wrangle_act-oziPC.ipynb

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    "# <a name=\"top\">WeRateDogs - Udacity Data Wrangling Project 03 </a>\n",
    "---\n",
    "## Gather 3 datasets from 3 different sources:\n",
    "1. [Gather Data #1](#gather1) - Twitter archive, twitter-archive-enhanced.csv (local archive). format: CSV\n",
    "2. [Gather Data #2](#gather2) - Tweet image predictions - Download data from file_url utilizing requests library. format: TSV\n",
    "3. [Gather Data #3](#gather3) - Query Twitter API for additional data - image_preds (local archive created from image recognition system). format: TXT\n",
    "\n",
    "## (8) Quality Issues \n",
    "Also known as dirty data which includes mislabeled, corrupted, duplicated, inconsistent content issues, etc.\n",
    "\n",
    "### twitter-archive-enhanced.csv quality issues:\n",
    "\n",
    "1. [Quality #1](#q1) - columns 'timestamp' & 'retweeted_status_timestamp' are objects (strings) and not of 'timestamp' type. Change type to timestamp.\n",
    "\n",
    "2. [Quality #2](#q2) - twitterDF.name contains a lot of non-dog names, e.g. 'a'; Replace with np.NaN\n",
    "   \n",
    "3. [Quality #3](#q3) - doggo, floofer, pupper, & puppo use None; Replace with 0, and 1 where 'doggo, floofer, etc...' \n",
    "\n",
    "4. [Quality #4](#q4) - remove URL from 'source' & replace with 4 categories: iphone, vine, twitter, tweetdeck\n",
    "\n",
    "5. [Quality #5](#q5) - retweeted_status_id is of type float; change to object(text)\n",
    "\n",
    "6. [Quality #6](#q6) - `in_reply_to_status_id` and `in_reply_to_user_id` are type float. Convert to string\n",
    " \n",
    "\n",
    "### rt_tweets quality issues:\n",
    "\n",
    "7. [Quality #7](#q7) - rename column for tweet ID uniformity\n",
    "\n",
    "8. [Quality #8](#q8) - remove retweets\n",
    "\n",
    "\n",
    "---\n",
    "## (2) Tidiness Issues\n",
    "Messy data includes structural issues where variables don't form a column, observations form rows, & each observational unit forms a table.\n",
    "\n",
    "1. [Tidy #1](#t1) - create new dataframe of columns needed\n",
    "\n",
    "2. [Tidy #2](#t2) - merge all 3 datasets\n",
    "\n",
    "3. Potential Tidy #3 - variables from rows and columns --> doggo, floofer, pupper, puppo. Create new column, e.g. 'Dog_type' and specify which, if any, is represented. The problem is there numerous tweets where more than 1 'dog type' is specified. I don't think one can arbitrarily choose which type should be used in the dataset where 1+ (doggo, floofer, etc.) are specified. \n",
    "---\n",
    "## Examples of assessments:\n",
    "### Visuals\n",
    "1. [Visual 1](#vis1) - Horizontal Bar Chart (WeRateDogs Dog Breeds represented (top 10))\n",
    "2. [Visual 2](#vis2) - Horizontal Bar Chart (Top 15 Favorites (tweets), by probable name)\n",
    "\n",
    "### Programatic\n",
    "1. [Programatic 1](#prog1) - Percentages, Value Counts, etc.\n",
    "2. [Programatic 2](#prog2) - Grouping of dataframe on the first predicted name for various mean data\n",
    "\n",
    "### Saved new dataframe to file \n",
    "[Save to file, WeRateDogs_migration.csv](#save1) to file.\n",
    "\n",
    "\n",
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import requests\n",
    "\n",
    "import tweepy\n",
    "from tweepy import OAuthHandler\n",
    "import json\n",
    "from timeit import default_timer as timer\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import ConnectionPatch\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <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",
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      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\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",
       "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",
       "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",
       "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",
       "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",
       "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",
       "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  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mainDF = pd.read_csv('data/twitter-archive-enhanced.csv')\n",
    "mainDF.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "replytweetsDF = mainDF[mainDF.in_reply_to_status_id.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>tweet_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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       "      <th>1356</th>\n",
       "      <td>703425003149250560</td>\n",
       "      <td>7.030419e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-02-27 03:42:44 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Really guys? Again? I know this is a rare Alba...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/703425003...</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",
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       "    <tr>\n",
       "      <th>1016</th>\n",
       "      <td>746906459439529985</td>\n",
       "      <td>7.468859e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-06-26 03:22:31 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>PUPDATE: can't see any. Even if I could, I cou...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/746906459...</td>\n",
       "      <td>0</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",
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       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>811647686436880384</td>\n",
       "      <td>8.116272e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-12-21 19:01:02 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>PUPDATE: I've been informed that Augie was act...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>611</th>\n",
       "      <td>797165961484890113</td>\n",
       "      <td>7.971238e+17</td>\n",
       "      <td>2.916630e+07</td>\n",
       "      <td>2016-11-11 19:55:50 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>@JODYHiGHROLLER it may be an 11/10 but what do...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
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       "    <tr>\n",
       "      <th>1866</th>\n",
       "      <td>675349384339542016</td>\n",
       "      <td>6.749998e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-12-11 16:20:15 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Yea I lied. Here's more. All 13/10 https://t.c...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/675349384...</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",
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       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "1356  703425003149250560           7.030419e+17         4.196984e+09   \n",
       "1016  746906459439529985           7.468859e+17         4.196984e+09   \n",
       "513   811647686436880384           8.116272e+17         4.196984e+09   \n",
       "611   797165961484890113           7.971238e+17         2.916630e+07   \n",
       "1866  675349384339542016           6.749998e+17         4.196984e+09   \n",
       "\n",
       "                      timestamp  \\\n",
       "1356  2016-02-27 03:42:44 +0000   \n",
       "1016  2016-06-26 03:22:31 +0000   \n",
       "513   2016-12-21 19:01:02 +0000   \n",
       "611   2016-11-11 19:55:50 +0000   \n",
       "1866  2015-12-11 16:20:15 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "1356  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1016  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "513   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "611   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1866  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "1356  Really guys? Again? I know this is a rare Alba...                  NaN   \n",
       "1016  PUPDATE: can't see any. Even if I could, I cou...                  NaN   \n",
       "513   PUPDATE: I've been informed that Augie was act...                  NaN   \n",
       "611   @JODYHiGHROLLER it may be an 11/10 but what do...                  NaN   \n",
       "1866  Yea I lied. Here's more. All 13/10 https://t.c...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "1356                       NaN                        NaN   \n",
       "1016                       NaN                        NaN   \n",
       "513                        NaN                        NaN   \n",
       "611                        NaN                        NaN   \n",
       "1866                       NaN                        NaN   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "1356  https://twitter.com/dog_rates/status/703425003...                 9   \n",
       "1016  https://twitter.com/dog_rates/status/746906459...                 0   \n",
       "513                                                 NaN                11   \n",
       "611                                                 NaN                11   \n",
       "1866  https://twitter.com/dog_rates/status/675349384...                13   \n",
       "\n",
       "      rating_denominator  name doggo floofer pupper puppo  \n",
       "1356                  10  None  None    None   None  None  \n",
       "1016                  10  None  None    None   None  None  \n",
       "513                   10  None  None    None   None  None  \n",
       "611                   10  None  None    None   None  None  \n",
       "1866                  10  None  None    None   None  None  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "replytweetsDF.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mainDF[mainDF.tweet_id.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   tweet_id                    2356 non-null   int64  \n",
      " 1   in_reply_to_status_id       78 non-null     float64\n",
      " 2   in_reply_to_user_id         78 non-null     float64\n",
      " 3   timestamp                   2356 non-null   object \n",
      " 4   source                      2356 non-null   object \n",
      " 5   text                        2356 non-null   object \n",
      " 6   retweeted_status_id         181 non-null    float64\n",
      " 7   retweeted_status_user_id    181 non-null    float64\n",
      " 8   retweeted_status_timestamp  181 non-null    object \n",
      " 9   expanded_urls               2297 non-null   object \n",
      " 10  rating_numerator            2356 non-null   int64  \n",
      " 11  rating_denominator          2356 non-null   int64  \n",
      " 12  name                        2356 non-null   object \n",
      " 13  doggo                       2356 non-null   object \n",
      " 14  floofer                     2356 non-null   object \n",
      " 15  pupper                      2356 non-null   object \n",
      " 16  puppo                       2356 non-null   object \n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "mainDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"gather1\">Gather Data #1 - Twitter archive</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <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": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitterDF = pd.read_csv(\"data/twitter-archive-enhanced.csv\")\n",
    "twitterDF.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
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       "      <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>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>32</th>\n",
       "      <td>886054160059072513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-15 02:45:48 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...</td>\n",
       "      <td>8.860537e+17</td>\n",
       "      <td>1.960740e+07</td>\n",
       "      <td>2017-07-15 02:44:07 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/886053434...</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>36</th>\n",
       "      <td>885311592912609280</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-13 01:35:06 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Lilly. She just paralle...</td>\n",
       "      <td>8.305833e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-02-12 01:04:29 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/830583320...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Lilly</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>879130579576475649</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-26 00:13:58 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Emmy. She was adopted t...</td>\n",
       "      <td>8.780576e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-06-23 01:10:23 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/878057613...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>Emmy</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>878404777348136964</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-06-24 00:09:53 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: Meet Shadow. In an attempt to r...</td>\n",
       "      <td>8.782815e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-06-23 16:00:04 +0000</td>\n",
       "      <td>https://www.gofundme.com/3yd6y1c,https://twitt...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Shadow</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</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>1023</th>\n",
       "      <td>746521445350707200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-06-25 01:52:36 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Shaggy. He knows exactl...</td>\n",
       "      <td>6.678667e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-21 00:46:50 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/667866724...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Shaggy</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>743835915802583040</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-06-17 16:01:16 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: Extremely intelligent dog here....</td>\n",
       "      <td>6.671383e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-19 00:32:12 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/667138269...</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>1242</th>\n",
       "      <td>711998809858043904</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-03-21 19:31:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @twitter: @dog_rates Awesome Tweet! 12/10. ...</td>\n",
       "      <td>7.119983e+17</td>\n",
       "      <td>7.832140e+05</td>\n",
       "      <td>2016-03-21 19:29:52 +0000</td>\n",
       "      <td>https://twitter.com/twitter/status/71199827977...</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>2259</th>\n",
       "      <td>667550904950915073</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-20 03:51:52 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com\" rel=\"nofollow\"&gt;Tw...</td>\n",
       "      <td>RT @dogratingrating: Exceptional talent. Origi...</td>\n",
       "      <td>6.675487e+17</td>\n",
       "      <td>4.296832e+09</td>\n",
       "      <td>2015-11-20 03:43:06 +0000</td>\n",
       "      <td>https://twitter.com/dogratingrating/status/667...</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>2260</th>\n",
       "      <td>667550882905632768</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-20 03:51:47 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com\" rel=\"nofollow\"&gt;Tw...</td>\n",
       "      <td>RT @dogratingrating: Unoriginal idea. Blatant ...</td>\n",
       "      <td>6.675484e+17</td>\n",
       "      <td>4.296832e+09</td>\n",
       "      <td>2015-11-20 03:41:59 +0000</td>\n",
       "      <td>https://twitter.com/dogratingrating/status/667...</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",
       "  </tbody>\n",
       "</table>\n",
       "<p>181 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "19    888202515573088257                    NaN                  NaN   \n",
       "32    886054160059072513                    NaN                  NaN   \n",
       "36    885311592912609280                    NaN                  NaN   \n",
       "68    879130579576475649                    NaN                  NaN   \n",
       "73    878404777348136964                    NaN                  NaN   \n",
       "...                  ...                    ...                  ...   \n",
       "1023  746521445350707200                    NaN                  NaN   \n",
       "1043  743835915802583040                    NaN                  NaN   \n",
       "1242  711998809858043904                    NaN                  NaN   \n",
       "2259  667550904950915073                    NaN                  NaN   \n",
       "2260  667550882905632768                    NaN                  NaN   \n",
       "\n",
       "                      timestamp  \\\n",
       "19    2017-07-21 01:02:36 +0000   \n",
       "32    2017-07-15 02:45:48 +0000   \n",
       "36    2017-07-13 01:35:06 +0000   \n",
       "68    2017-06-26 00:13:58 +0000   \n",
       "73    2017-06-24 00:09:53 +0000   \n",
       "...                         ...   \n",
       "1023  2016-06-25 01:52:36 +0000   \n",
       "1043  2016-06-17 16:01:16 +0000   \n",
       "1242  2016-03-21 19:31:59 +0000   \n",
       "2259  2015-11-20 03:51:52 +0000   \n",
       "2260  2015-11-20 03:51:47 +0000   \n",
       "\n",
       "                                                 source  \\\n",
       "19    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "32    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "36    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "68    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "73    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "...                                                 ...   \n",
       "1023  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1043  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1242  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "2259  <a href=\"http://twitter.com\" rel=\"nofollow\">Tw...   \n",
       "2260  <a href=\"http://twitter.com\" rel=\"nofollow\">Tw...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "19    RT @dog_rates: This is Canela. She attempted s...         8.874740e+17   \n",
       "32    RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...         8.860537e+17   \n",
       "36    RT @dog_rates: This is Lilly. She just paralle...         8.305833e+17   \n",
       "68    RT @dog_rates: This is Emmy. She was adopted t...         8.780576e+17   \n",
       "73    RT @dog_rates: Meet Shadow. In an attempt to r...         8.782815e+17   \n",
       "...                                                 ...                  ...   \n",
       "1023  RT @dog_rates: This is Shaggy. He knows exactl...         6.678667e+17   \n",
       "1043  RT @dog_rates: Extremely intelligent dog here....         6.671383e+17   \n",
       "1242  RT @twitter: @dog_rates Awesome Tweet! 12/10. ...         7.119983e+17   \n",
       "2259  RT @dogratingrating: Exceptional talent. Origi...         6.675487e+17   \n",
       "2260  RT @dogratingrating: Unoriginal idea. Blatant ...         6.675484e+17   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "19                4.196984e+09  2017-07-19 00:47:34 +0000   \n",
       "32                1.960740e+07  2017-07-15 02:44:07 +0000   \n",
       "36                4.196984e+09  2017-02-12 01:04:29 +0000   \n",
       "68                4.196984e+09  2017-06-23 01:10:23 +0000   \n",
       "73                4.196984e+09  2017-06-23 16:00:04 +0000   \n",
       "...                        ...                        ...   \n",
       "1023              4.196984e+09  2015-11-21 00:46:50 +0000   \n",
       "1043              4.196984e+09  2015-11-19 00:32:12 +0000   \n",
       "1242              7.832140e+05  2016-03-21 19:29:52 +0000   \n",
       "2259              4.296832e+09  2015-11-20 03:43:06 +0000   \n",
       "2260              4.296832e+09  2015-11-20 03:41:59 +0000   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "19    https://twitter.com/dog_rates/status/887473957...                13   \n",
       "32    https://twitter.com/dog_rates/status/886053434...                12   \n",
       "36    https://twitter.com/dog_rates/status/830583320...                13   \n",
       "68    https://twitter.com/dog_rates/status/878057613...                14   \n",
       "73    https://www.gofundme.com/3yd6y1c,https://twitt...                13   \n",
       "...                                                 ...               ...   \n",
       "1023  https://twitter.com/dog_rates/status/667866724...                10   \n",
       "1043  https://twitter.com/dog_rates/status/667138269...                10   \n",
       "1242  https://twitter.com/twitter/status/71199827977...                12   \n",
       "2259  https://twitter.com/dogratingrating/status/667...                12   \n",
       "2260  https://twitter.com/dogratingrating/status/667...                 5   \n",
       "\n",
       "      rating_denominator    name doggo floofer pupper puppo  \n",
       "19                    10  Canela  None    None   None  None  \n",
       "32                    10    None  None    None   None  None  \n",
       "36                    10   Lilly  None    None   None  None  \n",
       "68                    10    Emmy  None    None   None  None  \n",
       "73                    10  Shadow  None    None   None  None  \n",
       "...                  ...     ...   ...     ...    ...   ...  \n",
       "1023                  10  Shaggy  None    None   None  None  \n",
       "1043                  10    None  None    None   None  None  \n",
       "1242                  10    None  None    None   None  None  \n",
       "2259                  10    None  None    None   None  None  \n",
       "2260                  10    None  None    None   None  None  \n",
       "\n",
       "[181 rows x 17 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitterDF[twitterDF.retweeted_status_id.notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   tweet_id                    2356 non-null   int64  \n",
      " 1   in_reply_to_status_id       78 non-null     float64\n",
      " 2   in_reply_to_user_id         78 non-null     float64\n",
      " 3   timestamp                   2356 non-null   object \n",
      " 4   source                      2356 non-null   object \n",
      " 5   text                        2356 non-null   object \n",
      " 6   retweeted_status_id         181 non-null    float64\n",
      " 7   retweeted_status_user_id    181 non-null    float64\n",
      " 8   retweeted_status_timestamp  181 non-null    object \n",
      " 9   expanded_urls               2297 non-null   object \n",
      " 10  rating_numerator            2356 non-null   int64  \n",
      " 11  rating_denominator          2356 non-null   int64  \n",
      " 12  name                        2356 non-null   object \n",
      " 13  doggo                       2356 non-null   object \n",
      " 14  floofer                     2356 non-null   object \n",
      " 15  pupper                      2356 non-null   object \n",
      " 16  puppo                       2356 non-null   object \n",
      "dtypes: float64(4), int64(3), object(10)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# review data columns in DF, are Dtypes appropriate, etc.\n",
    "twitterDF.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None         745\n",
       "a             55\n",
       "Charlie       12\n",
       "Cooper        11\n",
       "Lucy          11\n",
       "            ... \n",
       "Snickers       1\n",
       "Juckson        1\n",
       "Jebberson      1\n",
       "Scruffers      1\n",
       "Daniel         1\n",
       "Name: name, Length: 957, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# review names of pups\n",
    "twitterDF.name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>883360690899218434</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-07 16:22:55 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Grizzwald. He may be the floofiest floofe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/883360690...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Grizzwald</td>\n",
       "      <td>None</td>\n",
       "      <td>floofer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>854010172552949760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-17 16:34:26 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>At first I thought this was a shy doggo, but i...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/854010172...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>floofer</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>800388270626521089</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-11-20 17:20:08 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Doc. He takes time out of every day to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/800388270...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Doc</td>\n",
       "      <td>None</td>\n",
       "      <td>floofer</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",
       "46   883360690899218434                    NaN                  NaN   \n",
       "200  854010172552949760                    NaN                  NaN   \n",
       "582  800388270626521089                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "46   2017-07-07 16:22:55 +0000   \n",
       "200  2017-04-17 16:34:26 +0000   \n",
       "582  2016-11-20 17:20:08 +0000   \n",
       "\n",
       "                                                source  \\\n",
       "46   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "200  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "582  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text  retweeted_status_id  \\\n",
       "46   Meet Grizzwald. He may be the floofiest floofe...                  NaN   \n",
       "200  At first I thought this was a shy doggo, but i...                  NaN   \n",
       "582  This is Doc. He takes time out of every day to...                  NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "46                        NaN                        NaN   \n",
       "200                       NaN                        NaN   \n",
       "582                       NaN                        NaN   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "46   https://twitter.com/dog_rates/status/883360690...                13   \n",
       "200  https://twitter.com/dog_rates/status/854010172...                11   \n",
       "582  https://twitter.com/dog_rates/status/800388270...                12   \n",
       "\n",
       "     rating_denominator       name  doggo  floofer pupper puppo  \n",
       "46                   10  Grizzwald   None  floofer   None  None  \n",
       "200                  10       None  doggo  floofer   None  None  \n",
       "582                  10        Doc   None  floofer   None  None  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# review dogtionary names; interesting to see id# 200 has 2 values, doggo & floofer\n",
    "twitterDF[twitterDF['floofer'] != 'None'].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"At first I thought this was a shy doggo, but it's actually a Rare Canadian Floofer Owl. Amateurs would confuse the two. 11/10 only send dogs https://t.co/TXdT3tmuYk\""
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# it appears the designations were pulled from the tweeted text, 'doggo' & 'floofer' in text below\n",
    "twitterDF.loc[200,'text']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\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>446</th>\n",
       "      <td>819015337530290176</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-11 02:57:27 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>RT @dog_rates: This is Bo. He was a very good ...</td>\n",
       "      <td>8.190048e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2017-01-11 02:15:36 +0000</td>\n",
       "      <td>https://twitter.com/dog_rates/status/819004803...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>Bo</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>344</th>\n",
       "      <td>832032802820481025</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-16 01:04:13 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Miguel. He was the only remaining dogg...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.petfinder.com/petdetail/34918210,h...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Miguel</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>760521673607086080</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-08-02 17:04:31 +0000</td>\n",
       "      <td>&lt;a href=\"http://vine.co\" rel=\"nofollow\"&gt;Vine -...</td>\n",
       "      <td>Doggo want what doggo cannot have. Temptation ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://vine.co/v/5ApKetxzmTB</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>845397057150107648</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-03-24 22:08:59 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Say hello to Mimosa. She's an emotional suppor...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://www.gofundme.com/help-save-a-pup,https...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Mimosa</td>\n",
       "      <td>doggo</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>919</th>\n",
       "      <td>756526248105566208</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-22 16:28:07 +0000</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>All hail sky doggo. 13/10 would jump super hig...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://twitter.com/dog_rates/status/756526248...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>doggo</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",
       "446  819015337530290176                    NaN                  NaN   \n",
       "344  832032802820481025                    NaN                  NaN   \n",
       "881  760521673607086080                    NaN                  NaN   \n",
       "248  845397057150107648                    NaN                  NaN   \n",
       "919  756526248105566208                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "446  2017-01-11 02:57:27 +0000   \n",
       "344  2017-02-16 01:04:13 +0000   \n",
       "881  2016-08-02 17:04:31 +0000   \n",
       "248  2017-03-24 22:08:59 +0000   \n",
       "919  2016-07-22 16:28:07 +0000   \n",
       "\n",
       "                                                source  \\\n",
       "446  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "344  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "881  <a href=\"http://vine.co\" rel=\"nofollow\">Vine -...   \n",
       "248  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "919  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                  text  retweeted_status_id  \\\n",
       "446  RT @dog_rates: This is Bo. He was a very good ...         8.190048e+17   \n",
       "344  This is Miguel. He was the only remaining dogg...                  NaN   \n",
       "881  Doggo want what doggo cannot have. Temptation ...                  NaN   \n",
       "248  Say hello to Mimosa. She's an emotional suppor...                  NaN   \n",
       "919  All hail sky doggo. 13/10 would jump super hig...                  NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "446              4.196984e+09  2017-01-11 02:15:36 +0000   \n",
       "344                       NaN                        NaN   \n",
       "881                       NaN                        NaN   \n",
       "248                       NaN                        NaN   \n",
       "919                       NaN                        NaN   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "446  https://twitter.com/dog_rates/status/819004803...                14   \n",
       "344  https://www.petfinder.com/petdetail/34918210,h...                12   \n",
       "881                      https://vine.co/v/5ApKetxzmTB                12   \n",
       "248  https://www.gofundme.com/help-save-a-pup,https...                13   \n",
       "919  https://twitter.com/dog_rates/status/756526248...                13   \n",
       "\n",
       "     rating_denominator    name  doggo floofer pupper puppo  \n",
       "446                  10      Bo  doggo    None   None  None  \n",
       "344                  10  Miguel  doggo    None   None  None  \n",
       "881                  10    None  doggo    None   None  None  \n",
       "248                  10  Mimosa  doggo    None   None  None  \n",
       "919                  10    None  doggo    None   None  None  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Illustrating that pup designations are NOT singular. Multiple \n",
    "twitterDF[twitterDF['doggo'] != 'None'].sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q1\"> Q1 - Convert dtype of timestamp columns</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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",
      " #   Column                      Non-Null Count  Dtype              \n",
      "---  ------                      --------------  -----              \n",
      " 0   tweet_id                    2356 non-null   int64              \n",
      " 1   in_reply_to_status_id       78 non-null     float64            \n",
      " 2   in_reply_to_user_id         78 non-null     float64            \n",
      " 3   timestamp                   2356 non-null   datetime64[ns, UTC]\n",
      " 4   source                      2356 non-null   object             \n",
      " 5   text                        2356 non-null   object             \n",
      " 6   retweeted_status_id         181 non-null    float64            \n",
      " 7   retweeted_status_user_id    181 non-null    float64            \n",
      " 8   retweeted_status_timestamp  181 non-null    datetime64[ns, UTC]\n",
      " 9   expanded_urls               2297 non-null   object             \n",
      " 10  rating_numerator            2356 non-null   int64              \n",
      " 11  rating_denominator          2356 non-null   int64              \n",
      " 12  name                        2356 non-null   object             \n",
      " 13  doggo                       2356 non-null   object             \n",
      " 14  floofer                     2356 non-null   object             \n",
      " 15  pupper                      2356 non-null   object             \n",
      " 16  puppo                       2356 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](2), float64(4), int64(3), object(8)\n",
      "memory usage: 313.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# Fixed 2 columns with incorrect datatypes, changed to datetime64\n",
    "twitterDF.timestamp = pd.to_datetime(twitterDF.timestamp)\n",
    "twitterDF.retweeted_status_timestamp = pd.to_datetime(twitterDF.retweeted_status_timestamp)\n",
    "twitterDF.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q2\"> Q2 - dog names = 'a', replace with NaN </a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace puppo's names that match 'a' with NaN\n",
    "twitterDF.name = np.where(twitterDF.name == 'a', np.NaN, twitterDF.name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check to ensure all 'a' names were removed \n",
    "twitterDF[twitterDF.name == 'a']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q3\"> Q3 - doggo, floofer, pupper, & puppo use None; Replace with NaN, or 0, & 1 for present </a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace 'None' with 0\n",
    "# replace 'doggo' with 1\n",
    "twitterDF.doggo = np.where(twitterDF.doggo == 'None', 0, twitterDF.doggo)\n",
    "twitterDF.doggo = np.where(twitterDF.doggo == 'doggo', 1, twitterDF.doggo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace 'None' with 0\n",
    "# replace 'floofer' with 1\n",
    "twitterDF.floofer = np.where(twitterDF.floofer == 'None', 0, twitterDF.floofer)\n",
    "twitterDF.floofer = np.where(twitterDF.floofer == 'floofer', 1, twitterDF.floofer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace 'None' with 0\n",
    "# replace 'pupper' with 1\n",
    "twitterDF.pupper = np.where(twitterDF.pupper == 'None', 0, twitterDF.pupper)\n",
    "twitterDF.pupper = np.where(twitterDF.pupper == 'pupper', 1, twitterDF.pupper)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace 'None' with 0\n",
    "# replace 'puppo' with 1\n",
    "twitterDF.puppo = np.where(twitterDF.puppo == 'None', 0, twitterDF.puppo)\n",
    "twitterDF.puppo = np.where(twitterDF.puppo == 'puppo', 1, twitterDF.puppo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tweet_id                      0\n",
       "in_reply_to_status_id         0\n",
       "in_reply_to_user_id           0\n",
       "timestamp                     0\n",
       "source                        0\n",
       "text                          0\n",
       "retweeted_status_id           0\n",
       "retweeted_status_user_id      0\n",
       "retweeted_status_timestamp    0\n",
       "expanded_urls                 0\n",
       "rating_numerator              0\n",
       "rating_denominator            0\n",
       "name                          0\n",
       "doggo                         0\n",
       "floofer                       0\n",
       "pupper                        0\n",
       "puppo                         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check to ensure cleaning successful\n",
    "twitterDF[twitterDF.puppo == 'None'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>883360690899218434</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-07 16:22:55+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Meet Grizzwald. He may be the floofiest floofe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/883360690...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Grizzwald</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>854010172552949760</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-04-17 16:34:26+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>At first I thought this was a shy doggo, but i...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/854010172...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>582</th>\n",
       "      <td>800388270626521089</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-11-20 17:20:08+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Doc. He takes time out of every day to...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/800388270...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Doc</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>774</th>\n",
       "      <td>776218204058357768</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-09-15 00:36:55+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Atlas rolled around in some chalk and now he's...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/776218204...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>749317047558017024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-07-02 19:01:20+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Blu. He's a wild bush Floofer. I wish ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/749317047...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Blu</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1022</th>\n",
       "      <td>746542875601690625</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-06-25 03:17:46+00:00</td>\n",
       "      <td>&lt;a href=\"http://vine.co\" rel=\"nofollow\"&gt;Vine -...</td>\n",
       "      <td>Here's a golden floofer helping with the groce...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://vine.co/v/5uZYwqmuDeT</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1091</th>\n",
       "      <td>737445876994609152</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-05-31 00:49:32+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Just wanted to share this super rare Rainbow F...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/737445876...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1110</th>\n",
       "      <td>733822306246479872</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-05-21 00:50:46+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>This is Moose. He's a Polynesian Floofer. Dapp...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/733822306...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Moose</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1534</th>\n",
       "      <td>689993469801164801</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-01-21 02:10:37+00:00</td>\n",
       "      <td>&lt;a href=\"http://vine.co\" rel=\"nofollow\"&gt;Vine -...</td>\n",
       "      <td>Here we are witnessing a rare High Stepping Al...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://vine.co/v/ienexVMZgi5</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1614</th>\n",
       "      <td>685307451701334016</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-01-08 03:50:03+00:00</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>Say hello to Petrick. He's an Altostratus Floo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/685307451...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Petrick</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "46    883360690899218434                    NaN                  NaN   \n",
       "200   854010172552949760                    NaN                  NaN   \n",
       "582   800388270626521089                    NaN                  NaN   \n",
       "774   776218204058357768                    NaN                  NaN   \n",
       "984   749317047558017024                    NaN                  NaN   \n",
       "1022  746542875601690625                    NaN                  NaN   \n",
       "1091  737445876994609152                    NaN                  NaN   \n",
       "1110  733822306246479872                    NaN                  NaN   \n",
       "1534  689993469801164801                    NaN                  NaN   \n",
       "1614  685307451701334016                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  \\\n",
       "46   2017-07-07 16:22:55+00:00   \n",
       "200  2017-04-17 16:34:26+00:00   \n",
       "582  2016-11-20 17:20:08+00:00   \n",
       "774  2016-09-15 00:36:55+00:00   \n",
       "984  2016-07-02 19:01:20+00:00   \n",
       "1022 2016-06-25 03:17:46+00:00   \n",
       "1091 2016-05-31 00:49:32+00:00   \n",
       "1110 2016-05-21 00:50:46+00:00   \n",
       "1534 2016-01-21 02:10:37+00:00   \n",
       "1614 2016-01-08 03:50:03+00:00   \n",
       "\n",
       "                                                 source  \\\n",
       "46    <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "200   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "582   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "774   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "984   <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1022  <a href=\"http://vine.co\" rel=\"nofollow\">Vine -...   \n",
       "1091  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1110  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1534  <a href=\"http://vine.co\" rel=\"nofollow\">Vine -...   \n",
       "1614  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "46    Meet Grizzwald. He may be the floofiest floofe...                  NaN   \n",
       "200   At first I thought this was a shy doggo, but i...                  NaN   \n",
       "582   This is Doc. He takes time out of every day to...                  NaN   \n",
       "774   Atlas rolled around in some chalk and now he's...                  NaN   \n",
       "984   This is Blu. He's a wild bush Floofer. I wish ...                  NaN   \n",
       "1022  Here's a golden floofer helping with the groce...                  NaN   \n",
       "1091  Just wanted to share this super rare Rainbow F...                  NaN   \n",
       "1110  This is Moose. He's a Polynesian Floofer. Dapp...                  NaN   \n",
       "1534  Here we are witnessing a rare High Stepping Al...                  NaN   \n",
       "1614  Say hello to Petrick. He's an Altostratus Floo...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "46                         NaN                        NaT   \n",
       "200                        NaN                        NaT   \n",
       "582                        NaN                        NaT   \n",
       "774                        NaN                        NaT   \n",
       "984                        NaN                        NaT   \n",
       "1022                       NaN                        NaT   \n",
       "1091                       NaN                        NaT   \n",
       "1110                       NaN                        NaT   \n",
       "1534                       NaN                        NaT   \n",
       "1614                       NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "46    https://twitter.com/dog_rates/status/883360690...                13   \n",
       "200   https://twitter.com/dog_rates/status/854010172...                11   \n",
       "582   https://twitter.com/dog_rates/status/800388270...                12   \n",
       "774   https://twitter.com/dog_rates/status/776218204...                13   \n",
       "984   https://twitter.com/dog_rates/status/749317047...                12   \n",
       "1022                      https://vine.co/v/5uZYwqmuDeT                11   \n",
       "1091  https://twitter.com/dog_rates/status/737445876...                13   \n",
       "1110  https://twitter.com/dog_rates/status/733822306...                10   \n",
       "1534                      https://vine.co/v/ienexVMZgi5                12   \n",
       "1614  https://twitter.com/dog_rates/status/685307451...                11   \n",
       "\n",
       "      rating_denominator       name doggo floofer pupper puppo  \n",
       "46                    10  Grizzwald     0       1      0     0  \n",
       "200                   10       None     1       1      0     0  \n",
       "582                   10        Doc     0       1      0     0  \n",
       "774                   10       None     0       1      0     0  \n",
       "984                   10        Blu     0       1      0     0  \n",
       "1022                  10       None     0       1      0     0  \n",
       "1091                  10       None     0       1      0     0  \n",
       "1110                  10      Moose     0       1      0     0  \n",
       "1534                  10       None     0       1      0     0  \n",
       "1614                  10    Petrick     0       1      0     0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check to ensure cleaning successful\n",
    "twitterDF.query(\"floofer == 1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q4\"> Q4 - remove URL from 'source' & replace with 4 categories: iphone, vine, twitter, tweetdeck </a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>     2221\n",
       "<a href=\"http://vine.co\" rel=\"nofollow\">Vine - Make a Scene</a>                          91\n",
       "<a href=\"http://twitter.com\" rel=\"nofollow\">Twitter Web Client</a>                       33\n",
       "<a href=\"https://about.twitter.com/products/tweetdeck\" rel=\"nofollow\">TweetDeck</a>      11\n",
       "Name: source, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# review names of sources\n",
    "twitterDF.source.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 16:23:56+00:00</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>NaT</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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+00:00</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>NaT</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "\n",
       "                  timestamp  \\\n",
       "0 2017-08-01 16:23:56+00:00   \n",
       "1 2017-08-01 00:17:27+00:00   \n",
       "\n",
       "                                              source  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...   \n",
       "1  <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",
       "\n",
       "   retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "0                       NaN                        NaT   \n",
       "1                       NaN                        NaT   \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",
       "\n",
       "   rating_denominator     name doggo floofer pupper puppo  \n",
       "0                  10  Phineas     0       0      0     0  \n",
       "1                  10    Tilly     0       0      0     0  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitterDF.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to categorize source column\n",
    "\n",
    "def update_source(row):\n",
    "    if 'iphone' in row:\n",
    "        return 'iphone'\n",
    "    elif 'vine' in row:\n",
    "        return 'vine'\n",
    "    elif 'Twitter' in row:\n",
    "        return 'twitter web client'\n",
    "    elif 'TweetDeck' in row:\n",
    "        return 'TweetDeck'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run update_source function on every row to replace source text with shorter description of source\n",
    "twitterDF.source = twitterDF.apply(lambda row: update_source(row['source']),axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2312</th>\n",
       "      <td>666776908487630848</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-18 00:36:17+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Josep. He is a Rye Manganese mix. Can ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/666776908...</td>\n",
       "      <td>5</td>\n",
       "      <td>10</td>\n",
       "      <td>Josep</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1350</th>\n",
       "      <td>704113298707505153</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-02-29 01:17:46+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>Meet Stanley. He's an inverted Uzbekistani wat...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/704113298...</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>Stanley</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>352</th>\n",
       "      <td>831315979191906304</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-14 01:35:49+00:00</td>\n",
       "      <td>twitter web client</td>\n",
       "      <td>I couldn't make it to the #WKCDogShow BUT I ha...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/831315979...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>727</th>\n",
       "      <td>782305867769217024</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-10-01 19:47:08+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Sampson. He just graduated. Ready to b...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/782305867...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Sampson</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2190</th>\n",
       "      <td>668960084974809088</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-11-24 01:11:27+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>Meet Jaycob. He got scared of the vacuum. Hide...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/668960084...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Jaycob</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "2312  666776908487630848                    NaN                  NaN   \n",
       "1350  704113298707505153                    NaN                  NaN   \n",
       "352   831315979191906304                    NaN                  NaN   \n",
       "727   782305867769217024                    NaN                  NaN   \n",
       "2190  668960084974809088                    NaN                  NaN   \n",
       "\n",
       "                     timestamp              source  \\\n",
       "2312 2015-11-18 00:36:17+00:00              iphone   \n",
       "1350 2016-02-29 01:17:46+00:00              iphone   \n",
       "352  2017-02-14 01:35:49+00:00  twitter web client   \n",
       "727  2016-10-01 19:47:08+00:00              iphone   \n",
       "2190 2015-11-24 01:11:27+00:00              iphone   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "2312  This is Josep. He is a Rye Manganese mix. Can ...                  NaN   \n",
       "1350  Meet Stanley. He's an inverted Uzbekistani wat...                  NaN   \n",
       "352   I couldn't make it to the #WKCDogShow BUT I ha...                  NaN   \n",
       "727   This is Sampson. He just graduated. Ready to b...                  NaN   \n",
       "2190  Meet Jaycob. He got scared of the vacuum. Hide...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "2312                       NaN                        NaT   \n",
       "1350                       NaN                        NaT   \n",
       "352                        NaN                        NaT   \n",
       "727                        NaN                        NaT   \n",
       "2190                       NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "2312  https://twitter.com/dog_rates/status/666776908...                 5   \n",
       "1350  https://twitter.com/dog_rates/status/704113298...                 8   \n",
       "352   https://twitter.com/dog_rates/status/831315979...                13   \n",
       "727   https://twitter.com/dog_rates/status/782305867...                12   \n",
       "2190  https://twitter.com/dog_rates/status/668960084...                10   \n",
       "\n",
       "      rating_denominator     name doggo floofer pupper puppo  \n",
       "2312                  10    Josep     0       0      0     0  \n",
       "1350                  10  Stanley     0       0      0     0  \n",
       "352                   10     None     0       0      1     0  \n",
       "727                   10  Sampson     1       0      0     0  \n",
       "2190                  10   Jaycob     0       0      0     0  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check to ensure function replaced items as intended\n",
    "twitterDF.sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q6\">Q6 - `in_reply_to_status_id` and `in_reply_to_user_id` are type float. Convert to string</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>886267009285017600</td>\n",
       "      <td>8.862664e+17</td>\n",
       "      <td>2.281182e+09</td>\n",
       "      <td>2017-07-15 16:51:35+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>@NonWhiteHat @MayhewMayhem omg hello tanner yo...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>881633300179243008</td>\n",
       "      <td>8.816070e+17</td>\n",
       "      <td>4.738443e+07</td>\n",
       "      <td>2017-07-02 21:58:53+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>@roushfenway These are good dogs but 17/10 is ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>879674319642796034</td>\n",
       "      <td>8.795538e+17</td>\n",
       "      <td>3.105441e+09</td>\n",
       "      <td>2017-06-27 12:14:36+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>@RealKentMurphy 14/10 confirmed</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>870726314365509632</td>\n",
       "      <td>8.707262e+17</td>\n",
       "      <td>1.648776e+07</td>\n",
       "      <td>2017-06-02 19:38:25+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>@ComplicitOwl @ShopWeRateDogs &amp;gt;10/10 is res...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>863427515083354112</td>\n",
       "      <td>8.634256e+17</td>\n",
       "      <td>7.759620e+07</td>\n",
       "      <td>2017-05-13 16:15:35+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>@Jack_Septic_Eye I'd need a few more pics to p...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>2038</th>\n",
       "      <td>671550332464455680</td>\n",
       "      <td>6.715449e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-12-01 04:44:10+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>After 22 minutes of careful deliberation this ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2149</th>\n",
       "      <td>669684865554620416</td>\n",
       "      <td>6.693544e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-26 01:11:28+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>After countless hours of research and hundreds...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2169</th>\n",
       "      <td>669353438988365824</td>\n",
       "      <td>6.678065e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-25 03:14:30+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Tessa. She is also very pleased after ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/669353438...</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>Tessa</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2189</th>\n",
       "      <td>668967877119254528</td>\n",
       "      <td>6.689207e+17</td>\n",
       "      <td>2.143566e+07</td>\n",
       "      <td>2015-11-24 01:42:25+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>12/10 good shit Bubka\\n@wane15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2298</th>\n",
       "      <td>667070482143944705</td>\n",
       "      <td>6.670655e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2015-11-18 20:02:51+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>After much debate this dog is being upgraded t...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>78 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "30    886267009285017600           8.862664e+17         2.281182e+09   \n",
       "55    881633300179243008           8.816070e+17         4.738443e+07   \n",
       "64    879674319642796034           8.795538e+17         3.105441e+09   \n",
       "113   870726314365509632           8.707262e+17         1.648776e+07   \n",
       "148   863427515083354112           8.634256e+17         7.759620e+07   \n",
       "...                  ...                    ...                  ...   \n",
       "2038  671550332464455680           6.715449e+17         4.196984e+09   \n",
       "2149  669684865554620416           6.693544e+17         4.196984e+09   \n",
       "2169  669353438988365824           6.678065e+17         4.196984e+09   \n",
       "2189  668967877119254528           6.689207e+17         2.143566e+07   \n",
       "2298  667070482143944705           6.670655e+17         4.196984e+09   \n",
       "\n",
       "                     timestamp  source  \\\n",
       "30   2017-07-15 16:51:35+00:00  iphone   \n",
       "55   2017-07-02 21:58:53+00:00  iphone   \n",
       "64   2017-06-27 12:14:36+00:00  iphone   \n",
       "113  2017-06-02 19:38:25+00:00  iphone   \n",
       "148  2017-05-13 16:15:35+00:00  iphone   \n",
       "...                        ...     ...   \n",
       "2038 2015-12-01 04:44:10+00:00  iphone   \n",
       "2149 2015-11-26 01:11:28+00:00  iphone   \n",
       "2169 2015-11-25 03:14:30+00:00  iphone   \n",
       "2189 2015-11-24 01:42:25+00:00  iphone   \n",
       "2298 2015-11-18 20:02:51+00:00  iphone   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "30    @NonWhiteHat @MayhewMayhem omg hello tanner yo...                  NaN   \n",
       "55    @roushfenway These are good dogs but 17/10 is ...                  NaN   \n",
       "64                      @RealKentMurphy 14/10 confirmed                  NaN   \n",
       "113   @ComplicitOwl @ShopWeRateDogs &gt;10/10 is res...                  NaN   \n",
       "148   @Jack_Septic_Eye I'd need a few more pics to p...                  NaN   \n",
       "...                                                 ...                  ...   \n",
       "2038  After 22 minutes of careful deliberation this ...                  NaN   \n",
       "2149  After countless hours of research and hundreds...                  NaN   \n",
       "2169  This is Tessa. She is also very pleased after ...                  NaN   \n",
       "2189                     12/10 good shit Bubka\\n@wane15                  NaN   \n",
       "2298  After much debate this dog is being upgraded t...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "30                         NaN                        NaT   \n",
       "55                         NaN                        NaT   \n",
       "64                         NaN                        NaT   \n",
       "113                        NaN                        NaT   \n",
       "148                        NaN                        NaT   \n",
       "...                        ...                        ...   \n",
       "2038                       NaN                        NaT   \n",
       "2149                       NaN                        NaT   \n",
       "2169                       NaN                        NaT   \n",
       "2189                       NaN                        NaT   \n",
       "2298                       NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "30                                                  NaN                12   \n",
       "55                                                  NaN                17   \n",
       "64                                                  NaN                14   \n",
       "113                                                 NaN                10   \n",
       "148                                                 NaN                12   \n",
       "...                                                 ...               ...   \n",
       "2038                                                NaN                 1   \n",
       "2149                                                NaN                11   \n",
       "2169  https://twitter.com/dog_rates/status/669353438...                10   \n",
       "2189                                                NaN                12   \n",
       "2298                                                NaN                10   \n",
       "\n",
       "      rating_denominator   name doggo floofer pupper puppo  \n",
       "30                    10   None     0       0      0     0  \n",
       "55                    10   None     0       0      0     0  \n",
       "64                    10   None     0       0      0     0  \n",
       "113                   10   None     0       0      0     0  \n",
       "148                   10   None     0       0      0     0  \n",
       "...                  ...    ...   ...     ...    ...   ...  \n",
       "2038                  10   None     0       0      0     0  \n",
       "2149                  10   None     0       0      0     0  \n",
       "2169                  10  Tessa     0       0      0     0  \n",
       "2189                  10   None     0       0      0     0  \n",
       "2298                  10   None     0       0      0     0  \n",
       "\n",
       "[78 rows x 17 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# see sample of is_reply_to_status_id...\n",
    "twitterDF[twitterDF.in_reply_to_status_id.notnull()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q8\"> Q8 - remove retweets & delete columns </a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>813944609378369540</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2016-12-28 03:08:11+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>RT @dog_rates: This is Bruce. He never backs d...</td>\n",
       "      <td>7.902771e+17</td>\n",
       "      <td>4.196984e+09</td>\n",
       "      <td>2016-10-23 19:42:02+00:00</td>\n",
       "      <td>https://twitter.com/dog_rates/status/790277117...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Bruce</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>345</th>\n",
       "      <td>831939777352105988</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-02-15 18:54:34+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Emanuel. He's a h*ckin rare doggo. Dwe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/831939777...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Emanuel</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "488  813944609378369540                    NaN                  NaN   \n",
       "345  831939777352105988                    NaN                  NaN   \n",
       "\n",
       "                    timestamp  source  \\\n",
       "488 2016-12-28 03:08:11+00:00  iphone   \n",
       "345 2017-02-15 18:54:34+00:00  iphone   \n",
       "\n",
       "                                                  text  retweeted_status_id  \\\n",
       "488  RT @dog_rates: This is Bruce. He never backs d...         7.902771e+17   \n",
       "345  This is Emanuel. He's a h*ckin rare doggo. Dwe...                  NaN   \n",
       "\n",
       "     retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "488              4.196984e+09  2016-10-23 19:42:02+00:00   \n",
       "345                       NaN                        NaT   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "488  https://twitter.com/dog_rates/status/790277117...                11   \n",
       "345  https://twitter.com/dog_rates/status/831939777...                12   \n",
       "\n",
       "     rating_denominator     name doggo floofer pupper puppo  \n",
       "488                  10    Bruce     0       0      0     0  \n",
       "345                  10  Emanuel     1       0      0     0  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twitterDF.sample(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1898</th>\n",
       "      <td>674690135443775488</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-09 20:40:38+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>Meet Patrick. He's an exotic pup. Jumps great ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/674690135...</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>Patrick</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>860563773140209665</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-05-05 18:36:06+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>Meet Lorenzo. He's an avid nifty hat wearer an...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://www.gofundme.com/help-lorenzo-beat-can...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Lorenzo</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1714</th>\n",
       "      <td>680440374763077632</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2015-12-25 17:30:01+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>Merry Christmas. My gift to you is this tiny u...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaT</td>\n",
       "      <td>https://twitter.com/dog_rates/status/680440374...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id  in_reply_to_status_id  in_reply_to_user_id  \\\n",
       "1898  674690135443775488                    NaN                  NaN   \n",
       "161   860563773140209665                    NaN                  NaN   \n",
       "1714  680440374763077632                    NaN                  NaN   \n",
       "\n",
       "                     timestamp  source  \\\n",
       "1898 2015-12-09 20:40:38+00:00  iphone   \n",
       "161  2017-05-05 18:36:06+00:00  iphone   \n",
       "1714 2015-12-25 17:30:01+00:00  iphone   \n",
       "\n",
       "                                                   text  retweeted_status_id  \\\n",
       "1898  Meet Patrick. He's an exotic pup. Jumps great ...                  NaN   \n",
       "161   Meet Lorenzo. He's an avid nifty hat wearer an...                  NaN   \n",
       "1714  Merry Christmas. My gift to you is this tiny u...                  NaN   \n",
       "\n",
       "      retweeted_status_user_id retweeted_status_timestamp  \\\n",
       "1898                       NaN                        NaT   \n",
       "161                        NaN                        NaT   \n",
       "1714                       NaN                        NaT   \n",
       "\n",
       "                                          expanded_urls  rating_numerator  \\\n",
       "1898  https://twitter.com/dog_rates/status/674690135...                 3   \n",
       "161   https://www.gofundme.com/help-lorenzo-beat-can...                13   \n",
       "1714  https://twitter.com/dog_rates/status/680440374...                11   \n",
       "\n",
       "      rating_denominator     name doggo floofer pupper puppo  \n",
       "1898                  10  Patrick     0       0      0     0  \n",
       "161                   10  Lorenzo     0       0      0     0  \n",
       "1714                  10     None     0       0      0     0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get indices of rows to drop, in this case, any row with a value in retweeted_status_id different that NaN.  \n",
    "drop_these = twitterDF[twitterDF['retweeted_status_id'].notnull()].index\n",
    "twitterDF.drop(drop_these,inplace=True)\n",
    "twitterDF.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>source</th>\n",
       "      <th>text</th>\n",
       "      <th>retweeted_status_id</th>\n",
       "      <th>retweeted_status_user_id</th>\n",
       "      <th>retweeted_status_timestamp</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [tweet_id, in_reply_to_status_id, in_reply_to_user_id, timestamp, source, text, retweeted_status_id, retweeted_status_user_id, retweeted_status_timestamp, expanded_urls, rating_numerator, rating_denominator, name, doggo, floofer, pupper, puppo]\n",
       "Index: []"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check if any 'notnull' entries exist in retweeted_status_id\n",
    "twitterDF[twitterDF['retweeted_status_id'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2175 entries, 0 to 2355\n",
      "Data columns (total 14 columns):\n",
      " #   Column                 Non-Null Count  Dtype              \n",
      "---  ------                 --------------  -----              \n",
      " 0   tweet_id               2175 non-null   int64              \n",
      " 1   in_reply_to_status_id  78 non-null     float64            \n",
      " 2   in_reply_to_user_id    78 non-null     float64            \n",
      " 3   timestamp              2175 non-null   datetime64[ns, UTC]\n",
      " 4   source                 2175 non-null   object             \n",
      " 5   text                   2175 non-null   object             \n",
      " 6   expanded_urls          2117 non-null   object             \n",
      " 7   rating_numerator       2175 non-null   int64              \n",
      " 8   rating_denominator     2175 non-null   int64              \n",
      " 9   name                   2120 non-null   object             \n",
      " 10  doggo                  2175 non-null   object             \n",
      " 11  floofer                2175 non-null   object             \n",
      " 12  pupper                 2175 non-null   object             \n",
      " 13  puppo                  2175 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](1), float64(2), int64(3), object(8)\n",
      "memory usage: 254.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# get rid of 3 empty columns representing the retweeted tweets\n",
    "drop_cols = ['retweeted_status_id','retweeted_status_user_id','retweeted_status_timestamp']\n",
    "twitterDF.drop(drop_cols,axis=1,inplace=True)\n",
    "twitterDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2175 entries, 0 to 2355\n",
      "Data columns (total 14 columns):\n",
      " #   Column                 Non-Null Count  Dtype              \n",
      "---  ------                 --------------  -----              \n",
      " 0   tweet_id               2175 non-null   int64              \n",
      " 1   in_reply_to_status_id  78 non-null     float64            \n",
      " 2   in_reply_to_user_id    78 non-null     float64            \n",
      " 3   timestamp              2175 non-null   datetime64[ns, UTC]\n",
      " 4   source                 2175 non-null   object             \n",
      " 5   text                   2175 non-null   object             \n",
      " 6   expanded_urls          2117 non-null   object             \n",
      " 7   rating_numerator       2175 non-null   int64              \n",
      " 8   rating_denominator     2175 non-null   int64              \n",
      " 9   name                   2120 non-null   object             \n",
      " 10  doggo                  2175 non-null   object             \n",
      " 11  floofer                2175 non-null   object             \n",
      " 12  pupper                 2175 non-null   object             \n",
      " 13  puppo                  2175 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](1), float64(2), int64(3), object(8)\n",
      "memory usage: 254.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# check to ensure cols dropped\n",
    "twitterDF.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"gather2\">Gather Data #2 - Tweet image predictions</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "335079"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Download data from file_url utilizing requests library & save to line #5\n",
    "file_url = \"https://d17h27t6h515a5.cloudfront.net/topher/2017/August/599fd2ad_image-predictions/image-predictions.tsv\"\n",
    "req = requests.get(file_url)\n",
    "fname = os.path.basename(file_url)\n",
    "open(\"data/\" + fname, 'wb').write(req.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\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>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>2048</th>\n",
       "      <td>886983233522544640</td>\n",
       "      <td>https://pbs.twimg.com/media/DE8yicJW0AAAvBJ.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.793469</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_terrier</td>\n",
       "      <td>0.143528</td>\n",
       "      <td>True</td>\n",
       "      <td>can_opener</td>\n",
       "      <td>0.032253</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1718</th>\n",
       "      <td>819015337530290176</td>\n",
       "      <td>https://pbs.twimg.com/media/C12whDoVEAALRxa.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>standard_poodle</td>\n",
       "      <td>0.351308</td>\n",
       "      <td>True</td>\n",
       "      <td>toy_poodle</td>\n",
       "      <td>0.271929</td>\n",
       "      <td>True</td>\n",
       "      <td>Tibetan_terrier</td>\n",
       "      <td>0.094759</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>738402415918125056</td>\n",
       "      <td>https://pbs.twimg.com/media/Cj9VEs_XAAAlTai.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>cocker_spaniel</td>\n",
       "      <td>0.346695</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>708810915978854401</td>\n",
       "      <td>https://pbs.twimg.com/media/CdYzwuYUIAAHPkB.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.976139</td>\n",
       "      <td>True</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.016301</td>\n",
       "      <td>True</td>\n",
       "      <td>Norfolk_terrier</td>\n",
       "      <td>0.001871</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1702</th>\n",
       "      <td>817171292965273600</td>\n",
       "      <td>https://pbs.twimg.com/media/C1cs8uAWgAEwbXc.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>golden_retriever</td>\n",
       "      <td>0.295483</td>\n",
       "      <td>True</td>\n",
       "      <td>Irish_setter</td>\n",
       "      <td>0.144431</td>\n",
       "      <td>True</td>\n",
       "      <td>Chesapeake_Bay_retriever</td>\n",
       "      <td>0.077879</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                tweet_id                                          jpg_url  \\\n",
       "2048  886983233522544640  https://pbs.twimg.com/media/DE8yicJW0AAAvBJ.jpg   \n",
       "1718  819015337530290176  https://pbs.twimg.com/media/C12whDoVEAALRxa.jpg   \n",
       "1182  738402415918125056  https://pbs.twimg.com/media/Cj9VEs_XAAAlTai.jpg   \n",
       "1002  708810915978854401  https://pbs.twimg.com/media/CdYzwuYUIAAHPkB.jpg   \n",
       "1702  817171292965273600  https://pbs.twimg.com/media/C1cs8uAWgAEwbXc.jpg   \n",
       "\n",
       "      img_num                p1   p1_conf  p1_dog                  p2  \\\n",
       "2048        2         Chihuahua  0.793469    True         toy_terrier   \n",
       "1718        1   standard_poodle  0.351308    True          toy_poodle   \n",
       "1182        1    cocker_spaniel  0.346695    True    Blenheim_spaniel   \n",
       "1002        2  golden_retriever  0.976139    True  Labrador_retriever   \n",
       "1702        1  golden_retriever  0.295483    True        Irish_setter   \n",
       "\n",
       "       p2_conf  p2_dog                        p3   p3_conf  p3_dog  \n",
       "2048  0.143528    True                can_opener  0.032253   False  \n",
       "1718  0.271929    True           Tibetan_terrier  0.094759    True  \n",
       "1182  0.193905    True                 Chihuahua  0.078000    True  \n",
       "1002  0.016301    True           Norfolk_terrier  0.001871    True  \n",
       "1702  0.144431    True  Chesapeake_Bay_retriever  0.077879    True  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# Nows read file downloaded & view sample\n",
    "image_preds = pd.read_csv(\"data/image-predictions.tsv\", sep=\"\\t\")\n",
    "image_preds.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "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",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   tweet_id  2075 non-null   int64  \n",
      " 1   jpg_url   2075 non-null   object \n",
      " 2   img_num   2075 non-null   int64  \n",
      " 3   p1        2075 non-null   object \n",
      " 4   p1_conf   2075 non-null   float64\n",
      " 5   p1_dog    2075 non-null   bool   \n",
      " 6   p2        2075 non-null   object \n",
      " 7   p2_conf   2075 non-null   float64\n",
      " 8   p2_dog    2075 non-null   bool   \n",
      " 9   p3        2075 non-null   object \n",
      " 10  p3_conf   2075 non-null   float64\n",
      " 11  p3_dog    2075 non-null   bool   \n",
      "dtypes: bool(3), float64(3), int64(2), object(4)\n",
      "memory usage: 152.1+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "image_preds.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"gather3\">Gather Data #3 - Query Twitter API for additional data</a>\n",
    "Query Twitter's API for JSON data for each tweet ID in the Twitter archive\n",
    "\n",
    " * retweet count\n",
    " * favorite count\n",
    " * any additional data found that's interesting\n",
    " * only tweets on Aug 1st, 2017 (image predictions present)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# define keys & API info \n",
    "# authenticate API using regenerated keys/tokens\n",
    "\n",
    "consumer_key = 'HIDDEN'\n",
    "consumer_secret = 'HIDDEN'\n",
    "access_token = 'HIDDEN'\n",
    "access_secret = 'HIDDEN'\n",
    "\n",
    "auth = OAuthHandler(consumer_key, consumer_secret)\n",
    "auth.set_access_token(access_token, access_secret)\n",
    "\n",
    "api = tweepy.API(auth, wait_on_rate_limit=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2175"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tweet_ids = twitterDF.tweet_id.values\n",
    "len(tweet_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\ncount = 0\\nfails_dict = {}\\nstart = timer()\\n# Save each tweet\\'s returned JSON as a new line in a .txt file\\nwith open(\\'tweet_json.txt\\', \\'w\\') as outfile:\\n    # This loop will likely take 20-30 minutes to run because of Twitter\\'s rate limit\\n    for tweet_id in tweet_ids:\\n        count += 1\\n        print(str(count) + \": \" + str(tweet_id))\\n        try:\\n            tweet = api.get_status(tweet_id, tweet_mode=\\'extended\\')\\n            print(\"Success\")\\n            json.dump(tweet._json, outfile)\\n            outfile.write(\\'\\n\\')\\n        except tweepy.TweepError as e:\\n            print(\"Fail\")\\n            fails_dict[tweet_id] = e\\n            pass\\nend = timer()\\nprint(end - start)\\nprint(fails_dict)\\n'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Query Twitter's API for JSON data for each tweet ID in the Twitter archive\n",
    "'''\n",
    "count = 0\n",
    "fails_dict = {}\n",
    "start = timer()\n",
    "# Save each tweet's returned JSON as a new line in a .txt file\n",
    "with open('tweet_json.txt', 'w') as outfile:\n",
    "    # This loop will likely take 20-30 minutes to run because of Twitter's rate limit\n",
    "    for tweet_id in tweet_ids:\n",
    "        count += 1\n",
    "        print(str(count) + \": \" + str(tweet_id))\n",
    "        try:\n",
    "            tweet = api.get_status(tweet_id, tweet_mode='extended')\n",
    "            print(\"Success\")\n",
    "            json.dump(tweet._json, outfile)\n",
    "            outfile.write('\\n')\n",
    "        except tweepy.TweepError as e:\n",
    "            print(\"Fail\")\n",
    "            fails_dict[tweet_id] = e\n",
    "            pass\n",
    "end = timer()\n",
    "print(end - start)\n",
    "print(fails_dict)\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Start from here if data already obtained from Twitter                                                   \n",
    "\n",
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\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>created_at</th>\n",
       "      <th>id</th>\n",
       "      <th>id_str</th>\n",
       "      <th>full_text</th>\n",
       "      <th>truncated</th>\n",
       "      <th>display_text_range</th>\n",
       "      <th>entities</th>\n",
       "      <th>extended_entities</th>\n",
       "      <th>source</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>...</th>\n",
       "      <th>favorited</th>\n",
       "      <th>retweeted</th>\n",
       "      <th>possibly_sensitive</th>\n",
       "      <th>possibly_sensitive_appealable</th>\n",
       "      <th>lang</th>\n",
       "      <th>retweeted_status</th>\n",
       "      <th>quoted_status_id</th>\n",
       "      <th>quoted_status_id_str</th>\n",
       "      <th>quoted_status_permalink</th>\n",
       "      <th>quoted_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-08-01 16:23:56+00:00</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>892420643555336192</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 85]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 892420639486877696, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-08-01 00:17:27+00:00</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>892177421306343424</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 892177413194625024, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 891815175371796480, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-30 15:58:51+00:00</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 79]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 891689552724799489, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-07-29 16:00:24+00:00</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>{'hashtags': [{'text': 'BarkWeek', 'indices': ...</td>\n",
       "      <td>{'media': [{'id': 891327551943041024, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 created_at                  id              id_str  \\\n",
       "0 2017-08-01 16:23:56+00:00  892420643555336193  892420643555336192   \n",
       "1 2017-08-01 00:17:27+00:00  892177421306343426  892177421306343424   \n",
       "2 2017-07-31 00:18:03+00:00  891815181378084864  891815181378084864   \n",
       "3 2017-07-30 15:58:51+00:00  891689557279858688  891689557279858688   \n",
       "4 2017-07-29 16:00:24+00:00  891327558926688256  891327558926688256   \n",
       "\n",
       "                                           full_text  truncated  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...      False   \n",
       "1  This is Tilly. She's just checking pup on you....      False   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...      False   \n",
       "3  This is Darla. She commenced a snooze mid meal...      False   \n",
       "4  This is Franklin. He would like you to stop ca...      False   \n",
       "\n",
       "  display_text_range                                           entities  \\\n",
       "0            [0, 85]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "1           [0, 138]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "2           [0, 121]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "3            [0, 79]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "4           [0, 138]  {'hashtags': [{'text': 'BarkWeek', 'indices': ...   \n",
       "\n",
       "                                   extended_entities  \\\n",
       "0  {'media': [{'id': 892420639486877696, 'id_str'...   \n",
       "1  {'media': [{'id': 892177413194625024, 'id_str'...   \n",
       "2  {'media': [{'id': 891815175371796480, 'id_str'...   \n",
       "3  {'media': [{'id': 891689552724799489, 'id_str'...   \n",
       "4  {'media': [{'id': 891327551943041024, 'id_str'...   \n",
       "\n",
       "                                              source  in_reply_to_status_id  \\\n",
       "0  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "1  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "2  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "3  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "4  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "\n",
       "   ...  favorited  retweeted  possibly_sensitive  \\\n",
       "0  ...      False      False                 0.0   \n",
       "1  ...      False      False                 0.0   \n",
       "2  ...      False      False                 0.0   \n",
       "3  ...      False      False                 0.0   \n",
       "4  ...      False      False                 0.0   \n",
       "\n",
       "  possibly_sensitive_appealable lang  retweeted_status  quoted_status_id  \\\n",
       "0                           0.0   en               NaN               NaN   \n",
       "1                           0.0   en               NaN               NaN   \n",
       "2                           0.0   en               NaN               NaN   \n",
       "3                           0.0   en               NaN               NaN   \n",
       "4                           0.0   en               NaN               NaN   \n",
       "\n",
       "  quoted_status_id_str  quoted_status_permalink  quoted_status  \n",
       "0                  NaN                      NaN            NaN  \n",
       "1                  NaN                      NaN            NaN  \n",
       "2                  NaN                      NaN            NaN  \n",
       "3                  NaN                      NaN            NaN  \n",
       "4                  NaN                      NaN            NaN  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read tweet JSON into dataframe using pandas\n",
    "# recived ValueError: Trailing data without 'lines=True'\n",
    "\n",
    "rt_tweets = pd.read_json(\"tweet.json\", lines=True)\n",
    "rt_tweets.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2330 entries, 0 to 2329\n",
      "Data columns (total 32 columns):\n",
      " #   Column                         Non-Null Count  Dtype              \n",
      "---  ------                         --------------  -----              \n",
      " 0   created_at                     2330 non-null   datetime64[ns, UTC]\n",
      " 1   id                             2330 non-null   int64              \n",
      " 2   id_str                         2330 non-null   int64              \n",
      " 3   full_text                      2330 non-null   object             \n",
      " 4   truncated                      2330 non-null   bool               \n",
      " 5   display_text_range             2330 non-null   object             \n",
      " 6   entities                       2330 non-null   object             \n",
      " 7   extended_entities              2058 non-null   object             \n",
      " 8   source                         2330 non-null   object             \n",
      " 9   in_reply_to_status_id          77 non-null     float64            \n",
      " 10  in_reply_to_status_id_str      77 non-null     float64            \n",
      " 11  in_reply_to_user_id            77 non-null     float64            \n",
      " 12  in_reply_to_user_id_str        77 non-null     float64            \n",
      " 13  in_reply_to_screen_name        77 non-null     object             \n",
      " 14  user                           2330 non-null   object             \n",
      " 15  geo                            0 non-null      float64            \n",
      " 16  coordinates                    0 non-null      float64            \n",
      " 17  place                          1 non-null      object             \n",
      " 18  contributors                   0 non-null      float64            \n",
      " 19  is_quote_status                2330 non-null   bool               \n",
      " 20  retweet_count                  2330 non-null   int64              \n",
      " 21  favorite_count                 2330 non-null   int64              \n",
      " 22  favorited                      2330 non-null   bool               \n",
      " 23  retweeted                      2330 non-null   bool               \n",
      " 24  possibly_sensitive             2196 non-null   float64            \n",
      " 25  possibly_sensitive_appealable  2196 non-null   float64            \n",
      " 26  lang                           2330 non-null   object             \n",
      " 27  retweeted_status               163 non-null    object             \n",
      " 28  quoted_status_id               26 non-null     float64            \n",
      " 29  quoted_status_id_str           26 non-null     float64            \n",
      " 30  quoted_status_permalink        26 non-null     object             \n",
      " 31  quoted_status                  24 non-null     object             \n",
      "dtypes: bool(4), datetime64[ns, UTC](1), float64(11), int64(4), object(12)\n",
      "memory usage: 518.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>created_at</th>\n",
       "      <th>id</th>\n",
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       "      <th>extended_entities</th>\n",
       "      <th>source</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>...</th>\n",
       "      <th>favorited</th>\n",
       "      <th>retweeted</th>\n",
       "      <th>possibly_sensitive</th>\n",
       "      <th>possibly_sensitive_appealable</th>\n",
       "      <th>lang</th>\n",
       "      <th>retweeted_status</th>\n",
       "      <th>quoted_status_id</th>\n",
       "      <th>quoted_status_id_str</th>\n",
       "      <th>quoted_status_permalink</th>\n",
       "      <th>quoted_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2017-07-15 02:45:48+00:00</td>\n",
       "      <td>886054160059072513</td>\n",
       "      <td>886054160059072512</td>\n",
       "      <td>RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 50]</td>\n",
       "      <td>{'hashtags': [{'text': 'BATP', 'indices': [21,...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>und</td>\n",
       "      <td>{'created_at': 'Sat Jul 15 02:44:07 +0000 2017...</td>\n",
       "      <td>8.860534e+17</td>\n",
       "      <td>8.860534e+17</td>\n",
       "      <td>{'url': 'https://t.co/WxwJmvjfxo', 'expanded':...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2017-07-13 01:35:06+00:00</td>\n",
       "      <td>885311592912609280</td>\n",
       "      <td>885311592912609280</td>\n",
       "      <td>RT @dog_rates: This is Lilly. She just paralle...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 133]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>{'media': [{'id': 830583314243268608, 'id_str'...</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>{'created_at': 'Sun Feb 12 01:04:29 +0000 2017...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2017-06-26 00:13:58+00:00</td>\n",
       "      <td>879130579576475649</td>\n",
       "      <td>879130579576475648</td>\n",
       "      <td>RT @dog_rates: This is Emmy. She was adopted t...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>en</td>\n",
       "      <td>{'created_at': 'Fri Jun 23 01:10:23 +0000 2017...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2017-06-24 00:09:53+00:00</td>\n",
       "      <td>878404777348136964</td>\n",
       "      <td>878404777348136960</td>\n",
       "      <td>RT @dog_rates: Meet Shadow. In an attempt to r...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>en</td>\n",
       "      <td>{'created_at': 'Fri Jun 23 16:00:04 +0000 2017...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2017-06-23 18:17:33+00:00</td>\n",
       "      <td>878316110768087041</td>\n",
       "      <td>878316110768087040</td>\n",
       "      <td>RT @dog_rates: Meet Terrance. He's being yelle...</td>\n",
       "      <td>False</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>{'hashtags': [], 'symbols': [], 'user_mentions...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>&lt;a href=\"http://twitter.com/download/iphone\" r...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>en</td>\n",
       "      <td>{'created_at': 'Tue Nov 24 03:51:38 +0000 2015...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  created_at                  id              id_str  \\\n",
       "31 2017-07-15 02:45:48+00:00  886054160059072513  886054160059072512   \n",
       "35 2017-07-13 01:35:06+00:00  885311592912609280  885311592912609280   \n",
       "67 2017-06-26 00:13:58+00:00  879130579576475649  879130579576475648   \n",
       "72 2017-06-24 00:09:53+00:00  878404777348136964  878404777348136960   \n",
       "73 2017-06-23 18:17:33+00:00  878316110768087041  878316110768087040   \n",
       "\n",
       "                                            full_text  truncated  \\\n",
       "31  RT @Athletics: 12/10 #BATP https://t.co/WxwJmv...      False   \n",
       "35  RT @dog_rates: This is Lilly. She just paralle...      False   \n",
       "67  RT @dog_rates: This is Emmy. She was adopted t...      False   \n",
       "72  RT @dog_rates: Meet Shadow. In an attempt to r...      False   \n",
       "73  RT @dog_rates: Meet Terrance. He's being yelle...      False   \n",
       "\n",
       "   display_text_range                                           entities  \\\n",
       "31            [0, 50]  {'hashtags': [{'text': 'BATP', 'indices': [21,...   \n",
       "35           [0, 133]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "67           [0, 140]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "72           [0, 140]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "73           [0, 140]  {'hashtags': [], 'symbols': [], 'user_mentions...   \n",
       "\n",
       "                                    extended_entities  \\\n",
       "31                                                NaN   \n",
       "35  {'media': [{'id': 830583314243268608, 'id_str'...   \n",
       "67                                                NaN   \n",
       "72                                                NaN   \n",
       "73                                                NaN   \n",
       "\n",
       "                                               source  in_reply_to_status_id  \\\n",
       "31  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "35  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "67  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "72  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "73  <a href=\"http://twitter.com/download/iphone\" r...                    NaN   \n",
       "\n",
       "    ...  favorited  retweeted  possibly_sensitive  \\\n",
       "31  ...      False      False                 0.0   \n",
       "35  ...      False      False                 0.0   \n",
       "67  ...      False      False                 NaN   \n",
       "72  ...      False      False                 NaN   \n",
       "73  ...      False      False                 NaN   \n",
       "\n",
       "   possibly_sensitive_appealable lang  \\\n",
       "31                           0.0  und   \n",
       "35                           0.0   en   \n",
       "67                           NaN   en   \n",
       "72                           NaN   en   \n",
       "73                           NaN   en   \n",
       "\n",
       "                                     retweeted_status  quoted_status_id  \\\n",
       "31  {'created_at': 'Sat Jul 15 02:44:07 +0000 2017...      8.860534e+17   \n",
       "35  {'created_at': 'Sun Feb 12 01:04:29 +0000 2017...               NaN   \n",
       "67  {'created_at': 'Fri Jun 23 01:10:23 +0000 2017...               NaN   \n",
       "72  {'created_at': 'Fri Jun 23 16:00:04 +0000 2017...               NaN   \n",
       "73  {'created_at': 'Tue Nov 24 03:51:38 +0000 2015...               NaN   \n",
       "\n",
       "   quoted_status_id_str                            quoted_status_permalink  \\\n",
       "31         8.860534e+17  {'url': 'https://t.co/WxwJmvjfxo', 'expanded':...   \n",
       "35                  NaN                                                NaN   \n",
       "67                  NaN                                                NaN   \n",
       "72                  NaN                                                NaN   \n",
       "73                  NaN                                                NaN   \n",
       "\n",
       "    quoted_status  \n",
       "31            NaN  \n",
       "35            NaN  \n",
       "67            NaN  \n",
       "72            NaN  \n",
       "73            NaN  \n",
       "\n",
       "[5 rows x 32 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# View retweeted tweets, first 5 of 163, these will be deleted\n",
    "\n",
    "rt_tweets[rt_tweets.retweeted_status.notnull()].head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "1       {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "2       {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "3       {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "4       {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "                              ...                        \n",
       "2325    {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "2326    {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "2327    {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "2328    {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "2329    {'id': 4196983835, 'id_str': '4196983835', 'na...\n",
       "Name: user, Length: 2330, dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets.user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['created_at', 'id', 'id_str', 'full_text', 'truncated',\n",
       "       'display_text_range', 'entities', 'extended_entities', 'source',\n",
       "       'in_reply_to_status_id', 'in_reply_to_status_id_str',\n",
       "       'in_reply_to_user_id', 'in_reply_to_user_id_str',\n",
       "       'in_reply_to_screen_name', 'user', 'geo', 'coordinates', 'place',\n",
       "       'contributors', 'is_quote_status', 'retweet_count', 'favorite_count',\n",
       "       'favorited', 'retweeted', 'possibly_sensitive',\n",
       "       'possibly_sensitive_appealable', 'lang', 'retweeted_status',\n",
       "       'quoted_status_id', 'quoted_status_id_str', 'quoted_status_permalink',\n",
       "       'quoted_status'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'media': [{'id': 892420639486877696,\n",
       "   'id_str': '892420639486877696',\n",
       "   'indices': [86, 109],\n",
       "   'media_url': 'http://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg',\n",
       "   'media_url_https': 'https://pbs.twimg.com/media/DGKD1-bXoAAIAUK.jpg',\n",
       "   'url': 'https://t.co/MgUWQ76dJU',\n",
       "   'display_url': 'pic.twitter.com/MgUWQ76dJU',\n",
       "   'expanded_url': 'https://twitter.com/dog_rates/status/892420643555336193/photo/1',\n",
       "   'type': 'photo',\n",
       "   'sizes': {'thumb': {'w': 150, 'h': 150, 'resize': 'crop'},\n",
       "    'medium': {'w': 540, 'h': 528, 'resize': 'fit'},\n",
       "    'small': {'w': 540, 'h': 528, 'resize': 'fit'},\n",
       "    'large': {'w': 540, 'h': 528, 'resize': 'fit'}}}]}"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# inspect the extended entities data\n",
    "rt_tweets.loc[0,'extended_entities']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'hashtags': [],\n",
       " 'symbols': [],\n",
       " 'user_mentions': [],\n",
       " 'urls': [],\n",
       " 'media': [{'id': 869702951354474496,\n",
       "   'id_str': '869702951354474496',\n",
       "   'indices': [140, 163],\n",
       "   'media_url': 'http://pbs.twimg.com/media/DBHOOfOXoAABKlU.jpg',\n",
       "   'media_url_https': 'https://pbs.twimg.com/media/DBHOOfOXoAABKlU.jpg',\n",
       "   'url': 'https://t.co/vmCu3PFCQq',\n",
       "   'display_url': 'pic.twitter.com/vmCu3PFCQq',\n",
       "   'expanded_url': 'https://twitter.com/dog_rates/status/869702957897576449/photo/1',\n",
       "   'type': 'photo',\n",
       "   'sizes': {'thumb': {'w': 150, 'h': 150, 'resize': 'crop'},\n",
       "    'large': {'w': 901, 'h': 1600, 'resize': 'fit'},\n",
       "    'small': {'w': 383, 'h': 680, 'resize': 'fit'},\n",
       "    'medium': {'w': 676, 'h': 1200, 'resize': 'fit'}}}]}"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# inspect the entities data\n",
    "rt_tweets.loc[115,'entities']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'id': 4196983835,\n",
       " 'id_str': '4196983835',\n",
       " 'name': 'WeRateDogs®',\n",
       " 'screen_name': 'dog_rates',\n",
       " 'location': 'merch ➜',\n",
       " 'description': 'Your Only Source For Professional Dog Ratings Instagram and Facebook ➜ WeRateDogs partnerships@weratedogs.com ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀',\n",
       " 'url': 'https://t.co/N7sNNHSfPq',\n",
       " 'entities': {'url': {'urls': [{'url': 'https://t.co/N7sNNHSfPq',\n",
       "     'expanded_url': 'http://weratedogs.com',\n",
       "     'display_url': 'weratedogs.com',\n",
       "     'indices': [0, 23]}]},\n",
       "  'description': {'urls': []}},\n",
       " 'protected': False,\n",
       " 'followers_count': 8894598,\n",
       " 'friends_count': 18,\n",
       " 'listed_count': 6035,\n",
       " 'created_at': 'Sun Nov 15 21:41:29 +0000 2015',\n",
       " 'favourites_count': 145946,\n",
       " 'utc_offset': None,\n",
       " 'time_zone': None,\n",
       " 'geo_enabled': True,\n",
       " 'verified': True,\n",
       " 'statuses_count': 13082,\n",
       " 'lang': None,\n",
       " 'contributors_enabled': False,\n",
       " 'is_translator': False,\n",
       " 'is_translation_enabled': False,\n",
       " 'profile_background_color': '000000',\n",
       " 'profile_background_image_url': 'http://abs.twimg.com/images/themes/theme1/bg.png',\n",
       " 'profile_background_image_url_https': 'https://abs.twimg.com/images/themes/theme1/bg.png',\n",
       " 'profile_background_tile': False,\n",
       " 'profile_image_url': 'http://pbs.twimg.com/profile_images/1322993722691211264/vyjR1ftm_normal.jpg',\n",
       " 'profile_image_url_https': 'https://pbs.twimg.com/profile_images/1322993722691211264/vyjR1ftm_normal.jpg',\n",
       " 'profile_banner_url': 'https://pbs.twimg.com/profile_banners/4196983835/1591077312',\n",
       " 'profile_link_color': 'F5ABB5',\n",
       " 'profile_sidebar_border_color': '000000',\n",
       " 'profile_sidebar_fill_color': '000000',\n",
       " 'profile_text_color': '000000',\n",
       " 'profile_use_background_image': False,\n",
       " 'has_extended_profile': False,\n",
       " 'default_profile': False,\n",
       " 'default_profile_image': False,\n",
       " 'following': False,\n",
       " 'follow_request_sent': False,\n",
       " 'notifications': False,\n",
       " 'translator_type': 'none'}"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets.loc[130,'user']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>in_reply_to_user_id_str</th>\n",
       "      <th>in_reply_to_screen_name</th>\n",
       "      <th>user</th>\n",
       "      <th>geo</th>\n",
       "      <th>coordinates</th>\n",
       "      <th>place</th>\n",
       "      <th>contributors</th>\n",
       "      <th>is_quote_status</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>...</th>\n",
       "      <th>favorited</th>\n",
       "      <th>retweeted</th>\n",
       "      <th>possibly_sensitive</th>\n",
       "      <th>possibly_sensitive_appealable</th>\n",
       "      <th>lang</th>\n",
       "      <th>retweeted_status</th>\n",
       "      <th>quoted_status_id</th>\n",
       "      <th>quoted_status_id_str</th>\n",
       "      <th>quoted_status_permalink</th>\n",
       "      <th>quoted_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>5549</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>3671</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>7649</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>8249</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>2759</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>1791</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>16725</td>\n",
       "      <td>...</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>en</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   in_reply_to_user_id  in_reply_to_user_id_str in_reply_to_screen_name  \\\n",
       "1                  NaN                      NaN                    None   \n",
       "2                  NaN                      NaN                    None   \n",
       "3                  NaN                      NaN                    None   \n",
       "4                  NaN                      NaN                    None   \n",
       "5                  NaN                      NaN                    None   \n",
       "6                  NaN                      NaN                    None   \n",
       "7                  NaN                      NaN                    None   \n",
       "\n",
       "                                                user  geo  coordinates place  \\\n",
       "1  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "2  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "3  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "4  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "5  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "6  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "7  {'id': 4196983835, 'id_str': '4196983835', 'na...  NaN          NaN  None   \n",
       "\n",
       "   contributors  is_quote_status  retweet_count  ...  favorited  retweeted  \\\n",
       "1           NaN            False           5549  ...      False      False   \n",
       "2           NaN            False           3671  ...      False      False   \n",
       "3           NaN            False           7649  ...      False      False   \n",
       "4           NaN            False           8249  ...      False      False   \n",
       "5           NaN            False           2759  ...      False      False   \n",
       "6           NaN            False           1791  ...      False      False   \n",
       "7           NaN            False          16725  ...      False      False   \n",
       "\n",
       "   possibly_sensitive  possibly_sensitive_appealable  lang retweeted_status  \\\n",
       "1                 0.0                            0.0    en              NaN   \n",
       "2                 0.0                            0.0    en              NaN   \n",
       "3                 0.0                            0.0    en              NaN   \n",
       "4                 0.0                            0.0    en              NaN   \n",
       "5                 0.0                            0.0    en              NaN   \n",
       "6                 0.0                            0.0    en              NaN   \n",
       "7                 0.0                            0.0    en              NaN   \n",
       "\n",
       "  quoted_status_id  quoted_status_id_str  quoted_status_permalink  \\\n",
       "1              NaN                   NaN                      NaN   \n",
       "2              NaN                   NaN                      NaN   \n",
       "3              NaN                   NaN                      NaN   \n",
       "4              NaN                   NaN                      NaN   \n",
       "5              NaN                   NaN                      NaN   \n",
       "6              NaN                   NaN                      NaN   \n",
       "7              NaN                   NaN                      NaN   \n",
       "\n",
       "  quoted_status  \n",
       "1           NaN  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  \n",
       "5           NaN  \n",
       "6           NaN  \n",
       "7           NaN  \n",
       "\n",
       "[7 rows x 21 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets.iloc[1:8,11:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"t1\">Tidy #1 - create new dataframe of columns needed</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# add columns to this list for creating a new DF with only columns we want only\n",
    "tweet_cols = ['created_at','id','full_text','display_text_range','retweet_count','favorite_count','user']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created_at</th>\n",
       "      <th>id</th>\n",
       "      <th>full_text</th>\n",
       "      <th>display_text_range</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>user</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-08-01 16:23:56+00:00</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>[0, 85]</td>\n",
       "      <td>7477</td>\n",
       "      <td>35388</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-08-01 00:17:27+00:00</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>5549</td>\n",
       "      <td>30638</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>3671</td>\n",
       "      <td>23034</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-30 15:58:51+00:00</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>[0, 79]</td>\n",
       "      <td>7649</td>\n",
       "      <td>38689</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-07-29 16:00:24+00:00</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>8249</td>\n",
       "      <td>36965</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2017-07-29 00:08:17+00:00</td>\n",
       "      <td>891087950875897856</td>\n",
       "      <td>Here we have a majestic great white breaching ...</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>2759</td>\n",
       "      <td>18630</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2017-07-28 16:27:12+00:00</td>\n",
       "      <td>890971913173991426</td>\n",
       "      <td>Meet Jax. He enjoys ice cream so much he gets ...</td>\n",
       "      <td>[0, 140]</td>\n",
       "      <td>1791</td>\n",
       "      <td>10828</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2017-07-28 00:22:40+00:00</td>\n",
       "      <td>890729181411237888</td>\n",
       "      <td>When you watch your owner call another dog a g...</td>\n",
       "      <td>[0, 118]</td>\n",
       "      <td>16725</td>\n",
       "      <td>59634</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2017-07-27 16:25:51+00:00</td>\n",
       "      <td>890609185150312448</td>\n",
       "      <td>This is Zoey. She doesn't want to be one of th...</td>\n",
       "      <td>[0, 122]</td>\n",
       "      <td>3815</td>\n",
       "      <td>25645</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2017-07-26 15:59:51+00:00</td>\n",
       "      <td>890240255349198849</td>\n",
       "      <td>This is Cassie. She is a college pup. Studying...</td>\n",
       "      <td>[0, 133]</td>\n",
       "      <td>6490</td>\n",
       "      <td>29261</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 created_at                  id  \\\n",
       "0 2017-08-01 16:23:56+00:00  892420643555336193   \n",
       "1 2017-08-01 00:17:27+00:00  892177421306343426   \n",
       "2 2017-07-31 00:18:03+00:00  891815181378084864   \n",
       "3 2017-07-30 15:58:51+00:00  891689557279858688   \n",
       "4 2017-07-29 16:00:24+00:00  891327558926688256   \n",
       "5 2017-07-29 00:08:17+00:00  891087950875897856   \n",
       "6 2017-07-28 16:27:12+00:00  890971913173991426   \n",
       "7 2017-07-28 00:22:40+00:00  890729181411237888   \n",
       "8 2017-07-27 16:25:51+00:00  890609185150312448   \n",
       "9 2017-07-26 15:59:51+00:00  890240255349198849   \n",
       "\n",
       "                                           full_text display_text_range  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...            [0, 85]   \n",
       "1  This is Tilly. She's just checking pup on you....           [0, 138]   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...           [0, 121]   \n",
       "3  This is Darla. She commenced a snooze mid meal...            [0, 79]   \n",
       "4  This is Franklin. He would like you to stop ca...           [0, 138]   \n",
       "5  Here we have a majestic great white breaching ...           [0, 138]   \n",
       "6  Meet Jax. He enjoys ice cream so much he gets ...           [0, 140]   \n",
       "7  When you watch your owner call another dog a g...           [0, 118]   \n",
       "8  This is Zoey. She doesn't want to be one of th...           [0, 122]   \n",
       "9  This is Cassie. She is a college pup. Studying...           [0, 133]   \n",
       "\n",
       "   retweet_count  favorite_count  \\\n",
       "0           7477           35388   \n",
       "1           5549           30638   \n",
       "2           3671           23034   \n",
       "3           7649           38689   \n",
       "4           8249           36965   \n",
       "5           2759           18630   \n",
       "6           1791           10828   \n",
       "7          16725           59634   \n",
       "8           3815           25645   \n",
       "9           6490           29261   \n",
       "\n",
       "                                                user  \n",
       "0  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "1  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "3  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "4  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "5  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "6  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "7  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "8  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "9  {'id': 4196983835, 'id_str': '4196983835', 'na...  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new DF with column defined above\n",
    "rt_tweets_sub = rt_tweets.loc[:,tweet_cols]\n",
    "rt_tweets_sub.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"t2\">Tidy #2 - Merge 3 datasets</a>\n",
    "\n",
    "1. twitterDF\n",
    "2. rt_tweets_sub\n",
    "3. image_preds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2175 entries, 0 to 2355\n",
      "Data columns (total 14 columns):\n",
      " #   Column                 Non-Null Count  Dtype              \n",
      "---  ------                 --------------  -----              \n",
      " 0   tweet_id               2175 non-null   int64              \n",
      " 1   in_reply_to_status_id  78 non-null     float64            \n",
      " 2   in_reply_to_user_id    78 non-null     float64            \n",
      " 3   timestamp              2175 non-null   datetime64[ns, UTC]\n",
      " 4   source                 2175 non-null   object             \n",
      " 5   text                   2175 non-null   object             \n",
      " 6   expanded_urls          2117 non-null   object             \n",
      " 7   rating_numerator       2175 non-null   int64              \n",
      " 8   rating_denominator     2175 non-null   int64              \n",
      " 9   name                   2120 non-null   object             \n",
      " 10  doggo                  2175 non-null   object             \n",
      " 11  floofer                2175 non-null   object             \n",
      " 12  pupper                 2175 non-null   object             \n",
      " 13  puppo                  2175 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](1), float64(2), int64(3), object(8)\n",
      "memory usage: 254.9+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "twitterDF.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2330 entries, 0 to 2329\n",
      "Data columns (total 7 columns):\n",
      " #   Column              Non-Null Count  Dtype              \n",
      "---  ------              --------------  -----              \n",
      " 0   created_at          2330 non-null   datetime64[ns, UTC]\n",
      " 1   id                  2330 non-null   int64              \n",
      " 2   full_text           2330 non-null   object             \n",
      " 3   display_text_range  2330 non-null   object             \n",
      " 4   retweet_count       2330 non-null   int64              \n",
      " 5   favorite_count      2330 non-null   int64              \n",
      " 6   user                2330 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](1), int64(3), object(3)\n",
      "memory usage: 127.5+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "rt_tweets_sub.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "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",
      " #   Column    Non-Null Count  Dtype  \n",
      "---  ------    --------------  -----  \n",
      " 0   tweet_id  2075 non-null   int64  \n",
      " 1   jpg_url   2075 non-null   object \n",
      " 2   img_num   2075 non-null   int64  \n",
      " 3   p1        2075 non-null   object \n",
      " 4   p1_conf   2075 non-null   float64\n",
      " 5   p1_dog    2075 non-null   bool   \n",
      " 6   p2        2075 non-null   object \n",
      " 7   p2_conf   2075 non-null   float64\n",
      " 8   p2_dog    2075 non-null   bool   \n",
      " 9   p3        2075 non-null   object \n",
      " 10  p3_conf   2075 non-null   float64\n",
      " 11  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_preds.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"q7\">Quality 7 - rename id column for common data uniformity</a> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2017-08-01 16:23:56+00:00</td>\n",
       "      <td>892420643555336193</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
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       "      <td>2017-08-01 00:17:27+00:00</td>\n",
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       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-30 15:58:51+00:00</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
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       "      <td>7649</td>\n",
       "      <td>38689</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-07-29 16:00:24+00:00</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>8249</td>\n",
       "      <td>36965</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 created_at            tweet_id  \\\n",
       "0 2017-08-01 16:23:56+00:00  892420643555336193   \n",
       "1 2017-08-01 00:17:27+00:00  892177421306343426   \n",
       "2 2017-07-31 00:18:03+00:00  891815181378084864   \n",
       "3 2017-07-30 15:58:51+00:00  891689557279858688   \n",
       "4 2017-07-29 16:00:24+00:00  891327558926688256   \n",
       "\n",
       "                                           full_text display_text_range  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...            [0, 85]   \n",
       "1  This is Tilly. She's just checking pup on you....           [0, 138]   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...           [0, 121]   \n",
       "3  This is Darla. She commenced a snooze mid meal...            [0, 79]   \n",
       "4  This is Franklin. He would like you to stop ca...           [0, 138]   \n",
       "\n",
       "   retweet_count  favorite_count  \\\n",
       "0           7477           35388   \n",
       "1           5549           30638   \n",
       "2           3671           23034   \n",
       "3           7649           38689   \n",
       "4           8249           36965   \n",
       "\n",
       "                                                user  \n",
       "0  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "1  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "2  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "3  {'id': 4196983835, 'id_str': '4196983835', 'na...  \n",
       "4  {'id': 4196983835, 'id_str': '4196983835', 'na...  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataframe has a different name for its shared column, id --> tweet_id\n",
    "rt_tweets_sub = rt_tweets_sub.rename(columns={\"id\":\"tweet_id\"})\n",
    "rt_tweets_sub.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>created_at</th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>full_text</th>\n",
       "      <th>display_text_range</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>user</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</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>0</th>\n",
       "      <td>2017-08-01 16:23:56+00:00</td>\n",
       "      <td>892420643555336193</td>\n",
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       "      <td>iphone</td>\n",
       "      <td>This is Phineas. He's a mystical boy. Only eve...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892420643...</td>\n",
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       "      <td>2017-08-01 00:17:27+00:00</td>\n",
       "      <td>892177421306343426</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>[0, 138]</td>\n",
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       "      <td>30638</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-08-01 00:17:27+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Tilly. She's just checking pup on you....</td>\n",
       "      <td>https://twitter.com/dog_rates/status/892177421...</td>\n",
       "      <td>13</td>\n",
       "      <td>10</td>\n",
       "      <td>Tilly</td>\n",
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       "      <th>2</th>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>3671</td>\n",
       "      <td>23034</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>iphone</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/891815181...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Archie</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 created_at            tweet_id  \\\n",
       "0 2017-08-01 16:23:56+00:00  892420643555336193   \n",
       "1 2017-08-01 00:17:27+00:00  892177421306343426   \n",
       "2 2017-07-31 00:18:03+00:00  891815181378084864   \n",
       "\n",
       "                                           full_text display_text_range  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...            [0, 85]   \n",
       "1  This is Tilly. She's just checking pup on you....           [0, 138]   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...           [0, 121]   \n",
       "\n",
       "   retweet_count  favorite_count  \\\n",
       "0           7477           35388   \n",
       "1           5549           30638   \n",
       "2           3671           23034   \n",
       "\n",
       "                                                user  in_reply_to_status_id  \\\n",
       "0  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "1  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "2  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "\n",
       "   in_reply_to_user_id                 timestamp  source  \\\n",
       "0                  NaN 2017-08-01 16:23:56+00:00  iphone   \n",
       "1                  NaN 2017-08-01 00:17:27+00:00  iphone   \n",
       "2                  NaN 2017-07-31 00:18:03+00:00  iphone   \n",
       "\n",
       "                                                text  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...   \n",
       "1  This is Tilly. She's just checking pup on you....   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...   \n",
       "\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",
       "\n",
       "   rating_denominator     name doggo floofer pupper puppo  \n",
       "0                  10  Phineas     0       0      0     0  \n",
       "1                  10    Tilly     0       0      0     0  \n",
       "2                  10   Archie     0       0      0     0  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# MERGE 2 dataframes!\n",
    "new_tweets_df = pd.merge(rt_tweets_sub, twitterDF, on='tweet_id')\n",
    "new_tweets_df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2167 entries, 0 to 2166\n",
      "Data columns (total 20 columns):\n",
      " #   Column                 Non-Null Count  Dtype              \n",
      "---  ------                 --------------  -----              \n",
      " 0   created_at             2167 non-null   datetime64[ns, UTC]\n",
      " 1   tweet_id               2167 non-null   int64              \n",
      " 2   full_text              2167 non-null   object             \n",
      " 3   display_text_range     2167 non-null   object             \n",
      " 4   retweet_count          2167 non-null   int64              \n",
      " 5   favorite_count         2167 non-null   int64              \n",
      " 6   user                   2167 non-null   object             \n",
      " 7   in_reply_to_status_id  78 non-null     float64            \n",
      " 8   in_reply_to_user_id    78 non-null     float64            \n",
      " 9   timestamp              2167 non-null   datetime64[ns, UTC]\n",
      " 10  source                 2167 non-null   object             \n",
      " 11  text                   2167 non-null   object             \n",
      " 12  expanded_urls          2109 non-null   object             \n",
      " 13  rating_numerator       2167 non-null   int64              \n",
      " 14  rating_denominator     2167 non-null   int64              \n",
      " 15  name                   2112 non-null   object             \n",
      " 16  doggo                  2167 non-null   object             \n",
      " 17  floofer                2167 non-null   object             \n",
      " 18  pupper                 2167 non-null   object             \n",
      " 19  puppo                  2167 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](2), float64(2), int64(5), object(11)\n",
      "memory usage: 355.5+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "new_tweets_df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MERGE newly merged dataframe and image_preds to get new_tweets_df2\n",
    "new_tweets_df2 = pd.merge(new_tweets_df, image_preds, on='tweet_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"save1\">New Dataframe saved to file</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# write new dataframe to file\n",
    "new_tweets_df2.to_csv(\"twitter_archive_master.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>bagel</td>\n",
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       "      <td>False</td>\n",
       "      <td>banana</td>\n",
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       "      <td>...</td>\n",
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       "      <td>Chihuahua</td>\n",
       "      <td>0.323581</td>\n",
       "      <td>True</td>\n",
       "      <td>Pekinese</td>\n",
       "      <td>0.090647</td>\n",
       "      <td>True</td>\n",
       "      <td>papillon</td>\n",
       "      <td>0.068957</td>\n",
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       "      <th>2</th>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>891815181378084864</td>\n",
       "      <td>This is Archie. He is a rare Norwegian Pouncin...</td>\n",
       "      <td>[0, 121]</td>\n",
       "      <td>3671</td>\n",
       "      <td>23034</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-31 00:18:03+00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>Chihuahua</td>\n",
       "      <td>0.716012</td>\n",
       "      <td>True</td>\n",
       "      <td>malamute</td>\n",
       "      <td>0.078253</td>\n",
       "      <td>True</td>\n",
       "      <td>kelpie</td>\n",
       "      <td>0.031379</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-30 15:58:51+00:00</td>\n",
       "      <td>891689557279858688</td>\n",
       "      <td>This is Darla. She commenced a snooze mid meal...</td>\n",
       "      <td>[0, 79]</td>\n",
       "      <td>7649</td>\n",
       "      <td>38689</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-30 15:58:51+00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>paper_towel</td>\n",
       "      <td>0.170278</td>\n",
       "      <td>False</td>\n",
       "      <td>Labrador_retriever</td>\n",
       "      <td>0.168086</td>\n",
       "      <td>True</td>\n",
       "      <td>spatula</td>\n",
       "      <td>0.040836</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-07-29 16:00:24+00:00</td>\n",
       "      <td>891327558926688256</td>\n",
       "      <td>This is Franklin. He would like you to stop ca...</td>\n",
       "      <td>[0, 138]</td>\n",
       "      <td>8249</td>\n",
       "      <td>36965</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-29 16:00:24+00:00</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>basset</td>\n",
       "      <td>0.555712</td>\n",
       "      <td>True</td>\n",
       "      <td>English_springer</td>\n",
       "      <td>0.225770</td>\n",
       "      <td>True</td>\n",
       "      <td>German_short-haired_pointer</td>\n",
       "      <td>0.175219</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 created_at            tweet_id  \\\n",
       "0 2017-08-01 16:23:56+00:00  892420643555336193   \n",
       "1 2017-08-01 00:17:27+00:00  892177421306343426   \n",
       "2 2017-07-31 00:18:03+00:00  891815181378084864   \n",
       "3 2017-07-30 15:58:51+00:00  891689557279858688   \n",
       "4 2017-07-29 16:00:24+00:00  891327558926688256   \n",
       "\n",
       "                                           full_text display_text_range  \\\n",
       "0  This is Phineas. He's a mystical boy. Only eve...            [0, 85]   \n",
       "1  This is Tilly. She's just checking pup on you....           [0, 138]   \n",
       "2  This is Archie. He is a rare Norwegian Pouncin...           [0, 121]   \n",
       "3  This is Darla. She commenced a snooze mid meal...            [0, 79]   \n",
       "4  This is Franklin. He would like you to stop ca...           [0, 138]   \n",
       "\n",
       "   retweet_count  favorite_count  \\\n",
       "0           7477           35388   \n",
       "1           5549           30638   \n",
       "2           3671           23034   \n",
       "3           7649           38689   \n",
       "4           8249           36965   \n",
       "\n",
       "                                                user  in_reply_to_status_id  \\\n",
       "0  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "1  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "2  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "3  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "4  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "\n",
       "   in_reply_to_user_id                 timestamp  ... img_num           p1  \\\n",
       "0                  NaN 2017-08-01 16:23:56+00:00  ...       1       orange   \n",
       "1                  NaN 2017-08-01 00:17:27+00:00  ...       1    Chihuahua   \n",
       "2                  NaN 2017-07-31 00:18:03+00:00  ...       1    Chihuahua   \n",
       "3                  NaN 2017-07-30 15:58:51+00:00  ...       1  paper_towel   \n",
       "4                  NaN 2017-07-29 16:00:24+00:00  ...       2       basset   \n",
       "\n",
       "    p1_conf  p1_dog                  p2   p2_conf p2_dog  \\\n",
       "0  0.097049   False               bagel  0.085851  False   \n",
       "1  0.323581    True            Pekinese  0.090647   True   \n",
       "2  0.716012    True            malamute  0.078253   True   \n",
       "3  0.170278   False  Labrador_retriever  0.168086   True   \n",
       "4  0.555712    True    English_springer  0.225770   True   \n",
       "\n",
       "                            p3   p3_conf p3_dog  \n",
       "0                       banana  0.076110  False  \n",
       "1                     papillon  0.068957   True  \n",
       "2                       kelpie  0.031379   True  \n",
       "3                      spatula  0.040836  False  \n",
       "4  German_short-haired_pointer  0.175219   True  \n",
       "\n",
       "[5 rows x 31 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "new_tweets_df2.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1986"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "# how many names are blank(null)\n",
    "new_tweets_df2.name.isnull().count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://twitter.com/dog_rates/status/772581559778025472/photo/1,https://twitter.com/dog_rates/status/772581559778025472/photo/1,https://twitter.com/dog_rates/status/772581559778025472/photo/1'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data exploration\n",
    "new_tweets_df2.loc[576,'expanded_urls']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 1986 entries, 0 to 1985\n",
      "Data columns (total 31 columns):\n",
      " #   Column                 Non-Null Count  Dtype              \n",
      "---  ------                 --------------  -----              \n",
      " 0   created_at             1986 non-null   datetime64[ns, UTC]\n",
      " 1   tweet_id               1986 non-null   int64              \n",
      " 2   full_text              1986 non-null   object             \n",
      " 3   display_text_range     1986 non-null   object             \n",
      " 4   retweet_count          1986 non-null   int64              \n",
      " 5   favorite_count         1986 non-null   int64              \n",
      " 6   user                   1986 non-null   object             \n",
      " 7   in_reply_to_status_id  23 non-null     float64            \n",
      " 8   in_reply_to_user_id    23 non-null     float64            \n",
      " 9   timestamp              1986 non-null   datetime64[ns, UTC]\n",
      " 10  source                 1986 non-null   object             \n",
      " 11  text                   1986 non-null   object             \n",
      " 12  expanded_urls          1986 non-null   object             \n",
      " 13  rating_numerator       1986 non-null   int64              \n",
      " 14  rating_denominator     1986 non-null   int64              \n",
      " 15  name                   1931 non-null   object             \n",
      " 16  doggo                  1986 non-null   object             \n",
      " 17  floofer                1986 non-null   object             \n",
      " 18  pupper                 1986 non-null   object             \n",
      " 19  puppo                  1986 non-null   object             \n",
      " 20  jpg_url                1986 non-null   object             \n",
      " 21  img_num                1986 non-null   int64              \n",
      " 22  p1                     1986 non-null   object             \n",
      " 23  p1_conf                1986 non-null   float64            \n",
      " 24  p1_dog                 1986 non-null   bool               \n",
      " 25  p2                     1986 non-null   object             \n",
      " 26  p2_conf                1986 non-null   float64            \n",
      " 27  p2_dog                 1986 non-null   bool               \n",
      " 28  p3                     1986 non-null   object             \n",
      " 29  p3_conf                1986 non-null   float64            \n",
      " 30  p3_dog                 1986 non-null   bool               \n",
      "dtypes: bool(3), datetime64[ns, UTC](2), float64(5), int64(6), object(15)\n",
      "memory usage: 535.8+ KB\n"
     ]
    }
   ],
   "source": [
    "# data exploration\n",
    "new_tweets_df2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "highest_accuracy = new_tweets_df2.query(\"p1_dog == true and \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "Afghan_hound            3\n",
       "African_crocodile       1\n",
       "African_grey            1\n",
       "African_hunting_dog     1\n",
       "Airedale               12\n",
       "                       ..\n",
       "wombat                  4\n",
       "wood_rabbit             3\n",
       "wooden_spoon            1\n",
       "wool                    2\n",
       "zebra                   1\n",
       "Length: 374, dtype: int64"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# count the number of times a name was used for pup. New series, count_by_name, is sorted by the index which is alphabetically \n",
    "# sorted by default \n",
    "\n",
    "count_by_name = new_tweets_df2.groupby('p1').size()\n",
    "count_by_name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "golden_retriever                  139\n",
       "Labrador_retriever                 93\n",
       "Pembroke                           87\n",
       "Chihuahua                          79\n",
       "pug                                54\n",
       "chow                               41\n",
       "Samoyed                            39\n",
       "Pomeranian                         38\n",
       "toy_poodle                         37\n",
       "malamute                           29\n",
       "cocker_spaniel                     27\n",
       "French_bulldog                     25\n",
       "Chesapeake_Bay_retriever           23\n",
       "miniature_pinscher                 22\n",
       "seat_belt                          21\n",
       "Siberian_husky                     20\n",
       "German_shepherd                    20\n",
       "Staffordshire_bullterrier          18\n",
       "Maltese_dog                        18\n",
       "Eskimo_dog                         18\n",
       "teddy                              18\n",
       "Shetland_sheepdog                  18\n",
       "beagle                             17\n",
       "Rottweiler                         17\n",
       "Shih-Tzu                           17\n",
       "Cardigan                           17\n",
       "kuvasz                             16\n",
       "Lakeland_terrier                   16\n",
       "Italian_greyhound                  16\n",
       "web_site                           15\n",
       "Great_Pyrenees                     14\n",
       "West_Highland_white_terrier        14\n",
       "vizsla                             13\n",
       "Pekinese                           13\n",
       "basset                             13\n",
       "Border_collie                      12\n",
       "dalmatian                          12\n",
       "Old_English_sheepdog               12\n",
       "American_Staffordshire_terrier     12\n",
       "Airedale                           12\n",
       "dtype: int64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# see top 40 most predicted names \n",
    "count_by_name.sort_values(ascending=False)[0:40]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p2\n",
       "Boston_bull                 1\n",
       "Chesapeake_Bay_retriever    1\n",
       "Eskimo_dog                  1\n",
       "Great_Dane                  1\n",
       "Labrador_retriever          2\n",
       "Lakeland_terrier            1\n",
       "Shih-Tzu                    1\n",
       "chow                        1\n",
       "golden_retriever            4\n",
       "ice_bear                    1\n",
       "miniature_pinscher          3\n",
       "sunglasses                  2\n",
       "toy_poodle                  1\n",
       "toy_terrier                 1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Investigate why 'seat_belt' is the 15th most predicted name for a dog picture. These are all tweets who's value equals\n",
    "# 'seat_belt' and groupby the 2nd predicted value\n",
    "\n",
    "new_tweets_df2.query(\"p1 == 'seat_belt'\").groupby('p2').size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "golden_retriever      139\n",
       "Labrador_retriever     93\n",
       "Pembroke               87\n",
       "Chihuahua              79\n",
       "pug                    54\n",
       "chow                   41\n",
       "Samoyed                39\n",
       "Pomeranian             38\n",
       "toy_poodle             37\n",
       "malamute               29\n",
       "Name: p1_conf, dtype: int64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new series of the top 10 names used for pups\n",
    "\n",
    "top10_names = count_by_name.sort_values(ascending=False).head(10)\n",
    "top10_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['golden_retriever', 'Labrador_retriever', 'Pembroke', 'Chihuahua',\n",
       "       'pug', 'chow', 'Samoyed', 'Pomeranian', 'toy_poodle', 'malamute'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top10_names.index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "lines_to_next_cell": 2
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([139,  93,  87,  79,  54,  41,  39,  38,  37,  29], dtype=int64)"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top10_val_array = top10_names.values\n",
    "top10_val_array"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"vis1\"> Horizontal Bar Chart to visualize the top 10 breeds represented during the timeframe </a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Horizontal Bar Chart to visualize the top 10 breeds represented during the timeframe\n",
    "\n",
    "# Fixing random state for reproducibility\n",
    "np.random.seed(19680801)\n",
    "\n",
    "\n",
    "plt.rcdefaults()\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "names = top10_names.index.values \n",
    "\n",
    "y_pos = np.arange(len(names))\n",
    "\n",
    "performance = top10_names.values\n",
    "error = np.random.rand(len(names))\n",
    "\n",
    "ax.barh(y_pos, performance, xerr=error, align='center')\n",
    "ax.set_yticks(y_pos)\n",
    "ax.set_yticklabels(names)\n",
    "ax.invert_yaxis()  # labels read top-to-bottom\n",
    "ax.set_xlabel('Dog Breeds (predicted) Count ')\n",
    "ax.set_ylabel('Predicted Breeds')\n",
    "ax.set_title('WeRateDogs Dog Breeds represented (top 10)')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>created_at</th>\n",
       "      <th>tweet_id</th>\n",
       "      <th>full_text</th>\n",
       "      <th>display_text_range</th>\n",
       "      <th>retweet_count</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>user</th>\n",
       "      <th>in_reply_to_status_id</th>\n",
       "      <th>in_reply_to_user_id</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>2017-01-24 17:04:50+00:00</td>\n",
       "      <td>823939628516474880</td>\n",
       "      <td>This is Cash. He's officially given pup on tod...</td>\n",
       "      <td>[0, 79]</td>\n",
       "      <td>2660</td>\n",
       "      <td>10508</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-24 17:04:50+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>2017-01-24 01:08:40+00:00</td>\n",
       "      <td>823699002998870016</td>\n",
       "      <td>This is Winston. The goggles make him a superh...</td>\n",
       "      <td>[0, 135]</td>\n",
       "      <td>2481</td>\n",
       "      <td>13827</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-24 01:08:40+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>2017-01-23 17:20:14+00:00</td>\n",
       "      <td>823581115634085888</td>\n",
       "      <td>This is Crawford. He's quite h*ckin good at th...</td>\n",
       "      <td>[0, 106]</td>\n",
       "      <td>2590</td>\n",
       "      <td>12889</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-23 17:20:14+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>2017-01-23 00:13:17+00:00</td>\n",
       "      <td>823322678127919110</td>\n",
       "      <td>This is Wyatt. He's got the fastest paws in th...</td>\n",
       "      <td>[0, 106]</td>\n",
       "      <td>3954</td>\n",
       "      <td>15570</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-23 00:13:17+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>2017-01-22 01:12:59+00:00</td>\n",
       "      <td>822975315408461824</td>\n",
       "      <td>This is Albus. He's soaked as h*ck. Seems to h...</td>\n",
       "      <td>[0, 118]</td>\n",
       "      <td>3390</td>\n",
       "      <td>17166</td>\n",
       "      <td>{'id': 4196983835, 'id_str': '4196983835', 'na...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-01-22 01:12:59+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   created_at            tweet_id  \\\n",
       "300 2017-01-24 17:04:50+00:00  823939628516474880   \n",
       "301 2017-01-24 01:08:40+00:00  823699002998870016   \n",
       "302 2017-01-23 17:20:14+00:00  823581115634085888   \n",
       "303 2017-01-23 00:13:17+00:00  823322678127919110   \n",
       "304 2017-01-22 01:12:59+00:00  822975315408461824   \n",
       "\n",
       "                                             full_text display_text_range  \\\n",
       "300  This is Cash. He's officially given pup on tod...            [0, 79]   \n",
       "301  This is Winston. The goggles make him a superh...           [0, 135]   \n",
       "302  This is Crawford. He's quite h*ckin good at th...           [0, 106]   \n",
       "303  This is Wyatt. He's got the fastest paws in th...           [0, 106]   \n",
       "304  This is Albus. He's soaked as h*ck. Seems to h...           [0, 118]   \n",
       "\n",
       "     retweet_count  favorite_count  \\\n",
       "300           2660           10508   \n",
       "301           2481           13827   \n",
       "302           2590           12889   \n",
       "303           3954           15570   \n",
       "304           3390           17166   \n",
       "\n",
       "                                                  user  in_reply_to_status_id  \\\n",
       "300  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "301  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "302  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "303  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "304  {'id': 4196983835, 'id_str': '4196983835', 'na...                    NaN   \n",
       "\n",
       "     in_reply_to_user_id                 timestamp  \n",
       "300                  NaN 2017-01-24 17:04:50+00:00  \n",
       "301                  NaN 2017-01-24 01:08:40+00:00  \n",
       "302                  NaN 2017-01-23 17:20:14+00:00  \n",
       "303                  NaN 2017-01-23 00:13:17+00:00  \n",
       "304                  NaN 2017-01-22 01:12:59+00:00  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Exploration\n",
    "new_tweets_df2.iloc[300:305,0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>expanded_urls</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>name</th>\n",
       "      <th>doggo</th>\n",
       "      <th>floofer</th>\n",
       "      <th>pupper</th>\n",
       "      <th>puppo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>300</th>\n",
       "      <td>This is Cash. He's officially given pup on tod...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/823939628...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Cash</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>301</th>\n",
       "      <td>This is Winston. The goggles make him a superh...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/823699002...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Winston</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302</th>\n",
       "      <td>This is Crawford. He's quite h*ckin good at th...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/823581115...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Crawford</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>303</th>\n",
       "      <td>This is Wyatt. He's got the fastest paws in th...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/823322678...</td>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>Wyatt</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>304</th>\n",
       "      <td>This is Albus. He's soaked as h*ck. Seems to h...</td>\n",
       "      <td>https://twitter.com/dog_rates/status/822975315...</td>\n",
       "      <td>12</td>\n",
       "      <td>10</td>\n",
       "      <td>Albus</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  text  \\\n",
       "300  This is Cash. He's officially given pup on tod...   \n",
       "301  This is Winston. The goggles make him a superh...   \n",
       "302  This is Crawford. He's quite h*ckin good at th...   \n",
       "303  This is Wyatt. He's got the fastest paws in th...   \n",
       "304  This is Albus. He's soaked as h*ck. Seems to h...   \n",
       "\n",
       "                                         expanded_urls  rating_numerator  \\\n",
       "300  https://twitter.com/dog_rates/status/823939628...                12   \n",
       "301  https://twitter.com/dog_rates/status/823699002...                12   \n",
       "302  https://twitter.com/dog_rates/status/823581115...                11   \n",
       "303  https://twitter.com/dog_rates/status/823322678...                11   \n",
       "304  https://twitter.com/dog_rates/status/822975315...                12   \n",
       "\n",
       "     rating_denominator      name doggo floofer pupper puppo  \n",
       "300                  10      Cash     0       0      0     0  \n",
       "301                  10   Winston     0       0      0     0  \n",
       "302                  10  Crawford     0       0      0     0  \n",
       "303                  10     Wyatt     0       0      0     0  \n",
       "304                  10     Albus     0       0      0     0  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Exploration\n",
    "new_tweets_df2.iloc[300:305,11:20]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"prog1\">Programmatic Assessment</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "doggo      0.036757\n",
       "floofer    0.004028\n",
       "pupper     0.106747\n",
       "puppo      0.011581\n",
       "dtype: float64"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Percentages that dog was catagorized affectionately\n",
    "## Averages of doggo, floofer, pupper, & puppo. Essentially, how often have these been designated\n",
    "\n",
    "## This means that 'doggo' was used to describe a pup 3.6% of the time\n",
    "\n",
    "desig = ['doggo', 'floofer', 'pupper', 'puppo']\n",
    "\n",
    "#new_tweets_df2.doggo.mean()\n",
    "\n",
    "new_tweets_df2[desig].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "None           546\n",
       "Oliver          10\n",
       "Cooper          10\n",
       "Charlie         10\n",
       "Tucker           9\n",
       "              ... \n",
       "Shakespeare      1\n",
       "Murphy           1\n",
       "Timofy           1\n",
       "Bradley          1\n",
       "Daniel           1\n",
       "Name: name, Length: 933, dtype: int64"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Owner named their dog this index the value number of times. There were a lot of missing values here\n",
    "## Data Exploration \n",
    "## Names most used\n",
    "\n",
    "new_tweets_df2.name.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "top10_names_used = list(top10_names.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['golden_retriever',\n",
       " 'Labrador_retriever',\n",
       " 'Pembroke',\n",
       " 'Chihuahua',\n",
       " 'pug',\n",
       " 'chow',\n",
       " 'Samoyed',\n",
       " 'Pomeranian',\n",
       " 'toy_poodle',\n",
       " 'malamute']"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newtop10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)\n",
    "\n",
    "### <a name=\"prog2\">More Programmatic Assessment</a> "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghan_hound</th>\n",
       "      <td>0.433959</td>\n",
       "      <td>9.666667</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15432.00</td>\n",
       "      <td>5072.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_crocodile</th>\n",
       "      <td>0.330625</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>864.00</td>\n",
       "      <td>230.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_grey</th>\n",
       "      <td>0.270468</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4729.00</td>\n",
       "      <td>1094.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_hunting_dog</th>\n",
       "      <td>0.733025</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1542.00</td>\n",
       "      <td>1021.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Airedale</th>\n",
       "      <td>0.583771</td>\n",
       "      <td>9.833333</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4716.75</td>\n",
       "      <td>1190.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American_Staffordshire_terrier</th>\n",
       "      <td>0.636330</td>\n",
       "      <td>10.833333</td>\n",
       "      <td>10.0</td>\n",
       "      <td>5562.50</td>\n",
       "      <td>1606.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American_black_bear</th>\n",
       "      <td>0.219166</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4362.00</td>\n",
       "      <td>1120.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angora</th>\n",
       "      <td>0.571526</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>42585.50</td>\n",
       "      <td>14058.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Appenzeller</th>\n",
       "      <td>0.503665</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6553.00</td>\n",
       "      <td>1227.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arabian_camel</th>\n",
       "      <td>0.682931</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>37607.50</td>\n",
       "      <td>17424.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 p1_conf  rating_numerator  \\\n",
       "p1                                                           \n",
       "Afghan_hound                    0.433959          9.666667   \n",
       "African_crocodile               0.330625         10.000000   \n",
       "African_grey                    0.270468         11.000000   \n",
       "African_hunting_dog             0.733025          8.000000   \n",
       "Airedale                        0.583771          9.833333   \n",
       "American_Staffordshire_terrier  0.636330         10.833333   \n",
       "American_black_bear             0.219166          8.000000   \n",
       "Angora                          0.571526          7.000000   \n",
       "Appenzeller                     0.503665         11.000000   \n",
       "Arabian_camel                   0.682931         10.000000   \n",
       "\n",
       "                                rating_denominator  favorite_count  \\\n",
       "p1                                                                   \n",
       "Afghan_hound                                  10.0        15432.00   \n",
       "African_crocodile                             10.0          864.00   \n",
       "African_grey                                  10.0         4729.00   \n",
       "African_hunting_dog                           10.0         1542.00   \n",
       "Airedale                                      10.0         4716.75   \n",
       "American_Staffordshire_terrier                10.0         5562.50   \n",
       "American_black_bear                           10.0         4362.00   \n",
       "Angora                                        10.0        42585.50   \n",
       "Appenzeller                                   10.0         6553.00   \n",
       "Arabian_camel                                 10.0        37607.50   \n",
       "\n",
       "                                retweet_count  \n",
       "p1                                             \n",
       "Afghan_hound                      5072.333333  \n",
       "African_crocodile                  230.000000  \n",
       "African_grey                      1094.000000  \n",
       "African_hunting_dog               1021.000000  \n",
       "Airedale                          1190.666667  \n",
       "American_Staffordshire_terrier    1606.500000  \n",
       "American_black_bear               1120.000000  \n",
       "Angora                           14058.000000  \n",
       "Appenzeller                       1227.500000  \n",
       "Arabian_camel                    17424.000000  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Create grouping of dataframe on the first predicted name, p1, & obtained the mean of specific data points\n",
    "\n",
    "# This one provides appropriate columns but it correctly displayed the resulting dataframe in p1 alphabetic order\n",
    "# which is not statistically significant\n",
    "\n",
    "name_by_avgs = new_tweets_df2.groupby(\"p1\")[['p1_conf','rating_numerator','rating_denominator','favorite_count',\n",
    "                                             'retweet_count']].mean()\n",
    "#Actually, you just need to pull out the rows you want, top10names, from the name_by_avgs. It's just sorted alphabetically\n",
    "#name_by_avgs = new_tweets_df2.groupby(new_tweets_df2[newtop10])[['p1_conf','rating_numerator','rating_denominator','doggo','floofer',\n",
    "#                                                 'pupper','puppo','favorite_count','retweet_count']].mean()\n",
    "\n",
    "\n",
    "name_by_avgs.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "Arabian_camel    17424.0\n",
       "conch            17304.0\n",
       "upright          15837.0\n",
       "bubble           14887.5\n",
       "gondola          14345.5\n",
       "Angora           14058.0\n",
       "beaver           13907.0\n",
       "laptop           13038.0\n",
       "prison           12646.5\n",
       "revolver         12633.0\n",
       "Name: retweet_count, dtype: float64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the highest average of retweets by predicted names.\n",
    "p1_retweets = name_by_avgs.retweet_count.sort_values(ascending=False)\n",
    "p1_retweets.head(10)\n",
    "\n",
    "# The results indicate that tweets with pictures that are predicted as an \"Arabian_camel\" had an average retweet count of 17,424\n",
    "# retweets. This insight says more about the neural network results and it's accuracy than the retweet specifics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>p1_conf</th>\n",
       "      <th>rating_numerator</th>\n",
       "      <th>rating_denominator</th>\n",
       "      <th>favorite_count</th>\n",
       "      <th>retweet_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p1</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>golden_retriever</th>\n",
       "      <td>0.721001</td>\n",
       "      <td>13.208633</td>\n",
       "      <td>11.424460</td>\n",
       "      <td>11135.107914</td>\n",
       "      <td>3126.431655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Labrador_retriever</th>\n",
       "      <td>0.652322</td>\n",
       "      <td>13.924731</td>\n",
       "      <td>12.580645</td>\n",
       "      <td>10439.086022</td>\n",
       "      <td>3269.989247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pembroke</th>\n",
       "      <td>0.714500</td>\n",
       "      <td>11.436782</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>10285.229885</td>\n",
       "      <td>2720.034483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chihuahua</th>\n",
       "      <td>0.588905</td>\n",
       "      <td>10.708861</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7962.835443</td>\n",
       "      <td>2466.367089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pug</th>\n",
       "      <td>0.759223</td>\n",
       "      <td>10.240741</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>5281.370370</td>\n",
       "      <td>1554.740741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chow</th>\n",
       "      <td>0.615648</td>\n",
       "      <td>11.609756</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9048.634146</td>\n",
       "      <td>2474.585366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Samoyed</th>\n",
       "      <td>0.740719</td>\n",
       "      <td>11.743590</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>12032.538462</td>\n",
       "      <td>3848.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pomeranian</th>\n",
       "      <td>0.743606</td>\n",
       "      <td>12.868421</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7310.131579</td>\n",
       "      <td>2439.236842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>toy_poodle</th>\n",
       "      <td>0.617548</td>\n",
       "      <td>11.081081</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>5748.837838</td>\n",
       "      <td>2055.270270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>malamute</th>\n",
       "      <td>0.589451</td>\n",
       "      <td>10.896552</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>7849.068966</td>\n",
       "      <td>2189.206897</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     p1_conf  rating_numerator  rating_denominator  \\\n",
       "p1                                                                   \n",
       "golden_retriever    0.721001         13.208633           11.424460   \n",
       "Labrador_retriever  0.652322         13.924731           12.580645   \n",
       "Pembroke            0.714500         11.436782           10.000000   \n",
       "Chihuahua           0.588905         10.708861           10.000000   \n",
       "pug                 0.759223         10.240741           10.000000   \n",
       "chow                0.615648         11.609756           10.000000   \n",
       "Samoyed             0.740719         11.743590           10.000000   \n",
       "Pomeranian          0.743606         12.868421           10.000000   \n",
       "toy_poodle          0.617548         11.081081           10.000000   \n",
       "malamute            0.589451         10.896552           10.000000   \n",
       "\n",
       "                    favorite_count  retweet_count  \n",
       "p1                                                 \n",
       "golden_retriever      11135.107914    3126.431655  \n",
       "Labrador_retriever    10439.086022    3269.989247  \n",
       "Pembroke              10285.229885    2720.034483  \n",
       "Chihuahua              7962.835443    2466.367089  \n",
       "pug                    5281.370370    1554.740741  \n",
       "chow                   9048.634146    2474.585366  \n",
       "Samoyed               12032.538462    3848.000000  \n",
       "Pomeranian             7310.131579    2439.236842  \n",
       "toy_poodle             5748.837838    2055.270270  \n",
       "malamute               7849.068966    2189.206897  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top10stats = name_by_avgs.loc[newtop10]\n",
    "top10stats.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "#name_by_avgs.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "#name_by_avgs.rename(columns= {'p1':'probable_name', 'p1_conf':'probability'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>favorite_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p1</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghan_hound</th>\n",
       "      <td>15432.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_crocodile</th>\n",
       "      <td>864.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_grey</th>\n",
       "      <td>4729.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>African_hunting_dog</th>\n",
       "      <td>1542.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Airedale</th>\n",
       "      <td>4716.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wombat</th>\n",
       "      <td>6820.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wood_rabbit</th>\n",
       "      <td>2232.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wooden_spoon</th>\n",
       "      <td>14500.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wool</th>\n",
       "      <td>1672.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zebra</th>\n",
       "      <td>1353.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>374 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     favorite_count\n",
       "p1                                 \n",
       "Afghan_hound               15432.00\n",
       "African_crocodile            864.00\n",
       "African_grey                4729.00\n",
       "African_hunting_dog         1542.00\n",
       "Airedale                    4716.75\n",
       "...                             ...\n",
       "wombat                      6820.25\n",
       "wood_rabbit                 2232.00\n",
       "wooden_spoon               14500.00\n",
       "wool                        1672.50\n",
       "zebra                       1353.00\n",
       "\n",
       "[374 rows x 1 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "favorites_by_name = name_by_avgs.loc[:,['favorite_count']]\n",
    "favorites_by_name. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "laptop           60764.0\n",
       "conch            43257.0\n",
       "limousine        42614.0\n",
       "Angora           42585.5\n",
       "fountain         40894.0\n",
       "Arabian_camel    37607.5\n",
       "bubble           37330.5\n",
       "orange           35388.0\n",
       "beaver           34891.0\n",
       "prison           32107.5\n",
       "revolver         31876.0\n",
       "barbell          31806.0\n",
       "basketball       31668.0\n",
       "upright          30931.0\n",
       "pole             30150.0\n",
       "Name: favorite_count, dtype: float64"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top15_favorites = favorites_by_name.iloc[0:15,:]\n",
    "top15_favorites.t.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <a name=\"vis2\">Notable analysis from visual bar chart </a>\n",
    "\n",
    "### None of the top 15 favorited 'dog's' images were acturately identified as dogs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "# create sub\n",
    "favorites_by_name = name_by_avgs.loc[:,['favorite_count']]\n",
    "favorites_by_name.sort_values(by=['favorite_count'], ascending=False, inplace=True)\n",
    "# get top 15 of new subset to create visual from\n",
    "top15_favorites = favorites_by_name.iloc[0:15,:]\n",
    "group_names = top15_favorites.index\n",
    "group_data = top15_favorites.favorite_count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "fig, ax = plt.subplots(figsize=(6, 4))\n",
    "ax.barh(group_names, group_data)\n",
    "labels = ax.get_xticklabels()\n",
    "plt.setp(labels, rotation=45, horizontalalignment='right')\n",
    "ax.set(xlim=[-10000, 70000], xlabel='No. of favorited tweets', ylabel='Names (guessed by learning model)',\n",
    "       title='Top 15 Favorites (tweets), by probable name')\n",
    "\n",
    "plt.show;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[BACK TO TOP](#top)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "bow_tie                        451.500000\n",
       "microphone                     420.000000\n",
       "lakeside                       108.000000\n",
       "clumber                         27.000000\n",
       "soft-coated_wheaten_terrier     25.454545\n",
       "                                  ...    \n",
       "desktop_computer                10.000000\n",
       "dingo                           10.000000\n",
       "espresso                        10.000000\n",
       "four-poster                     10.000000\n",
       "African_crocodile               10.000000\n",
       "Name: rating_numerator, Length: 237, dtype: float64"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name_by_avgs.query(\"rating_numerator >= 10\").rating_numerator.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "p1\n",
       "bow_tie                        451.500000\n",
       "microphone                     420.000000\n",
       "lakeside                       108.000000\n",
       "clumber                         27.000000\n",
       "soft-coated_wheaten_terrier     25.454545\n",
       "                                  ...    \n",
       "scorpion                         2.000000\n",
       "maze                             2.000000\n",
       "electric_fan                     1.000000\n",
       "lacewing                         1.000000\n",
       "traffic_light                    0.000000\n",
       "Name: rating_numerator, Length: 374, dtype: float64"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name_by_avgs.rating_numerator.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "jupytext": {
   "formats": "ipynb,py:percent"
  },
  "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}