Data_visualisation_tool_YT.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "nbpresent": {
     "id": "5a2cf86b-2d2e-4166-9dbd-1c9dda2e675f"
    }
   },
   "source": [
    "**Title:** YouTube Visualization tool\n",
    "    \n",
    "**Author:** Ben Mainye\n",
    "\n",
    "**Date:** 18/6/2017"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "nbpresent": {
     "id": "70c05d78-33c5-418f-b43f-6218213ea32b"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "####  Introduction:\n",
    "\n",
    "I've met a couple of YouTubers who put out a variety of content. From Vlogs, to pranks, to sports, to games en cetera. In addition to this, these channels are also repeated. Meaning you find someone who does exactly what you do in their channel for example vlogs. Often times some people accumulate so many subscribers and the way they got that many subscribers could range from doing YouTube Creator Academy classes, posting content on reddit, collaboration with YouTubers doing well, making very interractive videos, constantly telling the viewer to subscribe everywhere -- the content creator does some of them. Could they be more apart from the one i pointed out embedded in the YouTube data in the analytics section? In this notebook we'll explore this possibility."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "nbpresent": {
     "id": "104177c8-e93c-44a5-be77-62f76b858753"
    }
   },
   "source": [
    "#### Data:\n",
    "\n",
    "We'll be working with my YouTube analytics data provided by YouTube. They're already line graphs which can be used to see progress -- they are not interractive but we can boost the interractivity and there doesn't seem to be an option to compare data with other channels. In contrast, [Social blade](https://socialblade.com) does inform users about various important things about Twitter, YouTube and instagram accounts but the graphs generated are not interractive. Therefore, we'll attempt to make one/more with the **Bokeh** library."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "nbpresent": {
     "id": "95c5def2-5651-4149-b5d8-e1e1421109fb"
    }
   },
   "source": [
    "#### Exploratory Data analysis:\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "e75e5d2d-c489-4371-9697-d5ce6b5ec151"
    }
   },
   "source": [
    "#### Importing and cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbpresent": {
     "id": "efe9e1a3-6572-437d-bfe9-e5a2cf34568e"
    },
    "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",
       "        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>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>card_teasers_shown</th>\n",
       "      <th>clicks_per_card_teaser_shown</th>\n",
       "      <th>...</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>watch_time_hours</th>\n",
       "      <th>channel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-03-30</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06-01</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-30</th>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-03</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-05</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            watch_time_minutes  views  average_view_duration  \\\n",
       "date                                                           \n",
       "2011-03-30                   0    1.0                    0.0   \n",
       "2011-06-01                   0    0.0                    0.0   \n",
       "2011-07-30                   0    2.0                    0.0   \n",
       "2011-08-03                   0    1.0                    0.0   \n",
       "2011-08-05                   0    1.0                    0.0   \n",
       "\n",
       "            average_percentage_viewed  card_clicks  cards_shown  \\\n",
       "date                                                              \n",
       "2011-03-30                        0.0          0.0          0.0   \n",
       "2011-06-01                        0.0          0.0          0.0   \n",
       "2011-07-30                        0.0          0.0          0.0   \n",
       "2011-08-03                        0.0          0.0          0.0   \n",
       "2011-08-05                        0.0          0.0          0.0   \n",
       "\n",
       "            clicks_per_card_shown  card_teaser_clicks  card_teasers_shown  \\\n",
       "date                                                                        \n",
       "2011-03-30                      0                 0.0                 0.0   \n",
       "2011-06-01                      0                 0.0                 0.0   \n",
       "2011-07-30                      0                 0.0                 0.0   \n",
       "2011-08-03                      0                 0.0                 0.0   \n",
       "2011-08-05                      0                 0.0                 0.0   \n",
       "\n",
       "            clicks_per_card_teaser_shown    ...     shares  comments  \\\n",
       "date                                        ...                        \n",
       "2011-03-30                           0.0    ...        0.0       0.0   \n",
       "2011-06-01                           0.0    ...        0.0       0.0   \n",
       "2011-07-30                           0.0    ...        0.0       0.0   \n",
       "2011-08-03                           0.0    ...        0.0       0.0   \n",
       "2011-08-05                           0.0    ...        0.0       0.0   \n",
       "\n",
       "            videos_in_playlists  videos_added_to_playlists  \\\n",
       "date                                                         \n",
       "2011-03-30                  0.0                        0.0   \n",
       "2011-06-01                  0.0                        0.0   \n",
       "2011-07-30                  0.0                        0.0   \n",
       "2011-08-03                  0.0                        0.0   \n",
       "2011-08-05                  0.0                        0.0   \n",
       "\n",
       "            videos_removed_from_playlists  subscribers  subscribers_gained  \\\n",
       "date                                                                         \n",
       "2011-03-30                            0.0          0.0                 0.0   \n",
       "2011-06-01                            0.0          0.0                 0.0   \n",
       "2011-07-30                            0.0          0.0                 0.0   \n",
       "2011-08-03                            0.0          0.0                 0.0   \n",
       "2011-08-05                            0.0          0.0                 0.0   \n",
       "\n",
       "            subscribers_lost  watch_time_hours   channel  \n",
       "date                                                      \n",
       "2011-03-30               0.0                 0  Sliceace  \n",
       "2011-06-01               0.0                 0  Sliceace  \n",
       "2011-07-30               0.0                 0  Sliceace  \n",
       "2011-08-03               0.0                 0  Sliceace  \n",
       "2011-08-05               0.0                 0  Sliceace  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import modules\n",
    "import pandas as pd\n",
    "\n",
    "# importing two interesting data sets\n",
    "# You could use import os module\n",
    "# os.path.join\n",
    "\n",
    "df = pd.read_csv(\"data/yt_date.csv\", parse_dates = True, index_col = \"date\")\n",
    "df2 = pd.read_csv(\"data/yt_date.csv\", parse_dates = True, index_col = \"date\")\n",
    "df1 = pd.read_csv(\"data/yt_date.csv\")\n",
    "df3 = pd.read_csv(\"data/exotic_yt_date.csv\")\n",
    "\n",
    "\n",
    "# Seeing if the import process worked out, sampling the dataframe\n",
    "df.head() # looks fine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "nbpresent": {
     "id": "3cdd2122-a254-462f-8640-27b95bbc1291"
    }
   },
   "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>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>card_teasers_shown</th>\n",
       "      <th>clicks_per_card_teaser_shown</th>\n",
       "      <th>...</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>watch_time_hours</th>\n",
       "      <th>channel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-03-30</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06-01</th>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-30</th>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-03</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-05</th>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            watch_time_minutes  views  average_view_duration  \\\n",
       "date                                                           \n",
       "2011-03-30                   0    1.0                    0.0   \n",
       "2011-06-01                   0    0.0                    0.0   \n",
       "2011-07-30                   0    2.0                    0.0   \n",
       "2011-08-03                   0    1.0                    0.0   \n",
       "2011-08-05                   0    1.0                    0.0   \n",
       "\n",
       "            average_percentage_viewed  card_clicks  cards_shown  \\\n",
       "date                                                              \n",
       "2011-03-30                        0.0          0.0          0.0   \n",
       "2011-06-01                        0.0          0.0          0.0   \n",
       "2011-07-30                        0.0          0.0          0.0   \n",
       "2011-08-03                        0.0          0.0          0.0   \n",
       "2011-08-05                        0.0          0.0          0.0   \n",
       "\n",
       "            clicks_per_card_shown  card_teaser_clicks  card_teasers_shown  \\\n",
       "date                                                                        \n",
       "2011-03-30                      0                 0.0                 0.0   \n",
       "2011-06-01                      0                 0.0                 0.0   \n",
       "2011-07-30                      0                 0.0                 0.0   \n",
       "2011-08-03                      0                 0.0                 0.0   \n",
       "2011-08-05                      0                 0.0                 0.0   \n",
       "\n",
       "            clicks_per_card_teaser_shown    ...     shares  comments  \\\n",
       "date                                        ...                        \n",
       "2011-03-30                           0.0    ...        0.0       0.0   \n",
       "2011-06-01                           0.0    ...        0.0       0.0   \n",
       "2011-07-30                           0.0    ...        0.0       0.0   \n",
       "2011-08-03                           0.0    ...        0.0       0.0   \n",
       "2011-08-05                           0.0    ...        0.0       0.0   \n",
       "\n",
       "            videos_in_playlists  videos_added_to_playlists  \\\n",
       "date                                                         \n",
       "2011-03-30                  0.0                        0.0   \n",
       "2011-06-01                  0.0                        0.0   \n",
       "2011-07-30                  0.0                        0.0   \n",
       "2011-08-03                  0.0                        0.0   \n",
       "2011-08-05                  0.0                        0.0   \n",
       "\n",
       "            videos_removed_from_playlists  subscribers  subscribers_gained  \\\n",
       "date                                                                         \n",
       "2011-03-30                            0.0          0.0                 0.0   \n",
       "2011-06-01                            0.0          0.0                 0.0   \n",
       "2011-07-30                            0.0          0.0                 0.0   \n",
       "2011-08-03                            0.0          0.0                 0.0   \n",
       "2011-08-05                            0.0          0.0                 0.0   \n",
       "\n",
       "            subscribers_lost  watch_time_hours   channel  \n",
       "date                                                      \n",
       "2011-03-30               0.0                 0  Sliceace  \n",
       "2011-06-01               0.0                 0  Sliceace  \n",
       "2011-07-30               0.0                 0  Sliceace  \n",
       "2011-08-03               0.0                 0  Sliceace  \n",
       "2011-08-05               0.0                 0  Sliceace  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.head() # looks fine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "nbpresent": {
     "id": "796795b3-0d8c-408d-a351-500f0e488f02"
    }
   },
   "outputs": [],
   "source": [
    "df1.head()\n",
    "df1['channel'] = df1['channel'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "nbpresent": {
     "id": "0ea32e55-5c67-4aaa-9398-ff49db6c18e4"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>youtube_red_watch_time_minutes</th>\n",
       "      <th>youtube_red_views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>...</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>watch_time_hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013-04-16</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013-04-18</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>57.16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013-04-26</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>51.02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013-04-30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013-05-03</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>24.92</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 54 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  watch_time_minutes  views  youtube_red_watch_time_minutes  \\\n",
       "0  2013-04-16                   0      1                               0   \n",
       "1  2013-04-18                   2      1                               0   \n",
       "2  2013-04-26                   3      2                               0   \n",
       "3  2013-04-30                   0      0                               0   \n",
       "4  2013-05-03                   1      1                               0   \n",
       "\n",
       "   youtube_red_views  average_view_duration  card_clicks  cards_shown  \\\n",
       "0                  0                    0.0            0            0   \n",
       "1                  0                    1.8            0            0   \n",
       "2                  0                    1.6            0            0   \n",
       "3                  0                    0.0            0            0   \n",
       "4                  0                    0.8            0            0   \n",
       "\n",
       "   clicks_per_card_shown  card_teaser_clicks        ...         shares  \\\n",
       "0                    0.0                   0        ...              0   \n",
       "1                    0.0                   0        ...              0   \n",
       "2                    0.0                   0        ...              0   \n",
       "3                    0.0                   0        ...              0   \n",
       "4                    0.0                   0        ...              0   \n",
       "\n",
       "   comments  videos_in_playlists  videos_added_to_playlists  \\\n",
       "0         0                    0                          0   \n",
       "1         0                    0                          0   \n",
       "2         0                    0                          0   \n",
       "3         0                    0                          0   \n",
       "4         0                    0                          0   \n",
       "\n",
       "   videos_removed_from_playlists  subscribers  subscribers_gained  \\\n",
       "0                              0            0                   0   \n",
       "1                              0            0                   0   \n",
       "2                              0            5                   5   \n",
       "3                              0            1                   1   \n",
       "4                              0            1                   1   \n",
       "\n",
       "   subscribers_lost  average_percentage_viewed  watch_time_hours  \n",
       "0                 0                       0.00                 0  \n",
       "1                 0                      57.16                 0  \n",
       "2                 0                      51.02                 0  \n",
       "3                 0                       0.00                 0  \n",
       "4                 0                      24.92                 0  \n",
       "\n",
       "[5 rows x 54 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "nbpresent": {
     "id": "5140f5a4-46f7-4a30-929b-af4ced9c41ab"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 573 entries, 2011-03-30 to 2017-06-02\n",
      "Data columns (total 41 columns):\n",
      "watch_time_minutes                     573 non-null int64\n",
      "views                                  571 non-null float64\n",
      "average_view_duration                  573 non-null float64\n",
      "average_percentage_viewed              573 non-null float64\n",
      "card_clicks                            571 non-null float64\n",
      "cards_shown                            571 non-null float64\n",
      "clicks_per_card_shown                  573 non-null int64\n",
      "card_teaser_clicks                     571 non-null float64\n",
      "card_teasers_shown                     571 non-null float64\n",
      "clicks_per_card_teaser_shown           573 non-null float64\n",
      "end_screen_elements_shown              571 non-null float64\n",
      "end_screen_element_clicks              571 non-null float64\n",
      "clicks_per_end_screen_element_shown    573 non-null int64\n",
      "youtube_red_watch_time_minutes         573 non-null int64\n",
      "youtube_red_views                      571 non-null float64\n",
      "youtube_red_watch_time_hours           573 non-null int64\n",
      "annotation_clicks                      571 non-null float64\n",
      "clickable_annotations_shown            571 non-null float64\n",
      "annotation_click_through_rate          573 non-null int64\n",
      "annotation_closes                      571 non-null float64\n",
      "closable_annotations_shown             571 non-null float64\n",
      "annotation_close_rate                  573 non-null int64\n",
      "annotations_shown                      571 non-null float64\n",
      "videos_published                       34 non-null float64\n",
      "videos_added                           34 non-null float64\n",
      "likes                                  571 non-null float64\n",
      "likes_added                            571 non-null float64\n",
      "likes_removed                          571 non-null float64\n",
      "dislikes                               571 non-null float64\n",
      "dislikes_added                         571 non-null float64\n",
      "dislikes_removed                       571 non-null float64\n",
      "shares                                 571 non-null float64\n",
      "comments                               571 non-null float64\n",
      "videos_in_playlists                    571 non-null float64\n",
      "videos_added_to_playlists              571 non-null float64\n",
      "videos_removed_from_playlists          571 non-null float64\n",
      "subscribers                            571 non-null float64\n",
      "subscribers_gained                     571 non-null float64\n",
      "subscribers_lost                       571 non-null float64\n",
      "watch_time_hours                       573 non-null int64\n",
      "channel                                573 non-null object\n",
      "dtypes: float64(32), int64(8), object(1)\n",
      "memory usage: 188.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info() # getting more information about the dataset\n",
    "# the date column needs reformatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "nbpresent": {
     "id": "c38585ca-6cda-4afa-aa49-b936070e45f5"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 573 entries, 2011-03-30 to 2017-06-02\n",
      "Data columns (total 41 columns):\n",
      "watch_time_minutes                     573 non-null int64\n",
      "views                                  571 non-null float64\n",
      "average_view_duration                  573 non-null float64\n",
      "average_percentage_viewed              573 non-null float64\n",
      "card_clicks                            571 non-null float64\n",
      "cards_shown                            571 non-null float64\n",
      "clicks_per_card_shown                  573 non-null int64\n",
      "card_teaser_clicks                     571 non-null float64\n",
      "card_teasers_shown                     571 non-null float64\n",
      "clicks_per_card_teaser_shown           573 non-null float64\n",
      "end_screen_elements_shown              571 non-null float64\n",
      "end_screen_element_clicks              571 non-null float64\n",
      "clicks_per_end_screen_element_shown    573 non-null int64\n",
      "youtube_red_watch_time_minutes         573 non-null int64\n",
      "youtube_red_views                      571 non-null float64\n",
      "youtube_red_watch_time_hours           573 non-null int64\n",
      "annotation_clicks                      571 non-null float64\n",
      "clickable_annotations_shown            571 non-null float64\n",
      "annotation_click_through_rate          573 non-null int64\n",
      "annotation_closes                      571 non-null float64\n",
      "closable_annotations_shown             571 non-null float64\n",
      "annotation_close_rate                  573 non-null int64\n",
      "annotations_shown                      571 non-null float64\n",
      "videos_published                       34 non-null float64\n",
      "videos_added                           34 non-null float64\n",
      "likes                                  571 non-null float64\n",
      "likes_added                            571 non-null float64\n",
      "likes_removed                          571 non-null float64\n",
      "dislikes                               571 non-null float64\n",
      "dislikes_added                         571 non-null float64\n",
      "dislikes_removed                       571 non-null float64\n",
      "shares                                 571 non-null float64\n",
      "comments                               571 non-null float64\n",
      "videos_in_playlists                    571 non-null float64\n",
      "videos_added_to_playlists              571 non-null float64\n",
      "videos_removed_from_playlists          571 non-null float64\n",
      "subscribers                            571 non-null float64\n",
      "subscribers_gained                     571 non-null float64\n",
      "subscribers_lost                       571 non-null float64\n",
      "watch_time_hours                       573 non-null int64\n",
      "channel                                573 non-null object\n",
      "dtypes: float64(32), int64(8), object(1)\n",
      "memory usage: 188.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df2.info()\n",
    "# the date column needs reformatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "nbpresent": {
     "id": "80392431-bbd1-4dd6-9fd7-2bfe0cc2aea8"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1526 entries, 0 to 1525\n",
      "Data columns (total 54 columns):\n",
      "date                                         1526 non-null object\n",
      "watch_time_minutes                           1526 non-null int64\n",
      "views                                        1526 non-null int64\n",
      "youtube_red_watch_time_minutes               1526 non-null int64\n",
      "youtube_red_views                            1526 non-null int64\n",
      "average_view_duration                        1526 non-null float64\n",
      "card_clicks                                  1526 non-null int64\n",
      "cards_shown                                  1526 non-null int64\n",
      "clicks_per_card_shown                        1526 non-null float64\n",
      "card_teaser_clicks                           1526 non-null int64\n",
      "card_teasers_shown                           1526 non-null int64\n",
      "clicks_per_card_teaser_shown                 1526 non-null float64\n",
      "end_screen_elements_shown                    1526 non-null int64\n",
      "end_screen_element_clicks                    1526 non-null int64\n",
      "clicks_per_end_screen_element_shown          1526 non-null float64\n",
      "estimated_partner_revenue_usd                1526 non-null float64\n",
      "estimated_partner_ad_revenue_usd             1526 non-null float64\n",
      "estimated_partner_adsense_revenue_usd        1526 non-null float64\n",
      "estimated_partner_doubleclick_revenue_usd    1526 non-null float64\n",
      "partner_transaction_revenue_usd              1526 non-null float64\n",
      "transactions                                 1526 non-null int64\n",
      "partner_revenue_per_transaction_usd          1526 non-null float64\n",
      "estimated_monetized_playbacks                1526 non-null int64\n",
      "playback_based_cpm_usd                       1526 non-null float64\n",
      "ad_impressions                               1526 non-null int64\n",
      "cpm_usd                                      1526 non-null float64\n",
      "youtube_ad_revenue_usd                       1526 non-null float64\n",
      "youtube_red_partner_revenue_usd              1526 non-null float64\n",
      "youtube_red_watch_time_hours                 1526 non-null int64\n",
      "annotation_clicks                            1526 non-null int64\n",
      "clickable_annotations_shown                  1526 non-null int64\n",
      "annotation_click_through_rate                1526 non-null float64\n",
      "annotation_closes                            1526 non-null int64\n",
      "closable_annotations_shown                   1526 non-null int64\n",
      "annotation_close_rate                        1526 non-null float64\n",
      "annotations_shown                            1526 non-null int64\n",
      "videos_published                             363 non-null float64\n",
      "videos_added                                 363 non-null float64\n",
      "likes                                        1526 non-null int64\n",
      "likes_added                                  1526 non-null int64\n",
      "likes_removed                                1526 non-null int64\n",
      "dislikes                                     1526 non-null int64\n",
      "dislikes_added                               1526 non-null int64\n",
      "dislikes_removed                             1526 non-null int64\n",
      "shares                                       1526 non-null int64\n",
      "comments                                     1526 non-null int64\n",
      "videos_in_playlists                          1526 non-null int64\n",
      "videos_added_to_playlists                    1526 non-null int64\n",
      "videos_removed_from_playlists                1526 non-null int64\n",
      "subscribers                                  1526 non-null int64\n",
      "subscribers_gained                           1526 non-null int64\n",
      "subscribers_lost                             1526 non-null int64\n",
      "average_percentage_viewed                    1526 non-null float64\n",
      "watch_time_hours                             1526 non-null int64\n",
      "dtypes: float64(19), int64(34), object(1)\n",
      "memory usage: 643.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df3.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "nbpresent": {
     "id": "5d57017c-7472-4b80-9ed4-0ea6e3bd97a2"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['watch_time_minutes', 'views', 'average_view_duration',\n",
       "       'average_percentage_viewed', 'card_clicks', 'cards_shown',\n",
       "       'clicks_per_card_shown', 'card_teaser_clicks', 'card_teasers_shown',\n",
       "       'clicks_per_card_teaser_shown', 'end_screen_elements_shown',\n",
       "       'end_screen_element_clicks', 'clicks_per_end_screen_element_shown',\n",
       "       'youtube_red_watch_time_minutes', 'youtube_red_views',\n",
       "       'youtube_red_watch_time_hours', 'annotation_clicks',\n",
       "       'clickable_annotations_shown', 'annotation_click_through_rate',\n",
       "       'annotation_closes', 'closable_annotations_shown',\n",
       "       'annotation_close_rate', 'annotations_shown', 'videos_published',\n",
       "       'videos_added', 'likes', 'likes_added', 'likes_removed', 'dislikes',\n",
       "       'dislikes_added', 'dislikes_removed', 'shares', 'comments',\n",
       "       'videos_in_playlists', 'videos_added_to_playlists',\n",
       "       'videos_removed_from_playlists', 'subscribers', 'subscribers_gained',\n",
       "       'subscribers_lost', 'watch_time_hours', 'channel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns # the column labels are formatted correct, thanks YouTube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "nbpresent": {
     "id": "a237a1bc-7de0-448e-9805-aa4d339a6990"
    }
   },
   "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>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>card_teasers_shown</th>\n",
       "      <th>clicks_per_card_teaser_shown</th>\n",
       "      <th>...</th>\n",
       "      <th>dislikes_removed</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>watch_time_hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.499127</td>\n",
       "      <td>4.422067</td>\n",
       "      <td>0.930541</td>\n",
       "      <td>53.391955</td>\n",
       "      <td>0.003503</td>\n",
       "      <td>0.024518</td>\n",
       "      <td>0.174520</td>\n",
       "      <td>0.010508</td>\n",
       "      <td>0.490368</td>\n",
       "      <td>0.336161</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001751</td>\n",
       "      <td>0.115587</td>\n",
       "      <td>0.059545</td>\n",
       "      <td>0.045534</td>\n",
       "      <td>0.050788</td>\n",
       "      <td>0.005254</td>\n",
       "      <td>0.059545</td>\n",
       "      <td>0.073555</td>\n",
       "      <td>0.014011</td>\n",
       "      <td>0.012216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.289619</td>\n",
       "      <td>6.287733</td>\n",
       "      <td>0.612709</td>\n",
       "      <td>33.368099</td>\n",
       "      <td>0.059131</td>\n",
       "      <td>0.203723</td>\n",
       "      <td>2.951398</td>\n",
       "      <td>0.118002</td>\n",
       "      <td>1.474162</td>\n",
       "      <td>4.787228</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041849</td>\n",
       "      <td>0.533725</td>\n",
       "      <td>0.296102</td>\n",
       "      <td>0.267595</td>\n",
       "      <td>0.256587</td>\n",
       "      <td>0.072357</td>\n",
       "      <td>0.307724</td>\n",
       "      <td>0.310378</td>\n",
       "      <td>0.117637</td>\n",
       "      <td>0.124839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>29.270000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>51.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>74.320000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>102.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>280.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       watch_time_minutes       views  average_view_duration  \\\n",
       "count          573.000000  571.000000             573.000000   \n",
       "mean             4.499127    4.422067               0.930541   \n",
       "std              7.289619    6.287733               0.612709   \n",
       "min              0.000000    0.000000               0.000000   \n",
       "25%              1.000000    1.000000               0.600000   \n",
       "50%              3.000000    3.000000               0.900000   \n",
       "75%              5.000000    6.000000               1.200000   \n",
       "max            102.000000  110.000000               4.500000   \n",
       "\n",
       "       average_percentage_viewed  card_clicks  cards_shown  \\\n",
       "count                 573.000000   571.000000   571.000000   \n",
       "mean                   53.391955     0.003503     0.024518   \n",
       "std                    33.368099     0.059131     0.203723   \n",
       "min                     0.000000     0.000000     0.000000   \n",
       "25%                    29.270000     0.000000     0.000000   \n",
       "50%                    51.500000     0.000000     0.000000   \n",
       "75%                    74.320000     0.000000     0.000000   \n",
       "max                   280.250000     1.000000     2.000000   \n",
       "\n",
       "       clicks_per_card_shown  card_teaser_clicks  card_teasers_shown  \\\n",
       "count             573.000000          571.000000          571.000000   \n",
       "mean                0.174520            0.010508            0.490368   \n",
       "std                 2.951398            0.118002            1.474162   \n",
       "min                 0.000000            0.000000            0.000000   \n",
       "25%                 0.000000            0.000000            0.000000   \n",
       "50%                 0.000000            0.000000            0.000000   \n",
       "75%                 0.000000            0.000000            0.000000   \n",
       "max                50.000000            2.000000           22.000000   \n",
       "\n",
       "       clicks_per_card_teaser_shown        ...         dislikes_removed  \\\n",
       "count                    573.000000        ...               571.000000   \n",
       "mean                       0.336161        ...                 0.001751   \n",
       "std                        4.787228        ...                 0.041849   \n",
       "min                        0.000000        ...                 0.000000   \n",
       "25%                        0.000000        ...                 0.000000   \n",
       "50%                        0.000000        ...                 0.000000   \n",
       "75%                        0.000000        ...                 0.000000   \n",
       "max                      100.000000        ...                 1.000000   \n",
       "\n",
       "           shares    comments  videos_in_playlists  videos_added_to_playlists  \\\n",
       "count  571.000000  571.000000           571.000000                 571.000000   \n",
       "mean     0.115587    0.059545             0.045534                   0.050788   \n",
       "std      0.533725    0.296102             0.267595                   0.256587   \n",
       "min      0.000000    0.000000            -1.000000                   0.000000   \n",
       "25%      0.000000    0.000000             0.000000                   0.000000   \n",
       "50%      0.000000    0.000000             0.000000                   0.000000   \n",
       "75%      0.000000    0.000000             0.000000                   0.000000   \n",
       "max      6.000000    3.000000             3.000000                   3.000000   \n",
       "\n",
       "       videos_removed_from_playlists  subscribers  subscribers_gained  \\\n",
       "count                     571.000000   571.000000          571.000000   \n",
       "mean                        0.005254     0.059545            0.073555   \n",
       "std                         0.072357     0.307724            0.310378   \n",
       "min                         0.000000    -1.000000            0.000000   \n",
       "25%                         0.000000     0.000000            0.000000   \n",
       "50%                         0.000000     0.000000            0.000000   \n",
       "75%                         0.000000     0.000000            0.000000   \n",
       "max                         1.000000     3.000000            4.000000   \n",
       "\n",
       "       subscribers_lost  watch_time_hours  \n",
       "count        571.000000        573.000000  \n",
       "mean           0.014011          0.012216  \n",
       "std            0.117637          0.124839  \n",
       "min            0.000000          0.000000  \n",
       "25%            0.000000          0.000000  \n",
       "50%            0.000000          0.000000  \n",
       "75%            0.000000          0.000000  \n",
       "max            1.000000          2.000000  \n",
       "\n",
       "[8 rows x 40 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "nbpresent": {
     "id": "f3b9e8c5-4f33-441a-ae4d-5baee863561c"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 0.0    529\n",
       " 1.0     33\n",
       "-1.0      6\n",
       " 2.0      2\n",
       " 3.0      1\n",
       "Name: subscribers, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.subscribers.value_counts() \n",
    "# Viewers don't subscribe to the channel most 1 subscriber or lose one subscriber"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'They are 29 NaNs in the columms.'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# looks for missing data in the columns in this case 29 missing entries\n",
    "message1 = \"They are {} NaNs in the columms.\"\n",
    "message1.format(sum(df.isnull().any() == True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "nbpresent": {
     "id": "0d80c3ba-5a9b-438b-81bf-b3c1396fbc71"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['watch_time_minutes', 'views', 'average_view_duration',\n",
       "       'average_percentage_viewed', 'card_clicks', 'cards_shown',\n",
       "       'clicks_per_card_shown', 'card_teaser_clicks', 'card_teasers_shown',\n",
       "       'clicks_per_card_teaser_shown', 'end_screen_elements_shown',\n",
       "       'end_screen_element_clicks', 'clicks_per_end_screen_element_shown',\n",
       "       'youtube_red_watch_time_minutes', 'youtube_red_views',\n",
       "       'youtube_red_watch_time_hours', 'annotation_clicks',\n",
       "       'clickable_annotations_shown', 'annotation_click_through_rate',\n",
       "       'annotation_closes', 'closable_annotations_shown',\n",
       "       'annotation_close_rate', 'annotations_shown', 'videos_published',\n",
       "       'videos_added', 'likes', 'likes_added', 'likes_removed', 'dislikes',\n",
       "       'dislikes_added', 'dislikes_removed', 'shares', 'comments',\n",
       "       'videos_in_playlists', 'videos_added_to_playlists',\n",
       "       'videos_removed_from_playlists', 'subscribers', 'subscribers_gained',\n",
       "       'subscribers_lost', 'watch_time_hours', 'channel'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.columns # the column labels are formatted correct, thanks YouTube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "nbpresent": {
     "id": "50af902d-0730-4842-b725-f0c775a7d4e6"
    }
   },
   "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>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>card_teasers_shown</th>\n",
       "      <th>clicks_per_card_teaser_shown</th>\n",
       "      <th>...</th>\n",
       "      <th>dislikes_removed</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>watch_time_hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>571.000000</td>\n",
       "      <td>573.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.499127</td>\n",
       "      <td>4.422067</td>\n",
       "      <td>0.930541</td>\n",
       "      <td>53.391955</td>\n",
       "      <td>0.003503</td>\n",
       "      <td>0.024518</td>\n",
       "      <td>0.174520</td>\n",
       "      <td>0.010508</td>\n",
       "      <td>0.490368</td>\n",
       "      <td>0.336161</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001751</td>\n",
       "      <td>0.115587</td>\n",
       "      <td>0.059545</td>\n",
       "      <td>0.045534</td>\n",
       "      <td>0.050788</td>\n",
       "      <td>0.005254</td>\n",
       "      <td>0.059545</td>\n",
       "      <td>0.073555</td>\n",
       "      <td>0.014011</td>\n",
       "      <td>0.012216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>7.289619</td>\n",
       "      <td>6.287733</td>\n",
       "      <td>0.612709</td>\n",
       "      <td>33.368099</td>\n",
       "      <td>0.059131</td>\n",
       "      <td>0.203723</td>\n",
       "      <td>2.951398</td>\n",
       "      <td>0.118002</td>\n",
       "      <td>1.474162</td>\n",
       "      <td>4.787228</td>\n",
       "      <td>...</td>\n",
       "      <td>0.041849</td>\n",
       "      <td>0.533725</td>\n",
       "      <td>0.296102</td>\n",
       "      <td>0.267595</td>\n",
       "      <td>0.256587</td>\n",
       "      <td>0.072357</td>\n",
       "      <td>0.307724</td>\n",
       "      <td>0.310378</td>\n",
       "      <td>0.117637</td>\n",
       "      <td>0.124839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>29.270000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>51.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>74.320000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>102.000000</td>\n",
       "      <td>110.000000</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>280.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 40 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       watch_time_minutes       views  average_view_duration  \\\n",
       "count          573.000000  571.000000             573.000000   \n",
       "mean             4.499127    4.422067               0.930541   \n",
       "std              7.289619    6.287733               0.612709   \n",
       "min              0.000000    0.000000               0.000000   \n",
       "25%              1.000000    1.000000               0.600000   \n",
       "50%              3.000000    3.000000               0.900000   \n",
       "75%              5.000000    6.000000               1.200000   \n",
       "max            102.000000  110.000000               4.500000   \n",
       "\n",
       "       average_percentage_viewed  card_clicks  cards_shown  \\\n",
       "count                 573.000000   571.000000   571.000000   \n",
       "mean                   53.391955     0.003503     0.024518   \n",
       "std                    33.368099     0.059131     0.203723   \n",
       "min                     0.000000     0.000000     0.000000   \n",
       "25%                    29.270000     0.000000     0.000000   \n",
       "50%                    51.500000     0.000000     0.000000   \n",
       "75%                    74.320000     0.000000     0.000000   \n",
       "max                   280.250000     1.000000     2.000000   \n",
       "\n",
       "       clicks_per_card_shown  card_teaser_clicks  card_teasers_shown  \\\n",
       "count             573.000000          571.000000          571.000000   \n",
       "mean                0.174520            0.010508            0.490368   \n",
       "std                 2.951398            0.118002            1.474162   \n",
       "min                 0.000000            0.000000            0.000000   \n",
       "25%                 0.000000            0.000000            0.000000   \n",
       "50%                 0.000000            0.000000            0.000000   \n",
       "75%                 0.000000            0.000000            0.000000   \n",
       "max                50.000000            2.000000           22.000000   \n",
       "\n",
       "       clicks_per_card_teaser_shown        ...         dislikes_removed  \\\n",
       "count                    573.000000        ...               571.000000   \n",
       "mean                       0.336161        ...                 0.001751   \n",
       "std                        4.787228        ...                 0.041849   \n",
       "min                        0.000000        ...                 0.000000   \n",
       "25%                        0.000000        ...                 0.000000   \n",
       "50%                        0.000000        ...                 0.000000   \n",
       "75%                        0.000000        ...                 0.000000   \n",
       "max                      100.000000        ...                 1.000000   \n",
       "\n",
       "           shares    comments  videos_in_playlists  videos_added_to_playlists  \\\n",
       "count  571.000000  571.000000           571.000000                 571.000000   \n",
       "mean     0.115587    0.059545             0.045534                   0.050788   \n",
       "std      0.533725    0.296102             0.267595                   0.256587   \n",
       "min      0.000000    0.000000            -1.000000                   0.000000   \n",
       "25%      0.000000    0.000000             0.000000                   0.000000   \n",
       "50%      0.000000    0.000000             0.000000                   0.000000   \n",
       "75%      0.000000    0.000000             0.000000                   0.000000   \n",
       "max      6.000000    3.000000             3.000000                   3.000000   \n",
       "\n",
       "       videos_removed_from_playlists  subscribers  subscribers_gained  \\\n",
       "count                     571.000000   571.000000          571.000000   \n",
       "mean                        0.005254     0.059545            0.073555   \n",
       "std                         0.072357     0.307724            0.310378   \n",
       "min                         0.000000    -1.000000            0.000000   \n",
       "25%                         0.000000     0.000000            0.000000   \n",
       "50%                         0.000000     0.000000            0.000000   \n",
       "75%                         0.000000     0.000000            0.000000   \n",
       "max                         1.000000     3.000000            4.000000   \n",
       "\n",
       "       subscribers_lost  watch_time_hours  \n",
       "count        571.000000        573.000000  \n",
       "mean           0.014011          0.012216  \n",
       "std            0.117637          0.124839  \n",
       "min            0.000000          0.000000  \n",
       "25%            0.000000          0.000000  \n",
       "50%            0.000000          0.000000  \n",
       "75%            0.000000          0.000000  \n",
       "max            1.000000          2.000000  \n",
       "\n",
       "[8 rows x 40 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# gives a concise summary of the dataset \n",
    "df2.describe() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "nbpresent": {
     "id": "06a49ead-9de1-4e2c-bc8a-8a064d47c30d"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    534\n",
       "1.0     34\n",
       "2.0      2\n",
       "4.0      1\n",
       "Name: subscribers_gained, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.subscribers_gained.value_counts() # duplicated columns\n",
    "# mostly gets 1 subscriber within the period being looked at"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "nbpresent": {
     "id": "7e94dfd8-bc78-4210-85bb-4f41b1f68d41"
    }
   },
   "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>watch_time_minutes</th>\n",
       "      <th>views</th>\n",
       "      <th>youtube_red_watch_time_minutes</th>\n",
       "      <th>youtube_red_views</th>\n",
       "      <th>average_view_duration</th>\n",
       "      <th>card_clicks</th>\n",
       "      <th>cards_shown</th>\n",
       "      <th>clicks_per_card_shown</th>\n",
       "      <th>card_teaser_clicks</th>\n",
       "      <th>card_teasers_shown</th>\n",
       "      <th>...</th>\n",
       "      <th>shares</th>\n",
       "      <th>comments</th>\n",
       "      <th>videos_in_playlists</th>\n",
       "      <th>videos_added_to_playlists</th>\n",
       "      <th>videos_removed_from_playlists</th>\n",
       "      <th>subscribers</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>average_percentage_viewed</th>\n",
       "      <th>watch_time_hours</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>313.416121</td>\n",
       "      <td>117.204456</td>\n",
       "      <td>0.308650</td>\n",
       "      <td>0.230013</td>\n",
       "      <td>2.268480</td>\n",
       "      <td>0.010485</td>\n",
       "      <td>0.150066</td>\n",
       "      <td>0.271212</td>\n",
       "      <td>0.039974</td>\n",
       "      <td>3.062910</td>\n",
       "      <td>...</td>\n",
       "      <td>0.215596</td>\n",
       "      <td>0.914810</td>\n",
       "      <td>0.384010</td>\n",
       "      <td>0.618611</td>\n",
       "      <td>0.234600</td>\n",
       "      <td>0.570773</td>\n",
       "      <td>0.733945</td>\n",
       "      <td>0.163172</td>\n",
       "      <td>30.330852</td>\n",
       "      <td>5.220183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>349.328319</td>\n",
       "      <td>77.747824</td>\n",
       "      <td>1.387444</td>\n",
       "      <td>0.752816</td>\n",
       "      <td>1.082333</td>\n",
       "      <td>0.108135</td>\n",
       "      <td>0.779506</td>\n",
       "      <td>2.818677</td>\n",
       "      <td>0.264342</td>\n",
       "      <td>7.015858</td>\n",
       "      <td>...</td>\n",
       "      <td>0.619925</td>\n",
       "      <td>1.977069</td>\n",
       "      <td>1.762816</td>\n",
       "      <td>1.693194</td>\n",
       "      <td>1.521003</td>\n",
       "      <td>1.008767</td>\n",
       "      <td>0.975094</td>\n",
       "      <td>0.411610</td>\n",
       "      <td>10.355833</td>\n",
       "      <td>5.823751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>114.250000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.665000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>182.000000</td>\n",
       "      <td>99.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>29.835000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>381.750000</td>\n",
       "      <td>137.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>33.705000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2774.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>33.330000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>27.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>187.940000</td>\n",
       "      <td>46.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       watch_time_minutes        views  youtube_red_watch_time_minutes  \\\n",
       "count         1526.000000  1526.000000                     1526.000000   \n",
       "mean           313.416121   117.204456                        0.308650   \n",
       "std            349.328319    77.747824                        1.387444   \n",
       "min              0.000000     0.000000                        0.000000   \n",
       "25%            114.250000    75.000000                        0.000000   \n",
       "50%            182.000000    99.500000                        0.000000   \n",
       "75%            381.750000   137.000000                        0.000000   \n",
       "max           2774.000000   533.000000                       25.000000   \n",
       "\n",
       "       youtube_red_views  average_view_duration  card_clicks  cards_shown  \\\n",
       "count        1526.000000            1526.000000  1526.000000  1526.000000   \n",
       "mean            0.230013               2.268480     0.010485     0.150066   \n",
       "std             0.752816               1.082333     0.108135     0.779506   \n",
       "min             0.000000               0.000000     0.000000     0.000000   \n",
       "25%             0.000000               1.500000     0.000000     0.000000   \n",
       "50%             0.000000               1.900000     0.000000     0.000000   \n",
       "75%             0.000000               3.000000     0.000000     0.000000   \n",
       "max            12.000000               8.000000     2.000000     9.000000   \n",
       "\n",
       "       clicks_per_card_shown  card_teaser_clicks  card_teasers_shown  \\\n",
       "count            1526.000000         1526.000000         1526.000000   \n",
       "mean                0.271212            0.039974            3.062910   \n",
       "std                 2.818677            0.264342            7.015858   \n",
       "min                 0.000000            0.000000            0.000000   \n",
       "25%                 0.000000            0.000000            0.000000   \n",
       "50%                 0.000000            0.000000            0.000000   \n",
       "75%                 0.000000            0.000000            3.000000   \n",
       "max                33.330000            4.000000           77.000000   \n",
       "\n",
       "             ...              shares     comments  videos_in_playlists  \\\n",
       "count        ...         1526.000000  1526.000000          1526.000000   \n",
       "mean         ...            0.215596     0.914810             0.384010   \n",
       "std          ...            0.619925     1.977069             1.762816   \n",
       "min          ...            0.000000     0.000000           -21.000000   \n",
       "25%          ...            0.000000     0.000000             0.000000   \n",
       "50%          ...            0.000000     0.000000             0.000000   \n",
       "75%          ...            0.000000     1.000000             1.000000   \n",
       "max          ...            6.000000    21.000000            20.000000   \n",
       "\n",
       "       videos_added_to_playlists  videos_removed_from_playlists  subscribers  \\\n",
       "count                1526.000000                    1526.000000  1526.000000   \n",
       "mean                    0.618611                       0.234600     0.570773   \n",
       "std                     1.693194                       1.521003     1.008767   \n",
       "min                     0.000000                       0.000000    -2.000000   \n",
       "25%                     0.000000                       0.000000     0.000000   \n",
       "50%                     0.000000                       0.000000     0.000000   \n",
       "75%                     1.000000                       0.000000     1.000000   \n",
       "max                    27.000000                      31.000000     7.000000   \n",
       "\n",
       "       subscribers_gained  subscribers_lost  average_percentage_viewed  \\\n",
       "count         1526.000000       1526.000000                1526.000000   \n",
       "mean             0.733945          0.163172                  30.330852   \n",
       "std              0.975094          0.411610                  10.355833   \n",
       "min              0.000000          0.000000                   0.000000   \n",
       "25%              0.000000          0.000000                  25.665000   \n",
       "50%              0.000000          0.000000                  29.835000   \n",
       "75%              1.000000          0.000000                  33.705000   \n",
       "max              7.000000          3.000000                 187.940000   \n",
       "\n",
       "       watch_time_hours  \n",
       "count       1526.000000  \n",
       "mean           5.220183  \n",
       "std            5.823751  \n",
       "min            0.000000  \n",
       "25%            2.000000  \n",
       "50%            3.000000  \n",
       "75%            6.000000  \n",
       "max           46.000000  \n",
       "\n",
       "[8 rows x 53 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# gives a concise summary of the dataset \n",
    "df3.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "nbpresent": {
     "id": "2fa1be8e-7a59-4bba-b15b-95cccd7805a6"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       " 0    794\n",
       " 1    404\n",
       " 2    166\n",
       "-1     87\n",
       " 3     46\n",
       " 4     16\n",
       "-2      7\n",
       " 5      3\n",
       " 6      2\n",
       " 7      1\n",
       "Name: subscribers, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3.subscribers.value_counts() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'They are 2 NaNs in the columms.'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "message2 = \"They are {} NaNs in the columms.\"\n",
    "message2.format(sum(df3.isnull().any() == True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "** “Exploratory data analysis can never be the whole story, but nothing else can serve as the foundation stone.”\n",
    "John Tukey**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Why data visualization is important. [Anscombe quartet](https://en.wikipedia.org/wiki/Anscombe%27s_quartet). **\n",
    "\n",
    "![Anscombe](https://upload.wikimedia.org/wikipedia/commons/e/ec/Anscombe%27s_quartet_3.svg)\n",
    "\n",
    "Credit: By Anscombe.svg: Schutz Derivative works of this file:(label using subscripts): Avenue (Anscombe.svg) [GPL (http://www.gnu.org/licenses/gpl.html), CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0) or GFDL (http://www.gnu.org/copyleft/fdl.html)], via Wikimedia Commons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "15722b0f-415b-4843-9a5e-ad4f1aeede2a"
    }
   },
   "source": [
    "#### Getting required columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "nbpresent": {
     "id": "5fb09594-da8b-4094-b93c-cee7e19389d5"
    }
   },
   "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>views</th>\n",
       "      <th>subscribers_gained</th>\n",
       "      <th>subscribers_lost</th>\n",
       "      <th>channel</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-03-30</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06-01</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-30</th>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-03</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-05</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Sliceace</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            views  subscribers_gained  subscribers_lost   channel\n",
       "date                                                             \n",
       "2011-03-30    1.0                 0.0               0.0  Sliceace\n",
       "2011-06-01    0.0                 0.0               0.0  Sliceace\n",
       "2011-07-30    2.0                 0.0               0.0  Sliceace\n",
       "2011-08-03    1.0                 0.0               0.0  Sliceace\n",
       "2011-08-05    1.0                 0.0               0.0  Sliceace"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df date, views, subscribers_gained, subscribers lost\n",
    "df_3 = df[[\"views\", \"subscribers_gained\", \"subscribers_lost\", \"channel\"]]\n",
    "df_4 = df[[\"views\", \"subscribers_gained\", \"subscribers_lost\"]] # for initial plots\n",
    "df_3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "nbpresent": {
     "id": "7a45c60d-1dc1-46da-8d4e-eea3d2b6bfca"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(573, 4)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_3.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "nbpresent": {
     "id": "201ac076-2dcf-4931-be88-5a0c333bcb6c"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Drawing the graph roughly\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "plt.plot(df_4)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "nbpresent": {
     "id": "538f9094-e3b5-4438-b74a-f160e72ef84a"
    }
   },
   "outputs": [],
   "source": [
    "# Let's zoom in to 2015 - 2017\n",
    "# for views and subscribers\n",
    "views = df[\"views\"] # extracting a Pandas Series from views\n",
    "six_seven = views[\"2015\":\"2017\"] # specifying time period\n",
    "subs_gain = df[\"subscribers_gained\"]\n",
    "subs_gain_17_18 = subs_gain[\"2015\":\"2017\"]\n",
    "subs_lost = df[\"subscribers_lost\"]\n",
    "subs_lost_17_18 = subs_lost[\"2015\":\"2017\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "nbpresent": {
     "id": "38f3fa2d-ec00-4f0a-b865-cc1abdcdbd76"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Drawing subplots\n",
    "plt.subplot(2,1,1)\n",
    "plt.plot(six_seven, color = \"green\")\n",
    "plt.title(\"views between 2015- 2017\")\n",
    "plt.xlabel(\"years\")\n",
    "plt.ylabel(\"views\")\n",
    "\n",
    "plt.subplot(2,1,2)\n",
    "plt.plot(subs_gain_17_18, color = \"red\")\n",
    "plt.title(\"subscribers gained between 2015- 2017\")\n",
    "plt.xlabel(\"years\")\n",
    "plt.ylabel(\"subscribersgained\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "48b223c9-a9b3-491e-8839-7bd9285d0068"
    }
   },
   "source": [
    "I added a column for the channel because i'll add comparison of say 3 channels plus, the one the investigator is querying. I'm seeing some interesting insights already. I had numerous views before April 2015 then from then on i had viewers ranging between about 1 to less than 25. Viewer variation activity seems to be interesting from July. Besides that, there's the subscribers i got the most subscribers in July 2016. Before i forget the subscribers data is the same as watch_time data if you plot it. That's why i stuck to watch time.\n",
    "\n",
    "Next, i will try and make an interractive visualization tool. I still need to convert the columns in a format recognizable to Bokeh. A ColumnDataSource for the columns that stakeholder needed first then i'll convert the rest if my initial tests are successful. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "nbpresent": {
     "id": "c6540830-8083-4c19-8acf-07e497ffc767"
    }
   },
   "source": [
    "#### The Interractive plot:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "nbpresent": {
     "id": "5f4e7629-1b90-43c7-a626-ad4aa91a19bc"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.renderers.GlyphRenderer\">GlyphRenderer</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'f7344a45-d1a3-4eae-b949-23576c067123', <span id=\"6a383036-5bdd-46d6-a8df-57ca95bbeffb\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">data_source&nbsp;=&nbsp;ColumnDataSource(id='f7de87fd-6536-4f2d-816a-f7fe2c2bfc7c', ...),</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">glyph&nbsp;=&nbsp;Line(id='0073b266-4369-49e7-867f-5ce33cf1cb82', ...),</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">hover_glyph&nbsp;=&nbsp;None,</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">level&nbsp;=&nbsp;'glyph',</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">nonselection_glyph&nbsp;=&nbsp;Line(id='099e6a15-5662-4544-92b0-9bbf15e19950', ...),</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selection_glyph&nbsp;=&nbsp;None,</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[],</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible&nbsp;=&nbsp;True,</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">x_range_name&nbsp;=&nbsp;'default',</div></div><div class=\"91612024-afc4-475b-a30b-08f9fc2ce2c2\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">y_range_name&nbsp;=&nbsp;'default')</div></div></div>\n",
       "<script>\n",
       "(function() {\n",
       "  var expanded = false;\n",
       "  var ellipsis = document.getElementById(\"6a383036-5bdd-46d6-a8df-57ca95bbeffb\");\n",
       "  ellipsis.addEventListener(\"click\", function() {\n",
       "    var rows = document.getElementsByClassName(\"91612024-afc4-475b-a30b-08f9fc2ce2c2\");\n",
       "    for (var i = 0; i < rows.length; i++) {\n",
       "      var el = rows[i];\n",
       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
       "    }\n",
       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
       "    expanded = !expanded;\n",
       "  });\n",
       "})();\n",
       "</script>\n"
      ],
      "text/plain": [
       "GlyphRenderer(id='f7344a45-d1a3-4eae-b949-23576c067123', ...)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Making the necessary imports\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.io import output_file, output_notebook, show\n",
    "# use control + / to add comments\n",
    "\n",
    "# convert column to a datetime\n",
    "df1['date'] = pd.to_datetime(df1['date'])\n",
    "\n",
    "df1[\"date\"]\n",
    "\n",
    "# create a new plot with a datetime axis type\n",
    "# putting it in a fixed area\n",
    "p = figure(plot_width = 800, plot_height = 250, title = \"Attempt to make a line graph\", \n",
    "           x_axis_label = \"year\", y_axis_label = \"viewers\", x_axis_type =\"datetime\")\n",
    "\n",
    "# add line glyph\n",
    "p.line(df1[\"date\"], df1[\"views\"], color = \"green\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "nbpresent": {
     "id": "f9b66d10-2b15-4da3-afe0-bf9005a58237"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"3de4db69-490f-4e42-9c4e-e58cb22b80ea\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      document.getElementById(\"3de4db69-490f-4e42-9c4e-e58cb22b80ea\").textContent = \"BokehJS successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"3de4db69-490f-4e42-9c4e-e58cb22b80ea\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '3de4db69-490f-4e42-9c4e-e58cb22b80ea' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"3de4db69-490f-4e42-9c4e-e58cb22b80ea\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"3de4db69-490f-4e42-9c4e-e58cb22b80ea\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# embed plot to notebook\n",
    "output_notebook() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "nbpresent": {
     "id": "1b512f91-4d9c-4268-be49-5138eb472592"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"4d331051-f5c2-4e2c-a1b6-dcd3a25a704e\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        document.getElementById(\"4d331051-f5c2-4e2c-a1b6-dcd3a25a704e\").textContent = \"BokehJS successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"4d331051-f5c2-4e2c-a1b6-dcd3a25a704e\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '4d331051-f5c2-4e2c-a1b6-dcd3a25a704e' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"0271a659-4a45-4ce0-873b-3852ce926fa6\":{\"roots\":{\"references\":[{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"143f0a67-438c-4a05-b2e6-c806bb2a41ad\",\"type\":\"DaysTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"0b0781a6-8e9b-4e25-b567-a122322b3305\",\"type\":\"DataRange1d\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"d3a4ed54-a653-46d6-b5ee-5dbfa7ea6816\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"07658306-80f7-40a3-9cf1-85b35defec45\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"51863266-9aa0-4519-85f4-ad53a6456c67\",\"type\":\"DaysTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1e46ee86-126e-4395-aff5-8a644974372f\",\"type\":\"PanTool\"},{\"id\":\"869b8965-dae4-40dd-b4a8-852c7202cbdc\",\"type\":\"WheelZoomTool\"},{\"id\":\"b6166209-cafe-4e76-ba51-8b3492f300d9\",\"type\":\"BoxZoomTool\"},{\"id\":\"2b7646c3-0c34-4a7f-b3aa-a04d6f6eab3f\",\"type\":\"SaveTool\"},{\"id\":\"2869e2bd-5fa1-4166-bce0-73d73063a260\",\"type\":\"ResetTool\"},{\"id\":\"ba3e96d5-a83d-40be-9582-4651cb1a61a5\",\"type\":\"HelpTool\"}]},\"id\":\"0d7d7664-6888-4c03-aa7e-ced6d8efec1c\",\"type\":\"Toolbar\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"0cf46b18-5140-4656-ba5c-82a8b084a694\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"798f88a2-c3ed-41ee-be9d-acdde983d6a7\",\"type\":\"ToolEvents\"},{\"attributes\":{\"plot\":null,\"text\":\"Attempt to make a line graph\"},\"id\":\"1f6884ae-f5fd-467b-8ef3-66e29bb5be50\",\"type\":\"Title\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"428314bf-fca6-4736-a374-4206eabd98f9\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"be79a2c1-e82a-4f5f-9658-b72b08340dd1\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"d9db5a07-b798-45fa-85c9-c2b9fa470020\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"e8d5dcde-4b50-4067-836f-98b4d0aec82a\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"b1e10a37-07ed-4ef4-a38f-3852dfa6608f\",\"type\":\"YearsTicker\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9abe99ba-5853-4a44-95e0-09c6229ccddb\",\"type\":\"DatetimeTicker\"}},\"id\":\"37424b2d-06b3-4eae-8410-0cf6c73d76f1\",\"type\":\"Grid\"},{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"9abe99ba-5853-4a44-95e0-09c6229ccddb\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"axis_label\":\"viewers\",\"formatter\":{\"id\":\"2f208c22-72dc-42c1-852b-aea1b28011c7\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"511ddf1c-f670-42b9-80fb-92a9603dbfad\",\"type\":\"BasicTicker\"}},\"id\":\"174b39c8-c1ab-4249-b5fa-2e2a239726e8\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"511ddf1c-f670-42b9-80fb-92a9603dbfad\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"511ddf1c-f670-42b9-80fb-92a9603dbfad\",\"type\":\"BasicTicker\"}},\"id\":\"e25887c8-e7a7-4e1b-84c0-1764db29f0bf\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"8fc81771-010d-4eec-91ab-bd93c06967a1\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"axis_label\":\"year\",\"formatter\":{\"id\":\"8fc81771-010d-4eec-91ab-bd93c06967a1\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9abe99ba-5853-4a44-95e0-09c6229ccddb\",\"type\":\"DatetimeTicker\"}},\"id\":\"b9b0e416-c8f3-4c37-be6c-c57de3b4eecc\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"e6f99ee7-8e9c-4c27-8a99-1aebb80482a2\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"099e6a15-5662-4544-92b0-9bbf15e19950\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]}}},\"id\":\"f7de87fd-6536-4f2d-816a-f7fe2c2bfc7c\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"1e46ee86-126e-4395-aff5-8a644974372f\",\"type\":\"PanTool\"},{\"attributes\":{\"data_source\":{\"id\":\"f7de87fd-6536-4f2d-816a-f7fe2c2bfc7c\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"0073b266-4369-49e7-867f-5ce33cf1cb82\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"099e6a15-5662-4544-92b0-9bbf15e19950\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"f7344a45-d1a3-4eae-b949-23576c067123\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"869b8965-dae4-40dd-b4a8-852c7202cbdc\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"579b4076-bd6e-4a01-82e6-da31769b05c5\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"3a8459fa-df74-4095-944d-e9644749768f\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b6166209-cafe-4e76-ba51-8b3492f300d9\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2b7646c3-0c34-4a7f-b3aa-a04d6f6eab3f\",\"type\":\"SaveTool\"},{\"attributes\":{\"below\":[{\"id\":\"b9b0e416-c8f3-4c37-be6c-c57de3b4eecc\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"174b39c8-c1ab-4249-b5fa-2e2a239726e8\",\"type\":\"LinearAxis\"}],\"plot_height\":250,\"plot_width\":800,\"renderers\":[{\"id\":\"b9b0e416-c8f3-4c37-be6c-c57de3b4eecc\",\"type\":\"DatetimeAxis\"},{\"id\":\"37424b2d-06b3-4eae-8410-0cf6c73d76f1\",\"type\":\"Grid\"},{\"id\":\"174b39c8-c1ab-4249-b5fa-2e2a239726e8\",\"type\":\"LinearAxis\"},{\"id\":\"e25887c8-e7a7-4e1b-84c0-1764db29f0bf\",\"type\":\"Grid\"},{\"id\":\"3a8459fa-df74-4095-944d-e9644749768f\",\"type\":\"BoxAnnotation\"},{\"id\":\"f7344a45-d1a3-4eae-b949-23576c067123\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"1f6884ae-f5fd-467b-8ef3-66e29bb5be50\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"798f88a2-c3ed-41ee-be9d-acdde983d6a7\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"0d7d7664-6888-4c03-aa7e-ced6d8efec1c\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"e8d5dcde-4b50-4067-836f-98b4d0aec82a\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"0b0781a6-8e9b-4e25-b567-a122322b3305\",\"type\":\"DataRange1d\"}},\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2869e2bd-5fa1-4166-bce0-73d73063a260\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"ba3e96d5-a83d-40be-9582-4651cb1a61a5\",\"type\":\"HelpTool\"},{\"attributes\":{\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"0073b266-4369-49e7-867f-5ce33cf1cb82\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"2f208c22-72dc-42c1-852b-aea1b28011c7\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"8268b603-ca1a-42e2-aab1-087bf3c15d27\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"3a8459fa-df74-4095-944d-e9644749768f\",\"type\":\"BoxAnnotation\"}],\"root_ids\":[\"5dcbeb05-1070-4c55-b687-59418bf9faa7\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.4\"}};\n",
       "            var render_items = [{\"docid\":\"0271a659-4a45-4ce0-873b-3852ce926fa6\",\"elementid\":\"4d331051-f5c2-4e2c-a1b6-dcd3a25a704e\",\"modelid\":\"5dcbeb05-1070-4c55-b687-59418bf9faa7\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"4d331051-f5c2-4e2c-a1b6-dcd3a25a704e\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# See the plot\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "nbpresent": {
     "id": "8092a299-a676-4097-abc1-d630d50ebf8f"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.renderers.GlyphRenderer\">GlyphRenderer</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'abf89c4e-06ad-468e-8d56-73ba718a1674', <span id=\"fc830b9f-ea57-4b54-aa3d-ce3c714b9168\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">data_source&nbsp;=&nbsp;ColumnDataSource(id='84512644-5148-464a-9ffb-ec6688b99ad6', ...),</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">glyph&nbsp;=&nbsp;Line(id='c7a2348f-6dde-4fb0-a1bc-f5b8866dab75', ...),</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">hover_glyph&nbsp;=&nbsp;None,</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">level&nbsp;=&nbsp;'glyph',</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">nonselection_glyph&nbsp;=&nbsp;Line(id='3b9ac1d6-adcc-495a-b075-9ee9005bcad8', ...),</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selection_glyph&nbsp;=&nbsp;None,</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[],</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible&nbsp;=&nbsp;True,</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">x_range_name&nbsp;=&nbsp;'default',</div></div><div class=\"0e5706ab-ee23-4739-afab-30e364318f8b\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">y_range_name&nbsp;=&nbsp;'default')</div></div></div>\n",
       "<script>\n",
       "(function() {\n",
       "  var expanded = false;\n",
       "  var ellipsis = document.getElementById(\"fc830b9f-ea57-4b54-aa3d-ce3c714b9168\");\n",
       "  ellipsis.addEventListener(\"click\", function() {\n",
       "    var rows = document.getElementsByClassName(\"0e5706ab-ee23-4739-afab-30e364318f8b\");\n",
       "    for (var i = 0; i < rows.length; i++) {\n",
       "      var el = rows[i];\n",
       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
       "    }\n",
       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
       "    expanded = !expanded;\n",
       "  });\n",
       "})();\n",
       "</script>\n"
      ],
      "text/plain": [
       "GlyphRenderer(id='abf89c4e-06ad-468e-8d56-73ba718a1674', ...)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert column to a datetime\n",
    "df3['date'] = pd.to_datetime(df3['date'])\n",
    "\n",
    "# create a new plot with a datetime axis type\n",
    "# putting it in a fixed area\n",
    "p = figure(plot_width = 800, plot_height = 250, title = \"Attempt to make a line graph for 2nd channel\", \n",
    "           x_axis_label = \"year\", y_axis_label = \"viewers\", x_axis_type =\"datetime\")\n",
    "\n",
    "# add line glyph\n",
    "p.line(df3[\"date\"], df3[\"views\"], color = \"red\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "nbpresent": {
     "id": "affbdaf5-6793-4f31-b542-97f1cbe9e2ca"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"f9b45e4d-1102-4394-b58a-aebc7bc7579a\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      document.getElementById(\"f9b45e4d-1102-4394-b58a-aebc7bc7579a\").textContent = \"BokehJS successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"f9b45e4d-1102-4394-b58a-aebc7bc7579a\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'f9b45e4d-1102-4394-b58a-aebc7bc7579a' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"f9b45e4d-1102-4394-b58a-aebc7bc7579a\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"f9b45e4d-1102-4394-b58a-aebc7bc7579a\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# embed plot to notebook\n",
    "output_notebook() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "nbpresent": {
     "id": "18bda877-1feb-4118-815c-ffd37826da72"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"f1b8f3c2-b7e8-445f-be07-fa2c42753739\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        document.getElementById(\"f1b8f3c2-b7e8-445f-be07-fa2c42753739\").textContent = \"BokehJS successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"f1b8f3c2-b7e8-445f-be07-fa2c42753739\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'f1b8f3c2-b7e8-445f-be07-fa2c42753739' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"cf87d5ea-13a1-4f1b-bb3e-b92c3427a8ea\":{\"roots\":{\"references\":[{\"attributes\":{\"axis_label\":\"year\",\"formatter\":{\"id\":\"8cc3e368-e0d7-4e48-a163-ebe28af5fab2\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0a29575f-7df2-4f2b-ad06-99c271d10063\",\"type\":\"DatetimeTicker\"}},\"id\":\"6f64db46-42b0-4055-bac5-856381d84f59\",\"type\":\"DatetimeAxis\"},{\"attributes\":{},\"id\":\"231598ff-f688-4d85-b4e5-f7f3e2fe9fc0\",\"type\":\"YearsTicker\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"6da15f67-3a61-4bbb-8de3-e091bb117352\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"e68827cb-5ca5-4c01-a12c-b0b720f0f329\",\"type\":\"PanTool\"},{\"id\":\"bd719309-0b4e-4784-a993-64d31eba798f\",\"type\":\"WheelZoomTool\"},{\"id\":\"740a796d-ad78-4741-b555-09b3701a7cf3\",\"type\":\"BoxZoomTool\"},{\"id\":\"0c62be6c-56df-463d-82f3-ac5f46cdd6cb\",\"type\":\"SaveTool\"},{\"id\":\"66640daf-0dad-42f7-91e7-7bd586a05ad0\",\"type\":\"ResetTool\"},{\"id\":\"c5f9514e-05cf-4665-b6da-de2e09d2f458\",\"type\":\"HelpTool\"}]},\"id\":\"e51a8156-c98c-428e-838c-39b1f0a34681\",\"type\":\"Toolbar\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"796023e4-37b4-4d69-8545-ef607b5f8f5a\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"9ddb92dd-3013-4dde-9fae-5d62f559b5d7\",\"type\":\"ToolEvents\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"f532b1bc-78bf-4c0a-ac25-136a5961a5a1\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"8e8bb5da-9b75-4b34-afd1-2d1c7c5bea58\",\"type\":\"DataRange1d\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"49cbb995-6fad-4188-b411-68d92868fdae\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"plot\":null,\"text\":\"Attempt to make a line graph for 2nd channel\"},\"id\":\"77bfd0b5-6cb6-4ad1-b8ce-39e1ce211062\",\"type\":\"Title\"},{\"attributes\":{\"data_source\":{\"id\":\"84512644-5148-464a-9ffb-ec6688b99ad6\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"c7a2348f-6dde-4fb0-a1bc-f5b8866dab75\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"3b9ac1d6-adcc-495a-b075-9ee9005bcad8\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"abf89c4e-06ad-468e-8d56-73ba718a1674\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"5d6f5af6-d91a-4558-b99d-ee8fcfca32b7\",\"type\":\"DaysTicker\"},{\"attributes\":{\"below\":[{\"id\":\"6f64db46-42b0-4055-bac5-856381d84f59\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"c0cc16a2-76d9-4770-90f6-983cf74f0ce0\",\"type\":\"LinearAxis\"}],\"plot_height\":250,\"plot_width\":800,\"renderers\":[{\"id\":\"6f64db46-42b0-4055-bac5-856381d84f59\",\"type\":\"DatetimeAxis\"},{\"id\":\"c90c09bd-32c9-431a-96b5-c7e7b5991a7e\",\"type\":\"Grid\"},{\"id\":\"c0cc16a2-76d9-4770-90f6-983cf74f0ce0\",\"type\":\"LinearAxis\"},{\"id\":\"a284880f-964c-4719-ba96-9fd0ae373f4d\",\"type\":\"Grid\"},{\"id\":\"a10f38e5-cc50-4a6a-b4c4-73efbf754b86\",\"type\":\"BoxAnnotation\"},{\"id\":\"abf89c4e-06ad-468e-8d56-73ba718a1674\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"77bfd0b5-6cb6-4ad1-b8ce-39e1ce211062\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"9ddb92dd-3013-4dde-9fae-5d62f559b5d7\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"e51a8156-c98c-428e-838c-39b1f0a34681\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"8e8bb5da-9b75-4b34-afd1-2d1c7c5bea58\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"284e76ea-fb5f-4641-894c-607dc1abd1b2\",\"type\":\"DataRange1d\"}},\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"2d7c0d83-ee84-476b-ba69-1d5f7549053d\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"364210f7-6698-4ab3-b4a9-04619fc432fe\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"e86d7ce3-6da7-49e1-a6a6-1d5978af0a9f\",\"type\":\"DaysTicker\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"10fd46c2-1dbd-4255-84a5-d9cf7b0a5372\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"75799353-7c9a-405f-bb20-5cb2835b2e03\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"8cc3e368-e0d7-4e48-a163-ebe28af5fab2\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"3b9ac1d6-adcc-495a-b075-9ee9005bcad8\",\"type\":\"Line\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"f30e8ec7-fc02-4a6b-8a42-909d6a7fa0ac\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{},\"id\":\"ce3bc700-3073-4ca2-8b91-362f356090d7\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"c5f9514e-05cf-4665-b6da-de2e09d2f458\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"66640daf-0dad-42f7-91e7-7bd586a05ad0\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"0c62be6c-56df-463d-82f3-ac5f46cdd6cb\",\"type\":\"SaveTool\"},{\"attributes\":{\"overlay\":{\"id\":\"a10f38e5-cc50-4a6a-b4c4-73efbf754b86\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"740a796d-ad78-4741-b555-09b3701a7cf3\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"bd719309-0b4e-4784-a993-64d31eba798f\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_color\":{\"value\":\"red\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"c7a2348f-6dde-4fb0-a1bc-f5b8866dab75\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e68827cb-5ca5-4c01-a12c-b0b720f0f329\",\"type\":\"PanTool\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"a10f38e5-cc50-4a6a-b4c4-73efbf754b86\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1526]},\"y\":[1,1,2,0,1,1,5,2,2,5,1,3,3,1,2,1,2,3,3,12,3,2,17,2,5,1,1,2,2,2,2,2,2,3,3,2,1,2,1,21,10,2,2,2,3,1,1,3,4,3,3,2,7,3,7,1,1,1,16,19,2,18,1,1,4,37,9,22,17,12,12,5,7,4,78,10,18,7,3,26,7,17,14,8,3,8,55,13,4,11,9,3,3,11,21,10,4,3,12,2,96,47,43,31,26,22,29,51,40,42,24,25,41,23,32,23,35,41,39,61,38,32,22,105,60,44,63,86,89,50,42,36,57,41,59,51,158,65,59,69,64,57,94,44,33,55,62,45,47,52,40,62,35,74,80,45,53,55,39,40,56,59,68,104,66,46,45,69,49,63,69,59,85,91,75,53,54,57,41,72,39,34,44,42,43,45,34,37,27,51,31,48,36,27,34,34,64,70,40,107,92,109,89,72,79,59,53,61,64,48,61,61,58,70,87,75,79,55,71,73,67,88,61,91,71,85,89,102,148,72,110,129,102,98,148,92,73,112,86,108,97,96,120,108,90,87,89,82,70,166,85,98,93,85,110,85,100,83,114,121,91,93,101,143,119,104,128,121,111,71,91,180,172,169,173,161,169,143,220,209,217,173,167,182,217,176,190,340,258,289,221,242,254,280,249,221,172,166,201,223,220,230,259,234,235,227,258,262,332,311,287,264,262,311,235,248,265,274,243,251,267,257,260,284,257,269,301,271,307,285,265,227,263,327,377,347,348,299,324,276,261,284,242,334,300,256,304,298,285,300,376,327,264,310,323,328,320,317,316,324,340,252,274,265,293,311,374,456,533,429,486,472,474,459,392,403,396,320,389,336,372,328,406,375,310,268,285,313,260,290,276,296,294,340,324,377,469,362,358,425,414,342,434,308,284,304,365,385,377,286,235,206,214,170,207,167,182,173,161,185,171,184,209,215,182,168,173,186,187,189,183,219,181,203,202,163,181,183,205,187,169,184,179,205,331,457,360,289,293,223,231,299,252,316,235,198,227,214,211,192,185,203,190,159,175,149,127,106,151,120,148,138,135,123,157,143,157,176,128,118,114,96,125,136,110,112,84,114,91,128,119,126,112,108,116,109,107,121,140,122,89,107,120,122,146,125,150,131,135,147,162,160,124,112,118,122,125,103,122,166,149,130,116,110,110,208,149,131,126,99,132,104,166,142,136,128,104,133,155,159,183,134,135,138,149,149,168,161,138,158,148,165,204,182,172,200,177,154,171,153,162,198,143,134,168,119,134,122,155,153,159,125,134,117,141,175,144,142,129,148,141,147,134,114,119,141,109,111,139,146,117,94,148,118,172,156,143,148,121,133,127,126,141,139,110,120,100,145,111,120,102,92,100,116,129,113,143,143,137,124,108,150,118,147,134,103,124,115,151,107,101,116,126,111,86,117,136,117,114,89,92,117,103,227,205,118,115,119,105,119,133,178,197,159,115,135,134,138,143,138,112,138,134,117,133,164,143,152,126,126,173,151,175,119,136,154,141,154,143,121,122,124,134,140,135,148,162,208,170,151,135,127,149,174,179,143,141,132,105,133,136,134,119,92,119,129,180,145,137,120,116,118,144,114,132,136,105,93,113,115,138,124,129,99,106,99,103,76,132,142,128,101,114,131,135,115,124,106,137,98,134,121,114,142,100,96,113,80,106,126,96,92,118,90,86,119,109,101,113,109,137,157,111,101,172,119,131,170,169,156,144,136,142,153,110,154,139,105,113,129,121,128,105,110,119,109,132,110,152,105,124,115,123,108,117,202,137,94,115,113,165,121,162,129,119,170,164,121,112,155,144,103,79,138,95,100,84,89,65,105,86,171,140,121,172,110,85,78,88,77,129,93,85,130,87,65,68,147,129,90,113,84,107,96,161,119,92,92,101,80,80,111,87,142,92,93,61,78,94,77,107,96,88,96,110,121,80,90,97,85,61,82,134,131,122,103,103,84,70,101,76,68,60,60,72,75,85,72,73,87,80,90,58,68,81,88,66,89,84,65,114,86,42,63,86,84,77,77,88,68,84,78,77,53,73,76,86,84,77,61,74,56,72,93,98,82,94,51,68,72,128,101,86,104,106,122,72,80,77,89,119,143,97,95,131,91,92,89,80,93,64,147,94,96,108,101,206,98,121,70,93,85,84,129,88,107,109,84,70,92,114,129,137,83,147,92,72,144,95,99,106,87,54,61,183,103,152,86,93,101,86,93,78,78,84,89,61,76,91,101,153,89,92,69,58,138,144,78,81,75,65,136,66,85,97,90,63,72,67,111,92,130,91,54,83,72,91,85,70,97,70,107,89,72,95,80,84,75,88,95,61,47,100,74,88,60,49,98,88,57,110,140,82,111,132,93,73,86,37,63,51,41,74,219,138,87,113,92,67,42,91,86,67,50,61,60,66,71,99,68,78,75,102,97,101,59,64,72,45,318,130,129,92,104,105,107,91,66,138,120,108,182,109,91,103,118,86,85,67,73,136,100,116,86,73,90,88,113,94,77,74,93,63,80,117,83,114,76,56,72,72,107,66,120,75,69,70,68,100,67,112,67,83,85,65,79,83,103,100,86,74,71,130,95,102,98,97,63,75,68,88,111,80,76,86,85,114,69,59,87,76,77,72,81,72,207,365,247,205,171,152,197,281,329,447,295,292,229,200,162,121,117,129,114,131,114,80,120,90,85,91,95,105,95,130,81,125,123,90,89,112,201,98,76,75,103,73,162,158,139,111,151,188,177,128,137,122,97,86,100,95,104,100,62,84,113,123,89,100,125,73,87,75,94,69,94,143,103,85,78,119,89,83,91,75,67,92,65,90,75,88,59,48,84,58,44,68,67,53,55,56,57,113,91,80,66,94,56,101,82,65,89,77,71,60,79,98,76,75,72,105,86,94,88,92,82,69,87,81,82,69,90,87,81,89,65,89,88,96,55,87,79,80,130,69,82,146,86,64,79,113,69,53,77,73,83,82,85,78,83,78,89,77,61,62,94,79,65,83,72,74,62,45,75,77,93,68,74,114,95,97,98,91,94,82,66,99,83,106,94,122,82,73,64,85,91,83,55,72,94,60,98,95,85,74,78,104,102,97,113,69,60,68,86,75,89,103,103,68,75,69,95,111,98,99,63,92,164,124,100,93,92,76,72,68,97,74,90,110,77,63,65,71,50,81,84,168,140,115,80,111,170,93,99,110,116,226,144,110,121,143,103,104,83,102,100,112,115,87,97,79,88,113,76,78,100,86,104,132,119,109,99,73,96,92,96,84,111,83,90,104,76,102,102,143,97,93,84,97,89,98,88,88,72,72,80,98,123,96,87,70,101,101,78,94,121,80,78,118,88,81,90,104,72,64,95,104,146,97,95,93,106,75,89,109,108,90,107,113,111,106,94,80,87,85,97,99,99,118,112,97,98,94,100,122,0]}},\"id\":\"84512644-5148-464a-9ffb-ec6688b99ad6\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3f84e574-18b2-42bf-bb00-937500afb650\",\"type\":\"BasicTicker\"}},\"id\":\"a284880f-964c-4719-ba96-9fd0ae373f4d\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"3f84e574-18b2-42bf-bb00-937500afb650\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"viewers\",\"formatter\":{\"id\":\"ce3bc700-3073-4ca2-8b91-362f356090d7\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"3f84e574-18b2-42bf-bb00-937500afb650\",\"type\":\"BasicTicker\"}},\"id\":\"c0cc16a2-76d9-4770-90f6-983cf74f0ce0\",\"type\":\"LinearAxis\"},{\"attributes\":{\"plot\":{\"id\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"0a29575f-7df2-4f2b-ad06-99c271d10063\",\"type\":\"DatetimeTicker\"}},\"id\":\"c90c09bd-32c9-431a-96b5-c7e7b5991a7e\",\"type\":\"Grid\"},{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"0a29575f-7df2-4f2b-ad06-99c271d10063\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"284e76ea-fb5f-4641-894c-607dc1abd1b2\",\"type\":\"DataRange1d\"}],\"root_ids\":[\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.4\"}};\n",
       "            var render_items = [{\"docid\":\"cf87d5ea-13a1-4f1b-bb3e-b92c3427a8ea\",\"elementid\":\"f1b8f3c2-b7e8-445f-be07-fa2c42753739\",\"modelid\":\"139aa719-5a18-43b8-b6ee-c3ccb3a452db\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"f1b8f3c2-b7e8-445f-be07-fa2c42753739\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# See the plot\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "nbpresent": {
     "id": "115ccef9-abb0-4260-b509-d1f680d11030"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Label your graph for channel 1: start with the title e.g views for Sliceace channel from 2011 to 2017 and the y axis\n",
      "Please type in your title:views for Sliceace channel from 2011 to 2017\n",
      "Please type in your y axis labelviews\n",
      "Choose what variable you want on the y axis among these in the box below: watch_time_minutes,views,average_view_duration,average_percentage_viewed,card_clicks,cards_shown,clicks_per_card_shown,card_teaser_clicks,card_teasers_shown,clicks_per_card_teaser_shown,end_screen_elements_shown,end_screen_element_clicks,clicks_per_end_screen_element_shown,youtube_red_watch_time_minutes,youtube_red_views,youtube_red_watch_time_hours,annotation_clicks,clickable_annotations_shown,annotation_click_through_rate,annotation_closes,closable_annotations_shown,annotation_close_rate,annotations_shown,videos_published,videos_added,likes,likes_added,likes_removed,dislikes,dislikes_added,dislikes_removed,shares,comments,videos_in_playlists,videos_added_to_playlists,videos_removed_from_playlists,subscribers,subscribers_gained,subscribers_lost,watch_time_hours\n",
      "\n",
      "Type exactly how you see it in the list above\n",
      "views\n",
      "\n",
      "Label your graph for channel 2: start with the title e.g views for Sliceace channel from 2011 to 2017 and the y axis\n",
      "Choose what variable you want on the y axis among these in the box below: watch_time_minutes,views,average_view_duration,average_percentage_viewed,card_clicks,cards_shown,clicks_per_card_shown,card_teaser_clicks,card_teasers_shown,clicks_per_card_teaser_shown,end_screen_elements_shown,end_screen_element_clicks,clicks_per_end_screen_element_shown,youtube_red_watch_time_minutes,youtube_red_views,youtube_red_watch_time_hours,annotation_clicks,clickable_annotations_shown,annotation_click_through_rate,annotation_closes,closable_annotations_shown,annotation_close_rate,annotations_shown,videos_published,videos_added,likes,likes_added,likes_removed,dislikes,dislikes_added,dislikes_removed,shares,comments,videos_in_playlists,videos_added_to_playlists,videos_removed_from_playlists,subscribers,subscribers_gained,subscribers_lost,watch_time_hours\n",
      "\n",
      "Type exactly how you see it in the list above\n",
      "Please type in your title:views for other channel from 2013 to 2017\n",
      "Please type in your y axis labelviews\n",
      "views\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.renderers.GlyphRenderer\">GlyphRenderer</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'02bff993-6921-40d3-a75c-fbee5adbaeee', <span id=\"60ff4304-56f4-4974-be60-8f017405f468\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">data_source&nbsp;=&nbsp;ColumnDataSource(id='8b6b5006-7ec7-4c7f-a64e-2a68aa43e980', ...),</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">glyph&nbsp;=&nbsp;Line(id='8bf42caa-949d-479a-a994-eda51fbc3233', ...),</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">hover_glyph&nbsp;=&nbsp;None,</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">level&nbsp;=&nbsp;'glyph',</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">nonselection_glyph&nbsp;=&nbsp;Line(id='9d7ba061-741b-46ba-9cc5-7855272a10f1', ...),</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selection_glyph&nbsp;=&nbsp;None,</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[],</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible&nbsp;=&nbsp;True,</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">x_range_name&nbsp;=&nbsp;'default',</div></div><div class=\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">y_range_name&nbsp;=&nbsp;'default')</div></div></div>\n",
       "<script>\n",
       "(function() {\n",
       "  var expanded = false;\n",
       "  var ellipsis = document.getElementById(\"60ff4304-56f4-4974-be60-8f017405f468\");\n",
       "  ellipsis.addEventListener(\"click\", function() {\n",
       "    var rows = document.getElementsByClassName(\"c7d8f357-c5e6-45de-8993-1b79eb3b1cae\");\n",
       "    for (var i = 0; i < rows.length; i++) {\n",
       "      var el = rows[i];\n",
       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
       "    }\n",
       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
       "    expanded = !expanded;\n",
       "  });\n",
       "})();\n",
       "</script>\n"
      ],
      "text/plain": [
       "GlyphRenderer(id='02bff993-6921-40d3-a75c-fbee5adbaeee', ...)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Making the necessary imports\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.io import output_file, output_notebook, show\n",
    "from bokeh.layouts import column\n",
    "from bokeh.models import HoverTool, ColumnDataSource\n",
    "\n",
    "# use control + / to add comments\n",
    "\n",
    "# convert column to a datetime\n",
    "df1['date'] = pd.to_datetime(df1['date'])\n",
    "\n",
    "#df1['date']\n",
    "\n",
    "df3['date'] = pd.to_datetime(df3['date'])\n",
    "\n",
    "#df3['date']\n",
    "\n",
    "# Statement allowing user to label axes on their own.\n",
    "print (\"Label your graph for channel 1: start with the title e.g views for Sliceace channel from 2011 to 2017 and the y axis\")\n",
    "\n",
    "# create a new plot with a datetime axis type\n",
    "# putting it in a fixed area\n",
    "p = figure(plot_width = 800, plot_height = 250, title = input(\"Please type in your title:\"), \n",
    "           x_axis_label = \"year\", y_axis_label = input(\"Please type in your y axis label\"), x_axis_type = \"datetime\")\n",
    "\n",
    "# Variables available to be plotted on the y axis\n",
    "\n",
    "print (\"Choose what variable you want on the y axis among these in the box below: watch_time_minutes,views,average_view_duration,average_percentage_viewed,card_clicks,cards_shown,clicks_per_card_shown,card_teaser_clicks,card_teasers_shown,clicks_per_card_teaser_shown,end_screen_elements_shown,end_screen_element_clicks,clicks_per_end_screen_element_shown,youtube_red_watch_time_minutes,youtube_red_views,youtube_red_watch_time_hours,annotation_clicks,clickable_annotations_shown,annotation_click_through_rate,annotation_closes,closable_annotations_shown,annotation_close_rate,annotations_shown,videos_published,videos_added,likes,likes_added,likes_removed,dislikes,dislikes_added,dislikes_removed,shares,comments,videos_in_playlists,videos_added_to_playlists,videos_removed_from_playlists,subscribers,subscribers_gained,subscribers_lost,watch_time_hours\"); print (\"\")\n",
    "print(\"Type exactly how you see it in the list above\")\n",
    "\n",
    "\n",
    "# add line glyph\n",
    "p.line(df1['date'], df1[input(\"\")], color = \"green\")\n",
    "# print (\"Label your graph for channel 2: start with the title e.g views for Sliceace channel from 2011 to 2017 and the y axis\")\n",
    "\n",
    "\n",
    "# Variables available to be plotted on the y axis\n",
    "print(\"\")\n",
    "print (\"Label your graph for channel 2: start with the title e.g views for Sliceace channel from 2011 to 2017 and the y axis\")\n",
    "print (\"Choose what variable you want on the y axis among these in the box below: watch_time_minutes,views,average_view_duration,average_percentage_viewed,card_clicks,cards_shown,clicks_per_card_shown,card_teaser_clicks,card_teasers_shown,clicks_per_card_teaser_shown,end_screen_elements_shown,end_screen_element_clicks,clicks_per_end_screen_element_shown,youtube_red_watch_time_minutes,youtube_red_views,youtube_red_watch_time_hours,annotation_clicks,clickable_annotations_shown,annotation_click_through_rate,annotation_closes,closable_annotations_shown,annotation_close_rate,annotations_shown,videos_published,videos_added,likes,likes_added,likes_removed,dislikes,dislikes_added,dislikes_removed,shares,comments,videos_in_playlists,videos_added_to_playlists,videos_removed_from_playlists,subscribers,subscribers_gained,subscribers_lost,watch_time_hours\"); print (\"\")\n",
    "print(\"Type exactly how you see it in the list above\")\n",
    "\n",
    "# create a new plot with a datetime axis type\n",
    "# putting it in a fixed area\n",
    "p2 = figure(plot_width = 800, plot_height = 250, title = input(\"Please type in your title:\"), \n",
    "            x_axis_label = \"year\", y_axis_label = input(\"Please type in your y axis label\"), x_axis_type =\"datetime\")\n",
    "\n",
    "\n",
    "# add line glyph\n",
    "p2.line(df3[\"date\"], df3[input(\"\")], color = \"red\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "nbpresent": {
     "id": "47b6dcaa-21ec-493f-aac8-427e22f926c4"
    }
   },
   "outputs": [],
   "source": [
    "# put plots p1 and p2 on a column\n",
    "# So if you want more channels you'll just have to add more columns to put them\n",
    "# However, you'll have to use other layout such as a combination of tabbed layouts and with a couple of columns\n",
    "# from here https://bokeh.pydata.org/en/latest/docs/user_guide.html and here https://bokeh.pydata.org/en/latest/docs/gallery.html\n",
    "layout = column(p,p2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "nbpresent": {
     "id": "e4685550-324f-4276-91a6-3ee84394d334"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"abbf13c4-6de6-49ef-937e-7637bcc0d7db\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      document.getElementById(\"abbf13c4-6de6-49ef-937e-7637bcc0d7db\").textContent = \"BokehJS successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"abbf13c4-6de6-49ef-937e-7637bcc0d7db\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'abbf13c4-6de6-49ef-937e-7637bcc0d7db' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"abbf13c4-6de6-49ef-937e-7637bcc0d7db\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"abbf13c4-6de6-49ef-937e-7637bcc0d7db\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# embed plot to notebook\n",
    "output_notebook() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "nbpresent": {
     "id": "910cc8be-b0d4-49a2-8280-17e67240f729"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"508d129b-b5f6-4216-b1e7-efc9a02847e4\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        document.getElementById(\"508d129b-b5f6-4216-b1e7-efc9a02847e4\").textContent = \"BokehJS successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"508d129b-b5f6-4216-b1e7-efc9a02847e4\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '508d129b-b5f6-4216-b1e7-efc9a02847e4' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"010b8e55-4d25-4fe3-8c92-2a774b8c9ddd\":{\"roots\":{\"references\":[{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"9f759dbd-7599-4b32-ad00-0d5a078b39f2\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"9d7ba061-741b-46ba-9cc5-7855272a10f1\",\"type\":\"Line\"},{\"attributes\":{\"axis_label\":\"views\",\"formatter\":{\"id\":\"32e2ccc7-3ff6-479f-bf05-61b0dc88643c\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"768a728e-42fe-412a-8652-641b8dbd29b2\",\"type\":\"BasicTicker\"}},\"id\":\"7dec7f77-43bd-4215-a717-5d32100667b2\",\"type\":\"LinearAxis\"},{\"attributes\":{\"callback\":null},\"id\":\"f20802d5-cc70-4d71-ae7a-1502ab742b52\",\"type\":\"DataRange1d\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"60525515-1c63-429c-9ca2-090db9138a57\",\"type\":\"PanTool\"},{\"id\":\"fe41437d-46e6-4897-91d8-4fe72f0757c1\",\"type\":\"WheelZoomTool\"},{\"id\":\"5532c614-6053-4cf3-a584-e3b7095684a1\",\"type\":\"BoxZoomTool\"},{\"id\":\"4a5981bb-d5cd-4fde-a1f9-249a95c2d9f1\",\"type\":\"SaveTool\"},{\"id\":\"20cf8d60-0245-4bf6-a7de-3e48e9a4f1e1\",\"type\":\"ResetTool\"},{\"id\":\"3249cba4-0308-4582-9713-b4e4323a16f6\",\"type\":\"HelpTool\"}]},\"id\":\"27882984-dd78-493b-aa59-e3e8f30ca31a\",\"type\":\"Toolbar\"},{\"attributes\":{\"axis_label\":\"year\",\"formatter\":{\"id\":\"731f544d-2c97-4378-bf71-b308b7cf2752\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9f759dbd-7599-4b32-ad00-0d5a078b39f2\",\"type\":\"DatetimeTicker\"}},\"id\":\"16f27b72-8060-4600-bfdb-ea32ce80f685\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"callback\":null},\"id\":\"1eb84eba-bbf4-4a7b-a67d-dda2e1bb41ec\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9f759dbd-7599-4b32-ad00-0d5a078b39f2\",\"type\":\"DatetimeTicker\"}},\"id\":\"fdcd8338-1849-4b6e-b8e5-4f063960f1ef\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"768a728e-42fe-412a-8652-641b8dbd29b2\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"768a728e-42fe-412a-8652-641b8dbd29b2\",\"type\":\"BasicTicker\"}},\"id\":\"cb24e096-f404-47ab-83bf-df34a9e13d5d\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"8b6b5006-7ec7-4c7f-a64e-2a68aa43e980\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"8bf42caa-949d-479a-a994-eda51fbc3233\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"9d7ba061-741b-46ba-9cc5-7855272a10f1\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"02bff993-6921-40d3-a75c-fbee5adbaeee\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"line_color\":{\"value\":\"red\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"8bf42caa-949d-479a-a994-eda51fbc3233\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"32e2ccc7-3ff6-479f-bf05-61b0dc88643c\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"76de0fe9-f513-4127-89ff-a286450ecf0d\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"60525515-1c63-429c-9ca2-090db9138a57\",\"type\":\"PanTool\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"d9599d1e-eee2-4bd9-b5ab-3138c1e6c023\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"fe41437d-46e6-4897-91d8-4fe72f0757c1\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"children\":[{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}]},\"id\":\"cff67880-d3a7-4628-8e72-c17e012342da\",\"type\":\"Column\"},{\"attributes\":{\"overlay\":{\"id\":\"76de0fe9-f513-4127-89ff-a286450ecf0d\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"5532c614-6053-4cf3-a584-e3b7095684a1\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"4a5981bb-d5cd-4fde-a1f9-249a95c2d9f1\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"20cf8d60-0245-4bf6-a7de-3e48e9a4f1e1\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"3249cba4-0308-4582-9713-b4e4323a16f6\",\"type\":\"HelpTool\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"21287d6f-1011-4c29-96f8-4c2d740cbe38\",\"type\":\"DaysTicker\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[1526]},\"y\":[1,1,2,0,1,1,5,2,2,5,1,3,3,1,2,1,2,3,3,12,3,2,17,2,5,1,1,2,2,2,2,2,2,3,3,2,1,2,1,21,10,2,2,2,3,1,1,3,4,3,3,2,7,3,7,1,1,1,16,19,2,18,1,1,4,37,9,22,17,12,12,5,7,4,78,10,18,7,3,26,7,17,14,8,3,8,55,13,4,11,9,3,3,11,21,10,4,3,12,2,96,47,43,31,26,22,29,51,40,42,24,25,41,23,32,23,35,41,39,61,38,32,22,105,60,44,63,86,89,50,42,36,57,41,59,51,158,65,59,69,64,57,94,44,33,55,62,45,47,52,40,62,35,74,80,45,53,55,39,40,56,59,68,104,66,46,45,69,49,63,69,59,85,91,75,53,54,57,41,72,39,34,44,42,43,45,34,37,27,51,31,48,36,27,34,34,64,70,40,107,92,109,89,72,79,59,53,61,64,48,61,61,58,70,87,75,79,55,71,73,67,88,61,91,71,85,89,102,148,72,110,129,102,98,148,92,73,112,86,108,97,96,120,108,90,87,89,82,70,166,85,98,93,85,110,85,100,83,114,121,91,93,101,143,119,104,128,121,111,71,91,180,172,169,173,161,169,143,220,209,217,173,167,182,217,176,190,340,258,289,221,242,254,280,249,221,172,166,201,223,220,230,259,234,235,227,258,262,332,311,287,264,262,311,235,248,265,274,243,251,267,257,260,284,257,269,301,271,307,285,265,227,263,327,377,347,348,299,324,276,261,284,242,334,300,256,304,298,285,300,376,327,264,310,323,328,320,317,316,324,340,252,274,265,293,311,374,456,533,429,486,472,474,459,392,403,396,320,389,336,372,328,406,375,310,268,285,313,260,290,276,296,294,340,324,377,469,362,358,425,414,342,434,308,284,304,365,385,377,286,235,206,214,170,207,167,182,173,161,185,171,184,209,215,182,168,173,186,187,189,183,219,181,203,202,163,181,183,205,187,169,184,179,205,331,457,360,289,293,223,231,299,252,316,235,198,227,214,211,192,185,203,190,159,175,149,127,106,151,120,148,138,135,123,157,143,157,176,128,118,114,96,125,136,110,112,84,114,91,128,119,126,112,108,116,109,107,121,140,122,89,107,120,122,146,125,150,131,135,147,162,160,124,112,118,122,125,103,122,166,149,130,116,110,110,208,149,131,126,99,132,104,166,142,136,128,104,133,155,159,183,134,135,138,149,149,168,161,138,158,148,165,204,182,172,200,177,154,171,153,162,198,143,134,168,119,134,122,155,153,159,125,134,117,141,175,144,142,129,148,141,147,134,114,119,141,109,111,139,146,117,94,148,118,172,156,143,148,121,133,127,126,141,139,110,120,100,145,111,120,102,92,100,116,129,113,143,143,137,124,108,150,118,147,134,103,124,115,151,107,101,116,126,111,86,117,136,117,114,89,92,117,103,227,205,118,115,119,105,119,133,178,197,159,115,135,134,138,143,138,112,138,134,117,133,164,143,152,126,126,173,151,175,119,136,154,141,154,143,121,122,124,134,140,135,148,162,208,170,151,135,127,149,174,179,143,141,132,105,133,136,134,119,92,119,129,180,145,137,120,116,118,144,114,132,136,105,93,113,115,138,124,129,99,106,99,103,76,132,142,128,101,114,131,135,115,124,106,137,98,134,121,114,142,100,96,113,80,106,126,96,92,118,90,86,119,109,101,113,109,137,157,111,101,172,119,131,170,169,156,144,136,142,153,110,154,139,105,113,129,121,128,105,110,119,109,132,110,152,105,124,115,123,108,117,202,137,94,115,113,165,121,162,129,119,170,164,121,112,155,144,103,79,138,95,100,84,89,65,105,86,171,140,121,172,110,85,78,88,77,129,93,85,130,87,65,68,147,129,90,113,84,107,96,161,119,92,92,101,80,80,111,87,142,92,93,61,78,94,77,107,96,88,96,110,121,80,90,97,85,61,82,134,131,122,103,103,84,70,101,76,68,60,60,72,75,85,72,73,87,80,90,58,68,81,88,66,89,84,65,114,86,42,63,86,84,77,77,88,68,84,78,77,53,73,76,86,84,77,61,74,56,72,93,98,82,94,51,68,72,128,101,86,104,106,122,72,80,77,89,119,143,97,95,131,91,92,89,80,93,64,147,94,96,108,101,206,98,121,70,93,85,84,129,88,107,109,84,70,92,114,129,137,83,147,92,72,144,95,99,106,87,54,61,183,103,152,86,93,101,86,93,78,78,84,89,61,76,91,101,153,89,92,69,58,138,144,78,81,75,65,136,66,85,97,90,63,72,67,111,92,130,91,54,83,72,91,85,70,97,70,107,89,72,95,80,84,75,88,95,61,47,100,74,88,60,49,98,88,57,110,140,82,111,132,93,73,86,37,63,51,41,74,219,138,87,113,92,67,42,91,86,67,50,61,60,66,71,99,68,78,75,102,97,101,59,64,72,45,318,130,129,92,104,105,107,91,66,138,120,108,182,109,91,103,118,86,85,67,73,136,100,116,86,73,90,88,113,94,77,74,93,63,80,117,83,114,76,56,72,72,107,66,120,75,69,70,68,100,67,112,67,83,85,65,79,83,103,100,86,74,71,130,95,102,98,97,63,75,68,88,111,80,76,86,85,114,69,59,87,76,77,72,81,72,207,365,247,205,171,152,197,281,329,447,295,292,229,200,162,121,117,129,114,131,114,80,120,90,85,91,95,105,95,130,81,125,123,90,89,112,201,98,76,75,103,73,162,158,139,111,151,188,177,128,137,122,97,86,100,95,104,100,62,84,113,123,89,100,125,73,87,75,94,69,94,143,103,85,78,119,89,83,91,75,67,92,65,90,75,88,59,48,84,58,44,68,67,53,55,56,57,113,91,80,66,94,56,101,82,65,89,77,71,60,79,98,76,75,72,105,86,94,88,92,82,69,87,81,82,69,90,87,81,89,65,89,88,96,55,87,79,80,130,69,82,146,86,64,79,113,69,53,77,73,83,82,85,78,83,78,89,77,61,62,94,79,65,83,72,74,62,45,75,77,93,68,74,114,95,97,98,91,94,82,66,99,83,106,94,122,82,73,64,85,91,83,55,72,94,60,98,95,85,74,78,104,102,97,113,69,60,68,86,75,89,103,103,68,75,69,95,111,98,99,63,92,164,124,100,93,92,76,72,68,97,74,90,110,77,63,65,71,50,81,84,168,140,115,80,111,170,93,99,110,116,226,144,110,121,143,103,104,83,102,100,112,115,87,97,79,88,113,76,78,100,86,104,132,119,109,99,73,96,92,96,84,111,83,90,104,76,102,102,143,97,93,84,97,89,98,88,88,72,72,80,98,123,96,87,70,101,101,78,94,121,80,78,118,88,81,90,104,72,64,95,104,146,97,95,93,106,75,89,109,108,90,107,113,111,106,94,80,87,85,97,99,99,118,112,97,98,94,100,122,0]}},\"id\":\"8b6b5006-7ec7-4c7f-a64e-2a68aa43e980\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"df2c1e4f-2af5-4cb5-babf-236d71d34248\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{},\"id\":\"731f544d-2c97-4378-bf71-b308b7cf2752\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{},\"id\":\"4d8027a7-c94d-4141-acd9-8b6275761a77\",\"type\":\"ToolEvents\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"8252c04c-8df9-44f3-bfbf-83df89e3d26f\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"a9b387eb-7260-469d-9d7a-451c1ca6b837\",\"type\":\"DataRange1d\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"a7919f05-0c61-4b7d-b72e-d570ab16b07e\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"plot\":null,\"text\":\"views for Sliceace channel from 2011 to 2017\"},\"id\":\"ffb61afa-2e7f-4d6f-a31e-7d464febecd5\",\"type\":\"Title\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"9962a367-92cd-46b9-bed3-e429a20eed8b\",\"type\":\"PanTool\"},{\"id\":\"8f162ed5-1809-4aeb-a3d3-657838df02ec\",\"type\":\"WheelZoomTool\"},{\"id\":\"348d1fcf-54eb-49d7-807a-50f9272994f5\",\"type\":\"BoxZoomTool\"},{\"id\":\"e9765e8d-e619-413f-b57b-57953159424f\",\"type\":\"SaveTool\"},{\"id\":\"2e2bc3e3-27ba-47b0-8bd0-94486a03cdf1\",\"type\":\"ResetTool\"},{\"id\":\"c32c8c1d-fdba-4c2a-b491-a44e6d7a53ff\",\"type\":\"HelpTool\"}]},\"id\":\"8e044714-85e4-4f43-abff-ee693b3bbbfa\",\"type\":\"Toolbar\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"f5eaa3fe-8688-46a5-8551-7e65d141507e\",\"type\":\"DaysTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"853f254d-4b7a-4794-87dc-e0f29ad6b49d\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"1aef1a25-d277-475b-8e8a-d7041dcbda08\",\"type\":\"DaysTicker\"},{\"attributes\":{\"axis_label\":\"views\",\"formatter\":{\"id\":\"ed8352f2-4893-4bc0-84bd-e458a554a115\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"29ab8149-d89f-47f1-93a8-efeb83e049b5\",\"type\":\"BasicTicker\"}},\"id\":\"af8dfa0c-bbdf-468c-92e3-ffa289d2f0f7\",\"type\":\"LinearAxis\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"b23d282a-3122-4ade-9436-9d345d8aec5a\",\"type\":\"DaysTicker\"},{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"2a404123-95fb-4697-ac46-85d37577916b\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"10a54138-3457-4285-9785-c0c7bc17955b\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"below\":[{\"id\":\"de3a53e0-99e4-48fd-832a-a4f9ba2728ef\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"af8dfa0c-bbdf-468c-92e3-ffa289d2f0f7\",\"type\":\"LinearAxis\"}],\"plot_height\":250,\"plot_width\":800,\"renderers\":[{\"id\":\"de3a53e0-99e4-48fd-832a-a4f9ba2728ef\",\"type\":\"DatetimeAxis\"},{\"id\":\"c105acd1-f067-4b90-ae22-2ae65657f7fb\",\"type\":\"Grid\"},{\"id\":\"af8dfa0c-bbdf-468c-92e3-ffa289d2f0f7\",\"type\":\"LinearAxis\"},{\"id\":\"3c3f44a9-eaee-473e-9d47-3acc465d50df\",\"type\":\"Grid\"},{\"id\":\"1bcc5822-a18a-4d46-bcff-698699f54af7\",\"type\":\"BoxAnnotation\"},{\"id\":\"e86fe4e3-f7d8-4333-be8e-288a480a64e9\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"ffb61afa-2e7f-4d6f-a31e-7d464febecd5\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"4d8027a7-c94d-4141-acd9-8b6275761a77\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"8e044714-85e4-4f43-abff-ee693b3bbbfa\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"a9b387eb-7260-469d-9d7a-451c1ca6b837\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"d3ab8362-8f98-46cd-8658-a0a37499864b\",\"type\":\"DataRange1d\"}},\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"5a82aeb5-a5bb-4d0b-9e52-953a95bee547\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"axis_label\":\"year\",\"formatter\":{\"id\":\"df2c1e4f-2af5-4cb5-babf-236d71d34248\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"2a404123-95fb-4697-ac46-85d37577916b\",\"type\":\"DatetimeTicker\"}},\"id\":\"de3a53e0-99e4-48fd-832a-a4f9ba2728ef\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"31b6a16f-700c-483b-825a-aaa77ca29057\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"callback\":null},\"id\":\"d3ab8362-8f98-46cd-8658-a0a37499864b\",\"type\":\"DataRange1d\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"1dfcb937-a172-48b1-af89-ed265616b360\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"2a404123-95fb-4697-ac46-85d37577916b\",\"type\":\"DatetimeTicker\"}},\"id\":\"c105acd1-f067-4b90-ae22-2ae65657f7fb\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"2e2d297a-a818-4b83-b304-b594d891f6a2\",\"type\":\"YearsTicker\"},{\"attributes\":{},\"id\":\"29ab8149-d89f-47f1-93a8-efeb83e049b5\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"29ab8149-d89f-47f1-93a8-efeb83e049b5\",\"type\":\"BasicTicker\"}},\"id\":\"3c3f44a9-eaee-473e-9d47-3acc465d50df\",\"type\":\"Grid\"},{\"attributes\":{\"data_source\":{\"id\":\"e83567ae-885f-4893-9a64-e3d55864d7a4\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"740b2971-af79-470e-b21b-890f6204a146\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"6fc281d6-1d36-4903-9007-da1a85a0daa3\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"e86fe4e3-f7d8-4333-be8e-288a480a64e9\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"ed8352f2-4893-4bc0-84bd-e458a554a115\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1bcc5822-a18a-4d46-bcff-698699f54af7\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"9962a367-92cd-46b9-bed3-e429a20eed8b\",\"type\":\"PanTool\"},{\"attributes\":{\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"740b2971-af79-470e-b21b-890f6204a146\",\"type\":\"Line\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8f162ed5-1809-4aeb-a3d3-657838df02ec\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1bcc5822-a18a-4d46-bcff-698699f54af7\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"348d1fcf-54eb-49d7-807a-50f9272994f5\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e9765e8d-e619-413f-b57b-57953159424f\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"2e2bc3e3-27ba-47b0-8bd0-94486a03cdf1\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"fd10ab5c-bc3b-4365-93ad-5f97c4d2d723\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"c32c8c1d-fdba-4c2a-b491-a44e6d7a53ff\",\"type\":\"HelpTool\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]},\"y\":{\"__ndarray__\":\"AAAAAAAA8D8AAAAAAAAAAAAAAAAAAABAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAABBAAAAAAAAAFEAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAA8QAAAAAAAADRAAAAAAAAAEEAAAAAAAAAUQAAAAAAAAAAAAAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAAAIQAAAAAAAAAAAAAAAAAAACEAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAAD4fwAAAAAAACJAAAAAAAAAO0AAAAAAAIBbQAAAAAAAADhAAAAAAAAAIEAAAAAAAAAgQAAAAAAAAABAAAAAAAAAEEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAQQAAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAABBAAAAAAAAAAEAAAAAAAAAIQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAABAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAAhAAAAAAAAA8D8AAAAAAAAUQAAAAAAAACRAAAAAAAAAHEAAAAAAAAAQQAAAAAAAADZAAAAAAAAAHEAAAAAAAAAIQAAAAAAAABRAAAAAAAAACEAAAAAAAADwPwAAAAAAABxAAAAAAAAAIkAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAQQAAAAAAAABBAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAABhAAAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAABhAAAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAgQAAAAAAAABRAAAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAACEAAAAAAAADwPwAAAAAAAABAAAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAACEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAABAAAAAAAAAHEAAAAAAAAAAAAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAAAAAAAAAAAAAQQAAAAAAAAABAAAAAAAAA8D8AAAAAAAAAAAAAAAAAABBAAAAAAAAA8D8AAAAAAADwPwAAAAAAAAAAAAAAAAAAGEAAAAAAAAAsQAAAAAAAAAhAAAAAAAAAEEAAAAAAAADwPwAAAAAAAPA/AAAAAAAACEAAAAAAAADwPwAAAAAAAABAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAABRAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAABAAAAAAAAA8D8AAAAAAAAQQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAFEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAAhAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAYQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAAEEAAAAAAAADwPwAAAAAAAABAAAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAYQAAAAAAAAPA/AAAAAAAA8D8AAAAAAADwPwAAAAAAAPA/AAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAgQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAcQAAAAAAAAAhAAAAAAAAAGEAAAAAAAADwPwAAAAAAAPA/AAAAAAAACEAAAAAAAADwPwAAAAAAAABAAAAAAAAAAEAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAD4fwAAAAAAADxAAAAAAAAAJEAAAAAAAAAQQAAAAAAAAAhAAAAAAAAAAEAAAAAAAAAUQAAAAAAAAAAAAAAAAAAA8D8AAAAAAAAAQAAAAAAAACRAAAAAAAAAKEAAAAAAAAAQQAAAAAAAABhAAAAAAAAAGEAAAAAAAAAcQAAAAAAAAABAAAAAAAAAIEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAAJkAAAAAAAAAAQAAAAAAAACxAAAAAAAAAIEAAAAAAAAAyQAAAAAAAADBAAAAAAAAAFEAAAAAAAADwPwAAAAAAAPA/AAAAAAAAGEAAAAAAAAAUQAAAAAAAABxAAAAAAAAAEEAAAAAAAAAgQAAAAAAAACZAAAAAAAAACEAAAAAAAAAQQAAAAAAAAAhAAAAAAAAACEAAAAAAAAAIQAAAAAAAAPA/AAAAAAAAEEAAAAAAAAAUQAAAAAAAACRAAAAAAAAACEAAAAAAAADwPwAAAAAAAAhAAAAAAAAACEAAAAAAAADwPwAAAAAAAABAAAAAAAAAIkAAAAAAAADwPwAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAAhAAAAAAAAACEAAAAAAAADwPwAAAAAAABhAAAAAAAAACEAAAAAAAAAUQAAAAAAAACRAAAAAAAAAAAAAAAAAAAAQQAAAAAAAABBAAAAAAAAAAEAAAAAAAAAQQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAQQAAAAAAAAAhAAAAAAAAAAEAAAAAAAAAYQAAAAAAAADFAAAAAAAAAFEAAAAAAAAAUQAAAAAAAAABAAAAAAAAAGEAAAAAAAADwPwAAAAAAAAhAAAAAAAAAMkAAAAAAAAAiQAAAAAAAACZAAAAAAAAAIEAAAAAAAAAIQAAAAAAAAPA/AAAAAAAAIEAAAAAAAAAsQAAAAAAAABRAAAAAAAAACEAAAAAAAAAQQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAYQAAAAAAAAAhAAAAAAAAAFEAAAAAAAAAUQAAAAAAAAABAAAAAAAAAEEAAAAAAAAAAQAAAAAAAACJAAAAAAAAAAEAAAAAAAADwPwAAAAAAABhAAAAAAAAAJEAAAAAAAAAAQAAAAAAAABxAAAAAAAAAFEAAAAAAAAAIQAAAAAAAABBAAAAAAAAAGEAAAAAAAAAAQAAAAAAAABhAAAAAAAAAAEAAAAAAAAAiQAAAAAAAABhAAAAAAAAAGEAAAAAAAAAYQAAAAAAAABBAAAAAAAAAEEAAAAAAAAAUQAAAAAAAABhAAAAAAAAAIEAAAAAAAAAQQAAAAAAAAPA/AAAAAAAAEEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAAQAAAAAAAAABAAAAAAAAA8D8AAAAAAAAgQAAAAAAAABhAAAAAAAAAGEAAAAAAAAAUQAAAAAAAABBAAAAAAAAALEAAAAAAAAAYQAAAAAAAAC5AAAAAAAAAKkAAAAAAAAAiQAAAAAAAABxAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAgQAAAAAAAAAhAAAAAAAAAGEAAAAAAAAAIQAAAAAAAABhAAAAAAAAAFEAAAAAAAAAQQAAAAAAAAAhAAAAAAAAANkAAAAAAAAAcQAAAAAAAAAhAAAAAAAAAIkAAAAAAAAAQQAAAAAAAABRAAAAAAAAAFEAAAAAAAAAAQAAAAAAAAABAAAAAAAAACEAAAAAAAAAQQAAAAAAAAAhAAAAAAAAAFEAAAAAAAAAmQAAAAAAAAChAAAAAAAAAFEAAAAAAAAAYQAAAAAAAABRAAAAAAAAAGEAAAAAAAAAUQAAAAAAAABxAAAAAAAAAAEAAAAAAAAAkQAAAAAAAABhAAAAAAAAAEEAAAAAAAAAYQAAAAAAAAPA/AAAAAAAAAEAAAAAAAAAQQAAAAAAAACJAAAAAAAAAJEAAAAAAAAAYQAAAAAAAACBAAAAAAAAAEEAAAAAAAAAAQAAAAAAAACBAAAAAAAAAAEAAAAAAAAAAQAAAAAAAABBAAAAAAAAACEAAAAAAAAAQQAAAAAAAABhAAAAAAAAA8D8AAAAAAAAQQAAAAAAAAAhAAAAAAAAACEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAAEEAAAAAAAAAUQAAAAAAAAPA/AAAAAAAAHEAAAAAAAAAcQAAAAAAAAABAAAAAAAAAAEAAAAAAAADwPwAAAAAAAAhAAAAAAAAA8D8AAAAAAAAcQAAAAAAAAAhAAAAAAAAAGEAAAAAAAAAAQAAAAAAAABBAAAAAAAAAKkAAAAAAAADwPwAAAAAAABBAAAAAAAAAGEAAAAAAAAAAQAAAAAAAABxAAAAAAAAAAEAAAAAAAAAIQAAAAAAAABhAAAAAAAAAEEAAAAAAAAAIQAAAAAAAABBAAAAAAAAACEAAAAAAAAAAQAAAAAAAAAhAAAAAAAAAGEAAAAAAAAAQQAAAAAAAABxAAAAAAAAAKkAAAAAAAADwPwAAAAAAAPA/AAAAAAAAFEAAAAAAAAAoQAAAAAAAABRAAAAAAAAAFEAAAAAAAAAgQAAAAAAAABhAAAAAAAAANkAAAAAAAAAiQAAAAAAAADBAAAAAAAAAJkAAAAAAAAAgQAAAAAAAABxAAAAAAAAAAEAAAAAAAAAAQAAAAAAAAPA/AAAAAAAA8D8AAAAAAAAIQAAAAAAAAAhAAAAAAAAAEEAAAAAAAAAAQAAAAAAAABhAAAAAAAAAEEAAAAAAAAA8QAAAAAAAAD9AAAAAAAAAJEAAAAAAAAAuQAAAAAAAADNAAAAAAAAACEAAAAAAAAAkQAAAAAAAACRAAAAAAAAAIEAAAAAAAAAAQAAAAAAAABRAAAAAAAAAHEAAAAAAAAAcQAAAAAAAABhAAAAAAAAAFEAAAAAAAAAIQAAAAAAAABRAAAAAAAAAFEAAAAAAAAAUQAAAAAAAAPA/AAAAAAAAEEAAAAAAAAAwQAAAAAAAABhAAAAAAAAAAEAAAAAAAAAYQAAAAAAAAAhAAAAAAAAAFEAAAAAAAAAUQAAAAAAAABhAAAAAAAAAFEAAAAAAAAAIQAAAAAAAABBAAAAAAAAAEEAAAAAAAAAkQAAAAAAAACxAAAAAAAAAKEAAAAAAAAAUQAAAAAAAACBAAAAAAAAAAEAAAAAAAAAQQAAAAAAAAABAAAAAAAAACEAAAAAAAAAmQAAAAAAAABRAAAAAAAAAHEAAAAAAAAAQQAAAAAAAAABAAAAAAAAAEEAAAAAAAAAIQAAAAAAAACBAAAAAAAAALEAAAAAAAAAkQAAAAAAAABBAAAAAAAAA8D8AAAAAAAAUQAAAAAAAABBAAAAAAAAACEAAAAAAAAAgQAAAAAAAABRAAAAAAAAAAEAAAAAAAAAIQAAAAAAAAABAAAAAAAAANkAAAAAAAAAsQAAAAAAAAABAAAAAAAAA8D8AAAAAAAAIQAAAAAAAABhAAAAAAAAAHEAAAAAAAAAAQAAAAAAAAAhA\",\"dtype\":\"float64\",\"shape\":[573]}}},\"id\":\"e83567ae-885f-4893-9a64-e3d55864d7a4\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6fc281d6-1d36-4903-9007-da1a85a0daa3\",\"type\":\"Line\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"aa316ad5-6c3d-4852-839a-e1c76dd8079a\",\"type\":\"DaysTicker\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"db14c9de-acaa-4658-980f-730152882a9f\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"7e1776fa-3c4d-45de-aafa-cc28f0fee937\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"5c7e41a8-3299-45dc-8d18-4f8a1e542121\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"59f07aa4-4845-42e5-9490-676f61049f61\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"209d56dc-2df3-4137-ad23-21cd81a0ef80\",\"type\":\"DaysTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"e7413976-6bc5-4c4c-815e-1f7341961b70\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"ecdfcc1f-aace-4190-9e21-44bb5c2ea1be\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"5d9506fc-5f0e-45c1-8061-b38b1a25fa65\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"e6d6d504-71af-4aab-a6fd-6a0e857f1d12\",\"type\":\"MonthsTicker\"},{\"attributes\":{},\"id\":\"b03cb5b3-12ac-474d-ab71-5e7f8a46a17a\",\"type\":\"YearsTicker\"},{\"attributes\":{\"plot\":null,\"text\":\"views for other channel from 2013 to 2017\"},\"id\":\"14b47846-6273-4e16-94a9-b2b4ac71d285\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"faf994a9-0909-4e91-a925-e512222b861a\",\"type\":\"ToolEvents\"},{\"attributes\":{\"below\":[{\"id\":\"16f27b72-8060-4600-bfdb-ea32ce80f685\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"7dec7f77-43bd-4215-a717-5d32100667b2\",\"type\":\"LinearAxis\"}],\"plot_height\":250,\"plot_width\":800,\"renderers\":[{\"id\":\"16f27b72-8060-4600-bfdb-ea32ce80f685\",\"type\":\"DatetimeAxis\"},{\"id\":\"fdcd8338-1849-4b6e-b8e5-4f063960f1ef\",\"type\":\"Grid\"},{\"id\":\"7dec7f77-43bd-4215-a717-5d32100667b2\",\"type\":\"LinearAxis\"},{\"id\":\"cb24e096-f404-47ab-83bf-df34a9e13d5d\",\"type\":\"Grid\"},{\"id\":\"76de0fe9-f513-4127-89ff-a286450ecf0d\",\"type\":\"BoxAnnotation\"},{\"id\":\"02bff993-6921-40d3-a75c-fbee5adbaeee\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"14b47846-6273-4e16-94a9-b2b4ac71d285\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"faf994a9-0909-4e91-a925-e512222b861a\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"27882984-dd78-493b-aa59-e3e8f30ca31a\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"f20802d5-cc70-4d71-ae7a-1502ab742b52\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"1eb84eba-bbf4-4a7b-a67d-dda2e1bb41ec\",\"type\":\"DataRange1d\"}},\"id\":\"b3db8d04-2ed1-4263-97ce-4acd348006d3\",\"subtype\":\"Figure\",\"type\":\"Plot\"}],\"root_ids\":[\"cff67880-d3a7-4628-8e72-c17e012342da\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.4\"}};\n",
       "            var render_items = [{\"docid\":\"010b8e55-4d25-4fe3-8c92-2a774b8c9ddd\",\"elementid\":\"508d129b-b5f6-4216-b1e7-efc9a02847e4\",\"modelid\":\"cff67880-d3a7-4628-8e72-c17e012342da\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"508d129b-b5f6-4216-b1e7-efc9a02847e4\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show result\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "f078328e-cc03-4d14-9567-c57ae53d323f"
    }
   },
   "source": [
    "We've successfully replicated the graphs we made using **seaborn**. How will we make this more interractive? I wonder. Maybe i could keep the X axis constant and change the title and y axis label. Though we'll have to move from a column data source to easily manipulate the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next cells, i'm trying other alternatives. That would be more convienent. Otherwise, the cells above is all you need to modify."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "nbpresent": {
     "id": "4432251b-b44c-4c97-b376-70aa62d382c6"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"display: table;\"><div style=\"display: table-row;\"><div style=\"display: table-cell;\"><b title=\"bokeh.models.renderers.GlyphRenderer\">GlyphRenderer</b>(</div><div style=\"display: table-cell;\">id&nbsp;=&nbsp;'5e01278c-84f9-477b-ae49-886eff4b5127', <span id=\"7ee973cf-e7e4-40f5-a6c6-bf34416951cc\" style=\"cursor: pointer;\">&hellip;)</span></div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">data_source&nbsp;=&nbsp;ColumnDataSource(id='5a586f09-7c32-4e10-8b16-845071d6a84d', ...),</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">glyph&nbsp;=&nbsp;Line(id='a6710486-cb74-463e-b7e5-6fbe8c9316fe', ...),</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">hover_glyph&nbsp;=&nbsp;None,</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">js_callbacks&nbsp;=&nbsp;{},</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">level&nbsp;=&nbsp;'glyph',</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">name&nbsp;=&nbsp;None,</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">nonselection_glyph&nbsp;=&nbsp;Line(id='b6b9186a-68af-4302-935a-4ca7d4e5ad1c', ...),</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">selection_glyph&nbsp;=&nbsp;None,</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">tags&nbsp;=&nbsp;[],</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">visible&nbsp;=&nbsp;True,</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">x_range_name&nbsp;=&nbsp;'default',</div></div><div class=\"17c8d4d9-822f-45cf-8737-a08ac1266d18\" style=\"display: none;\"><div style=\"display: table-cell;\"></div><div style=\"display: table-cell;\">y_range_name&nbsp;=&nbsp;'default')</div></div></div>\n",
       "<script>\n",
       "(function() {\n",
       "  var expanded = false;\n",
       "  var ellipsis = document.getElementById(\"7ee973cf-e7e4-40f5-a6c6-bf34416951cc\");\n",
       "  ellipsis.addEventListener(\"click\", function() {\n",
       "    var rows = document.getElementsByClassName(\"17c8d4d9-822f-45cf-8737-a08ac1266d18\");\n",
       "    for (var i = 0; i < rows.length; i++) {\n",
       "      var el = rows[i];\n",
       "      el.style.display = expanded ? \"none\" : \"table-row\";\n",
       "    }\n",
       "    ellipsis.innerHTML = expanded ? \"&hellip;)\" : \"&lsaquo;&lsaquo;&lsaquo;\";\n",
       "    expanded = !expanded;\n",
       "  });\n",
       "})();\n",
       "</script>\n"
      ],
      "text/plain": [
       "GlyphRenderer(id='5e01278c-84f9-477b-ae49-886eff4b5127', ...)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Making a ColumnDatasource and making graph interractive\n",
    "# Make a column data source for the above graphs\n",
    "# zoom in to one year\n",
    "# plot views and subscribes x and y\n",
    "source = ColumnDataSource(data = {\n",
    "    'x'       : df1[\"date\"],\n",
    "    'y'       : df1[\"views\"],\n",
    "     })\n",
    "\n",
    "columns = df1.drop('date', axis = 1)\n",
    "columns = sorted(df.columns)\n",
    "\n",
    "p = figure(plot_width = 850, plot_height = 400, title = \"viewers for the channel Sliceace from 2011 to 2017\", \n",
    "           x_axis_label = \"year\", y_axis_label = \"viewers\", x_axis_type =\"datetime\")\n",
    "\n",
    "p.line(x = \"x\", y = \"y\", source = source, color = \"green\", legend = \"Sliceace\")\n",
    "\n",
    "# output_file(\"exploratory_linegraph.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "nbpresent": {
     "id": "f2bf6603-4468-4d23-b144-1eb0efc71e07"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"9c1b86b0-b142-4cfa-bce8-213055605474\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      document.getElementById(\"9c1b86b0-b142-4cfa-bce8-213055605474\").textContent = \"BokehJS successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"9c1b86b0-b142-4cfa-bce8-213055605474\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '9c1b86b0-b142-4cfa-bce8-213055605474' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"9c1b86b0-b142-4cfa-bce8-213055605474\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"9c1b86b0-b142-4cfa-bce8-213055605474\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# embed plot to notebook\n",
    "output_notebook() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "nbpresent": {
     "id": "d0dc3a7c-2f15-4910-87af-d9b8f24396fa"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"842e86e1-b4a5-40c0-8769-34c9e6951605\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        document.getElementById(\"842e86e1-b4a5-40c0-8769-34c9e6951605\").textContent = \"BokehJS successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"842e86e1-b4a5-40c0-8769-34c9e6951605\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid '842e86e1-b4a5-40c0-8769-34c9e6951605' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"f7fc9056-e704-46a6-b5d8-3b676105ecfc\":{\"roots\":{\"references\":[{\"attributes\":{\"items\":[{\"id\":\"f0bc6952-abc3-4405-9325-ce327a2cf493\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"da87968b-197f-4bee-b22a-fedee40b7f9a\",\"type\":\"Legend\"},{\"attributes\":{},\"id\":\"1057d621-2e1d-4882-a947-9b7f87314826\",\"type\":\"YearsTicker\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"8ea1c76c-559b-4343-8ca8-1c42c35eb359\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"label\":{\"value\":\"Sliceace\"},\"renderers\":[{\"id\":\"5e01278c-84f9-477b-ae49-886eff4b5127\",\"type\":\"GlyphRenderer\"}]},\"id\":\"f0bc6952-abc3-4405-9325-ce327a2cf493\",\"type\":\"LegendItem\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"a96da4ad-7ed5-42ed-8d21-5d3885d126d0\",\"type\":\"PanTool\"},{\"id\":\"b96959ee-f95f-4c29-b2f9-d3bdf5bbfcb0\",\"type\":\"WheelZoomTool\"},{\"id\":\"00742f10-7f1f-41df-ba69-f23294234cd9\",\"type\":\"BoxZoomTool\"},{\"id\":\"60ccd608-284a-446f-adb6-5d94014d02b7\",\"type\":\"SaveTool\"},{\"id\":\"4e5b87b2-eebb-4ce8-aba0-8776a1ad3c5d\",\"type\":\"ResetTool\"},{\"id\":\"cde29a58-9268-48cc-b2ad-b82b5edd4e90\",\"type\":\"HelpTool\"}]},\"id\":\"242ed6f3-5c0c-47b0-b5a2-c889094da721\",\"type\":\"Toolbar\"},{\"attributes\":{\"callback\":null},\"id\":\"dca9bbf1-aecd-4be2-af80-85367bcaff95\",\"type\":\"DataRange1d\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"4d05c264-8445-4494-bf6e-fce83b2315a6\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"below\":[{\"id\":\"e13863a9-6a35-411d-9f31-ac228d871f90\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"74671ade-ab60-4b09-86ce-b9e55b2620fb\",\"type\":\"LinearAxis\"}],\"plot_height\":400,\"plot_width\":850,\"renderers\":[{\"id\":\"e13863a9-6a35-411d-9f31-ac228d871f90\",\"type\":\"DatetimeAxis\"},{\"id\":\"f3d56062-1ca9-4529-a9c9-46fb4f28c466\",\"type\":\"Grid\"},{\"id\":\"74671ade-ab60-4b09-86ce-b9e55b2620fb\",\"type\":\"LinearAxis\"},{\"id\":\"db6d076a-9baa-460f-8292-a50fbcc8c83c\",\"type\":\"Grid\"},{\"id\":\"f591ee6f-b72a-43ea-8717-da590a555683\",\"type\":\"BoxAnnotation\"},{\"id\":\"da87968b-197f-4bee-b22a-fedee40b7f9a\",\"type\":\"Legend\"},{\"id\":\"5e01278c-84f9-477b-ae49-886eff4b5127\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"e0ca9e26-b920-41af-9846-608e576d636f\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"d32d422f-425d-4086-8414-dfb3a8f505e2\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"242ed6f3-5c0c-47b0-b5a2-c889094da721\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"ad4b4e30-7c9d-47b7-9867-335453fe38ff\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"dca9bbf1-aecd-4be2-af80-85367bcaff95\",\"type\":\"DataRange1d\"}},\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"dcbefa27-91cf-40a5-a1fc-670d9a6ff6f6\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"2579e3f2-5c49-4cf7-ba4b-3afd4008fb83\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"plot\":null,\"text\":\"viewers for the channel Sliceace from 2011 to 2017\"},\"id\":\"e0ca9e26-b920-41af-9846-608e576d636f\",\"type\":\"Title\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"c751c77a-5540-433f-9bf0-b42d6de712ec\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"axis_label\":\"year\",\"formatter\":{\"id\":\"34f3ccbe-603e-464e-9789-dda639825569\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"4e95f039-1894-474f-88fd-7b0344ec0334\",\"type\":\"DatetimeTicker\"}},\"id\":\"e13863a9-6a35-411d-9f31-ac228d871f90\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"60ccd608-284a-446f-adb6-5d94014d02b7\",\"type\":\"SaveTool\"},{\"attributes\":{\"callback\":null},\"id\":\"ad4b4e30-7c9d-47b7-9867-335453fe38ff\",\"type\":\"DataRange1d\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"4e95f039-1894-474f-88fd-7b0344ec0334\",\"type\":\"DatetimeTicker\"}},\"id\":\"f3d56062-1ca9-4529-a9c9-46fb4f28c466\",\"type\":\"Grid\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"b6b9186a-68af-4302-935a-4ca7d4e5ad1c\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"ff9eda3b-27f8-4a91-9085-f4deb32cde09\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"d32d422f-425d-4086-8414-dfb3a8f505e2\",\"type\":\"ToolEvents\"},{\"attributes\":{},\"id\":\"9ff27e90-c0c0-4629-9b27-57889f161ddf\",\"type\":\"BasicTicker\"},{\"attributes\":{\"axis_label\":\"viewers\",\"formatter\":{\"id\":\"ff9eda3b-27f8-4a91-9085-f4deb32cde09\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9ff27e90-c0c0-4629-9b27-57889f161ddf\",\"type\":\"BasicTicker\"}},\"id\":\"74671ade-ab60-4b09-86ce-b9e55b2620fb\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"34f3ccbe-603e-464e-9789-dda639825569\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"30190928-b31c-4204-bcda-3c5c7b5f9b2c\",\"type\":\"DaysTicker\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"a96da4ad-7ed5-42ed-8d21-5d3885d126d0\",\"type\":\"PanTool\"},{\"attributes\":{\"data_source\":{\"id\":\"5a586f09-7c32-4e10-8b16-845071d6a84d\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"a6710486-cb74-463e-b7e5-6fbe8c9316fe\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"b6b9186a-68af-4302-935a-4ca7d4e5ad1c\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"5e01278c-84f9-477b-ae49-886eff4b5127\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"9ff27e90-c0c0-4629-9b27-57889f161ddf\",\"type\":\"BasicTicker\"}},\"id\":\"db6d076a-9baa-460f-8292-a50fbcc8c83c\",\"type\":\"Grid\"},{\"attributes\":{\"line_color\":{\"value\":\"green\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"a6710486-cb74-463e-b7e5-6fbe8c9316fe\",\"type\":\"Line\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"717770ea-77eb-45d2-9fab-d36da517ce6f\",\"type\":\"DaysTicker\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]}}},\"id\":\"5a586f09-7c32-4e10-8b16-845071d6a84d\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"f591ee6f-b72a-43ea-8717-da590a555683\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b96959ee-f95f-4c29-b2f9-d3bdf5bbfcb0\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"775bc482-58c1-414f-bdce-0933c80f29f7\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"4e95f039-1894-474f-88fd-7b0344ec0334\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"overlay\":{\"id\":\"f591ee6f-b72a-43ea-8717-da590a555683\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"00742f10-7f1f-41df-ba69-f23294234cd9\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"7f200c66-1974-43d7-9e95-b60557761a0e\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"cde29a58-9268-48cc-b2ad-b82b5edd4e90\",\"type\":\"HelpTool\"},{\"attributes\":{\"plot\":{\"id\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"4e5b87b2-eebb-4ce8-aba0-8776a1ad3c5d\",\"type\":\"ResetTool\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"26c4f0e4-49fc-4e28-bad4-8f185d8cb53b\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"c093b7d5-5413-42e0-8541-e7cab44feb25\",\"type\":\"DaysTicker\"}],\"root_ids\":[\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.4\"}};\n",
       "            var render_items = [{\"docid\":\"f7fc9056-e704-46a6-b5d8-3b676105ecfc\",\"elementid\":\"842e86e1-b4a5-40c0-8769-34c9e6951605\",\"modelid\":\"b671e72a-bf4b-4b54-8e9d-20d214cd0abd\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"842e86e1-b4a5-40c0-8769-34c9e6951605\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "dbcb27c7-1dd7-4449-a1e3-48605601c9ab"
    }
   },
   "source": [
    "Looking good thus far. Next, we'll try adding a dropdown to change the variable since a YouTuber may be interested in how other data is moving through the graph like subscribers_lost and card clicks to mention afew. \n",
    "\n",
    "Let's get at it: \n",
    "* Add a dropdown\n",
    "* Make the line update like the gapminder visualization tool here [gapminder bubble plot](https://www.gapminder.org/tools/#_locale_id=en;&chart-type=bubbles)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "nbpresent": {
     "id": "2cacab62-71ba-47fa-87b6-bc5581150e3f"
    }
   },
   "outputs": [],
   "source": [
    "# Making the necessary imports\n",
    "from bokeh.models import ColumnDataSource\n",
    "from bokeh.models import Select\n",
    "from bokeh.layouts import row\n",
    "from bokeh.io import curdoc\n",
    "from bokeh.layouts import widgetbox\n",
    "from bokeh.models import Slider\n",
    "\n",
    "# Create ColumnDataSource: source\n",
    "# add a drop duplicates column to ensure that the rows are of the same length\n",
    "source = ColumnDataSource(data={\n",
    "    'x' : df1[\"date\"],\n",
    "    'y' : df1[\"views\"]\n",
    "})\n",
    "\n",
    "# Create a plot\n",
    "plot = figure(x_axis_type =\"datetime\")\n",
    "\n",
    "# Add lines to the plot\n",
    "plot.line('x', 'y', source = source, legend = \"Sliceace\")\n",
    "\n",
    "# Defining a callback function: update_plot\n",
    "def update_plot(attr, old, new):\n",
    "    # if the new selection is views\n",
    "    if new == \"views\":\n",
    "        source.data = {\n",
    "            \"x\" : df1[\"date\"],\n",
    "            \"y\" : df1[\"views\"]\n",
    "        }\n",
    "    # else, update y\n",
    "    else:\n",
    "        source.data = {\n",
    "            \"x\" : df1[\"date\"],\n",
    "            \"y\" : df1[\"subscribers\"]\n",
    "        }\n",
    "        \n",
    "# remove the date column\n",
    "columns = df1.drop('date', axis = 1)\n",
    "columns = df1.drop('channel', axis = 1)\n",
    "columns = sorted(df.columns)\n",
    "\n",
    "# create a dropdown select widget\n",
    "select = Select(title = \"y-axis\", options = columns, value = \"views\")\n",
    "\n",
    "# Attach the update_plot callback to the 'value' property of select\n",
    "select.on_change(\"value\", update_plot)\n",
    "\n",
    "# Create layout and add to current document\n",
    "layout2 = row(select, plot)\n",
    "curdoc().add_root(layout2)        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "nbpresent": {
     "id": "12df08be-201d-454d-bc02-aace5e92fd72"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"http://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"67f0e7b2-b715-4a61-ac39-9e37012e17f6\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(global) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "\n",
       "  if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "    window._bokeh_onload_callbacks = [];\n",
       "    window._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "\n",
       "  \n",
       "  if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    window._bokeh_timeout = Date.now() + 5000;\n",
       "    window._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    if (window.Bokeh !== undefined) {\n",
       "      document.getElementById(\"67f0e7b2-b715-4a61-ac39-9e37012e17f6\").textContent = \"BokehJS successfully loaded.\";\n",
       "    } else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "    delete window._bokeh_onload_callbacks\n",
       "    console.info(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(js_urls, callback) {\n",
       "    window._bokeh_onload_callbacks.push(callback);\n",
       "    if (window._bokeh_is_loading > 0) {\n",
       "      console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    window._bokeh_is_loading = js_urls.length;\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      var s = document.createElement('script');\n",
       "      s.src = url;\n",
       "      s.async = false;\n",
       "      s.onreadystatechange = s.onload = function() {\n",
       "        window._bokeh_is_loading--;\n",
       "        if (window._bokeh_is_loading === 0) {\n",
       "          console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "          run_callbacks()\n",
       "        }\n",
       "      };\n",
       "      s.onerror = function() {\n",
       "        console.warn(\"failed to load library \" + url);\n",
       "      };\n",
       "      console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "    }\n",
       "  };var element = document.getElementById(\"67f0e7b2-b715-4a61-ac39-9e37012e17f6\");\n",
       "  if (element == null) {\n",
       "    console.log(\"Bokeh: ERROR: autoload.js configured with elementid '67f0e7b2-b715-4a61-ac39-9e37012e17f6' but no matching script tag was found. \")\n",
       "    return false;\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.js\"];\n",
       "\n",
       "  var inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    \n",
       "    function(Bokeh) {\n",
       "      \n",
       "      document.getElementById(\"67f0e7b2-b715-4a61-ac39-9e37012e17f6\").textContent = \"BokehJS is loading...\";\n",
       "\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-0.12.4.min.css\");\n",
       "      console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "      Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-0.12.4.min.css\");\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i](window.Bokeh);\n",
       "      }if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < window._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!window._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      window._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      var cell = $(document.getElementById(\"67f0e7b2-b715-4a61-ac39-9e37012e17f6\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (window._bokeh_is_loading === 0) {\n",
       "    console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(js_urls, function() {\n",
       "      console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(this));"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "nbpresent": {
     "id": "1cba4f5c-9a00-4026-871b-4de978ec4b03"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <div class=\"bk-plotdiv\" id=\"ca2f28d5-3427-452e-883d-2df58dd8f0c5\"></div>\n",
       "    </div>\n",
       "<script type=\"text/javascript\">\n",
       "  \n",
       "  (function(global) {\n",
       "    function now() {\n",
       "      return new Date();\n",
       "    }\n",
       "\n",
       "    var force = false;\n",
       "\n",
       "    if (typeof (window._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
       "      window._bokeh_onload_callbacks = [];\n",
       "      window._bokeh_is_loading = undefined;\n",
       "    }\n",
       "\n",
       "\n",
       "    \n",
       "    if (typeof (window._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "      window._bokeh_timeout = Date.now() + 0;\n",
       "      window._bokeh_failed_load = false;\n",
       "    }\n",
       "\n",
       "    var NB_LOAD_WARNING = {'data': {'text/html':\n",
       "       \"<div style='background-color: #fdd'>\\n\"+\n",
       "       \"<p>\\n\"+\n",
       "       \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "       \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "       \"</p>\\n\"+\n",
       "       \"<ul>\\n\"+\n",
       "       \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "       \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "       \"</ul>\\n\"+\n",
       "       \"<code>\\n\"+\n",
       "       \"from bokeh.resources import INLINE\\n\"+\n",
       "       \"output_notebook(resources=INLINE)\\n\"+\n",
       "       \"</code>\\n\"+\n",
       "       \"</div>\"}};\n",
       "\n",
       "    function display_loaded() {\n",
       "      if (window.Bokeh !== undefined) {\n",
       "        document.getElementById(\"ca2f28d5-3427-452e-883d-2df58dd8f0c5\").textContent = \"BokehJS successfully loaded.\";\n",
       "      } else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(display_loaded, 100)\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function run_callbacks() {\n",
       "      window._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
       "      delete window._bokeh_onload_callbacks\n",
       "      console.info(\"Bokeh: all callbacks have finished\");\n",
       "    }\n",
       "\n",
       "    function load_libs(js_urls, callback) {\n",
       "      window._bokeh_onload_callbacks.push(callback);\n",
       "      if (window._bokeh_is_loading > 0) {\n",
       "        console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "        return null;\n",
       "      }\n",
       "      if (js_urls == null || js_urls.length === 0) {\n",
       "        run_callbacks();\n",
       "        return null;\n",
       "      }\n",
       "      console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "      window._bokeh_is_loading = js_urls.length;\n",
       "      for (var i = 0; i < js_urls.length; i++) {\n",
       "        var url = js_urls[i];\n",
       "        var s = document.createElement('script');\n",
       "        s.src = url;\n",
       "        s.async = false;\n",
       "        s.onreadystatechange = s.onload = function() {\n",
       "          window._bokeh_is_loading--;\n",
       "          if (window._bokeh_is_loading === 0) {\n",
       "            console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
       "            run_callbacks()\n",
       "          }\n",
       "        };\n",
       "        s.onerror = function() {\n",
       "          console.warn(\"failed to load library \" + url);\n",
       "        };\n",
       "        console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      }\n",
       "    };var element = document.getElementById(\"ca2f28d5-3427-452e-883d-2df58dd8f0c5\");\n",
       "    if (element == null) {\n",
       "      console.log(\"Bokeh: ERROR: autoload.js configured with elementid 'ca2f28d5-3427-452e-883d-2df58dd8f0c5' but no matching script tag was found. \")\n",
       "      return false;\n",
       "    }\n",
       "\n",
       "    var js_urls = [];\n",
       "\n",
       "    var inline_js = [\n",
       "      function(Bokeh) {\n",
       "        (function() {\n",
       "          var fn = function() {\n",
       "            var docs_json = {\"813049c3-092b-42ef-b76f-44031ac41397\":{\"roots\":{\"references\":[{\"attributes\":{\"children\":[{\"id\":\"b7db8962-c905-448f-80c2-23b40858da69\",\"type\":\"Select\"}]},\"id\":\"0fc1bc79-e6f0-4dd2-ad13-46a0b16b2d81\",\"type\":\"WidgetBox\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"3a546f7f-a050-4881-b77a-a838c721e522\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"a8162641-4fe4-4f68-8262-4f60092c16c4\",\"type\":\"PanTool\"},{\"attributes\":{\"plot\":null,\"text\":\"\"},\"id\":\"ee00686b-6277-42be-bcdb-2428dcb0cf59\",\"type\":\"Title\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"9f2eb565-6794-4613-8b35-6d01f81ff0b9\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"3a546f7f-a050-4881-b77a-a838c721e522\",\"type\":\"BoxAnnotation\"},\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"8af987cb-8e06-4deb-a47e-a82e9d1bed8e\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"17b4cbef-8158-4e08-b62d-5611044d8934\",\"type\":\"SaveTool\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"1eb73e9b-4749-45a2-a28f-ab268f09f5e6\",\"type\":\"ResetTool\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"b2411341-3ea5-475b-8338-7ed60aba8a8f\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"28e13363-25a7-4c10-b191-f91787954c20\",\"type\":\"DatetimeTickFormatter\"},{\"attributes\":{},\"id\":\"8aff884b-1847-46f2-8411-59909d8592a9\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"max_interval\":500.0,\"num_minor_ticks\":0},\"id\":\"0a28064e-54b0-4cb7-a549-821169fc5e88\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"base\":60,\"mantissas\":[1,2,5,10,15,20,30],\"max_interval\":1800000.0,\"min_interval\":1000.0,\"num_minor_ticks\":0},\"id\":\"5d4b34e4-f2ab-4bd3-8551-dc5759050440\",\"type\":\"AdaptiveTicker\"},{\"attributes\":{\"callback\":null,\"options\":[\"annotation_click_through_rate\",\"annotation_clicks\",\"annotation_close_rate\",\"annotation_closes\",\"annotations_shown\",\"average_percentage_viewed\",\"average_view_duration\",\"card_clicks\",\"card_teaser_clicks\",\"card_teasers_shown\",\"cards_shown\",\"channel\",\"clickable_annotations_shown\",\"clicks_per_card_shown\",\"clicks_per_card_teaser_shown\",\"clicks_per_end_screen_element_shown\",\"closable_annotations_shown\",\"comments\",\"dislikes\",\"dislikes_added\",\"dislikes_removed\",\"end_screen_element_clicks\",\"end_screen_elements_shown\",\"likes\",\"likes_added\",\"likes_removed\",\"shares\",\"subscribers\",\"subscribers_gained\",\"subscribers_lost\",\"videos_added\",\"videos_added_to_playlists\",\"videos_in_playlists\",\"videos_published\",\"videos_removed_from_playlists\",\"views\",\"watch_time_hours\",\"watch_time_minutes\",\"youtube_red_views\",\"youtube_red_watch_time_hours\",\"youtube_red_watch_time_minutes\"],\"title\":\"y-axis\",\"value\":\"views\"},\"id\":\"b7db8962-c905-448f-80c2-23b40858da69\",\"type\":\"Select\"},{\"attributes\":{\"days\":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]},\"id\":\"f4789b30-e668-44e8-8dad-a18c42654fa1\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,4,7,10,13,16,19,22,25,28]},\"id\":\"808d9749-0018-429b-b0a9-527aa56590e8\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,8,15,22]},\"id\":\"7611b419-6fa0-430c-8541-c7b849b92ce0\",\"type\":\"DaysTicker\"},{\"attributes\":{\"days\":[1,15]},\"id\":\"12d149e0-333a-45a5-b30e-a4a85693c1b8\",\"type\":\"DaysTicker\"},{\"attributes\":{\"months\":[0,1,2,3,4,5,6,7,8,9,10,11]},\"id\":\"fc8e3bae-7955-4e04-85e3-78290de10903\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1529d167-acda-410c-af25-e4a4b419a7d8\",\"type\":\"Line\"},{\"attributes\":{\"months\":[0,2,4,6,8,10]},\"id\":\"57f3b011-14b1-490d-9dac-998b534387fb\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"data_source\":{\"id\":\"d1177d64-feb7-464e-b00e-5ff701337447\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1529d167-acda-410c-af25-e4a4b419a7d8\",\"type\":\"Line\"},\"hover_glyph\":null,\"nonselection_glyph\":{\"id\":\"632f4f63-5f87-484e-aab1-10138ae87968\",\"type\":\"Line\"},\"selection_glyph\":null},\"id\":\"0d2bebdb-2acf-42bf-a4ec-5a4b23c2570d\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"months\":[0,4,8]},\"id\":\"19af4e24-1723-4cd5-b92e-61d55e520756\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"below\":[{\"id\":\"93c3d098-19d6-4a0e-b01d-dde39c7ca138\",\"type\":\"DatetimeAxis\"}],\"left\":[{\"id\":\"4d622e79-ed9b-4571-8d81-783ad2c4eb97\",\"type\":\"LinearAxis\"}],\"renderers\":[{\"id\":\"93c3d098-19d6-4a0e-b01d-dde39c7ca138\",\"type\":\"DatetimeAxis\"},{\"id\":\"0b231543-8091-49ad-9a62-feddca6449f9\",\"type\":\"Grid\"},{\"id\":\"4d622e79-ed9b-4571-8d81-783ad2c4eb97\",\"type\":\"LinearAxis\"},{\"id\":\"ba2aa6ac-f2fe-4adf-9172-bce87e4ecbf8\",\"type\":\"Grid\"},{\"id\":\"3a546f7f-a050-4881-b77a-a838c721e522\",\"type\":\"BoxAnnotation\"},{\"id\":\"e409943a-b5c5-4959-b004-85d42adf83e5\",\"type\":\"Legend\"},{\"id\":\"0d2bebdb-2acf-42bf-a4ec-5a4b23c2570d\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"ee00686b-6277-42be-bcdb-2428dcb0cf59\",\"type\":\"Title\"},\"tool_events\":{\"id\":\"efca58bb-e557-48a8-9e51-ede19c4c6e57\",\"type\":\"ToolEvents\"},\"toolbar\":{\"id\":\"ba67de7d-5659-486c-9726-23b27ab353b7\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"8b9b51be-61e8-457a-8dcf-37fbd33e7ea2\",\"type\":\"DataRange1d\"},\"y_range\":{\"id\":\"8a42a674-4107-48af-b4ed-c0133fbc492a\",\"type\":\"DataRange1d\"}},\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"months\":[0,6]},\"id\":\"bd2bbcd3-2678-4197-a412-d9270062aa4b\",\"type\":\"MonthsTicker\"},{\"attributes\":{\"callback\":null,\"column_names\":[\"x\",\"y\"],\"data\":{\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"shape\":[573]}}},\"id\":\"d1177d64-feb7-464e-b00e-5ff701337447\",\"type\":\"ColumnDataSource\"},{\"attributes\":{},\"id\":\"66bab308-14ae-44a7-a86d-662018267bf8\",\"type\":\"YearsTicker\"},{\"attributes\":{},\"id\":\"efca58bb-e557-48a8-9e51-ede19c4c6e57\",\"type\":\"ToolEvents\"},{\"attributes\":{\"items\":[{\"id\":\"39100605-9d8a-441e-96aa-ff52161e5cfb\",\"type\":\"LegendItem\"}],\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}},\"id\":\"e409943a-b5c5-4959-b004-85d42adf83e5\",\"type\":\"Legend\"},{\"attributes\":{\"callback\":null},\"id\":\"8b9b51be-61e8-457a-8dcf-37fbd33e7ea2\",\"type\":\"DataRange1d\"},{\"attributes\":{\"label\":{\"value\":\"Sliceace\"},\"renderers\":[{\"id\":\"0d2bebdb-2acf-42bf-a4ec-5a4b23c2570d\",\"type\":\"GlyphRenderer\"}]},\"id\":\"39100605-9d8a-441e-96aa-ff52161e5cfb\",\"type\":\"LegendItem\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"a8162641-4fe4-4f68-8262-4f60092c16c4\",\"type\":\"PanTool\"},{\"id\":\"9f2eb565-6794-4613-8b35-6d01f81ff0b9\",\"type\":\"WheelZoomTool\"},{\"id\":\"8af987cb-8e06-4deb-a47e-a82e9d1bed8e\",\"type\":\"BoxZoomTool\"},{\"id\":\"17b4cbef-8158-4e08-b62d-5611044d8934\",\"type\":\"SaveTool\"},{\"id\":\"1eb73e9b-4749-45a2-a28f-ab268f09f5e6\",\"type\":\"ResetTool\"},{\"id\":\"b2411341-3ea5-475b-8338-7ed60aba8a8f\",\"type\":\"HelpTool\"}]},\"id\":\"ba67de7d-5659-486c-9726-23b27ab353b7\",\"type\":\"Toolbar\"},{\"attributes\":{\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"632f4f63-5f87-484e-aab1-10138ae87968\",\"type\":\"Line\"},{\"attributes\":{\"callback\":null},\"id\":\"8a42a674-4107-48af-b4ed-c0133fbc492a\",\"type\":\"DataRange1d\"},{\"attributes\":{\"children\":[{\"id\":\"0fc1bc79-e6f0-4dd2-ad13-46a0b16b2d81\",\"type\":\"WidgetBox\"},{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"}]},\"id\":\"a7045b9e-314b-4de9-8972-f9f91d47484e\",\"type\":\"Row\"},{\"attributes\":{\"formatter\":{\"id\":\"28e13363-25a7-4c10-b191-f91787954c20\",\"type\":\"DatetimeTickFormatter\"},\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"77f7ad63-6a12-4b62-bea9-cd1cdcca50f7\",\"type\":\"DatetimeTicker\"}},\"id\":\"93c3d098-19d6-4a0e-b01d-dde39c7ca138\",\"type\":\"DatetimeAxis\"},{\"attributes\":{\"num_minor_ticks\":5},\"id\":\"77f7ad63-6a12-4b62-bea9-cd1cdcca50f7\",\"type\":\"DatetimeTicker\"},{\"attributes\":{\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"77f7ad63-6a12-4b62-bea9-cd1cdcca50f7\",\"type\":\"DatetimeTicker\"}},\"id\":\"0b231543-8091-49ad-9a62-feddca6449f9\",\"type\":\"Grid\"},{\"attributes\":{\"formatter\":{\"id\":\"8aff884b-1847-46f2-8411-59909d8592a9\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"182f76a9-f02a-4806-9135-a6262fdd6ba3\",\"type\":\"BasicTicker\"}},\"id\":\"4d622e79-ed9b-4571-8d81-783ad2c4eb97\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"182f76a9-f02a-4806-9135-a6262fdd6ba3\",\"type\":\"BasicTicker\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"e9424bd7-6314-40cf-8712-d20385ddc540\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"182f76a9-f02a-4806-9135-a6262fdd6ba3\",\"type\":\"BasicTicker\"}},\"id\":\"ba2aa6ac-f2fe-4adf-9172-bce87e4ecbf8\",\"type\":\"Grid\"},{\"attributes\":{\"base\":24,\"mantissas\":[1,2,4,6,8,12],\"max_interval\":43200000.0,\"min_interval\":3600000.0,\"num_minor_ticks\":0},\"id\":\"44f659f6-a07e-4550-9665-915308a4b2dc\",\"type\":\"AdaptiveTicker\"}],\"root_ids\":[\"a7045b9e-314b-4de9-8972-f9f91d47484e\"]},\"title\":\"Bokeh Application\",\"version\":\"0.12.4\"}};\n",
       "            var render_items = [{\"docid\":\"813049c3-092b-42ef-b76f-44031ac41397\",\"elementid\":\"ca2f28d5-3427-452e-883d-2df58dd8f0c5\",\"modelid\":\"a7045b9e-314b-4de9-8972-f9f91d47484e\"}];\n",
       "            \n",
       "            Bokeh.embed.embed_items(docs_json, render_items);\n",
       "          };\n",
       "          if (document.readyState != \"loading\") fn();\n",
       "          else document.addEventListener(\"DOMContentLoaded\", fn);\n",
       "        })();\n",
       "\n",
       "      },\n",
       "      function(Bokeh) {\n",
       "      }\n",
       "    ];\n",
       "\n",
       "    function run_inline_js() {\n",
       "      \n",
       "      if ((window.Bokeh !== undefined) || (force === true)) {\n",
       "        for (var i = 0; i < inline_js.length; i++) {\n",
       "          inline_js[i](window.Bokeh);\n",
       "        }if (force === true) {\n",
       "          display_loaded();\n",
       "        }} else if (Date.now() < window._bokeh_timeout) {\n",
       "        setTimeout(run_inline_js, 100);\n",
       "      } else if (!window._bokeh_failed_load) {\n",
       "        console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "        window._bokeh_failed_load = true;\n",
       "      } else if (force !== true) {\n",
       "        var cell = $(document.getElementById(\"ca2f28d5-3427-452e-883d-2df58dd8f0c5\")).parents('.cell').data().cell;\n",
       "        cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "      }\n",
       "\n",
       "    }\n",
       "\n",
       "    if (window._bokeh_is_loading === 0) {\n",
       "      console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "      run_inline_js();\n",
       "    } else {\n",
       "      load_libs(js_urls, function() {\n",
       "        console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "        run_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }(this));\n",
       "</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show(layout2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "nbpresent": {
     "id": "24030466-be5e-466d-9a35-7e2c46b47700"
    }
   },
   "source": [
    "As you can see the plot is not updating. However, i've made the visualization that i intended to make that compares different variables YouTube reports about a YouTube channel. Can you improve it?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  },
  "nbpresent": {
   "slides": {
    "7a95bdd6-f576-41ed-817c-e4cfc1968961": {
     "id": "7a95bdd6-f576-41ed-817c-e4cfc1968961",
     "prev": null,
     "regions": {
      "f4129462-0923-4605-a425-9d8c3261b965": {
       "attrs": {
        "height": 1,
        "width": 1,
        "x": -0.0023752969121140144,
        "y": 0.002111375032990235
       },
       "id": "f4129462-0923-4605-a425-9d8c3261b965"
      }
     }
    }
   },
   "themes": {
    "default": "c763f58e-a863-4673-ad29-9b407cec08f3",
    "theme": {
     "c763f58e-a863-4673-ad29-9b407cec08f3": {
      "backgrounds": {
       "backgroundColor": {
        "background-color": "backgroundColor",
        "id": "backgroundColor"
       }
      },
      "id": "c763f58e-a863-4673-ad29-9b407cec08f3",
      "palette": {
       "backgroundColor": {
        "id": "backgroundColor",
        "rgb": [
         43,
         43,
         43
        ]
       },
       "headingColor": {
        "id": "headingColor",
        "rgb": [
         238,
         238,
         238
        ]
       },
       "linkColor": {
        "id": "linkColor",
        "rgb": [
         19,
         218,
         236
        ]
       },
       "mainColor": {
        "id": "mainColor",
        "rgb": [
         238,
         238,
         238
        ]
       }
      },
      "rules": {
       "a": {
        "color": "linkColor"
       },
       "h1": {
        "color": "headingColor",
        "font-family": "Oswald",
        "font-size": 7
       },
       "h2": {
        "color": "headingColor",
        "font-family": "Oswald",
        "font-size": 5
       },
       "h3": {
        "color": "headingColor",
        "font-family": "Oswald",
        "font-size": 3.75
       },
       "h4": {
        "color": "headingColor",
        "font-family": "Oswald",
        "font-size": 3
       },
       "h5": {
        "color": "headingColor",
        "font-family": "Oswald"
       },
       "h6": {
        "color": "headingColor",
        "font-family": "Oswald"
       },
       "h7": {
        "color": "headingColor",
        "font-family": "Oswald"
       },
       "li": {
        "color": "mainColor",
        "font-family": "Lato",
        "font-size": 5
       },
       "p": {
        "color": "mainColor",
        "font-family": "Lato",
        "font-size": 5
       }
      },
      "text-base": {
       "color": "mainColor",
       "font-family": "Lato",
       "font-size": 5
      }
     }
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}