>\n",
       "      <td>1126.0</td>\n",
       "      <td>3890.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1013</th>\n",
       "      <td>747103485104099331</td>\n",
       "      <td>2016-06-26 16:25:26</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Guys... I said DOGS with \"shark qualities\" or \"costumes.\" Not actual sharks. This did me a real frighten ...11/10 https://t.co/DX1JUHJVN7</td>\n",
       "      <td>https://twitter.com/dog_rates/status/747103485104099331/photo/1,https://twitter.com/dog_rates/status/747103485104099331/photo/1,https://twitter.co...</td>\n",
       "      <td>0.11</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cl4-pevXEAAb8VW.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.002228</td>\n",
       "      <td>True</td>\n",
       "      <td>doormat</td>\n",
       "      <td>0.001404</td>\n",
       "      <td>False</td>\n",
       "      <td>4280.0</td>\n",
       "      <td>10073.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1338</th>\n",
       "      <td>704847917308362754</td>\n",
       "      <td>2016-03-02 01:56:53</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>\"Yes hi could I get a number 4 with no pickles\" ...12/10 https://t.co/kQPVxqA3gq</td>\n",
       "      <td>https://twitter.com/dog_rates/status/704847917308362754/photo/1</td>\n",
       "      <td>0.12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CcgfcANW4AA9hzr.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>labrador_retriever</td>\n",
       "      <td>0.135460</td>\n",
       "      <td>True</td>\n",
       "      <td>tibetan_mastiff</td>\n",
       "      <td>0.001903</td>\n",
       "      <td>True</td>\n",
       "      <td>1632.0</td>\n",
       "      <td>5352.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1263</th>\n",
       "      <td>709852847387627521</td>\n",
       "      <td>2016-03-15 21:24:41</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>*lets out a tiny whimper and then collapses* ...12/10 https://t.co/BNdVZEHRow</td>\n",
       "      <td>https://twitter.com/dog_rates/status/709852847387627521/photo/1,https://twitter.com/dog_rates/status/709852847387627521/photo/1,https://twitter.co...</td>\n",
       "      <td>0.12</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CdnnZhhWAAEAoUc.jpg</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>pomeranian</td>\n",
       "      <td>0.019204</td>\n",
       "      <td>True</td>\n",
       "      <td>west_highland_white_terrier</td>\n",
       "      <td>0.010134</td>\n",
       "      <td>True</td>\n",
       "      <td>1270.0</td>\n",
       "      <td>3664.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1432</th>\n",
       "      <td>697259378236399616</td>\n",
       "      <td>2016-02-10 03:22:44</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Please stop sending in saber-toothed tigers. This is getting ridiculous. We only rate dogs.\\n...8/10 https://t.co/iAeQNueou8</td>\n",
       "      <td>https://twitter.com/dog_rates/status/697259378236399616/photo/1</td>\n",
       "      <td>0.80</td>\n",
       "      <td>10</td>\n",
       "      <td>getting</td>\n",
       "      <td>https://pbs.twimg.com/media/Ca0ps3AXEAAnp9m.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>boxer</td>\n",
       "      <td>0.000187</td>\n",
       "      <td>True</td>\n",
       "      <td>whippet</td>\n",
       "      <td>0.000151</td>\n",
       "      <td>True</td>\n",
       "      <td>1063.0</td>\n",
       "      <td>3447.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1022</th>\n",
       "      <td>746369468511756288</td>\n",
       "      <td>2016-06-24 15:48:42</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>This is an Iraqi Speed Kangaroo. It is not a dog. Please only send in dogs. I'm very angry with all of you ...9/10 https://t.co/5qpBTTpgUt</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746369468511756288/photo/1</td>\n",
       "      <td>0.90</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/ClujESVXEAA4uH8.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>malinois</td>\n",
       "      <td>0.338884</td>\n",
       "      <td>True</td>\n",
       "      <td>wallaby</td>\n",
       "      <td>0.024161</td>\n",
       "      <td>False</td>\n",
       "      <td>1763.0</td>\n",
       "      <td>6474.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1606</th>\n",
       "      <td>685532292383666176</td>\n",
       "      <td>2016-01-08 18:43:29</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>For the last time, WE. DO. NOT. RATE. BULBASAUR. We only rate dogs. Please only send dogs. Thank you ...9/10 https://t.co/GboDG8WhJG</td>\n",
       "      <td>https://twitter.com/dog_rates/status/685532292383666176/photo/1</td>\n",
       "      <td>0.90</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/CYN_-6iW8AQhPu2.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>dingo</td>\n",
       "      <td>0.215436</td>\n",
       "      <td>False</td>\n",
       "      <td>collie</td>\n",
       "      <td>0.095805</td>\n",
       "      <td>True</td>\n",
       "      <td>1231.0</td>\n",
       "      <td>3193.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>702217446468493312</td>\n",
       "      <td>2016-02-23 19:44:20</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>I know it's tempting, but please stop sending in pics of Donald Trump. Thank you ...9/10 https://t.co/y35Y1TJERY</td>\n",
       "      <td>https://twitter.com/dog_rates/status/702217446468493312/photo/1</td>\n",
       "      <td>0.90</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/media/Cb7HCMkWEAAV9zY.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>chow</td>\n",
       "      <td>0.226800</td>\n",
       "      <td>True</td>\n",
       "      <td>cocker_spaniel</td>\n",
       "      <td>0.194086</td>\n",
       "      <td>True</td>\n",
       "      <td>1425.0</td>\n",
       "      <td>5033.0</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id           timestamp  \\\n",
       "1068  740214038584557568 2016-06-07 16:09:13   \n",
       "1074  739544079319588864 2016-06-05 19:47:03   \n",
       "1007  747512671126323200 2016-06-27 19:31:23   \n",
       "803   772114945936949249 2016-09-03 16:52:02   \n",
       "986   748977405889503236 2016-07-01 20:31:43   \n",
       "1108  733482008106668032 2016-05-20 02:18:32   \n",
       "1081  738402415918125056 2016-06-02 16:10:29   \n",
       "888   759566828574212096 2016-07-31 01:50:18   \n",
       "1095  736010884653420544 2016-05-27 01:47:23   \n",
       "1623  684594889858887680 2016-01-06 04:38:35   \n",
       "1319  706291001778950144 2016-03-06 01:31:11   \n",
       "1014  746872823977771008 2016-06-26 01:08:52   \n",
       "1006  747594051852075008 2016-06-28 00:54:46   \n",
       "1013  747103485104099331 2016-06-26 16:25:26   \n",
       "1338  704847917308362754 2016-03-02 01:56:53   \n",
       "1263  709852847387627521 2016-03-15 21:24:41   \n",
       "1432  697259378236399616 2016-02-10 03:22:44   \n",
       "1022  746369468511756288 2016-06-24 15:48:42   \n",
       "1606  685532292383666176 2016-01-08 18:43:29   \n",
       "1369  702217446468493312 2016-02-23 19:44:20   \n",
       "\n",
       "                                                                                  source  \\\n",
       "1068  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1074  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1007  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "803   <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "986   <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1108  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1081  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "888   <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1095  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1623  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1319  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1014  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1006  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1013  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1338  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1263  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1432  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1022  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1606  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "1369  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "\n",
       "                                                                                                                                              text  \\\n",
       "1068   This is getting incredibly frustrating. This is a Mexican Golden Beaver. We only rate dogs. Only send dogs ...10/10 https://t.co/0yolOOyD3X   \n",
       "1074                       This... is a Tyrannosaurus rex. We only rate dogs. Please only send in dogs. Thank you ...10/10 https://t.co/zxw8d5g94P   \n",
       "1007   Guys pls stop sending actual sharks. It's too dangerous for me and the people taking the photos. Thank you ...10/10 https://t.co/12lICZN2SP   \n",
       "803           This is Finn. He's very nervous for the game. Has a lot of money riding on it.10/10 would attempt to comfort https://t.co/CbtNfecWiT   \n",
       "986       What jokester sent in a pic without a dog in it? This is not @rock_rates. This is @dog_rates. Thank you ...10/10 https://t.co/nDPaYHrtNX   \n",
       "1108                                                                          \"Ello this is dog how may I assist\" ...10/10 https://t.co/jeAENpjH7L   \n",
       "1081                                                             \"Don't talk to me or my son ever again\" ...10/10 for both https://t.co/s96OYXZIfK   \n",
       "888         RT @dog_rates: This... is a Tyrannosaurus rex. We only rate dogs. Please only send in dogs. Thank you ...10/10 https://t.co/zxw8d5g94P   \n",
       "1095   Right after you graduate vs when you remember you're on your own now and can barely work a washing machine ...10/10 https://t.co/O1TLuYjsNS   \n",
       "1623                          \"FOR THE LAST TIME I DON'T WANNA PLAY TWISTER ALL THE SPOTS ARE GREY DAMN IT CINDY\" ...10/10 https://t.co/uhQNehTpIu   \n",
       "1319            When you're just relaxin and having a swell time but then remember you have to fill out the FAFSA ...11/10 https://t.co/qy33OBcexg   \n",
       "1014        This is a carrot. We only rate dogs. Please only send in dogs. You all really should know this by now ...11/10 https://t.co/9e48aPrBm2   \n",
       "1006  Again w the sharks guys. This week is about dogs ACTING or DRESSING like sharks. NOT actual sharks. Thank u ...11/10 https://t.co/Ie2mWXWjpr   \n",
       "1013     Guys... I said DOGS with \"shark qualities\" or \"costumes.\" Not actual sharks. This did me a real frighten ...11/10 https://t.co/DX1JUHJVN7   \n",
       "1338                                                              \"Yes hi could I get a number 4 with no pickles\" ...12/10 https://t.co/kQPVxqA3gq   \n",
       "1263                                                                 *lets out a tiny whimper and then collapses* ...12/10 https://t.co/BNdVZEHRow   \n",
       "1432                  Please stop sending in saber-toothed tigers. This is getting ridiculous. We only rate dogs.\\n...8/10 https://t.co/iAeQNueou8   \n",
       "1022    This is an Iraqi Speed Kangaroo. It is not a dog. Please only send in dogs. I'm very angry with all of you ...9/10 https://t.co/5qpBTTpgUt   \n",
       "1606          For the last time, WE. DO. NOT. RATE. BULBASAUR. We only rate dogs. Please only send dogs. Thank you ...9/10 https://t.co/GboDG8WhJG   \n",
       "1369                              I know it's tempting, but please stop sending in pics of Donald Trump. Thank you ...9/10 https://t.co/y35Y1TJERY   \n",
       "\n",
       "                                                                                                                                              expanded_urls  \\\n",
       "1068                                                                                        https://twitter.com/dog_rates/status/740214038584557568/photo/1   \n",
       "1074                                                                                        https://twitter.com/dog_rates/status/739544079319588864/photo/1   \n",
       "1007                                                                                        https://twitter.com/dog_rates/status/747512671126323200/photo/1   \n",
       "803                                                                                         https://twitter.com/dog_rates/status/772114945936949249/photo/1   \n",
       "986                                                                                         https://twitter.com/dog_rates/status/748977405889503236/photo/1   \n",
       "1108                                                                                        https://twitter.com/dog_rates/status/733482008106668032/photo/1   \n",
       "1081                                                                                        https://twitter.com/dog_rates/status/738402415918125056/photo/1   \n",
       "888                         https://twitter.com/dog_rates/status/739544079319588864/photo/1,https://twitter.com/dog_rates/status/739544079319588864/photo/1   \n",
       "1095                        https://twitter.com/dog_rates/status/736010884653420544/photo/1,https://twitter.com/dog_rates/status/736010884653420544/photo/1   \n",
       "1623                                                                                        https://twitter.com/dog_rates/status/684594889858887680/photo/1   \n",
       "1319                        https://twitter.com/dog_rates/status/706291001778950144/photo/1,https://twitter.com/dog_rates/status/706291001778950144/photo/1   \n",
       "1014                        https://twitter.com/dog_rates/status/746872823977771008/photo/1,https://twitter.com/dog_rates/status/746872823977771008/photo/1   \n",
       "1006                                                                                        https://twitter.com/dog_rates/status/747594051852075008/photo/1   \n",
       "1013  https://twitter.com/dog_rates/status/747103485104099331/photo/1,https://twitter.com/dog_rates/status/747103485104099331/photo/1,https://twitter.co...   \n",
       "1338                                                                                        https://twitter.com/dog_rates/status/704847917308362754/photo/1   \n",
       "1263  https://twitter.com/dog_rates/status/709852847387627521/photo/1,https://twitter.com/dog_rates/status/709852847387627521/photo/1,https://twitter.co...   \n",
       "1432                                                                                        https://twitter.com/dog_rates/status/697259378236399616/photo/1   \n",
       "1022                                                                                        https://twitter.com/dog_rates/status/746369468511756288/photo/1   \n",
       "1606                                                                                        https://twitter.com/dog_rates/status/685532292383666176/photo/1   \n",
       "1369                                                                                        https://twitter.com/dog_rates/status/702217446468493312/photo/1   \n",
       "\n",
       "      rating_numerator  rating_denominator     name  \\\n",
       "1068              0.10                  10  getting   \n",
       "1074              0.10                  10      NaN   \n",
       "1007              0.10                  10      NaN   \n",
       "803               0.10                  10     Finn   \n",
       "986               0.10                  10      not   \n",
       "1108              0.10                  10      NaN   \n",
       "1081              0.10                  10      NaN   \n",
       "888               0.10                  10      NaN   \n",
       "1095              0.10                  10      NaN   \n",
       "1623              0.10                  10      NaN   \n",
       "1319              0.11                  10      NaN   \n",
       "1014              0.11                  10      NaN   \n",
       "1006              0.11                  10      NaN   \n",
       "1013              0.11                  10      NaN   \n",
       "1338              0.12                  10      NaN   \n",
       "1263              0.12                  10      NaN   \n",
       "1432              0.80                  10  getting   \n",
       "1022              0.90                  10      NaN   \n",
       "1606              0.90                  10      NaN   \n",
       "1369              0.90                  10      NaN   \n",
       "\n",
       "                                              jpg_url  img_num  ...   p1_dog  \\\n",
       "1068  https://pbs.twimg.com/media/CkXEu2OUoAAs8yU.jpg      1.0  ...     True   \n",
       "1074  https://pbs.twimg.com/media/CkNjahBXAAQ2kWo.jpg      1.0  ...     True   \n",
       "1007  https://pbs.twimg.com/media/Cl-yykwWkAAqUCE.jpg      1.0  ...     True   \n",
       "803   https://pbs.twimg.com/media/Crcacf9WgAEcrMh.jpg      1.0  ...     True   \n",
       "986   https://pbs.twimg.com/media/CmTm-XQXEAAEyN6.jpg      1.0  ...     True   \n",
       "1108  https://pbs.twimg.com/media/Ci3Z_idUkAA8RUh.jpg      1.0  ...     True   \n",
       "1081  https://pbs.twimg.com/media/Cj9VEs_XAAAlTai.jpg      1.0  ...     True   \n",
       "888   https://pbs.twimg.com/media/CkNjahBXAAQ2kWo.jpg      1.0  ...     True   \n",
       "1095  https://pbs.twimg.com/media/CjbV-lEWgAAr6WY.jpg      2.0  ...     True   \n",
       "1623  https://pbs.twimg.com/media/CYAra7JWsAACPZH.jpg      1.0  ...     True   \n",
       "1319  https://pbs.twimg.com/media/Cc0_2tXXEAA2iTY.jpg      1.0  ...     True   \n",
       "1014  https://pbs.twimg.com/media/Cl1s1p7WMAA44Vk.jpg      1.0  ...     True   \n",
       "1006  https://pbs.twimg.com/media/Cl_80k5WkAEbo9m.jpg      1.0  ...     True   \n",
       "1013  https://pbs.twimg.com/media/Cl4-pevXEAAb8VW.jpg      1.0  ...     True   \n",
       "1338  https://pbs.twimg.com/media/CcgfcANW4AA9hzr.jpg      1.0  ...     True   \n",
       "1263  https://pbs.twimg.com/media/CdnnZhhWAAEAoUc.jpg      2.0  ...     True   \n",
       "1432  https://pbs.twimg.com/media/Ca0ps3AXEAAnp9m.jpg      1.0  ...     True   \n",
       "1022  https://pbs.twimg.com/media/ClujESVXEAA4uH8.jpg      1.0  ...     True   \n",
       "1606  https://pbs.twimg.com/media/CYN_-6iW8AQhPu2.jpg      1.0  ...    False   \n",
       "1369  https://pbs.twimg.com/media/Cb7HCMkWEAAV9zY.jpg      1.0  ...     True   \n",
       "\n",
       "                      p2   p2_conf p2_dog                           p3  \\\n",
       "1068  labrador_retriever  0.189782   True                       vizsla   \n",
       "1074    golden_retriever  0.016641   True                     ice_bear   \n",
       "1007            malinois  0.095089   True              german_shepherd   \n",
       "803          toy_terrier  0.052980   True            italian_greyhound   \n",
       "986             bluetick  0.152810   True               english_setter   \n",
       "1108   computer_keyboard  0.142274  False                        mouse   \n",
       "1081    blenheim_spaniel  0.193905   True                    chihuahua   \n",
       "888     golden_retriever  0.016641   True                     ice_bear   \n",
       "1095  labrador_retriever  0.119475   True                     bluetick   \n",
       "1623      english_setter  0.035352   True             brittany_spaniel   \n",
       "1319        bull_mastiff  0.164087   True    staffordshire_bullterrier   \n",
       "1014              beagle  0.207835   True            italian_greyhound   \n",
       "1006               dingo  0.270226  False                    chihuahua   \n",
       "1013    golden_retriever  0.002228   True                      doormat   \n",
       "1338  labrador_retriever  0.135460   True              tibetan_mastiff   \n",
       "1263          pomeranian  0.019204   True  west_highland_white_terrier   \n",
       "1432               boxer  0.000187   True                      whippet   \n",
       "1022            malinois  0.338884   True                      wallaby   \n",
       "1606               dingo  0.215436  False                       collie   \n",
       "1369                chow  0.226800   True               cocker_spaniel   \n",
       "\n",
       "       p3_conf p3_dog  retweet_count  favorite_count  stage  \n",
       "1068  0.067607   True         2102.0          7004.0   None  \n",
       "1074  0.014858  False        22841.0         41575.0   None  \n",
       "1007  0.080146   True         1701.0          5837.0   None  \n",
       "803   0.037239   True          512.0          2885.0   None  \n",
       "986   0.051835   True         3654.0         11286.0   None  \n",
       "1108  0.058505  False         1012.0          3287.0   None  \n",
       "1081  0.078000   True          901.0          3412.0   None  \n",
       "888   0.014858  False        22841.0             0.0   None  \n",
       "1095  0.077475   True         3171.0          8258.0   None  \n",
       "1623  0.003879   True         3785.0          9372.0   None  \n",
       "1319  0.105011   True          499.0          1779.0   None  \n",
       "1014  0.043565   True         2304.0          6304.0   None  \n",
       "1006  0.098939   True         1126.0          3890.0   None  \n",
       "1013  0.001404  False         4280.0         10073.0   None  \n",
       "1338  0.001903   True         1632.0          5352.0   None  \n",
       "1263  0.010134   True         1270.0          3664.0   None  \n",
       "1432  0.000151   True         1063.0          3447.0   None  \n",
       "1022  0.024161  False         1763.0          6474.0   None  \n",
       "1606  0.095805   True         1231.0          3193.0   None  \n",
       "1369  0.194086   True         1425.0          5033.0   None  \n",
       "\n",
       "[20 rows x 22 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Sort the master dataframe by rating_numerator values so that we can see the top 3 highest and lowest rated dogs\n",
    "pd.set_option('display.max_colwidth', 150)\n",
    "df_twitter_master.sort_values(by = 'rating_numerator').head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations**<br />\n",
    "\n",
    "First highest rated dog<br />\n",
    "Tweet: This is Atticus. He's quite simply America af. 1776/10 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/CmgBZ7kWcAAlzFD.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Second highest rated dog<br />\n",
    "Tweet: After so many requests... here you go.\\n\\nGood dogg. 420/10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/CU9P717W4AAOlKx.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Third highest rated dog<br />\n",
    "Tweet: Say hello to this unbelievably well behaved squad of doggos. 204/170 would try to pet all at once "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/CiWWhVNUYAAab_r.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First lowest rated dog<br />\n",
    "Tweet: This is getting incredibly frustrating. This is a Mexican Golden Beaver. We only rate dogs. Only send dogs ...10/10 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/CkXEu2OUoAAs8yU.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Second lowest rated dog<br />\n",
    "Tweet: This... is a Tyrannosaurus rex. We only rate dogs. Please only send in dogs. Thank you ...10/10 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/CkNjahBXAAQ2kWo.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Third lowest rated dog<br />\n",
    "Tweet: Guys pls stop sending actual sharks. It's too dangerous for me and the people taking the photos. Thank you ...10/10 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://pbs.twimg.com/media/Cl-yykwWkAAqUCE.jpg\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Insight #2: Most retweeted photo ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83717.0"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the max value in retweet_count column and then locate that row\n",
    "df_twitter_master.retweet_count.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>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>jpg_url</th>\n",
       "      <th>img_num</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>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>stage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1036</th>\n",
       "      <td>744234799360020481</td>\n",
       "      <td>2016-06-18 18:26:18</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\"&gt;Twitter for iPhone&lt;/a&gt;</td>\n",
       "      <td>Here's a doggo realizing you can stand in a pool. 13/10 enlightened af (vid by Tina Conrad) https://t.co/7wE9LTEXC4</td>\n",
       "      <td>https://twitter.com/dog_rates/status/744234799360020481/video/1</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://pbs.twimg.com/ext_tw_video_thumb/744234667679821824/pu/img/1GaWmtJtdqzZV7jy.jpg</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>True</td>\n",
       "      <td>ice_bear</td>\n",
       "      <td>0.044681</td>\n",
       "      <td>False</td>\n",
       "      <td>whippet</td>\n",
       "      <td>0.018442</td>\n",
       "      <td>True</td>\n",
       "      <td>83717.0</td>\n",
       "      <td>164384.0</td>\n",
       "      <td>doggo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id           timestamp  \\\n",
       "1036  744234799360020481 2016-06-18 18:26:18   \n",
       "\n",
       "                                                                                  source  \\\n",
       "1036  <a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>   \n",
       "\n",
       "                                                                                                                     text  \\\n",
       "1036  Here's a doggo realizing you can stand in a pool. 13/10 enlightened af (vid by Tina Conrad) https://t.co/7wE9LTEXC4   \n",
       "\n",
       "                                                        expanded_urls  \\\n",
       "1036  https://twitter.com/dog_rates/status/744234799360020481/video/1   \n",
       "\n",
       "      rating_numerator  rating_denominator name  \\\n",
       "1036              13.0                  10  NaN   \n",
       "\n",
       "                                                                                      jpg_url  \\\n",
       "1036  https://pbs.twimg.com/ext_tw_video_thumb/744234667679821824/pu/img/1GaWmtJtdqzZV7jy.jpg   \n",
       "\n",
       "      img_num  ...   p1_dog        p2   p2_conf p2_dog       p3   p3_conf  \\\n",
       "1036      1.0  ...     True  ice_bear  0.044681  False  whippet  0.018442   \n",
       "\n",
       "     p3_dog  retweet_count  favorite_count  stage  \n",
       "1036   True        83717.0        164384.0  doggo  \n",
       "\n",
       "[1 rows x 22 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_twitter_master.loc[df_twitter_master['retweet_count'] == 83717.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations:**<br />\n",
    "Tweet_id 744234799360020481\tis the most retweeted tweet with 83727 retweets. This tweet is a short clip of a dog realizing he can stand in the pool."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Insight #3: Tweet source types ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>     2019\n",
       "<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>                       29\n",
       "<a href=\"https://about.twitter.com/products/tweetdeck\" rel=\"nofollow\">TweetDeck</a>      11\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count the unique values of source types\n",
    "df_twitter_master.source.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2059\n"
     ]
    }
   ],
   "source": [
    "print(2019+29+11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9805730937348227\n",
      "0.014084507042253521\n",
      "0.005342399222923749\n"
     ]
    }
   ],
   "source": [
    "print(2019/2059)\n",
    "print(29/2059)\n",
    "print(11/2059)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations:**<br />\n",
    "98% of users are using an iPhone to view tweets, 1.4% are using a desktop, and 0.5% are using Tweetdeck."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Report (and Visualizations) ##"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization #1: Correlation between retweet and favorite count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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H3Osc45+de9Rgx+wO4DhLMMZEna7Qb4hIHVbAv4kdxxsI24GLnTmHHdiPr46MObOxuBhNP2w/83NYa7sw1rz4R6TMHQEmYB/QZuwX7vPAvLT97AR+lGH/DwBbeih7KnC/c3G7nH08zGHz4SqONE+/ADuHI4idu3MhR1rzjce29proex7Vhzk8j6qBnudRnZK23RH7ynB8a+huRZX4gr+JNPNt7AfCr506B7GTge/CMa138nwDOyYTxRoxJNInOfv/S0qaG/tg1GSoVwH2oXrXueb7gadwLNtS8n0W21INOtf+JeDrvV3bTNcsQ/k95sFakkWAyn7UI+P1dtb9i5OWOtfsCift5gzlZ3MdxmBfaHuc81eHNVpYmJLnfOz9GaL3eVQl2Gegyfndw2ELz1N6O189nP/LnTqHsB8o88jNPKrJHDbD348Vl88726Vb+iYshXeTYZoCtpX/XMr1fBiYmLI+o7Wcsy7d6m8iVuCaOXIe1UXOOejEPguvYMfYXH2cCzfWQvAl7DMbcq7ld4CylHzvw7aUEnPuVgHvy3De/uCUvxP74ZBxHlXadh7neD6fkjbPqVMnfcyjSsylUBRFUZQRydFmnq4oiqIcZahQKYqiKCMaFSpFURRlRKNCpSiKooxoVKgURVGUEc1RM48qF4wfP95UVVUNdzUURVFGFVu3bj1kjJmQr/2rUKVQVVXFli09uQZTFEVRMiEivfmoHDTa9acoiqKMaFSoFEVRlBGNCpWiKIoyolGhUhRFUUY0KlSKoijKiEaFSlEURRnRqFApiqIoIxoVKkVRFGXADEWoKJ3wqyiKovQbYwytwQiRmAqVoiiKMsIIhKM0doSJxOKUFORfRlSoFEVRlKwIR+M0dYYJhKNDWq4KlaIoitIr8bihJRihNRgZkjGpdFSoFEVRlB7p6IrS1BEmGo8PWx1UqBRFUZQj6IrGaOwIE4rEhrsqKlSKoijKYWJxQ3MgTFswMtxVSaJCpSiKogDQForQ3BkmFh/6cajeUKFSFEU5xglFYjR2hukaAd18mVChUhRFOUaJxuI0BcJ0hIbW3Ly/qFApiqIcYxhjaAtGaQ6EiQ+DuXl/UaFSFEU5hgiGYxzq6CISGz5z8/6SV6e0IjJDRJ4TkbdFZJuIfNVJHysiz4jIDuf/CiddROSnIvKuiLwuImek7OtaJ/8OEbk2Jf1MEXnD2eanIiK9laEoinIsEonFOdAWor41OKpECvLvPT0KfMMYcyKwAPiiiJwEfAt41hhzHPCsswzwUeA453cjcCdY0QFuAc4C5gO3pAjPnU7exHYXOOk9laEoinLMYIyhuTNMXXOQzq6RPRbVE3kVKmNMvTHmZefvduBtYBpwKfCgk+1B4OPO35cCDxnLRqBcRKYAfwc8Y4xpMsY0A88AFzjryowxLxrr1+OhtH1lKkNRFOWYoLMrSl1zkOZAeFhcH+WKIRujEpEq4APAS8AkY0w9WDETkYlOtmnAnpTN6py03tLrMqTTSxnp9boR2yKjsrJygEenKIoycghH4zR2dhEM59/cfCjmXA2JUIlICfAb4GvGmDZnGClj1gxpZgDpWWOMuRu4G2Du3Lmj95NDUZRjnnjCq0QomvcWlDGGF95r5P4NO/NaDgyBUImIFytSvzTG/NZJPiAiU5yWzhSgwUmvA2akbD4d2OekL01LX+OkT8+Qv7cyFEVRjjraQxGaOyND4jz2jbpWVqyr4c19bXkvC/Jv9SfAvcDbxpgfp6xaBSQs964Ffp+Sfo1j/bcAaHW6754GzheRCseI4nzgaWddu4gscMq6Jm1fmcpQFEU5auiKxtjXEuRge1feRarmYAf/+sQbfPXRV5MidfascXktE/LfoloIXA28ISKvOmn/CtwGPCYi1wO7gcuddU8CFwLvAgHgcwDGmCYR+T6w2cl3qzGmyfn7C8ADQCHwZ+dHL2UoiqKMemJxQ1NnmPZQ/p3H7m8Ncf8LO/nrWweSYytzJpdy45JZLJo9npU35bd8Gc2WILlm7ty5ZsuWLcNdDUVRlF5pDUZoCeTfeWxLIMzDG3ez6rV9RJ2yKscWsWxRFYtnj0dEKCnwMGlM4VZjzNx81UM9UyiKoowSQhHrVSIczW8XXyAc5fEtdTy2pY6g46h2fImP686p4u9Onozb1aNBXF5QoVIURRnhRGNxmjrDdOR5wm44GuePr9fz8MZdtDjxqEr9Hq6aX8knTp9Kgded1/J7QoVKURRlhGKMcbr5Inl1Hhs3hmffbuD+DTvZ3xYCoMDj4u/PmMaV8yop8Q+vVKhQKYqijEAC4SiNHeG8+uUzxvBSbRP3rK+l5mAnAC6Bi94/havPnsn4koK8ld0fVKgURVFGEJFYnMaOMIFwfrv5tu1rZcW6Wl6va02mffD4CSxbWMWMsUV5Lbu/qFApiqKMAIwxNAcitAYjefUqsbOxk3vX1bLhvcZk2pkzK7hhUTUnTC7NW7mDQYVKURRlmOnoitLUEc7rhN0DbSEefGEXf3lrPwmr9hMmlXLD4mrOnDmyoyCpUCmKogwTQ+E8tjUY4Vcv7eZ3r+4lErMKNb2ikGULq/ng8XYu1EhHhUpRFGWIGQrnscFIjN9srePRzXvodIRwXLGPa86eyUdPmYzHne9whLlDhUpRFGUIaQ9FaOrMn1eJaCzOn96o56EXd9EcsHOhigvcXDWvksvOmIZ/mOZCDQYVKkVRlCEgFInR2BmmK5Kfbr64MTy3/SD3v1DLvhY7F8rncXHZB6Zx5bwZlBV681LuUKBCpSiKkkfy7TzWGMOWXc2sWFfLuw0dgJ0LdcEpk7n27ComlOZvLlSRz8OYovwLoAqVoihKnmgNRmjuDOfNq8Tb9W2sWFfLq3takmmLjxvP9QurqRyXv7lQxQUeyou8FHiGphtRhUpRFCXHBMMxGjvz5zx2d2OA+zbUsnbHoWTa6TPKWb64mhOnlOWlTICSAg/lRT58nqE1xFChUhRFyRH5dh57sL2LB1/cyVNvHp4LNXtCCcuXVDN3ZkVeTM1FhOICN+WFQy9QCVSoFEVRBkm+nce2hyI8smkPv31lb7KVNrXcz7KF1Sw9YQKuPAlUidPF5x1mU3YVKkVRlEGQT+exoUiMJ17ZyyOb9iRbaRVFXq45eyYXvn9KXgRERCj1eygv9I6YuVYqVIqiKAMgHLXdfPlwHhuLG/78Zj0PvriLxo4wAEU+N1fMm8Enz5hOoS/3RgwiQpnfw5gRJFAJVKgURVH6QTxuaAnmx3msMYa1Ow5x7/pa6pqDAHjdwsdPn8an51fmxRTcJUJZoZcxhd4hj9ybLSpUiqIoWZJP57Ev77Zzof62vx2wc6HOO2kS151TxaQyf87Lc4kwptBL2QgWqAQqVIqiKH3QFY3R2BEmlAevEu8caGfFulq27mpOpi183ziWLaqmenxxzstzuxyB8ntxjXCBSqBCpSiK0gOxhPPYYO69StQ1B7hv/U7WvHMwmfb+aWUsXzyLU6aNyXl5HpeLMYVeSv2eUSNQCVSoFEVRMtAWsl4lcu08trGji4c27uLJN/Yn9z1rfDE3LK7mrOqxOZ8L5XG5GFPkpczvGRUhPTKhQqUoipJCvpzHdoSirNy8m9+8vJcuZy7U5DI/1y2s4sNzJuZ8nMjrtgJVWtCzQK3Z3sBda2vY0xxgRkURNy2ZxdI5E3Naj1ygQqUoioLt5mvs7KIjlFtz865IjN+9uo9HNu2mzdl3eaGXzy6o5OJTp+bc24PX7aK8yEtJLwIFVqRuXrUNr1soL/TS0B7i5lXbuBVGnFipUCmKckxjjKEtGKU5kFvnsbG44S/b9vPAC7s42NEFQKHXzafmTufyudMp8uX29et1u6go9lFSkN1+71pbg9ctyXoU+TwEwlHuWlujQqUoijJSCIZjHOroyqlXCWMMG95t5N71texqCgDgcQmXnDaVzyyopKLIl7OywMacqijyUZylQCXY0xygPC1GVaHXTV1zIJfVywkqVIqiHHNEHOexnTl2HvvanhZWrKvhrXo7F0qAj5w0ievOmcmUMYU5LavA66aiyDvgltmMiiIa2kPdtg9GYkyvyF94kIGiQqUoyjGDMYaWQISWHHuVeK+hgxXra9lU25RMWzBrLNcvquZ9E0pyVg6A3+umosg3aDdKNy2Zxc2rthEIRyn0uglGYkRihpuWzMpRTXOHCpWiKMcEnV1Rmjpz6zx2X0uQ+zfs5NntDcm0k6aUceOSak6dXp6zcgAKfTbURq78/C2dM5FbsWNVdc0BpqvVn6IoyvCQD+exTZ1hfrFxF398vT45F2rmuCJuWFTNOe8bl9P5SkU+G2rD7829I9qlcyaOSGFKR4VKUZSjknjCq0QomrNuvs6uKI9t2cPjW+sIRWzLbGJpAdedU8V5J03K6Vyo4gLryTwfAjXaUKFSFOWooz0UobkzkjPnseFonFWv7eOXL+2m1XGnVOb38JmzKrn09Gk5nQtVUuBhTJGXAo8KVAIVKkVRjhpy7Tw2Fjc8+/YB7n9hJwfa7Fwov8fFJ+dO51NzZ2Q9ZykbSvyeYQ33PpLJq1CJyH3AxUCDMeYUJ+27wHIg4YnxX40xTzrrvg1cD8SArxhjnnbSLwDuANzAPcaY25z0amAlMBZ4GbjaGBMWkQLgIeBMoBG4whizM5/HqijK8BGLG5o6w7SHcuM81hjDxpom7llfS+2hTsB6Hb/4/VO4+uyZjC3OzVyokRTufSST7xbVA8D/YEUjlZ8YY36UmiAiJwFXAicDU4G/isjxzuqfA+cBdcBmEVlljHkLuN3Z10oR+T+syN3p/N9sjJktIlc6+a7IxwEqijK8tAYjtARy5zz2jbpWVqyr4c19bcm0c0+YwLKF1UyryM1cqES49zGFKlDZkFehMsasFZGqLLNfCqw0xnQBtSLyLjDfWfeuMaYGQERWApeKyNvAh4BPO3keBL6LFapLnb8Bfg38j4iIyXU4TkVRho1QxHqVCEdzMw5Vc7CDe9bXsrHm8FyoeVUVXL+omuMnleakjJEc7n0kM1xjVF8SkWuALcA3jDHNwDRgY0qeOicNYE9a+lnAOKDFGBPNkH9aYhtjTFREWp38h/JwLIqiDCHRWJymQDhnzmP3t4V4YMNOnnnrAIkv2TmTS1m+uJoPVFbkpIzREO59JDMcQnUn8H3AOP//F7AM620kHQNk+uwwveSnj3XdEJEbgRsBKisre6u3oijDSK6dx7YEwjz80m7+8No+IjG7vxkVhVy/uJrFs8fnZC7UaAr3PpIZcqEyxhxI/C0iK4A/Oot1wIyUrNOBfc7fmdIPAeUi4nFaVan5E/uqExEPMAZoIgPGmLuBuwHmzp2rXYOKMgIJhKM0duTGq0QwHOPxrXt4bEsdgbC1Dhxf4uPas6u44JTJORGU0RjufSQz5EIlIlOMMfXO4ieAN52/VwG/EpEfY40pjgM2YVtHxzkWfnuxBhefNsYYEXkO+CTW8u9a4Pcp+7oWeNFZv1rHpxRl9JFL57GRWJw/vl7Pwxt30Ryw1oGlfg9Xza/kE6dPpSAHE2tVoPJDvs3THwGWAuNFpA64BVgqIqdju+J2AjcBGGO2ichjwFtAFPiiMSbm7OdLwNNY8/T7jDHbnCL+BVgpIj8AXgHuddLvBX7hGGQ0YcVNUZRRQi6dx8aNYfX2Bu7fsJP61hAABR4Xl50xjavmVVLiH/xr0ONyOV18ozfc+0hGtKFxmLlz55otW7YMdzUU5Zims8t28w3Wq4Qxhk07m7hnXS3vHbRzoVwCFzlzocaXFAy6rl63i7JCL2X+Y1ugRGSrMWZuvvavnikU5RhkzfYG7lpbw57mADNGiNfscDROY2cXwfDgvUq8ta+Nu9fV8HpdazLtg8dPYNnCKmaMHXy8Ja/bxZgiL6V9hHtXckNWQiUiXzXG3NFXmqIoI5812xu4edU2vG6hvNBLQ3uIm1dt41YYFrHKpfPYXY2d3LO+lg3vNibTzqgsZ/niWZwwefBzobxuF+VFXkr93r4zKzkj2xbVtVgXRqlclyFNUZQRzl1ra/C6JRnZtcjnIRCOctfamiEXqvZQhKbOwXuVaGgL8cALu/jLW/tJ7Oq4iSUsX1zN3Kqxg66nz+OivMiXU99+SvYuLNEBAAAgAElEQVT0etZF5Cqs54dqEVmVsqoU60NPUZRRxp7mAOWF3VsEhV43dc2BIatDKBKjsTNM1yCdx7YGI/zqpd387tW9yblQ08oLWbawig+eMAHXILvlCrxuygu9FKtADSt9nf0XgHpgPHZiboJ24PV8VUpRlPwxo6KIhvZQskUFEIzEmF4x+LGbvsiV89hgJMZvX65j5aY9dDpjWuOKfVx99kwuPGXyoN0TFXjdVBR5u50jZfjo9SoYY3YBu4Czh6Y6iqLkm5uWzOLmVdsIhKMUet0EIzEiMcNNS2bltdzWYITmzsF5lYjG4jz55n4eenEXTZ1hAIoL3Fw1r5LLzpg26CCDuQ73ruSGbI0pLsN6IJ+InYArgDHGlOWxboqi5IGlcyZyK3asqq45wPQ8W/0FwzEaOwfnPDZuDM//7SD3bdjJ3pYgAF638IkPTOOq+ZWMKRyccUOhz01FkU+j6Y5Qsm3X/ifwMWPM2/msjKIoQ8PSORPzbjgRdbxKdAzCq4Qxhq27mlmxrpYdDR2AnQt1wcmTuebsmUws8w+qjkU+GwtKBWpkk61QHVCRUhQlG4wxToyoyKC6+bbvb2PFulpe2d2STFs0ezzXL6pi5rjiQdVRw72PLrIVqi0i8ijwO6ArkWiM+W1eaqUoyqgkF85jdzcFuG9DLWvfORyV57TpY1i+eBYnTR3caIONpqvh3kcb2QpVGRAAzk9JM4AKlaIoRGJxGjvCBMID7+Y72N7FQy/u4s9v1ifnQs2eUMINi6uZV1UxYA8QIkJxgTWSUIEanWQlVMaYz+W7IoqijD7icUNLMELrIJzHtociPLJpD799ZW/S4GLKGD/LFlZx7pyJA54LJSJOC0rDvY92srX6u58MgQeNMctyXiNFUUYFHV1RmgbhPLYrEuOJV/byq017kgYXFUVerl4wk4tOndKruGyqaWLl5j3UtwWZUlbIlfNmMH+W9UAhIpT6PZRruPejhmy7/v6Y8rcfG0dqXw95FUU5iumKxmjsCBMaoFeJWNzw5zf38+CLO2nssHOhinxurpg7g0+eOb3POUybapq4Y/UOPC6hzO+hsbOLO1bv4GtyHB85aRJjVKCOOrLt+vtN6rITZ+qveamRoigjkljCeWxwYF4ljDGs23GIe9fXsqf58FyoS0+fymfmz2RMUXZzoVZu3oPHJRQ6JuWFPjfhaJwnXtnLFfMrB1Q3ZWQzUP8gxwF6RyjKMUJbyHqVGKjz2Jd327lQf9vfDliPAeefPIlrz6licj/nQtW3BSnze0DALYLbJfjcruREYOXoI9sxqnbsGJU4/+/HRtdVFOUoZrDOY9850M6KdbVs3dWcTDt71jhuWFxN9fiBzYWaOqaQ5kCYkgJ30hIwEI4Oia9CZXjItutv8IFcFOUoZSQGIRwssbihsbOLjtDAzM33Nge5b0Mtz/3tYDLt/dPKWL54FqdMGzOgfSbCvX/lQ7O55Q9vEYzEkr4KW4MRfG4Xi25ffdRcA+UwWXf9icglwBJncY0x5o+95VeUY4GRFoRwsBhjaAtGaQ4MzHlsY0cXD23cxZNv7E92E1aPL+aGRdUsmDV2QHOhPC4bTTcR7v3cEychIklfhcU+NwKEY/Gj4hooR5Jt199twDzgl07SV0VkoTHm23mrmaKMAkZSEMLBEgzHONTRNSCvEh1dUR7dvIffbK0j5MyFmlRWwOfOqeLDJ07C7eq/QPUW7j3VV+FVd28kEjdHxTVQMpNti+pC4HRjTBxARB4EXgFUqJRjmpEQhHCwDMZ5bDga53ev7uVXL+2mzekmHFPo5bMLKvnYqVMH5AkiEe69JINAZeJouAZK7/TH6q8caHL+Hlgns6IcZQxnEMLBknAe2xzov1eJWNzwl7cO8OALO2lot+4/C71uLp87ncvPnD6giLgDDfc+mq+Bkh3Z3hH/AbwiIs9hLf+WoK0pRRm2IISDpbMrSlNn/53HGmPY8G4j966vZVeTbbF4XMLHTpvKZxdUUlHk63ddfB4XFUW+AYd7H63XQMkeyfZLSkSmYMepBHjJGLM/nxUbDubOnWu2bNky3NVQRhkJq7+hCEI4WMJR2803EOexr9W1sGJtLW/VtwH2RfDhEydy3TlVTC0v7Pf+chnufTRdg6MREdlqjJmbt/1nI1Qi8glgtTGm1VkuB5YaY36Xr4oNBypUytHKYJzHvtfQwYr1tWyqbUqmza8ey/JF1bxvYkm/6+L32mi6Gu796CHfQpXtp8wtxpgnEgvGmBYRuQUbn0pRlBHMQJ3H7msJ8sALO3n27YakR+qTppSyfPEsTptR3u96aLh3ZaBkK1SZTHcG315XFCVvDNR5bFNnmIc37uKPr9cTdeZCzRxbxPWLqlk4e1y/50JpuHdlsPQnwu+PgZ9jXSh9Gdiat1opijJg4gnnsaFov7r5OruiPL6ljse27iEUsa2viaUFXHtOFeef1P+5UMVOLCgN964MlmyF6svAd4BHneW/AP+elxopijJgBuI8NhyNs+q1ffzypd20Op7Ry/wePn1WJR8/fVq/50KVFHgYowKl5JBsff11At/qab2I/MwY8+Wc1UpRlH4xEOexsbjh2bcPcP8LOznQZudC+T0u/v7M6VwxdwYl/v717pf4PRruXckLuRpnWpij/SiK0g9icUNTZ5j2UPYxoowxbKxp4t71tdQc6gTA7RIuev8Url5QybiSgqz3peHelaFADSIUZZTSGrTdfP1xHvvm3lZWrKvhjb1tybRzT5jAsoXVTKvIfi5UItz7mEIVKCX/qFApyigjFInxx9f28fDG3dS3BZlSVsiV82Ywf9bYHrepPdTJPetqebGmMZk2d2YFNyyu5vhJ2UfxEbHh3zXcuzKU5Eqo+u8aWVGUfpFwHrv67QbuWL0Dj8uKRmNnF3es3sFXOe4IsdrfFuKBDTt55q0DyblQJ0wuZfnias6orMi6bJcIZYVexhR6B+QJXVEGQ7+ESkSKHcOKdO7IUX0URUkj4Ty2JRAhbgwrN+/B4xIKnXlJCf92KzfvSQpVayDCwy/tYtVr+4jErETNqCjk+sXVLJ49Puu5UC4RxhR6KVOBUoaRrNruInKOiLwFvO0snyYi/5tYb4x5oIft7hORBhF5MyVtrIg8IyI7nP8rnHQRkZ+KyLsi8rqInJGyzbVO/h0icm1K+pki8oazzU/Fefp6KkNRRhuBcJS65iBNKWNR9W1B/N7uj67f62J/W5BgOMYvXtzFZ+59id+8vJdIzDC+xMc3zjue+66bx5LjJmQlUm6XMLbYR+XYIiqKfSpSyrCSbSfzT4C/AxoBjDGvcTjab288AFyQlvYt4FljzHHAsxw2e/8ocJzzuxG4E6zoALcAZwHzgVtShOdOJ29iuwv6KENRRgWRWJz9rSH2t4aO8HA+pawwOSE3QTAcw+1y8dl7X+L+F3YSCMco9Xu4ccksfrFsPhedOiUrsXG7hHHFBcyoKKK8yIdLBUoZAWQ9GmqM2ZOW1OeEDWPMWg7HsEpwKfCg8/eDwMdT0h8ylo1AueOx/e+AZ4wxTcaYZuAZ4AJnXZkx5kVjp98/lLavTGUoyogm7pib1zUHe/RwfuW8GUTjhmAkRtzEOdTZRX1bF3tbgjQHIvg8Lq6cN4OHr5/PlfNmUJCF6yKPy8W44gIqxxYxpsirAqWMKLIdo9ojIucARkR8wFdwugEHwCRjTD2AMaZeRBK++KcBqWJY56T1ll6XIb23MhRlxJKt89j5s8byFTObFetq2dkYSPrjcwlc+P4pXL1gJhNKs5sL1Vu4d0UZKWQrVJ/HGkwkxOEvwD/kuC6ZnhIzgPT+FSpyI7b7kMrKyv5uriiDpr/OY9/a18ajW/dQ03jYrmnJ8eNZtrCayrHZRbVVgVJGE9kK1QnGmM+kJojIQmDDAMo8ICJTnJbOFKDBSa8DZqTkmw7sc9KXpqWvcdKnZ8jfWxlHYIy5G7gbbDyqARyPogyIWMJ5bDA7rxK7Gju5d/1O1r97KJn2gcpyli+uZs7ksqz24XW7KC/yUur3DqjOijIcZCtUPwPOyCItG1YB1wK3Of//PiX9SyKyEms40eoIzdPA/5diQHE+8G1jTJOItIvIAuAl4BqnTr2VoSgjgv44j21oC/HQi7t4att+EtlnTyxh+eJq5s6syKpF5PO4KC/yUTLAcO+KMpz0eteKyNnAOcAEEfl6yqoyoM8RWhF5BNsaGi8idVjrvduAx0TkemA3cLmT/UngQuBdIAB8DsARpO8Dm518txpjEgYaX8BaFhYCf3Z+9FKGogwr/XEe2xaM8KtNu3nilb3JuVDTygtZtrCKD54wAVcWAlXgdVNe6KVYBUoZxfR19/qAEidfqp+VNuCTfe3cGHNVD6s+nCGvAb7Yw37uA+7LkL4FOCVDemOmMhRluIjFDY2dXXSEMlvybappYuXmPdS3BZlY4mdquZ/17x2is8sK2thiH9ecPZMLT5mclesiv9dNeZGXIp8KlDL66fUuNsY8DzwvIg8YY3YNUZ0UZchYs72Bu9bWsKc5wIyKIm5aMoulc3JnJGqMoS0YpTnQs/PYTTVN3LF6B26BuDFsq2/ljX2tABT73Fw5fwaXnTE96YmiNwp9bsoLfRT6NBaUcvTQV9fffxtjvgb8j4gc8ZQZYy7JW80UJc+s2d7Azau24XUL5YVeGtpD3LxqG7dCTsQqGI5xqKPriAm76TyyaTfhaIy2UDTZxQcwoaSAu685kzGFfRs+aLh35Wimr36BXzj//yjfFVGUoeautTV43ZLsHivyeQiEo9y1tmZQQhVxnMd2dmXu5ktl665mttW3JedCgY2uO7bYSygS71OkVKCUY4G+uv62iogbWG6M+ewQ1UlRhoQ9zQHK04Sg0OumrjkwoP0ZY2gJRGgJRjB9xIj62/52Vqyr4eXdLcm0Yp+b8SUFFHhcBCMxJpf1HB9Kw70rxxJ9jrQaY2IiMkFEfMaY8FBUSlGGghkVRTS0h7oZHAQjMaZXZDdpNpXOrihNneE+u/n2NAW4b8NOnn/nYDKtelwxbaEIRT43Po8QjMSIxg1XzptxxPY2mq6Ge1eOLbI1CdoJbBCRVUByOrwx5sf5qJSiDAU3LZnFzau2EQhHk6EyIjHDTUtmZb2PcDROY2cXwXDv5uaHOrp46MVdPPlGfXIu1PsmFHPD4mrmV41lc20zKzfvYX9bkMlpgRBFhOICayShAqUci2QrVPucn4vuZuqKMmpZOmcit2LHquqaA0zvh9VfPOFVIhTttZuvPRRh5eY9/PblvXRFbWtryhg/n1tYxYfmTEzOhZo/a+wRQQ9FxGlBabh35dgmK6EyxnwPQERK7aLpyGutFCULcmFavnTOxKy3SZS3q6mTSaV+rpjbc/j3rkiMJ17ZyyOb99DuzJ2qKPLy2QUzufjUKb0Kj4hQ6vdQruHeFQXIUqhE5BSsBeBYZ/kQcI0xZlse66YoPZJv0/JM5X3n928iYo0eDnVkDv8eixv+/OZ+HnxxJ40ddki30OvminnTufzMGb3Ob3I5AjVGBUpRupFt19/dwNeNMc8BiMhSYAXWvZKiDDn5Mi3PRCxu+NnqdwHwezKHfzfGsO7dQ9y7rpY9zUEAvG7hY6dN5bNnVVJe5OvmfWJKyjiUS4SyQi9jNNy7omQkW6EqTogUgDFmjYgU56lOitInuTYt74nWYISWQJi6lgBl/u6PSyL8+yu7m1mxrpbt+9sBG3/mvJMmcd05VUwe4wcOe5/wuIQyv4fGTtsi+7eCE7nw1CkaqFBReiFboaoRke9weALwZ4Ha/FRJGc3k2yVRglyalmciFInxx9f28fDG3dS3BekIRYnF4owtPhyQsC0YJRCO8Y3HX0+mLZg1lhsWVTNrQkm3/a3cvAePS6wbJIESv4euSIxfbtrNxadPzUmdFeVoJVuhWgZ8D/gt9oPxeRzv5oqSYCjHjXJhWp6JqONVYvXbDd1aQPF4nMZOGzequMDDwfYwgRQP6KdMLWP54lm8f/qYjPutbwsyxm/HnlxiDSbcPsl5C1BRjkayFaoqY8xX8loTZdSSaEW9vLsZASaP8SMieR03GoxpeSaMMU43X4S4Md1bQEBFUQHxuKElGOVQ5+FAh1XjirhhcTVnzxrXY1woj8tFZUURjZ1dFKS4OsplC1BRjmayFaofO5FyHwdWqrWfkiC1FRU3BgH2tYSYWg6lfu+Ax42y6ULsj2l5bwTCURo7unuVqG8LJsekEpF4mwNREjOmJpUV8LlzqvjwiZN6NIBIDff+xXNn56UFqCjHAtnOozpXRCYDnwLuFpEy4FFjzA/yWjtlxJNqfedzu4jGDAgcbO+i1O8dUKthqLoQI7E4jR1hAuEjncdOKSvkUEeIrmicxs5w0puE2yXctGQWl5w2tUcvEYlw7yUFnmQrK9ctQEU5lsg6qpoxZj/wUxF5Dvhn4GZAheoYJ9X6bnxJAftag4iBrmicQDg6oFZDvk3PjTE0ByK09uA8NhY3zJ5Ywut7W5ICJUBxgZtvnncCS06YkHG/fYV7z1ULUFGONbKd8HsicAU2qm8jsBL4Rh7rpYwSEtZ30ZjhUEcXcWOFwCUwsdQ/oFZDPk3Pe3Mea4zhhfcauWd9LbsabVkCFHpdVI8v4eoFMzN6ovB5XFQU+TTcu6LkiWyfrPuBR4DzjTH78lgfZZRx05JZfPPXr9ESiOASbJRahIoi74C7tvJhet6X89jX61pYsa6WbfvaACtQH5ozkc8trGJqeeZwGwVeNxUa7l1R8k62Y1QL8l0RZXSydM5EJpQU2HlGxuBzu5hQWoDbJQPuqsul6XlfzmPfO9jBvetr2VjTlEybXz2W5Yuqed/EkiPyA/i9biqKNNy7ogwV2Xb9HQf8B3AS4E+kG2PUZEnhYEcXLoGUKOqD6qrLleFBeyhCc2eEaPzIbr761iD3b9jJs283JC35TpxSyo2LZ3HajPKM+yv0WYHSaLqKMrT0p+vvFuAnwLnYyb7q80VhzfYG2kNR4sbgdgnRuGFfS4hxJV6qxmVukWTDYAwPuqIxGjvChCJHdvM1B8I8vHE3f3htXzL8+8yxRVy/qJqFszPPhdJw74oyvGQrVIXGmGdFRIwxu4Dvisg6rHgpRxn9cYN019oaKoq8NHaGMXEQgTiGps4I//GJoW1wJ+Y7tQUjR6wLhKM8tqWOx7fUEXQEbEJJAdedM5PzT56ccS5UsRMLSsO9K8rwkq1QhUTEBewQkS8BewG1sz0K6e8cpj3NAcaXFFDgcXOgLZQMDuh29RxMMB+0hSI0d4aJxbuXG47G+ePr1mdfiyNgZX4Pnz6rkktPm9rNU0SCkgIPY1SgFGXE0KtQicgvjDFXA78HioCvAN8HPgRcm//qKUNNf+cwJSz0RCBurKm2MQaXS/IaHypBKBLjUEcX4Wj3cahY3LB6ewP3b9jJ/rYQAAUeF39/xjSunFdJSZondA33rigjl75aVGeKyEzgM9j4UwF0/tRRTX/nMCUs9BraQoABIxhgUqkfj3vgln99EYsbGju76Ah19yphjOGl2ibuWVdLzaFOAFwCF506hWsWzGRcSUG3/BruXVFGPn0J1f8BTwGzgK1YAwqT8r9a/R1l9HcOU8JC76aHt2KwwQLHl/gpK/RijMm5d3BjDG3BKM2BMPE0c/M397ayYl0tb+xtTaade8IEPrew6oj6a7h3RRk99CpUxpifYt0m3WmM+cIQ1UkZRgYyh2npnImcUVmR1/hQAMGw7eZL9ypRe6iTe9fX8sJ7jcm0M2dWsHxxNcdPKu2WV8SG7dBw74oyesh2wq+K1DHCQOcw5Ss+FByOEdXR1b2bb39biAdf2Mkzbx1I+uQ7YVIpy5dUc0ZlRbe8Gu5dUUYv6vtFOYKBzGHKh3fwRIyo5kB357GtgQi/3LSL37+6j4gzy3h6RSHLFlbzwePHd5sL5RJhTKGXMhUoRRm1qFApgyJfoeczxYgKRmL8emsdj23eQ6fjs29ciY9rz57JBSdP7taV53Y5AuX34lKBUpRRjQqVMmAyzbn65q9fY0JJAe1d0QEJV6YYUZFYnCffqOehF3fRHLBzoUoKPFw1fwaf+MC0bh4j3C6hvNBHqd+TUaDyJayKouQPFSplwKTPuYrGDC2BCB2hKLMnlvQr4GGmGFFxY3hu+0Hu21BLfaudC+XzuLjsA9O4av4M3t7Xzr/+9k3q24JMHVPIDYuqufDUKT2GhB+qgIyKouQWFSrlCLJtdaTPuTqUdE5rEJGsAx52dEVp6ggnnccaY9i8s5l71tXy7sEOwM6F+ugpU7jm7JlMKC1gU00Td6zegdctjC3y0RoMc/vTf6O4wNOru6eeJjMn1mtLS1FGHipUSjf60+pID5rYGY4hgM99uEXT22ThTDGi3q5vY8W6Gl7dc3gu1JLjxrNsYTWV4w6buj+6ZQ9+j4tiJ9y7x+3qUxR7msy840CbtrQUZQQzbBNJRGSniLwhIq+KyBYnbayIPCMiO5z/K5x0EZGfisi7IvK6iJyRsp9rnfw7ROTalPQznf2/62yrI+pZkNrqSLSKvI6HiXRuWjKL1mCEvS3BpNGDwYb7SDiGzTSXKh43NHZ0sbclmBSp3Y0Bblm1jS/+6pWkSH2gspyff/oDfPeSk5Mi5XW7mFjm52BHV1KkEvQVWmRGRVHSIW2CYCRGOGayPmZFUYae4W5RnWuMOZSy/C3gWWPMbSLyLWf5X4CPAsc5v7OAO4GzRGQs1oP7XOw7cquIrDLGNDt5bgQ2Ak8CFwB/HprDGn4GajTQHxdK6UET/R4X0bhBxHYDetxyxFyq9lCEphTnsQfbu3jwxZ089eb+5Fyo2RNLWL64mrkzK5JC5PO4KC/yUeKEex9IFOCe5nr5PC4K05zTDiaelqIouWW4hSqdS4Glzt8PAmuwQnUp8JCxo+wbRaRcRKY4eZ8xxjQBiMgzwAUisgYoM8a86KQ/BHycY0SoBmM0kEkAGju76OyKsej21d1Eb832BmoOdRKNG4wxxLARfo0xhKJxJpb6k3lDkRh/em0fv9i4m/q2IBNKChhb7GNjbVPSoezUcj/LFlaz9IQJuByBKvC6KS/0UlzQ/VYdqAeNTHO97lpbk3evGoqiDJzhFCoD/EVEDHCXMeZuYJIxph7AGFMvIom36jRgT8q2dU5ab+l1GdKPQERuxLa8qKysHOwxDTtrtjfwlZWv0BmO4ve4mVBaQKnfm5VRAxwpAI2dXTS0h5lQ4usmep+sa+HXL++1ApUSWsMaRAjHTyzhkRsXEIsbDrZ38exbB7hj9Q5cYj1NbKtvIzGHt6LIyzVnz+TC909JOob1e92UF3m7iUcqA51g3NNk5nx51VAUZfAMp1AtNMbsc8ToGRHZ3kveTONLZgDpRyZagbwbYO7cuUMbRCnHJFpSgXAMT0q03anl1pLu5d3NLLp9NSU+NyKSca5TugB0dsWYUOJjQqkfOGwpd8/6WiaUFjgtn1ShAjC0h6ypeUvAdvM9smk3oUiMtlA0KWwCTCrzc+91c5Ndb4U+G2qj0Nd3LKjBRAFO30+uvWooipI7hk2ojDH7nP8bROQJYD5wQESmOK2pKUCDk70OmJGy+XRgn5O+NC19jZM+PUP+o5rb/vw2De0hYnFDLG49mYvgGDsYBDjYFqI+bs3Hp5X7M3YLpgrAottXZxyz6gzHqPS6iRmTFMVU6lpCLP3hc1RWFHHytDG8Wd/WTaDKC71UFHsJhGMUet3DHu49V6KnKEruGRarPxEpFpHSxN/A+cCbwCoOB2S8FhuwESf9Gsf6bwHQ6nQRPg2cLyIVjoXg+cDTzrp2EVngWPtdk7Kvo4412xv46H+vZfuBDroi8WQMlnAsTjQWT/rD87ggHDM4ixzqCPdp4daTpVyxz3aR+dwuYnGTsQnbEYrw1v42frVpd1KkyvweqsYVMaG0gEjMMK28iKnlhUwe4x82kVIUZWQzXObpk4D1IvIasAn4kzHmKeA24DwR2QGc5yyDtdqrAd7FBnD8BwDHiOL7wGbnd2vCsAL4AnCPs817HKWGFInuvlonSKABUoNgJETJ6wKP+7AQxI0h7JiU9xUYMRIzBMJRjLH/R2KGGxZVE4kZygo9GI7sVxUgEicpkkU+N+NLfE54DaErasXvyx+arQKlKEqvDEvXnzGmBjgtQ3oj8OEM6Qb4Yg/7ug+4L0P6FuCUQVd2mOnNzDzVcCIeB7ccFqZUPAIul/0mEQFjbNj4QsdwIZvAiJnGb06dXs7/rnmPg21dxEx3sUr8Xeh1Ma7ERzRm+NqHj+fxrXUcaAsyY2zxEeNA6odPUZRMiDGj2n4gp8ydO9ds2bJluKuRJNXMPNUa7dZLTgaspdq+lqC1vMtwGdPDMYuAmMMtrpljC/G4Xcl9DtR57F+3HeC/V+8gEO7eRTiu2MvYIl/SVH3lTQt6DPfe27GqWCnKyEZEthpj5uZr/yNtHpWSQl++6RLGEtF45u1dTgsroWEm5W+3S9jf1kX1uCK+c9FJPYpBeitn+eJqTq+soDUYoT0YYeXm3Ty+tS7ZxQdWGMcVe6go9hF20r/8odk9ilRfx6pCpSjHNipUI5jevEQEIzECXdFuApGOq4euQAH8Hhdd0Ti1jQFer2vJKAY//es7/Oy5d5MWg/tbgmzf38bXP3I8e1qCPLJpN+2haLKsccU+CjwuOsMxyou8BMOxjF18/T1WRVGObVSoRjAzKorY2dhBWzBKOBbH53ZRVuihvNBHfWuQWA8tqQSRHtYbbEgOj0uIGcPP17zHqdPLk94m7lpbwzsH2mjsjHTfxkBzIMJ3Vm1LprvExoaaWFKAyy24RfB5XEwoLeSRGxf061jVO4SiKJkYNqe0St9MLvNR32q9kkdjhlA0RkN7mIa2YLduvFSy9bzrcgkigtslRONx7lpbkxwnamgPEepJ5VIo8rkp9XuYVObH63Hhc84WhDgAABLnSURBVLvwuF0U+Tz9bgn1ZF2o3iEURdEW1QhlzfYGnnzzAIkgtXEDsTi4xdAYiPa4XX9NY4yBAreLuuYAtz+1nYa2EDFjeu1STJAwnnARYvrY4mR6oiXUHys+9Q6hKEpPqNVfCiPJ6u+CnzzP9gMdedu/z21bVMbAuBIv5YU+3mnowIXB5RK6ov27L0p8LgxCVzSO2yVceMoktu5uxesWorE4B9q7iMQMx08s4V8umKMCpChHEfm2+tOuvxHImu0N/C2PIgWOh4pYnHElXrxuN/F4HI/LtrCyaU2l0xGOE4rE8LmFscVennzzAOGo7bLc1xrCOPO8ag91cvOqbazZ3tD3ThVFUVChGpHc/tT2fnfhDYSogZbOCB1dEWoczxZRZzJwtqSOibldNqjh+BI/0Xic9lDUhqdHcLnsL2aMBiVUFKVf6BjVCCIxpvP2/va8liNYv3+RuA3LEY6KtRDsQaHcAuNLCmgNRgilTNqSxD/OZiI2EGKp30uB25q/i4DbiS1lDPjcLjU7VxSlX6hQDTMJcXpjbzOd4XjWVnuDwXDYdD0Sh0hX7Ig8brEtpPJCD42dYQ60d9lxLVImEHN4wS1WqBL+A8cUeWnqjCBiQ88LVqgmlBao2bmiKP1ChWoYSIjTtn2ttIeiGX3kDTcGG3G31O+lJRAm7pjDF/ncuAXaHHFzCZT43ASjcWJxg9clBMJRvG43X1xayZNv1LPjYAdeESaPKcDtOjI8vaIoSm+oUA0xiblKkZgNIjiSKfVbTxExrEDNmlCSXNcWDFPXEqRqXDGFXjeHOrpoDkQoKvB0C0H/lY8cnxTmuuZAt3WKoijZoEI1xCR82jW0RfrOPEhcgNtl51953JL0u5e6PnVar4AzAdjmM8YQjMTwuFyU+rvfKh63i+MmlFBRXEBdc4Dq8SXc1oMAaVBCRVEGgwrVELOjoZ1AV7SbUUK+sD5ghTgmKVIJD+rTxxbiEmFn42GjBm9ybpXBJUJrMML0iiIuPW0qv355L4Fw9Ig5Udo6UhQl36hQDSE//es7NHaGGao51tZg4nD497HFXvxuoaEzwr6WEAUeFz632LElt8uajruEscUFVI0r6ear79Tp5dz257fZ2RjE63IxvdxPOBY/Ioy9oihKrtF5VEPEmu0N/HzNe0MmUql4XDCvqoL/uvx03B4P40t8+NxCKBojbgwlfg/TKgo5YVIpk8f48brdRxg7LJ0zkYriAqrGFXPcpFLKCn19hrFXFEXJBdqiGiLuWltD1xB096VjzcmFf1g6Ozk+NqbQTsoFrIWeS5JjTb352NNQHIqiDAcqVEPEjob8TuLtCQNMKStg6ZyJ/Pvv38woNK3BCE/9Y98hOTQUh6Iow4EKVZ5I9RxeWuDhUEd4yOvgdVunswkz88EKzU1LZnHzqm0EwtFu4eJ1TpSiKPlEx6jyQGpcJ7fA9jy7RMqEYN0VTSv309Fl52sNNubT0jkTufWSk5lY6qc1GGFiqZ9bLzlZDSkURckr2qLKA4mxoCKfh7f3tQ65twkBZo4rotTvJRCOMrHUjkflIuaTzolSFGWoUaHKAwmjg7ZghH6GdcoJifDwmVpMKjSKoow2tOsvD8yoKCIYibGvNTik5XpcgttlvU3saOjA6xLtmlMUZdSjLaocs2Z7Ay2BMDsbA8T6E9gpB8TiBrdLqKzw43G7CDgu0vsTEl5RFGWkoUKVQxJGFOFoDDOEM3tdYkNJicC08kLKHBP0QDjK7U9tpzMcw+sWygu9NLSH1JuEoiijCu36yyF3ra0hHP3/27v3IDmrMo/j31+/Mz2XTELugLmYCwkxXtAYdhMEjBEJimVYixUsUOJKKetagFllw7q1te7W1opQ2V1XlKKism4JuGTBzWphCjVA0BASQIhIQmICZDAhCZfMJE4yM93P/nFOT7qTuSXTPdPT/Xyquvp9z3uZ8546M8+8b59+Toa9LUdPapbcgRBQG5L6kaTUFaQgfEdq54HDXQM7JHk2CefcsON3VEW0+40/cuDQ0UH9mUZu5tww1Xu+to4wZ1RDbVJQ7tkknHPDid9RFdHIuhoGO0tSSjCuqZbTGmq7Rvrlf0dq+rjGroCV49kknHPDid9RFdHu1w8P2s9K4udSYxtrmTauqWsI+vHfkQI8m4RzbljzQFUkD2/dx6H2wbmdSilMXPhXi2Zy/UWzC7Z1N0BioF/ydc65oeSBqkhKMTihNhEffecZ7G1pZ/u+Vto7s6QTMev0UScVbPxLvs654cwDVZFs2PlaUc83ZUwD/7T0HR5gnHNVzwNVEUxb8dOinm/5RbNOeKTnnHPVqqJH/Um6RNI2STskrSjFzyhmkBrflOauZed6kHLOuTwVe0clKQFuBz4ENAObJK0xs98V62csWbmuWKcC4MChdpbdtanP/WpSkMlSkJU9JairSdGYTmhM17D3YBsxgxICGtIJjemEWRNHdn2+lUut9MKrLXRkjHRNqtvtuc/HzAxJ1CZidt7nZA9v3cff/XgLrxw8ghk01iZc9/4ZvGvy6ILUTQtnjGXDztd7TOVUzameqvnaneuLBjPVz2CStBD4BzNbEtdvBjCzf+npmPnz59vmzZv7df5f7TjAVas2FqOqgyYRTBxVR22ScPm8Sax+6hXaOzO8djhO6mgwfmS6YHtHJsOB1nayGJlsCIhJSowbkSZdE/ZbtX4nLUcLv6slYGRdwoRR9TTUJrx2+Cj7WtuZ0JRmfFNd1zD5XNLcXPqp2kQFw+irIaluNV+7qwySnjSz+aU6fyU/+psE7M5bb45lA7Kl+SBXr9o47IIUhO9dtbR1UpuIVY/tojYRrUc6SSFqUilSKZ2wvaWtk1QqzBSckyIcl9vvUHsIUlJ8Ee72DrVnulI3tbR1khK0HunsNpVT/hxe1ZbqqZqv3bn+qNhHf4S/l8c74fZR0ueAzwFMnTq1x5PtOnCY29Zu46db9hStgoPNgPZMlobahMPtGabWJrRnsiQKTSX1sD0vUJmduF9PeQ3zy9szWVLxuJz8VE65ObzyVUuqp2q+duf6o5LvqJqBKXnrk4E/HL+Tmd1pZvPNbP6ECRNOOMm+liP87f1b+NDKR7qC1OzTm/jespLd5ZZMbnr6to4MI9LhEVM6SRUEoZ62x1iGdOJ+qe7+JYCC8nSSIhuPy8lP5ZSbwytftaR6quZrd64/KjlQbQJmSZouKQ1cCazp78EH2zq45WdbufDWddz9xMt0Zo23jK7nX684hwdvuJDFc04vWcVLJSUY1VBDR8a49vzpdGSMkfU1ZDE6s1myWTth+6iGGrJZ6wpUAFnCcbn9mtIh6a1ZfBGCYlM66co9OKqhhqzByPqaglyEuVROn79wBh0ZOyFXYTWkeqrma3euPyr20Z+ZdUr6IrAWSIDvmdlzfR13pCPDXb9+ke88/HsOtnUAMKaxli8unsXVC6ZSV3MsE/mLX7+0x+Hp6ZSoTyd0ZowjHRmKmVypt1F/I9IJDb2M+svlBVw0Z2LXqLzOTAvtcdRfd9s7MoWj/tKJmD6+cL/eRv01v/FHpo1r4pPnhlF/3aVyWjRnYtWmeqrma3euPyp21N+pmPG2d9mEq1fyamuYqqMxnfDZ86fz+ffPpKmuYmO6c84NSKlH/flf3zyvvNlGtvUoNSnxiflTWH7xbMY31Q11tZxzrqp5oDrOpe88k5uWnM1bx48Y6qo455zDA1WBsyY0cftV84a6Gs455/JU8qi/k9aQTvreyTnn3KDyQOWcc66seaByzjlX1jxQOeecK2seqJxzzpU1D1TOOefKmgcq55xzZc0DlXPOubLmgco551xZ86S0eSTtB146xcPHAweKWJ1K5G3UO2+fvnkb9W0o2uitZnbihH5F4oGqSCRtLmX24ErgbdQ7b5++eRv1rRLbyB/9OeecK2seqJxzzpU1D1TFc+dQV2AY8DbqnbdP37yN+lZxbeSfUTnnnCtrfkflnHOurHmgcs45V9Y8UBWBpEskbZO0Q9KKoa5PKUmaImmdpOclPSfphlg+VtJDkrbH9zGxXJK+GdvmWUnz8s51Tdx/u6Rr8srfK2lLPOabkjT4VzowkhJJT0v6SVyfLmljvNYfSUrH8rq4viNun5Z3jptj+TZJS/LKh31/kzRa0mpJW2NfWuh9qJCkL8Xfsd9KukdSfdX2IzPz1wBeQAL8HpgBpIFngLlDXa8SXu+ZwLy4PBJ4AZgLfANYEctXALfE5Y8ADwICFgAbY/lYYGd8HxOXx8RtTwAL4zEPAh8e6us+hXZaDtwN/CSu/zdwZVy+A/jLuPwF4I64fCXwo7g8N/alOmB67GNJpfQ34D+Ba+NyGhjtfaigfSYBu4CGvP6zrFr7kd9RDdyfADvMbKeZtQP3AkuHuE4lY2Z7zOypuNwKPE/4pVpK+ONDfL8sLi8FfmDB48BoSWcCS4CHzOx1M3sDeAi4JG4bZWYbLPym/SDvXMOCpMnApcCquC5gMbA67nJ8++TabTXwwbj/UuBeMztqZruAHYS+Nuz7m6RRwIXAdwHMrN3M3sT70PFqgAZJNUAjsIcq7UceqAZuErA7b705llW8+HjhPcBG4HQz2wMhmAET4249tU9v5c3dlA8n/wbcBGTj+jjgTTPrjOv519TVDnH7wbj/ybbbcDID2A98Pz4eXSVpBN6HupjZK8BtwMuEAHUQeJIq7UceqAauu2ffFT/mX1IT8D/AjWbW0tuu3ZTZKZQPC5I+Cuwzsyfzi7vZ1frYVpHtE9UA84DvmNl7gMOER309qbo2ip/PLSU8rnsLMAL4cDe7VkU/8kA1cM3AlLz1ycAfhqgug0JSLSFI/dDM7o/Fr8ZHLsT3fbG8p/bprXxyN+XDxfuAj0l6kfA4ZTHhDmt0fIQDhdfU1Q5x+2nA65x8uw0nzUCzmW2M66sJgcv70DEXAbvMbL+ZdQD3A+dRpf3IA9XAbQJmxdE4acIHmWuGuE4lE597fxd43sxW5m1aA+RGXV0D/G9e+afjyK0FwMH4WGctcLGkMfG/x4uBtXFbq6QF8Wd9Ou9cZc/MbjazyWY2jdAXfmlmVwHrgMvjbse3T67dLo/7Wyy/Mo7mmg7MIgwQGPb9zcz2ArslnR2LPgj8Du9D+V4GFkhqjNeQa6Pq7EdDPZqjEl6EUUkvEEbRfHWo61Piaz2f8IjgWeA38fURwvPwXwDb4/vYuL+A22PbbAHm553rLwgf7u4APpNXPh/4bTzmW8QMKsPtBSzi2Ki/GYQ/EDuA+4C6WF4f13fE7TPyjv9qbINt5I1aq4T+Brwb2Bz70Y8Jo/a8DxW20deArfE6/oswcq8q+5GnUHLOOVfW/NGfc865suaByjnnXFnzQOWcc66seaByzjlX1jxQOTdAkm6U1FjC818maW6pzt/POiySdN5Q1sFVLw9UzvVD/A5PT78vNxJysZXKZYTkokNpEeELp84NOg9UzvVA0jSFKSi+DTwFfErSBklPSbpPUpOk6wkpbtYpTH/yCUkr4/E3SNoZl2dKeiwuv1fSI5KelLQ2LxvDTEk/i+XrJc2JdzEfA26V9BtJM3uo61mSfi7pmVi/mTG43qowTcQWSVfEfRcpTj8S178laVlcflHS1+I5tsQ6TAOuA74U63BBCZrbuR7V9L2Lc1XtbOAzwN8T0thcZGaHJf0NsNzM/lHScuADZnZA0hnAV+KxFwCvSZpE+KL0+ph+6j+ApWa2PwaPfyZ8cfVO4Doz2y7pT4Fvm9liSWsIXxxeTc9+CHzdzB6QVE/4J/TjhC/WngOMBzZJerQf13zAzOZJ+gLwZTO7VtIdwCEzu62/DedcsXigcq53L5nZ4wrJZucCvwoZbUgDG47f2cz2xjutkYRcancTprS4gBDozgbeATwUz5MAexSS/J4H3Kdjc/zV9aeC8WdNMrMHYh2OxPLzgXvMLEPIo/cIcC7QWxJhYj0hZOv+eH/q4FwpeaByrneH47sIcx99sh/HbCDchW0D1hPulhYCfw1MBZ4zs4X5ByjM0fSmmb37FOrY0+y1PZV3UvjYv/647Ufjewb/G+HKgH9G5Vz/PA68T9JZADFZ6Oy4rZUw23HOo8CX4/vTwAeAo2Z2kBC8JkhaGM9TK+ntFqZK2SXpz2O5JJ3Tw/kLxGObJV0Wj62LoxAfBa6QlEiaQLizewJ4CZgb9zuNkPC0L73WwblS8kDlXD+Y2X7CVOD3SHqWELjmxM13Ag9KWhfX1xMe+z0aH7vtBh6L52knZLe+RdIzhKS+udF0VwGfjeXPcWzG1XuBryhMMtjtYArgU8D1sW6/Bs4AHiAkfX0G+CVwk5ntNbPdhCnNnyV8tvV0P5rg/4A/88EUbih4UlrnnHNlze+onHPOlTX/oNS5YUTS7YRZhPP9u5l9fyjq49xg8Ed/zjnnypo/+nPOOVfWPFA555wrax6onHPOlTUPVM4558qaByrnnHNlzQOVc865svb/FSRuy6gkyewAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbfeeaca668>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a new dataframe with only the columns we need\n",
    "df_1 = df_twitter_master[['retweet_count', 'favorite_count']]\n",
    "\n",
    "# We will use seaborn to make a scatterplot with a regression line\n",
    "sns.regplot(df_1['retweet_count'], df_1['favorite_count']).set_title(\n",
    "    \"Correlation Between Retweet and Favorite Count\", size = 15)\n",
    "\n",
    "# Save the plot so that we can use it for the separate reports\n",
    "plt.savefig('Correlation Between Retweet and Favorite Count.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations:**<br />\n",
    "I chose this visualization because I noticed that while assessing for 3 insights, the most favorited and most retweeted tweet are the same. It got me thinking what is the correlation betweetn retweet_count and favorite_count variables? By looking at the graph above and doing a visual assessment, we can infer that a greater number of retweets will increase the likelihood that the tweet will also be favorited. There is a steep, positive correlation based on the best fit line of the graph. Every increase in retweet count will get multiple favorite hits. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization #2: Algorithms' Success Rate###<br />\n",
    "We will condense the 3 algorithms with 6 columns into 2 columns by melting it. We will then be able to use this new dataframe to create a boxplot graph. This graph will show how successful each of the alogrithims are compared to one another."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py:2746: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "\n",
       "    .dataframe tbody tr 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>p1_conf</th>\n",
       "      <th>p1_bool</th>\n",
       "      <th>p2_conf</th>\n",
       "      <th>p2_bool</th>\n",
       "      <th>p3_conf</th>\n",
       "      <th>p3_bool</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.097049</td>\n",
       "      <td>False</td>\n",
       "      <td>0.085851</td>\n",
       "      <td>False</td>\n",
       "      <td>0.076110</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.323581</td>\n",
       "      <td>True</td>\n",
       "      <td>0.090647</td>\n",
       "      <td>True</td>\n",
       "      <td>0.068957</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.716012</td>\n",
       "      <td>True</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.555712</td>\n",
       "      <td>True</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    p1_conf  p1_bool   p2_conf  p2_bool   p3_conf  p3_bool\n",
       "0  0.097049    False  0.085851    False  0.076110    False\n",
       "1  0.323581     True  0.090647     True  0.068957     True\n",
       "2  0.716012     True  0.078253     True  0.031379     True\n",
       "3  0.170278    False  0.168086     True  0.040836    False\n",
       "4  0.555712     True  0.225770     True  0.175219     True"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Start off by gathering the columns from the master dataframe that we only need.\n",
    "df_2 = df_twitter_master[['p1_conf', 'p1_dog', 'p2_conf', 'p2_dog', 'p3_conf', 'p3_dog']]\n",
    "df_2.rename(columns={'p1_dog':'p1_bool',\n",
    "                          'p2_dog':'p2_bool',\n",
    "                          'p3_dog':'p3_bool'}, \n",
    "                 inplace=True)\n",
    "# Test it out\n",
    "df_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>p1_conf</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>p1_conf</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>p1_conf</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p1_conf</td>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>p1_conf</td>\n",
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       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  algorithm  confidence_interval   bool\n",
       "0   p1_conf             0.097049  False\n",
       "1   p1_conf             0.323581   True\n",
       "2   p1_conf             0.716012   True\n",
       "3   p1_conf             0.170278  False\n",
       "4   p1_conf             0.555712   True"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We want to melt each of the columns into 2 columns.\n",
    "p1_df = pd.melt(df_2, value_vars=['p1_conf'],\n",
    "          var_name='algorithm', value_name='confidence_interval')\n",
    "p1_df['bool'] = df_2['p1_bool']\n",
    "\n",
    "# Test it out\n",
    "p1_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <td>p2_conf</td>\n",
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       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>p2_conf</td>\n",
       "      <td>0.090647</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>p2_conf</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p2_conf</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>p2_conf</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  algorithm  confidence_interval   bool\n",
       "0   p2_conf             0.085851  False\n",
       "1   p2_conf             0.090647   True\n",
       "2   p2_conf             0.078253   True\n",
       "3   p2_conf             0.168086   True\n",
       "4   p2_conf             0.225770   True"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Do the same with the other remaining columns\n",
    "p2_df = pd.melt(df_2, value_vars=['p2_conf'],\n",
    "               var_name='algorithm', value_name= 'confidence_interval')\n",
    "p2_df['bool'] = df_2['p2_bool']\n",
    "\n",
    "# Test it out\n",
    "p2_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>confidence_interval</th>\n",
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       "      <th>1</th>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>p3_conf</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>p3_conf</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>p3_conf</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  algorithm  confidence_interval   bool\n",
       "0   p3_conf             0.076110  False\n",
       "1   p3_conf             0.068957   True\n",
       "2   p3_conf             0.031379   True\n",
       "3   p3_conf             0.040836  False\n",
       "4   p3_conf             0.175219   True"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Do the same with the other remaining columns\n",
    "p3_df = pd.melt(df_2, value_vars=['p3_conf'],\n",
    "               var_name='algorithm', value_name= 'confidence_interval')\n",
    "p3_df['bool'] = df_2['p3_bool']\n",
    "\n",
    "# Test it out\n",
    "p3_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 6177 entries, 0 to 6176\n",
      "Data columns (total 3 columns):\n",
      "algorithm              6177 non-null object\n",
      "confidence_interval    6177 non-null float64\n",
      "bool                   5358 non-null object\n",
      "dtypes: float64(1), object(2)\n",
      "memory usage: 144.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# Create a new dataframe from the melted dataframes. \n",
    "df_2_new = pd.concat([p1_df, p2_df, p3_df], ignore_index= True)\n",
    "\n",
    "# Test it out\n",
    "df_2_new.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
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       "      <td>True</td>\n",
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       "      <td>p1</td>\n",
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       "      <td>True</td>\n",
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       "      <td>p1</td>\n",
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       "      <td>True</td>\n",
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       "      <th>11</th>\n",
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       "      <td>True</td>\n",
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       "      <th>12</th>\n",
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       "      <td>True</td>\n",
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       "      <th>13</th>\n",
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       "      <td>True</td>\n",
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       "      <th>14</th>\n",
       "      <td>p1</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.626152</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
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       "      <td>0.714719</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.469760</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.700377</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.809197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.995026</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.821664</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.130432</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.809197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.330741</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.733942</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.793469</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.309706</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.738995</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>p1</td>\n",
       "      <td>0.999201</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>6147</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.062071</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6148</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.241878</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6149</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.001117</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6150</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.142860</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6151</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.173810</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6152</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.004577</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6153</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.206803</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6154</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6155</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.093412</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>6156</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.014241</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6157</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.102643</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6158</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.013207</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6159</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.111152</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>6160</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.079480</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>6161</th>\n",
       "      <td>p3</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>6162</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.089688</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6163</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.075628</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6164</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.048960</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6165</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.097471</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6166</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.109454</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6167</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.072427</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6168</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.082086</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6169</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.007959</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6170</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.054449</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6171</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.016199</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6172</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.154629</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6173</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.222752</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6174</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.116197</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6175</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.072010</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6176</th>\n",
       "      <td>p3</td>\n",
       "      <td>0.061428</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6177 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     algorithm  confidence_interval   bool\n",
       "0           p1             0.097049  False\n",
       "1           p1             0.323581   True\n",
       "2           p1             0.716012   True\n",
       "3           p1             0.170278  False\n",
       "4           p1             0.555712   True\n",
       "5           p1             0.425595   True\n",
       "6           p1             0.341703   True\n",
       "7           p1             0.566142   True\n",
       "8           p1             0.487574   True\n",
       "9           p1             0.511319   True\n",
       "10          p1             0.957979   True\n",
       "11          p1             0.377417   True\n",
       "12          p1             0.966327   True\n",
       "13          p1             0.991650   True\n",
       "14          p1             0.953442   True\n",
       "15          p1             0.626152   True\n",
       "16          p1             0.714719   True\n",
       "17          p1             0.469760   True\n",
       "18          p1             0.700377   True\n",
       "19          p1             0.809197   True\n",
       "20          p1             0.995026   True\n",
       "21          p1             0.821664   True\n",
       "22          p1             0.130432  False\n",
       "23          p1             0.809197   True\n",
       "24          p1             0.330741   True\n",
       "25          p1             0.733942   True\n",
       "26          p1             0.793469   True\n",
       "27          p1             0.309706   True\n",
       "28          p1             0.738995  False\n",
       "29          p1             0.999201   True\n",
       "...        ...                  ...    ...\n",
       "6147        p3             0.062071  False\n",
       "6148        p3             0.241878  False\n",
       "6149        p3             0.001117   True\n",
       "6150        p3             0.142860  False\n",
       "6151        p3             0.173810   True\n",
       "6152        p3             0.004577  False\n",
       "6153        p3             0.206803   True\n",
       "6154        p3             0.000461  False\n",
       "6155        p3             0.093412   True\n",
       "6156        p3             0.014241  False\n",
       "6157        p3             0.102643   True\n",
       "6158        p3             0.013207  False\n",
       "6159        p3             0.111152  False\n",
       "6160        p3             0.079480  False\n",
       "6161        p3             0.133649   True\n",
       "6162        p3             0.089688  False\n",
       "6163        p3             0.075628  False\n",
       "6164        p3             0.048960   True\n",
       "6165        p3             0.097471   True\n",
       "6166        p3             0.109454  False\n",
       "6167        p3             0.072427   True\n",
       "6168        p3             0.082086   True\n",
       "6169        p3             0.007959  False\n",
       "6170        p3             0.054449   True\n",
       "6171        p3             0.016199  False\n",
       "6172        p3             0.154629   True\n",
       "6173        p3             0.222752   True\n",
       "6174        p3             0.116197   True\n",
       "6175        p3             0.072010   True\n",
       "6176        p3             0.061428   True\n",
       "\n",
       "[6177 rows x 3 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop the \"_conf\" in each of the rows because we do not need it anymore\n",
    "df_2_new['algorithm'].replace('_conf','', regex=True, inplace=True)\n",
    "\n",
    "# Test it out\n",
    "df_2_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Xixcvhqurq1hu0aJFmDZtGiZNmgRnZ2dMmjQJmzZt0qmrZcuWWL9+PZYsWYJJkybB0tISjRs3xptvvgkg9xv6li1bsGDBAsydOxfZ2dlwc3PDhx9+CCC3KWD58uVYvXo1Nm3ahAcPHsDOzg6NGjUS+6J7eHjg8OHDiIqKEuPt27ev2JTh5eWFjRs3QqlU4unTp3jttdcwduxYDBkypMTHpmbNmggKCsKWLVswYsQIeHh4ICoqCsuXL8fPP/+MRo0aYcmSJfjkk090XvfRRx/hwYMH+Pjjj5GRkYGoqCj07t0bw4cPR/Xq1bFp0yZs2LABFSpUQJ06ddCjRw8Auc0mjo6OWL16NZKSklClShX4+fkV26Q1e/ZsLFy4ECtXrkRaWhrc3d2xevVqtGjRokTvV6lUok6dOvmSAJD7zbd79+5QKpX5ul8Cuedu5cqViIiIQHh4OJycnDBy5EgcPHgQFStWFMs1bNgQ69atw5dffokxY8agcuXKCAwMxKRJk0oUa57CjrWcSnueTJGZUFj7ABGZhPT0dLz55psYOHBgvgcPyTTwioDIxGzZsgUKhQJubm5ISUnBxo0bkZ2djZCQEEOHRgbCREBkYqysrLBu3To8ePAAZmZm8PLywoYNG1CzZk1Dh0YGwqYhIiITx+6jREQmziibhkrzSD4REaHA50CMMhEABb8ZIiIqXGFfotk0RERk4pgIiIhMHBMBEZGJYyIgIjJxTARERCZO1kQQHh6ONm3a4O233y5wvyAImD17Nrp06YKgoKB8Q+ESEZH8ZE0EvXv3FifhLsjRo0cRHx+Pn376CbNmzSpwtEQiIpKXrM8RtGzZEvfu3St0/6FDh9CrVy+YmZnBx8cHaWlpSEpKKnSuXLlFR0fj2LFjxZbLyMgAgHyTlBSmffv2CA0N/VexFURqvED5iZmIyh+DPlCmUqnEWbWA3IlVVCqVpEQgx9PFKpVK0tyxmZmZACB5ekGVSmXQeIHyEzPRq+Lhw4dYsWLFv2rJWL16Ndq1a1fgzH5lyaCJoKDx7qTOfyrHk8VS68ybPOXlCV/KWkmOQXmJmehVce/ePVSuXPlffRY5OjrC3d29zEZKKOzLnUETgYuLCxITE8X1xMREgzULERGVVGZmJsLDw3H79m24u7tj5syZmDt3Li5cuAC1Wo33338fPXv2REpKCj777DNkZGRAq9Vi2rRpaNKkiaHDFxm0+2hAQIA4ifq5c+dga2vLREBERuPu3buYNGkStm7divT0dPz6669ITk7G1q1b8c0332DFihVITU3F2rVr0aFDB8TExGD69OmIiIgwdOg6ZL0imDBhAv7880+kpqaiQ4cOGDt2LNRqNQCgf//+8Pf3x5EjR9ClSxdYW1tj7ty5coZDRKRXderUgYODA4DcptqbN2+KzTw2NjZwd3dHQkICbt68Kc7R7OHhgYcPHxos5oLImgi+/PLLIvebmZlh+vTpcoZARCSbO3fuIDU1FVWrVsXZs2fRvXt3KJVKDBo0CM+ePcO1a9dQq1Yt1KtXD6dOnYK7uzv+/vtvODk5GTp0HUY7DDURkaHVqlULUVFRuHv3Lho0aIDOnTvjxIkT6NevH3JycjBq1Cg4ODjgww8/RHh4OPbt2we1Wo2ZM2caOnQdTARERKVQq1Yt7NmzJ9/2zz//PN82BwcHrFmzJt/2efPmyRJbSXGsISIiE8dEQERk4pgIiIhMHBMBEZGJYyIgIjJxTARERCaO3UeJyKSEfjgOjx6l6q0+R8eqiF6ztMgyjRs3hru7u7i+YsUK1KpVq8Cy9+7dw8iRI7F37169xVgcJgIiMimPHqXinHqW3urzeZT/uYGXVaxYscBnDsoLJgIiIgO4d+8eJk+eLM4V8vnnn+P111/XKXP9+nWEh4cjJycHWq0Wy5YtQ506dbBnzx5s3rwZOTk5aNasGaZPnw5zc/NSx8JEQEQks+fPn+Odd94BkPtE8ooVK+Do6IgNGzagQoUKiI+Px4QJE7Br1y6d123dulUcyjo7OxtarRY3b97E/v37sWXLFlhaWmLGjBmIjY1Fr169Sh0fEwERkcwKahpSq9WIjIzE1atXoVAoEB8fn+91Pj4+WL16NRITE/HWW2+hTp06OHHiBC5evIg+ffoAyE0yjo6O/yo+JgIiIgPYuHEjnJycsGfPHmi1Wnh7e+crExQUhGbNmuG3337DsGHDMHv2bAiCgODgYISFhektFnYfJSIygPT0dFSrVg0KhQJ79uyBRqPJVyYhIQGurq54//33ERAQgL///htt2rTBwYMH8ejRIwDA48ePcf/+/X8VC68IiMikODpWldTTpyT1lcaAAQMwduxYHDhwAH5+frCxsclXZt++ffjxxx9hYWEBJycnjB49Gvb29vj4448xdOhQaLVaWFpaIiIiAjVr1iz1ezATCppBvpw7ffp0mU32XBBjnAjeGGMmIv0q7LOTTUNERCaOiYCIyMQxERARmTgmAiIiE8dEQERk4pgIiIhMHJ8jICKTEjpuBB6lpOitPkcHB0QvXVvo/tTUVPznP/8BACQnJ0OhUMDBwQEAsH37dlhZWektltJiIiAik/IoJQXnJmXqrT6fBUUnlapVq4rjDC1btgw2NjYYNmyYThlBECAIAhQKwzTSsGmIiMgA7ty5g7fffhsREREIDg7GgwcP0KJFC3G/UqnE1KlTAeReSYwZMwa9e/dGnz59cO7cOb3G8spfEYSFhSE5OVmvdebVl/e0rj6lp6fD1tZW7/XKGbOTkxMWLVqk93qJXnU3btzA3LlzERkZCbVaXWi52bNnIzQ0FD4+PrLMYPbKJ4Lk5GSokpKhhr3e6lQgt03vflLhJ640LPAY5grgWVYm1FX0WjUUlrn/3s9O0mu9Fml6rY7IpNSuXbvAUUdfduLECdy+fVtcf/LkCZ4/f46KFSvqJY5XPhEAgBr2uFlhjqHDKFb9rKkwx2OoqwA3PzWOVrv687SGDoHIaFlbW4vLCoUCLw79lpWVJS4LgiDrjWXj+LQhInrFKRQK2NnZIT4+HlqtFj///LO4r02bNvjuu+/E9StXruj1d5vEFQERUR5HB4die/qUtD59mThxIkJDQ1GjRg00aNAA2dnZAIDp06djxowZ2LlzJzQaDfz8/DB9+nS9/V7ZE8HRo0cxZ84caLVa9O3bFyNGjNDZ/88//2DKlClIT0+HRqPBxIkT4e/vL3dYRGSiiurzL7exY8eKy25ubvmmr+zRowd69OiR73UODg5YunSpbHHJmgg0Gg0iIyOxYcMGODs7o0+fPggICECDBg3EMqtWrUL37t0xYMAA3LhxAyNGjMDhw4flDIuIiF4g6z2CuLg4uLm5wdXVFVZWVggMDMShQ4d0ypiZmSEjIwNAbtfJ6tWryxkSERG9RNYrApVKBRcXF3Hd2dkZcXFxOmXGjBmDYcOGISYmBpmZmdiwYYOkuk+fPi2pXG4bm/HcEzfCCeOQnZ0t+XwQUfkjayIo6EPNzMxMZ12pVCI4OBhDhw7F2bNnMXnyZOzdu7fYR62lTlWZ291Kv/395ZR7fIwrGVhZWRl06lAikqawL2yyflV2cXFBYmKiuK5SqfI1/ezYsQPdu3cHAPj6+iIrKwupqalyhkVERC+QNRF4eXkhPj4eCQkJyM7OhlKpREBAgE6ZGjVq4MSJEwCAmzdvIisrSxyZj4iI5Cdr05CFhQUiIiIQGhoKjUaDkJAQNGzYEEuWLIGnpyc6d+6MTz/9FNOmTcPGjRthZmaGefPm5Ws+IiIi+cj+HIG/v3++5wLGjx8vLjdo0ABbt26VOwwiIiqE8XSnISIiWTAREBGZuGKbhsaNG1dkm/2SJUv0GhAREZWtYhNBp06dyiIOIiIykGITQXBwcFnEQUREBiK515BarcbOnTtx5coVnQkToqKiZAmMiIjKhuSbxREREThz5gx+++031KlTBxcvXtTbNGlERGQ4khPBhQsX8MUXX8DW1hYffvghvvvuO9y9e1fO2IiIqAxITgQVKlQAAJibmyMzMxO2trZIStLvROhERFT2JN8jsLOzw5MnT9C+fXsMHz4cVatWhZOTk5yxERFRGZCcCNauXQtzc3N88skniI2NRXp6Onr16iVnbEREVAYkJ4LY2Fh069YNFStWxDvvvCNnTEREVIYk3yM4fPgwOnXqhGnTpnE2KiKiV4jkRLB06VLs378fjRo1wpw5c9C1a1esWbNGztiIiKgMlGjQOXt7ewwaNAjr16+Hn58fvvrqK7niIiKiMiI5EWg0Gvz6668YO3YsunfvDq1Wi5iYGDljIyKiMiD5ZrG/vz8aNmyIXr16YcGCBXyqmIjoFSEpEWi1WkycOJHdRYmIXkGSmoYUCgWnkyQiekVJvkfg6emJuLg4OWMhIiIDkHyP4NSpU9iyZQvc3NxgY2Mjbt+xY4csgRERUdmQnAg+++wzOeMgIiIDkZwIWrVqBQBISUmBg4ODbAEREVHZknyP4Pz58+jUqZM4deWFCxfw+eefyxYYERGVDcmJICoqCuvWrUPVqlUBAF5eXjhz5oxsgRERUdmQnAhycnLQoEEDnW2WlpZ6D4iIiMqW5ERgZWWFp0+fwszMDABw48YNcdYyIiIyXpJvFo8cORLDhg1DUlISPv30Uxw7dgwLFiyQMzYiIioDJRprqF69ejh27BgEQcCoUaPg5uYmZ2xERFQGJDcNrVu3Dq6urhgwYAAGDhwINzc3rFu3Ts7YiIioDEhOBPv27ZO07WVHjx5F165d0aVLF6xdu7bQunv06IHAwECEhYVJDYmIiPSg2Kah//73vzh+/DiSkpIwf/58cXtGRkaxlWs0GkRGRmLDhg1wdnZGnz59EBAQoNP7KD4+HmvXrsWWLVtgZ2eHR48elfKtEBFRaRSbCCwtLVGpUiWYmZnpjDFUvXp1jBgxosjXxsXFwc3NDa6urgCAwMBAHDp0SCcRfP/99xg4cCDs7OwAAI6OjqV6I4XJyMiABZ6jftZUvdYrBws8hlarNXQYRGRiik0ErVq1QqtWrfDWW2/B3d29RJWrVCq4uLiI687OzvlGMI2PjwcA9OvXD1qtFmPGjEGHDh2Krfv06dOSYtBoNNIDplLJzs6WfD6IqPyR3GvIzc0N27dvR0JCAtRqtbh98uTJhb5GEIR82/KeQ8ij0Whw584dbN68GYmJiRg4cCD27t2LKlWqFBlP8+bNJcVtZ2eHjCQ1blaYI6m8IdXPmooKiscAjOuqwMrKSvL5ICLDKewLm+REMH78eOTk5MDb2xtWVlaSXuPi4oLExERxXaVSoXr16jplnJ2d4ePjA0tLS7i6uqJu3bqIj4+Ht7e31NCIiOhfkJwI7ty5g/3795eoci8vL8THxyMhIQHOzs5QKpVYtGiRTpk333wTSqUSvXv3RkpKCuLj48V7CqZIq9XC4glQf55xXBVYPAEyrIvvOEBE5ZfkRODq6oqMjAxUrlxZeuUWFoiIiEBoaCg0Gg1CQkLQsGFDLFmyBJ6enujcuTPat2+P//73v+jRowfMzc0xefJkcWA7IiKSn+REYGtri5CQELRv316naaioewRA7hPJ/v7+OtvGjx8vLpuZmSE8PBzh4eFSQ3mlKRQKZFXR4uankh/xMKj687SobCX9ywERlT+SE0HdunVRt25dOWMhIiIDkJwIxowZI2ccRERkIMUmgv3796N79+749ttvC9w/cOBAvQdFRERlp9hEcP36dXTv3h0XL14si3iIiKiMFZsIxo0bByB3qsqi7NixA3369NFPVEREVGb01jWlsKYjIiIq3/SWCAoaToKIiMo/vSWCl8cQIiIi42AcTy0REZFs2DRERGTiSpQIMjIycOnSpQL3zZs3Ty8BERFR2ZKcCI4cOYLAwECMHTsWAHDhwgWMHDlS3N+oUSP9R0dERLKTnAiWLl2KHTt2iBPGeHl54e7du7IFRkT/ExcXl292PyJ9KVHTULVq1XTWpU5QQ0T/TkxMDGJiYgwdBr2iJCeCSpUqITk5WewmevLkSdja2soWGBHliouLw4ULF3DhwgVeFZAsJCeCiRMnYvjw4bh37x4GDx6MiRMnYsqUKXLGRkSAzpUArwpIDpKHofb29sY333yDM2fOAAD/7nD1AAAUsElEQVR8fX2LnWCeiIjKP8lXBNeuXYO5ubk445iFhQWuX78uZ2xEBGDQoEEFLhPpi+RE8Omnn8LS0lJct7CwYNMQEdErQHIi0Gg0OonAysoKGo1GlqCI6H9Wr15d4DKRvkhOBBYWFkhISBDX7969C3Nzc1mCIpKTsfXJf/DgQYHLRPpSojmL+/fvD39/fwC5TxrPnj1btsCI5JLX82b+/PkGjkSaF6+8eRVOcpCcCDp16oTNmzfj999/BwCMGDECbm5usgVGJIe8Pvl5y97e3gaOqHgvDujIwR1JDpITAQDUrVsXdevWlSsWItm93CffGK4KeEVAcpOcCM6cOYMFCxYgISEBGo0GgiDAzMwMJ06ckDM+IiKSmeREMHXqVHz00Ufw8fGBQsH5bMg4DRo0SOz2bCx98tk0RHKTnAgqVqyIoKAgOWMhIiIDkPzVvkOHDjhy5IicsRDJzhjH7XnxCpxX4yQHyVcE27Ztw5o1a1CpUiVYWVnxHgGVK9HR0Th27Fix5VJTU8Xlq1evYsiQIcW+pn379ggNDf1X8f0bzs7O4vMDzs7OBouDXl2SE8HOnTvljIOoTFSqVAmPHz8Wl41BVlZWgctE+iI5EdSsWRMZGRm4c+cOmjZtKmdMRCUWGhoq+Vt7z549AQBbtmyRMyS9efEq5sVlIn3R25zFhTl69Ci6du2KLl26YO3atYWWO3DgADw8PMSHfYjkUqlSJaO5GgDYa4jkJ+ucxRqNBpGRkYiOjoZSqcTevXtx48aNfOUyMjKwefNmNGvWrIThE5WclZUVp1kleoGscxbHxcXBzc0Nrq6usLKyQmBgIA4dOpSv3JIlSxAaGooKFSqUJBwiItIDyfcISjNnsUqlgouLi7ju7Oycb9THy5cvIzExEZ06dcL69eslB3769GlJ5bKzs1HCfGdQxnjpn52dLfl8lAe5fxPS/4bkcuDAAVy8eLHYcmZmZuLfhZmZGfr371/sazw9PdGtW7d/HSOZBsmJ4OU5i+Pj47Fq1aoiX1PQh1peIgEArVaLqKgoREVFlSDkXM2bN5dULveqRV3i+g0l9/gYVzKwsrKSfD7Kg7wrWUPHfPbsWVy7dq3YctWqVUNSUpK4LIWzs7PB3x+VP4V9+ZF1zmIXFxckJiaK6yqVCtWrVxfXnz59imvXruH9998HADx8+BCjRo3CqlWr4OXlJTU0IqNUkp5OgYGBAIBNmzbJGRKZqGITQWZm5v8KW1igVatWOvusra0Lfa2Xlxfi4+ORkJAAZ2dnKJVKLFq0SNxva2uLkydPiuuDBw/G5MmTmQSIXuLk5GToEOgVVmwi8PX11WnOedmVK1cKr9zCAhEREQgNDYVGo0FISAgaNmyIJUuWwNPTE507dy5d1EREpDfFJoKrV68CAFatWgVLS0u89957EAQB27dv15nDuDD+/v7irGZ5xo8fX2DZzZs3S4mZiIj0SPI9gqNHj+o8iTls2DD0799fbN8vzyzwGPWzpuqtPgWeAQC0sNFbnUBunEREZU1yInj8+DHu3LkjTk959+5dccyW8kyOttXk5Oz/r7vom+Ul54TU1FRYpGlRf55WrzUr/v9Wj7bwWzqlYpEGgM3XREZNciL45JNP8O6778LT0xNAbv//WbNmyRaYvrx4c1pf8kaslKMHR1hYGJKTk/Veb3Jabp1Odnr+1HbijUwiYyc5Ebz11lto3rw5zp8/D0EQ4OvrCwcHBzljM0lyJC5A3uRFRMatRJPXOzo6IiAgQK5YiIjIAIpNBEOGDMGmTZvQunVrnW6knJiGiOjVUGwiyBv+gRPTEBG9moodjW3MmDEAgK+++go1a9bM90NERMZN0hATFy9exKVLl3Dz5s18A8k1aNBAtuCIiEh+xSaCvPF/7t69i+HDh+vsMzMzK3B+ASIiMh7FJoIBAwZgwIAB+OSTT7B48eKyiImIiMqQ5BlbmASIiF5Nkp8jOHPmDBYsWICEhARoNBp2HyUiekVITgRTp07FRx99BB8fHygUxjP1IxERFU1yIqhYsSKCgoLkjIWIiAxA8lf7Dh064MiRI3LGQkT0ylmxYgVWrFhh6DCKJPmKYNu2bVizZg0qVaoEKysr3iMgIpJg3759AIDRo0cbOJLCSU4EHGKCiKhkVqxYAa1WKy6X12QguWmoZs2acHZ2xrNnz5CZmQlnZ2cOMUFEVIS8q4GXl8sbyVcEFy5cwLhx48RmIbVajWXLlqFp06ZyxkdERDKTnAjmzJmDuXPnok2bNgCAP/74A7NmzcLWrVtlC46IyJi1atUKf/zxh7hcXkluGsrMzBSTAAC0bt0amZmZsgRFRFSYuLg4xMXFGToMSZ4+fVrgcnkjORFYW1uLmQ0A/vzzT1hb63kmdCKiYsTExCAmJsbQYUjy4vzjcsxFri8lerI47x4BAOTk5GDp0qWyBUZE9LK4uDhcuHBBXPb29jZwREVLTU0tcLm8kZwI0tPTsWPHDjx69AiCIMDJyQnXrl2TMzYiIh0vXgnExMRg/vz5BoymeObm5gUulzeSm4bmz58PBwcHuLu7w8PDA1WrVi33J4GIyJA6depU4HJ5IzkR5D1JLL5QoYBGo5ElKCKiggwaNKjA5fLq0qVLBS6XN5ITQaVKlXD+/Hlx/fz587CxsZElKCKignh7e6NevXqoV69eub8/AAB3794tcLm8kXyPYNKkSRg9erQ4R/GNGzewfPly2QIjIirIy/Oml2cvtpqU5xYUyYnA19cXSqUS586dgyAI8PX1hZ2dnZyxERHpiIuLw+3bt8VlY7gqMAYlmmHGzs4O/v7+6Nixo+QkcPToUXTt2hVdunTB2rVr8+3fsGEDevTogaCgIAwZMgT3798vSUhEZEJe7jVE+iHrVGMajQaRkZGIjo6GUqnE3r17cePGDZ0yjRs3xs6dOxEbG4uuXbtiwYIFcoZEREQvkdw0VBpxcXFwc3ODq6srACAwMBCHDh0S7zMAuUNV5PHx8cGPP/4oZ0hkRMLCwmR5GjOvziFDhui9bicnJyxatEjv9VKuQYMGYcqUKeKyoURHR+PYsWMlfp2Uv7n27dsjNDS0NGGVmqyJQKVSwcXFRVx3dnYucoyQHTt2oEOHDpLqPn369L+Or7Sys7MNHkNJGWPM//zzD1Ifp0ENe73Wq0Du0/H3k9R6rdcCj5GdnS3LMTbG81cSBw4cwMWLFyWVzevGHhUVJam8p6cnunXrVurYCqJSqcRzUhJSXqNSqcr8PMuaCAq6u//iswgv2rNnDy5evCi53a958+b/KrZ/I2+YDUPGUFLGGrMa9rhZYY6hQ5GkftZUPH2aLsvQK2lpaQAgS93l4Srm7NmzJR6pIO9vujjOzs56/7uXWt/u3bvFe6MjRoxAcHCwXuMoqcISjKyJwMXFBYmJieK6SqVC9erV85X7/fffsXr1asTExEg+uUTlkUajgSo5Ceoq+q1XYZn77/3sJL3Wa5Gm1+pKLTQ0VHJzSF7zyqZNm+QMSS+Cg4PFRGDoJFAUWROBl5cX4uPjkZCQAGdnZyiVynzfPC5fvoyIiAhER0fD0dFRznCIyoS6CnDzU1n7YehN/XlaQ4fwyqtUqZKhQyiWrInAwsICERERCA0NhUajQUhICBo2bIglS5bA09MTnTt3xvz58/Hs2TOMHz8eAFCjRg2sXr1azrCIiMqMyScCAPD394e/v7/OtrwPfQDYuHGj3CEQEVERjOP6lYiIZMNEQERk4pgIiIhMHBMBEZGJYyIgIjJxTARERCaOiYCIyMQxERARmTgmAiIiEyf7k8VEpkSr1cLiifGM4WPxBMiwzjB0GGRgTARUbmVkZMACz1E/a6qhQ5HEAo8NHQJRqTAREOmZ2s64Rh+tbFXZ0GGQgTERULlVuXJlPHlW0agmpqmgeAzAOJqFiPIYx9cWIiKSDRMBEZGJY9MQEckiLCwMycnJeq83r868KSv1JTU1FQBQtWpVvdYrV7yA/uabZiIgIlkkJydDlZQMNez1Wq8CufOa309S67VeC+QACv3PC20M800zERCRbNSwN5qb/R5Zo6GuojWqHl/6YhzvmIiIZMNEQERk4pgIiIhMHO8RGLHo6GgcO3ZMUtmS9lxo3749QkNDSx0bERkPJgITUbFiRUOHUCoWeKz3sYYUeAYA0MJGr/XmjTVkkab/QecUmbn/aq31Wm1uzxMn/dZJxoeJwIiFhoa+0t/anZzk+YRKTs7+//qr6LlmJ6Snp8PW1lbP9QLJablXdE52ej4mTvIdZ2MbNBDQwuKxaY4cy0TwAqlNLWxmKRv6eFCmIHnnbdOmTbLULwdjjJmMBxNBKRhrMwtRWTK2QQM9skZDbW9czxHoa+RYJoIXvOpNLUREBTGO1EdERLJhIiAiMnFsGiIi+n+m2vWXiYCIZGNMz4EAWphDAWcr/XanNYauv7IngqNHj2LOnDnQarXo27cvRowYobM/OzsbkydPxqVLl2Bvb4/FixejVq1acodFRDIzvudAquttfP8XGUPXX1kTgUajQWRkJDZs2ABnZ2f06dMHAQEBaNCggVhm+/btqFKlCn7++WcolUosXLgQX331lZxhEVEZ4HMgxkPWRBAXFwc3Nze4uroCAAIDA3Ho0CGdRHD48GGMGTMGANC1a1dERkZCEASYmZnJGRq9Yoxx3CVjjFkuxnYsjC3e4siaCFQqFVxcXMR1Z2dnxMXF5StTo0aN3GAsLGBra4vU1FQ4ODgUWffp06f1HzAZLZVKhezsbEllLS1zp4ySWl6lUsny92aMMcvF2I6FscVbHFkTgSAI+ba9/E1fSpmCNG/evPSB0SvHGP8ejDFmuRjbsTC2ePMUlmBkfY7AxcUFiYmJ4rpKpUL16tXzlXnw4AEAQK1WIz09Hfb2+p3jlIiICidrIvDy8kJ8fDwSEhKQnZ0NpVKJgIAAnTIBAQHYvXs3AODgwYNo3bo17w8QEZUhWZuGLCwsEBERgdDQUGg0GoSEhKBhw4ZYsmQJPD090blzZ/Tp0weTJk1Cly5dYGdnh8WLF8sZEhERvcRMKKiRvpw7ffq00bbREREZSmGfnRxriIjIxDEREBGZOCYCIiITx0RARGTijHb0UWN6apKIqDwzyl5DRESkP2waIiIycUwEREQmjomAiMjEMREQEZk4JgIiIhPHREBEZOKM9jmCV1lMTAw2bdqEu3fv4sSJE8XO1kblS1hYGC5evAhLS0t4eXkhMjJSnKWKyr/PPvsMFy9ehCAIqFu3LqKiolCpUiVDhyUrXhGUQ6+//jo2bNiAmjVrGjoUKoWePXviwIEDiI2NRVZWFrZv327okKgEPvvsM/z444+IjY1FjRo18O233xo6JNnxisCA7t27h9DQUDRr1gyXL19G3bp18cUXX6BJkyaGDo0kKOz8+fv7i2W8vb2hUqkMGCUVprDzV7lyZQC50+g+f/7cwFGWDV4RGNjt27fx7rvvIjY2FpUqVcJ3331n6JCoBIo6fzk5OdizZw/at29vwAipKIWdv/DwcLRr1w63bt3C4MGDDRyl/JgIDKxGjRriRBE9e/bkGEpGpqjzN3PmTLRo0QItWrQwVHhUjMLOX1RUFI4dO4b69etj3759hgyxTDARGNjL8zNzvmbjUtj5W758OVJSUhAeHm6IsEiiov7/mZubo0ePHvjpp5/KOqwyx0RgYP/88w/Onj0LAFAqlZyC08gUdP62b9+O48eP48svv4RCwf9i5VlB5+/OnTsAcu8R/Prrr6hXr54hQywT/Cs1sPr162P37t0ICgrCkydP0L9/f3zzzTfo0KEDEhMT0bNnT0ydOtXQYVIhCjp/06dPR3JyMt577z288847WL58uaHDpEIUdP6mTJmCoKAgBAUFISkpCaNHjzZ0mLLjMNQGdO/ePYwcORJ79+41dChUCjx/xo3n7394RUBEZOJ4RUBEZOJ4RUBEZOKYCIiITBwTARGRiWMiIJN28uRJ9O7dW+/1Tp06FadOnQIA/PLLL4iLi5P9dxKVFgedI9IzjUaDOXPmiOu//PILPD094e3tbcCoiArHREAmIywsDLdv30ZOTg5q166NuXPn5isTExODb775Bra2tvD398e3336LkydPAgB++OEHfP311wCA2rVrIzIyEo6Ojti1axeUSiUcHBxw8+ZNzJkzB3PnzsXQoUNhYWGBw4cP4/fff8f27dvxwQcfoEaNGtBoNIiIiMDZs2dhZmaGxYsXo379+jh58iTmzJkDb29vnD9/HhYWFpg/fz6WL1+O69evo0aNGli2bBlsbGzK9NjRq41NQ2Qypk6dil27diE2NhYNGjTAunXrdPZfvXoVa9aswdatW7Fz506kp6eL+65du4aFCxfi66+/RmxsLBo2bIhZs2aJ+8+cOYOxY8di165daNy4sbi9ffv2CAgIwIgRI7Bnzx706tULAHDjxg3069cPsbGx6N69O1auXCm+5ubNmxg4cCBiY2Ph4+ODYcOGITw8HPv27YNCoYBSqZTrEJGJYiIgk7Fnzx707t0bQUFB2Lt3L65cuaKz/88//4S/v784I1xISIi47+TJk/D390f16tUBAP369cOJEyfE/a+//jpq164tOZa6deuK8074+PggISFBZ19eMmnSpAkaN24MFxcXAEDTpk3FsXCI9IVNQ2QSTp06hS1btmDr1q1wcHBAbGwsvv/+e50ygiAUOvprUfsAlHgqQysrK3FZoVBArVYXuM/c3BwVKlTQWc/KyirR7yIqDq8IyCSkpaWhcuXKsLe3R3Z2Nnbu3JmvjJ+fH44cOYKUlBQAwO7du8V9bdq0wZEjR/Dw4UMAwPfff4+2bdtK+t2VK1fWaWYiKm94RUAmoUOHDvjxxx/RvXt3ODs7w9PTExcuXNAp06hRI4SGhqJfv35wcnJC27ZtYWtrCwBo2LAhwsLCMHToUACAq6srIiMjJf3unj17Ijw8HAcOHBBvFhOVJxxriOgFGRkZ4py1y5Ytw507d7Bw4UIDR0UkL14REL1g0aJFOHPmDHJyckr0rZ/ImPGKgIjIxPFmMRGRiWMiICIycUwEREQmjomAiMjEMREQEZm4/wPMbLGDq7OUbgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbfee56ef98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fbfee53e128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set the style of the boxplot to whitegrid\n",
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "# Set boxplot parameters and properties to my liking\n",
    "sns.boxplot(x=\"algorithm\", y=\"confidence_interval\", hue=\"bool\", data=df_2_new, palette=\"bright\").set_title(\n",
    "    'Success Rates of Algorithms', size= 15)\n",
    "plt.figure(figsize=(5, 8))\n",
    "\n",
    "# Save the figure for the separate reports\n",
    "plt.savefig('Success Rates of Algorithms.jpg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observations:**<br />\n",
    "Based on confidence intervals, p1 had highest percentage of confidence but there is a less amount of predictions that came out to be true. With p2, there is less confidence percentage (10-20%) but more predictions that came true. Lastly, p3 had the lowest confidence percentage(5-10%) and had about the same amount of true and false outcomes. The results show that there is approximately an equal amount of True and False outcomes for each of the algorithms, suggesting that each of the algorithms have a success rate of the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}