Ted_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9c991e8e",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Introduction to dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f1b3b29c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "22c50985",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "57b5a236",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted=pd.read_csv('ted.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8c629a1f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>comments</th>\n",
       "      <th>description</th>\n",
       "      <th>duration</th>\n",
       "      <th>event</th>\n",
       "      <th>film_date</th>\n",
       "      <th>languages</th>\n",
       "      <th>main_speaker</th>\n",
       "      <th>name</th>\n",
       "      <th>num_speaker</th>\n",
       "      <th>published_date</th>\n",
       "      <th>ratings</th>\n",
       "      <th>related_talks</th>\n",
       "      <th>speaker_occupation</th>\n",
       "      <th>tags</th>\n",
       "      <th>title</th>\n",
       "      <th>url</th>\n",
       "      <th>views</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4553</td>\n",
       "      <td>Sir Ken Robinson makes an entertaining and pro...</td>\n",
       "      <td>1164</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140825600</td>\n",
       "      <td>60</td>\n",
       "      <td>Ken Robinson</td>\n",
       "      <td>Ken Robinson: Do schools kill creativity?</td>\n",
       "      <td>1</td>\n",
       "      <td>1151367060</td>\n",
       "      <td>[{'id': 7, 'name': 'Funny', 'count': 19645}, {...</td>\n",
       "      <td>[{'id': 865, 'hero': 'https://pe.tedcdn.com/im...</td>\n",
       "      <td>Author/educator</td>\n",
       "      <td>['children', 'creativity', 'culture', 'dance',...</td>\n",
       "      <td>Do schools kill creativity?</td>\n",
       "      <td>https://www.ted.com/talks/ken_robinson_says_sc...</td>\n",
       "      <td>47227110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>265</td>\n",
       "      <td>With the same humor and humanity he exuded in ...</td>\n",
       "      <td>977</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140825600</td>\n",
       "      <td>43</td>\n",
       "      <td>Al Gore</td>\n",
       "      <td>Al Gore: Averting the climate crisis</td>\n",
       "      <td>1</td>\n",
       "      <td>1151367060</td>\n",
       "      <td>[{'id': 7, 'name': 'Funny', 'count': 544}, {'i...</td>\n",
       "      <td>[{'id': 243, 'hero': 'https://pe.tedcdn.com/im...</td>\n",
       "      <td>Climate advocate</td>\n",
       "      <td>['alternative energy', 'cars', 'climate change...</td>\n",
       "      <td>Averting the climate crisis</td>\n",
       "      <td>https://www.ted.com/talks/al_gore_on_averting_...</td>\n",
       "      <td>3200520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>124</td>\n",
       "      <td>New York Times columnist David Pogue takes aim...</td>\n",
       "      <td>1286</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140739200</td>\n",
       "      <td>26</td>\n",
       "      <td>David Pogue</td>\n",
       "      <td>David Pogue: Simplicity sells</td>\n",
       "      <td>1</td>\n",
       "      <td>1151367060</td>\n",
       "      <td>[{'id': 7, 'name': 'Funny', 'count': 964}, {'i...</td>\n",
       "      <td>[{'id': 1725, 'hero': 'https://pe.tedcdn.com/i...</td>\n",
       "      <td>Technology columnist</td>\n",
       "      <td>['computers', 'entertainment', 'interface desi...</td>\n",
       "      <td>Simplicity sells</td>\n",
       "      <td>https://www.ted.com/talks/david_pogue_says_sim...</td>\n",
       "      <td>1636292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>200</td>\n",
       "      <td>In an emotionally charged talk, MacArthur-winn...</td>\n",
       "      <td>1116</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140912000</td>\n",
       "      <td>35</td>\n",
       "      <td>Majora Carter</td>\n",
       "      <td>Majora Carter: Greening the ghetto</td>\n",
       "      <td>1</td>\n",
       "      <td>1151367060</td>\n",
       "      <td>[{'id': 3, 'name': 'Courageous', 'count': 760}...</td>\n",
       "      <td>[{'id': 1041, 'hero': 'https://pe.tedcdn.com/i...</td>\n",
       "      <td>Activist for environmental justice</td>\n",
       "      <td>['MacArthur grant', 'activism', 'business', 'c...</td>\n",
       "      <td>Greening the ghetto</td>\n",
       "      <td>https://www.ted.com/talks/majora_carter_s_tale...</td>\n",
       "      <td>1697550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>593</td>\n",
       "      <td>You've never seen data presented like this. Wi...</td>\n",
       "      <td>1190</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140566400</td>\n",
       "      <td>48</td>\n",
       "      <td>Hans Rosling</td>\n",
       "      <td>Hans Rosling: The best stats you've ever seen</td>\n",
       "      <td>1</td>\n",
       "      <td>1151440680</td>\n",
       "      <td>[{'id': 9, 'name': 'Ingenious', 'count': 3202}...</td>\n",
       "      <td>[{'id': 2056, 'hero': 'https://pe.tedcdn.com/i...</td>\n",
       "      <td>Global health expert; data visionary</td>\n",
       "      <td>['Africa', 'Asia', 'Google', 'demo', 'economic...</td>\n",
       "      <td>The best stats you've ever seen</td>\n",
       "      <td>https://www.ted.com/talks/hans_rosling_shows_t...</td>\n",
       "      <td>12005869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   comments                                        description  duration  \\\n",
       "0      4553  Sir Ken Robinson makes an entertaining and pro...      1164   \n",
       "1       265  With the same humor and humanity he exuded in ...       977   \n",
       "2       124  New York Times columnist David Pogue takes aim...      1286   \n",
       "3       200  In an emotionally charged talk, MacArthur-winn...      1116   \n",
       "4       593  You've never seen data presented like this. Wi...      1190   \n",
       "\n",
       "     event   film_date  languages   main_speaker  \\\n",
       "0  TED2006  1140825600         60   Ken Robinson   \n",
       "1  TED2006  1140825600         43        Al Gore   \n",
       "2  TED2006  1140739200         26    David Pogue   \n",
       "3  TED2006  1140912000         35  Majora Carter   \n",
       "4  TED2006  1140566400         48   Hans Rosling   \n",
       "\n",
       "                                            name  num_speaker  published_date  \\\n",
       "0      Ken Robinson: Do schools kill creativity?            1      1151367060   \n",
       "1           Al Gore: Averting the climate crisis            1      1151367060   \n",
       "2                  David Pogue: Simplicity sells            1      1151367060   \n",
       "3             Majora Carter: Greening the ghetto            1      1151367060   \n",
       "4  Hans Rosling: The best stats you've ever seen            1      1151440680   \n",
       "\n",
       "                                             ratings  \\\n",
       "0  [{'id': 7, 'name': 'Funny', 'count': 19645}, {...   \n",
       "1  [{'id': 7, 'name': 'Funny', 'count': 544}, {'i...   \n",
       "2  [{'id': 7, 'name': 'Funny', 'count': 964}, {'i...   \n",
       "3  [{'id': 3, 'name': 'Courageous', 'count': 760}...   \n",
       "4  [{'id': 9, 'name': 'Ingenious', 'count': 3202}...   \n",
       "\n",
       "                                       related_talks  \\\n",
       "0  [{'id': 865, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "1  [{'id': 243, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "2  [{'id': 1725, 'hero': 'https://pe.tedcdn.com/i...   \n",
       "3  [{'id': 1041, 'hero': 'https://pe.tedcdn.com/i...   \n",
       "4  [{'id': 2056, 'hero': 'https://pe.tedcdn.com/i...   \n",
       "\n",
       "                     speaker_occupation  \\\n",
       "0                       Author/educator   \n",
       "1                      Climate advocate   \n",
       "2                  Technology columnist   \n",
       "3    Activist for environmental justice   \n",
       "4  Global health expert; data visionary   \n",
       "\n",
       "                                                tags  \\\n",
       "0  ['children', 'creativity', 'culture', 'dance',...   \n",
       "1  ['alternative energy', 'cars', 'climate change...   \n",
       "2  ['computers', 'entertainment', 'interface desi...   \n",
       "3  ['MacArthur grant', 'activism', 'business', 'c...   \n",
       "4  ['Africa', 'Asia', 'Google', 'demo', 'economic...   \n",
       "\n",
       "                             title  \\\n",
       "0      Do schools kill creativity?   \n",
       "1      Averting the climate crisis   \n",
       "2                 Simplicity sells   \n",
       "3              Greening the ghetto   \n",
       "4  The best stats you've ever seen   \n",
       "\n",
       "                                                 url     views  \n",
       "0  https://www.ted.com/talks/ken_robinson_says_sc...  47227110  \n",
       "1  https://www.ted.com/talks/al_gore_on_averting_...   3200520  \n",
       "2  https://www.ted.com/talks/david_pogue_says_sim...   1636292  \n",
       "3  https://www.ted.com/talks/majora_carter_s_tale...   1697550  \n",
       "4  https://www.ted.com/talks/hans_rosling_shows_t...  12005869  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5542d886",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "comments               int64\n",
       "description           object\n",
       "duration               int64\n",
       "event                 object\n",
       "film_date              int64\n",
       "languages              int64\n",
       "main_speaker          object\n",
       "name                  object\n",
       "num_speaker            int64\n",
       "published_date         int64\n",
       "ratings               object\n",
       "related_talks         object\n",
       "speaker_occupation    object\n",
       "tags                  object\n",
       "title                 object\n",
       "url                   object\n",
       "views                  int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "50f77e4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "comments              0\n",
       "description           0\n",
       "duration              0\n",
       "event                 0\n",
       "film_date             0\n",
       "languages             0\n",
       "main_speaker          0\n",
       "name                  0\n",
       "num_speaker           0\n",
       "published_date        0\n",
       "ratings               0\n",
       "related_talks         0\n",
       "speaker_occupation    6\n",
       "tags                  0\n",
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       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.isna().sum() # check for missing values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "75084870",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Which talks provoke the most online discussion?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "dca80049",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>comments</th>\n",
       "      <th>description</th>\n",
       "      <th>duration</th>\n",
       "      <th>event</th>\n",
       "      <th>film_date</th>\n",
       "      <th>languages</th>\n",
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       "      <th>speaker_occupation</th>\n",
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       "      <th>views</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1787</th>\n",
       "      <td>2673</td>\n",
       "      <td>Our consciousness is a fundamental aspect of o...</td>\n",
       "      <td>1117</td>\n",
       "      <td>TED2014</td>\n",
       "      <td>1395100800</td>\n",
       "      <td>33</td>\n",
       "      <td>David Chalmers</td>\n",
       "      <td>David Chalmers: How do you explain consciousness?</td>\n",
       "      <td>1</td>\n",
       "      <td>1405350484</td>\n",
       "      <td>[{'id': 25, 'name': 'OK', 'count': 280}, {'id'...</td>\n",
       "      <td>[{'id': 1308, 'hero': 'https://pe.tedcdn.com/i...</td>\n",
       "      <td>Philosopher</td>\n",
       "      <td>['brain', 'consciousness', 'neuroscience', 'ph...</td>\n",
       "      <td>How do you explain consciousness?</td>\n",
       "      <td>https://www.ted.com/talks/david_chalmers_how_d...</td>\n",
       "      <td>2162764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>2877</td>\n",
       "      <td>Jill Bolte Taylor got a research opportunity f...</td>\n",
       "      <td>1099</td>\n",
       "      <td>TED2008</td>\n",
       "      <td>1204070400</td>\n",
       "      <td>49</td>\n",
       "      <td>Jill Bolte Taylor</td>\n",
       "      <td>Jill Bolte Taylor: My stroke of insight</td>\n",
       "      <td>1</td>\n",
       "      <td>1205284200</td>\n",
       "      <td>[{'id': 22, 'name': 'Fascinating', 'count': 14...</td>\n",
       "      <td>[{'id': 184, 'hero': 'https://pe.tedcdn.com/im...</td>\n",
       "      <td>Neuroanatomist</td>\n",
       "      <td>['biology', 'brain', 'consciousness', 'global ...</td>\n",
       "      <td>My stroke of insight</td>\n",
       "      <td>https://www.ted.com/talks/jill_bolte_taylor_s_...</td>\n",
       "      <td>21190883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>644</th>\n",
       "      <td>3356</td>\n",
       "      <td>Questions of good and evil, right and wrong ar...</td>\n",
       "      <td>1386</td>\n",
       "      <td>TED2010</td>\n",
       "      <td>1265846400</td>\n",
       "      <td>39</td>\n",
       "      <td>Sam Harris</td>\n",
       "      <td>Sam Harris: Science can answer moral questions</td>\n",
       "      <td>1</td>\n",
       "      <td>1269249180</td>\n",
       "      <td>[{'id': 8, 'name': 'Informative', 'count': 923...</td>\n",
       "      <td>[{'id': 666, 'hero': 'https://pe.tedcdn.com/im...</td>\n",
       "      <td>Neuroscientist, philosopher</td>\n",
       "      <td>['culture', 'evolutionary psychology', 'global...</td>\n",
       "      <td>Science can answer moral questions</td>\n",
       "      <td>https://www.ted.com/talks/sam_harris_science_c...</td>\n",
       "      <td>3433437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4553</td>\n",
       "      <td>Sir Ken Robinson makes an entertaining and pro...</td>\n",
       "      <td>1164</td>\n",
       "      <td>TED2006</td>\n",
       "      <td>1140825600</td>\n",
       "      <td>60</td>\n",
       "      <td>Ken Robinson</td>\n",
       "      <td>Ken Robinson: Do schools kill creativity?</td>\n",
       "      <td>1</td>\n",
       "      <td>1151367060</td>\n",
       "      <td>[{'id': 7, 'name': 'Funny', 'count': 19645}, {...</td>\n",
       "      <td>[{'id': 865, 'hero': 'https://pe.tedcdn.com/im...</td>\n",
       "      <td>Author/educator</td>\n",
       "      <td>['children', 'creativity', 'culture', 'dance',...</td>\n",
       "      <td>Do schools kill creativity?</td>\n",
       "      <td>https://www.ted.com/talks/ken_robinson_says_sc...</td>\n",
       "      <td>47227110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>6404</td>\n",
       "      <td>Richard Dawkins urges all atheists to openly s...</td>\n",
       "      <td>1750</td>\n",
       "      <td>TED2002</td>\n",
       "      <td>1012608000</td>\n",
       "      <td>42</td>\n",
       "      <td>Richard Dawkins</td>\n",
       "      <td>Richard Dawkins: Militant atheism</td>\n",
       "      <td>1</td>\n",
       "      <td>1176689220</td>\n",
       "      <td>[{'id': 3, 'name': 'Courageous', 'count': 3236...</td>\n",
       "      <td>[{'id': 86, 'hero': 'https://pe.tedcdn.com/ima...</td>\n",
       "      <td>Evolutionary biologist</td>\n",
       "      <td>['God', 'atheism', 'culture', 'religion', 'sci...</td>\n",
       "      <td>Militant atheism</td>\n",
       "      <td>https://www.ted.com/talks/richard_dawkins_on_m...</td>\n",
       "      <td>4374792</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      comments                                        description  duration  \\\n",
       "1787      2673  Our consciousness is a fundamental aspect of o...      1117   \n",
       "201       2877  Jill Bolte Taylor got a research opportunity f...      1099   \n",
       "644       3356  Questions of good and evil, right and wrong ar...      1386   \n",
       "0         4553  Sir Ken Robinson makes an entertaining and pro...      1164   \n",
       "96        6404  Richard Dawkins urges all atheists to openly s...      1750   \n",
       "\n",
       "        event   film_date  languages       main_speaker  \\\n",
       "1787  TED2014  1395100800         33     David Chalmers   \n",
       "201   TED2008  1204070400         49  Jill Bolte Taylor   \n",
       "644   TED2010  1265846400         39         Sam Harris   \n",
       "0     TED2006  1140825600         60       Ken Robinson   \n",
       "96    TED2002  1012608000         42    Richard Dawkins   \n",
       "\n",
       "                                                   name  num_speaker  \\\n",
       "1787  David Chalmers: How do you explain consciousness?            1   \n",
       "201             Jill Bolte Taylor: My stroke of insight            1   \n",
       "644      Sam Harris: Science can answer moral questions            1   \n",
       "0             Ken Robinson: Do schools kill creativity?            1   \n",
       "96                    Richard Dawkins: Militant atheism            1   \n",
       "\n",
       "      published_date                                            ratings  \\\n",
       "1787      1405350484  [{'id': 25, 'name': 'OK', 'count': 280}, {'id'...   \n",
       "201       1205284200  [{'id': 22, 'name': 'Fascinating', 'count': 14...   \n",
       "644       1269249180  [{'id': 8, 'name': 'Informative', 'count': 923...   \n",
       "0         1151367060  [{'id': 7, 'name': 'Funny', 'count': 19645}, {...   \n",
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       "\n",
       "                                          related_talks  \\\n",
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       "\n",
       "               speaker_occupation  \\\n",
       "1787                  Philosopher   \n",
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       "644   Neuroscientist, philosopher   \n",
       "0                 Author/educator   \n",
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       "\n",
       "                                                   tags  \\\n",
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       "\n",
       "                                   title  \\\n",
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       "644   Science can answer moral questions   \n",
       "0            Do schools kill creativity?   \n",
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       "\n",
       "                                                    url     views  \n",
       "1787  https://www.ted.com/talks/david_chalmers_how_d...   2162764  \n",
       "201   https://www.ted.com/talks/jill_bolte_taylor_s_...  21190883  \n",
       "644   https://www.ted.com/talks/sam_harris_science_c...   3433437  \n",
       "0     https://www.ted.com/talks/ken_robinson_says_sc...  47227110  \n",
       "96    https://www.ted.com/talks/richard_dawkins_on_m...   4374792  "
      ]
     },
     "execution_count": 15,
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   ],
   "source": [
    "ted.sort_values('comments').tail()"
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  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cc0bffb6",
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   "outputs": [],
   "source": [
    "ted['comments_per_view']=ted.comments/ted.views #new column created"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9004da44",
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       "694      1502  Filmmaker Sharmeen Obaid-Chinoy takes on a ter...       489   \n",
       "96       6404  Richard Dawkins urges all atheists to openly s...      1750   \n",
       "803       834  David Bismark demos a new system for voting th...       422   \n",
       "744       649  Hours before New York lawmakers rejected a key...       453   \n",
       "\n",
       "                     event   film_date  languages           main_speaker  \\\n",
       "954                TED2011  1299110400         35         Janet Echelman   \n",
       "694                TED2010  1265760000         32  Sharmeen Obaid-Chinoy   \n",
       "96                 TED2002  1012608000         42        Richard Dawkins   \n",
       "803         TEDGlobal 2010  1279065600         36          David Bismark   \n",
       "744  New York State Senate  1259712000          0        Diane J. Savino   \n",
       "\n",
       "                                                  name  num_speaker  \\\n",
       "954       Janet Echelman: Taking imagination seriously            1   \n",
       "694  Sharmeen Obaid-Chinoy: Inside a school for sui...            1   \n",
       "96                   Richard Dawkins: Militant atheism            1   \n",
       "803              David Bismark: E-voting without fraud            1   \n",
       "744    Diane J. Savino: The case for same-sex marriage            1   \n",
       "\n",
       "     published_date                                            ratings  \\\n",
       "954      1307489760  [{'id': 23, 'name': 'Jaw-dropping', 'count': 3...   \n",
       "694      1274865960  [{'id': 23, 'name': 'Jaw-dropping', 'count': 3...   \n",
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       "744      1282062180  [{'id': 25, 'name': 'OK', 'count': 100}, {'id'...   \n",
       "\n",
       "                                         related_talks  \\\n",
       "954  [{'id': 453, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "694  [{'id': 171, 'hero': 'https://pe.tedcdn.com/im...   \n",
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       "744  [{'id': 217, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "\n",
       "         speaker_occupation  \\\n",
       "954                  Artist   \n",
       "694               Filmmaker   \n",
       "96   Evolutionary biologist   \n",
       "803  Voting system designer   \n",
       "744                 Senator   \n",
       "\n",
       "                                                  tags  \\\n",
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       "803  ['culture', 'democracy', 'design', 'global iss...   \n",
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       "\n",
       "                                   title  \\\n",
       "954         Taking imagination seriously   \n",
       "694  Inside a school for suicide bombers   \n",
       "96                      Militant atheism   \n",
       "803               E-voting without fraud   \n",
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       "\n",
       "                                                   url    views  \\\n",
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       "694  https://www.ted.com/talks/sharmeen_obaid_chino...  1057238   \n",
       "96   https://www.ted.com/talks/richard_dawkins_on_m...  4374792   \n",
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       "\n",
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   "execution_count": 21,
   "id": "afecc634",
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   "outputs": [],
   "source": [
    "ted['views_per_comment']=ted.views/ted.comments # per user views- comment"
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  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f1b80d52",
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   "outputs": [
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       "     comments                                        description  duration  \\\n",
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       "803       834  David Bismark demos a new system for voting th...       422   \n",
       "96       6404  Richard Dawkins urges all atheists to openly s...      1750   \n",
       "694      1502  Filmmaker Sharmeen Obaid-Chinoy takes on a ter...       489   \n",
       "954      2492  Janet Echelman found her true voice as an arti...       566   \n",
       "\n",
       "                     event   film_date  languages           main_speaker  \\\n",
       "744  New York State Senate  1259712000          0        Diane J. Savino   \n",
       "803         TEDGlobal 2010  1279065600         36          David Bismark   \n",
       "96                 TED2002  1012608000         42        Richard Dawkins   \n",
       "694                TED2010  1265760000         32  Sharmeen Obaid-Chinoy   \n",
       "954                TED2011  1299110400         35         Janet Echelman   \n",
       "\n",
       "                                                  name  num_speaker  \\\n",
       "744    Diane J. Savino: The case for same-sex marriage            1   \n",
       "803              David Bismark: E-voting without fraud            1   \n",
       "96                   Richard Dawkins: Militant atheism            1   \n",
       "694  Sharmeen Obaid-Chinoy: Inside a school for sui...            1   \n",
       "954       Janet Echelman: Taking imagination seriously            1   \n",
       "\n",
       "     published_date                                            ratings  \\\n",
       "744      1282062180  [{'id': 25, 'name': 'OK', 'count': 100}, {'id'...   \n",
       "803      1288685640  [{'id': 25, 'name': 'OK', 'count': 111}, {'id'...   \n",
       "96       1176689220  [{'id': 3, 'name': 'Courageous', 'count': 3236...   \n",
       "694      1274865960  [{'id': 23, 'name': 'Jaw-dropping', 'count': 3...   \n",
       "954      1307489760  [{'id': 23, 'name': 'Jaw-dropping', 'count': 3...   \n",
       "\n",
       "                                         related_talks  \\\n",
       "744  [{'id': 217, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "803  [{'id': 803, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "96   [{'id': 86, 'hero': 'https://pe.tedcdn.com/ima...   \n",
       "694  [{'id': 171, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "954  [{'id': 453, 'hero': 'https://pe.tedcdn.com/im...   \n",
       "\n",
       "         speaker_occupation  \\\n",
       "744                 Senator   \n",
       "803  Voting system designer   \n",
       "96   Evolutionary biologist   \n",
       "694               Filmmaker   \n",
       "954                  Artist   \n",
       "\n",
       "                                                  tags  \\\n",
       "744  ['God', 'LGBT', 'culture', 'government', 'law'...   \n",
       "803  ['culture', 'democracy', 'design', 'global iss...   \n",
       "96   ['God', 'atheism', 'culture', 'religion', 'sci...   \n",
       "694  ['TED Fellows', 'children', 'culture', 'film',...   \n",
       "954  ['art', 'cities', 'culture', 'data', 'design',...   \n",
       "\n",
       "                                   title  \\\n",
       "744       The case for same-sex marriage   \n",
       "803               E-voting without fraud   \n",
       "96                      Militant atheism   \n",
       "694  Inside a school for suicide bombers   \n",
       "954         Taking imagination seriously   \n",
       "\n",
       "                                                   url    views  \\\n",
       "744  https://www.ted.com/talks/diane_j_savino_the_c...   292395   \n",
       "803  https://www.ted.com/talks/david_bismark_e_voti...   543551   \n",
       "96   https://www.ted.com/talks/richard_dawkins_on_m...  4374792   \n",
       "694  https://www.ted.com/talks/sharmeen_obaid_chino...  1057238   \n",
       "954           https://www.ted.com/talks/janet_echelman  1832930   \n",
       "\n",
       "     comments_per_view  views_per_comment  \n",
       "744           0.002220         450.531587  \n",
       "803           0.001534         651.739808  \n",
       "96            0.001464         683.134291  \n",
       "694           0.001421         703.886818  \n",
       "954           0.001360         735.525682  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.sort_values('views_per_comment').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "0da60cf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Visualize the distribution of comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "73cabada",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32, 19)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted[ted.comments>=1000].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8f003c81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SkpL0wQcf6Oqrr3ZqlixZotzcXK1du1Zdu3bV448/rkGDBunw4cOKi4uTJGVlZemPf/yj8vLylJCQoFmzZmnYsGEqKipSWFhYUHoFAACtV0CB6Oqrr9bdd98d7F4aWbx4sVJSUrRmzRpnrHPnzs7/NsZo+fLlWrBggUaMGCFJWrdunZKTk7VhwwZNnjxZPp9Pq1ev1gsvvKCBAwdKktavX6+UlBRt3bpVgwcPbvLzAAAALVtAgejvA0pT2rx5swYPHqyf//znKigo0LXXXqupU6fql7/8pSSppKREZWVlyszMdN4TFRWlvn37qrCwUJMnT1ZRUZHOnj3rV+P1epWenq7CwkICEQAACOwaIkk6d+6ctm7dqmeffVZVVVWSpFOnTqm6ujpozX344YdauXKl0tLS9Kc//UlTpkzRgw8+qOeff16SVFZWJklKTk72e19ycrKzr6ysTJGRkWrbtu0Fa86ntrZWlZWVfhsAALgyBbRCdPToUd1xxx06duyYamtrNWjQIMXFxWnJkiX68ssv9cwzzwSluYaGBvXs2dP5frQePXro0KFDWrlypcaPH+/UffM5SMaY73w20nfV5OTk6NFHH72M7gEAQGsR0ArRjBkz1LNnT1VUVCg6OtoZv/vuu/Xmm28Grbn27dvrhhtu8Bu7/vrrdezYMUmSx+ORpEYrPeXl5c6qkcfjUV1dnSoqKi5Ycz7z58+Xz+dztuPHj1/2+QAAgJYpoEC0Y8cOPfzww4qMjPQb79Spk06ePBmUxiTptttu0+HDh/3Gjhw54nyJbGpqqjwej/Lz8539dXV1KigoUO/evSVJGRkZioiI8KspLS3VwYMHnZrziYqKUnx8vN8GAACuTAF9ZNbQ0KD6+vpG4ydOnHBudQ+Ghx56SL1791Z2drZGjhypXbt2adWqVVq1apWkrz4qy8rKUnZ2ttLS0pSWlqbs7GzFxMRo9OjRkiS3261JkyZp1qxZSkhIULt27TR79mx1797duesMAADYLaBANGjQIC1fvtwvmFRXV+uRRx4J6td53HLLLdq0aZPmz5+vxx57TKmpqVq+fLnGjBnj1MyZM0c1NTWaOnWqKioq1KtXL23ZssUvmC1btkzh4eEaOXKkampqNGDAAK1du5ZnEAEAAEmSywTwuOlTp06pf//+CgsL0/vvv6+ePXvq/fffV2Jiot566y0lJSU1Ra8hVVlZKbfbLZ/PF/SPzzrPezWox8OFfbRoaKhbAAA0o4v9+x3QCpHX61VxcbFeeukl7d27Vw0NDZo0aZLGjBnjd5E1AABAaxBQIJKk6OhoTZw4URMnTgxmPwAAAM0uoED09YMRL+TvnxEEAADQ0gUUiGbMmOH3+uzZszpz5owiIyMVExNDIAIAAK1KQM8hqqio8Nuqq6t1+PBh9enTRy+99FKwewQAAGhSAX+X2TelpaVp0aJFjVaPAAAAWrqgBSJJCgsL06lTp4J5SAAAgCYX0DVEmzdv9nttjFFpaalWrFih2267LSiNAQAANJeAAtFdd93l99rlcumaa67RT37yEz355JPB6AsAAKDZBPxdZgAAAFeKoF5DBAAA0BoFtEI0c+bMi67Nzc0N5EcAAAA0m4AC0b59+7R3716dO3dO3/ve9yRJR44cUVhYmG6++WanzuVyBadLAACAJhRQILrzzjsVFxendevWqW3btpK+eljj/fffrx//+MeaNWtWUJsEAABoSgFdQ/Tkk08qJyfHCUOS1LZtWz3++OPcZQYAAFqdgAJRZWWlPv7440bj5eXlqqqquuymAAAAmlNAgejuu+/W/fffr9/97nc6ceKETpw4od/97neaNGmSRowYEeweAQAAmlRA1xA988wzmj17tsaOHauzZ89+daDwcE2aNElLly4NaoMAAABNLaBAFBMTo6efflpLly7VBx98IGOMrrvuOsXGxga7PwAAgCZ3WQ9mLC0tVWlpqbp27arY2FgZY4LVFwAAQLMJKBB99tlnGjBggLp27aohQ4aotLRUkvSLX/yCW+4BAECrE1AgeuihhxQREaFjx44pJibGGR81apTeeOONoDUHAADQHAK6hmjLli3605/+pA4dOviNp6Wl6ejRo0FpDAAAoLkEtEJ0+vRpv5Whr3366aeKioq67KYAAACaU0CB6Pbbb9fzzz/vvHa5XGpoaNDSpUvVv3//oDUHAADQHAL6yGzp0qXq16+f9uzZo7q6Os2ZM0eHDh3S559/rv/7v/8Ldo8AAABNKqAVohtuuEHvvvuufvjDH2rQoEE6ffq0RowYoX379ukf//Efg90jAABAk7rkFaKzZ88qMzNTzz77rB599NGm6AkAAKBZXfIKUUREhA4ePCiXy9UU/QAAADS7gD4yGz9+vFavXh3sXgAAAEIioIuq6+rq9F//9V/Kz89Xz549G32HWW5ublCaAwAAaA6XFIg+/PBDde7cWQcPHtTNN98sSTpy5IhfDR+lAQCA1uaSAlFaWppKS0u1fft2SV99VcdTTz2l5OTkJmkOAACgOVzSNUTf/Db7119/XadPnw5qQwAAAM0toIuqv/bNgAQAANAaXVIgcrlcja4R4pohAADQ2l3SNUTGGN13333OF7h++eWXmjJlSqO7zDZu3Bi8DgEAAJrYJQWiCRMm+L0eO3ZsUJsBAAAIhUsKRGvWrGmqPgAAAELmsi6qBgAAuBIQiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYr1UFopycHLlcLmVlZTljxhgtXLhQXq9X0dHR6tevnw4dOuT3vtraWk2fPl2JiYmKjY3V8OHDdeLEiWbuHgAAtFStJhDt3r1bq1at0k033eQ3vmTJEuXm5mrFihXavXu3PB6PBg0apKqqKqcmKytLmzZtUl5ennbs2KHq6moNGzZM9fX1zX0aAACgBWoVgai6ulpjxozRc889p7Zt2zrjxhgtX75cCxYs0IgRI5Senq5169bpzJkz2rBhgyTJ5/Np9erVevLJJzVw4ED16NFD69ev14EDB7R169ZQnRIAAGhBWkUgeuCBBzR06FANHDjQb7ykpERlZWXKzMx0xqKiotS3b18VFhZKkoqKinT27Fm/Gq/Xq/T0dKcGAADYLTzUDXyXvLw8FRUVac+ePY32lZWVSZKSk5P9xpOTk3X06FGnJjIy0m9l6euar99/PrW1taqtrXVeV1ZWBnwOAACgZWvRK0THjx/XjBkz9OKLL6pNmzYXrHO5XH6vjTGNxr7pu2pycnLkdrudLSUl5dKaBwAArUaLDkRFRUUqLy9XRkaGwsPDFR4eroKCAj311FMKDw93Voa+udJTXl7u7PN4PKqrq1NFRcUFa85n/vz58vl8znb8+PEgnx0AAGgpWnQgGjBggA4cOKDi4mJn69mzp8aMGaPi4mJ16dJFHo9H+fn5znvq6upUUFCg3r17S5IyMjIUERHhV1NaWqqDBw86NecTFRWl+Ph4vw0AAFyZWvQ1RHFxcUpPT/cbi42NVUJCgjOelZWl7OxspaWlKS0tTdnZ2YqJidHo0aMlSW63W5MmTdKsWbOUkJCgdu3aafbs2erevXuji7QBAICdWnQguhhz5sxRTU2Npk6dqoqKCvXq1UtbtmxRXFycU7Ns2TKFh4dr5MiRqqmp0YABA7R27VqFhYWFsHMAANBSuIwxJtRNtAaVlZVyu93y+XxB//is87xXg3o8XNhHi4aGugUAQDO62L/fLfoaIgAAgOZAIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwXnioGwCaU+d5r4a6hUv20aKhoW4BAK54rBABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsF6LDkQ5OTm65ZZbFBcXp6SkJN111106fPiwX40xRgsXLpTX61V0dLT69eunQ4cO+dXU1tZq+vTpSkxMVGxsrIYPH64TJ04056kAAIAWrEUHooKCAj3wwAN6++23lZ+fr3PnzikzM1OnT592apYsWaLc3FytWLFCu3fvlsfj0aBBg1RVVeXUZGVladOmTcrLy9OOHTtUXV2tYcOGqb6+PhSnBQAAWhiXMcaEuomL9cknnygpKUkFBQW6/fbbZYyR1+tVVlaW5s6dK+mr1aDk5GQtXrxYkydPls/n0zXXXKMXXnhBo0aNkiSdOnVKKSkpeu211zR48OCL+tmVlZVyu93y+XyKj48P6nl1nvdqUI+HK8tHi4aGugUAaLUu9u93i14h+iafzydJateunSSppKREZWVlyszMdGqioqLUt29fFRYWSpKKiop09uxZvxqv16v09HSn5nxqa2tVWVnptwEAgCtTqwlExhjNnDlTffr0UXp6uiSprKxMkpScnOxXm5yc7OwrKytTZGSk2rZte8Ga88nJyZHb7Xa2lJSUYJ4OAABoQVpNIJo2bZreffddvfTSS432uVwuv9fGmEZj3/RdNfPnz5fP53O248ePB9Y4AABo8VpFIJo+fbo2b96s7du3q0OHDs64x+ORpEYrPeXl5c6qkcfjUV1dnSoqKi5Ycz5RUVGKj4/32wAAwJWpRQciY4ymTZumjRs3atu2bUpNTfXbn5qaKo/Ho/z8fGesrq5OBQUF6t27tyQpIyNDERERfjWlpaU6ePCgUwMAAOwWHuoGvs0DDzygDRs26L//+78VFxfnrAS53W5FR0fL5XIpKytL2dnZSktLU1pamrKzsxUTE6PRo0c7tZMmTdKsWbOUkJCgdu3aafbs2erevbsGDhwYytMDAAAtRIsORCtXrpQk9evXz298zZo1uu+++yRJc+bMUU1NjaZOnaqKigr16tVLW7ZsUVxcnFO/bNkyhYeHa+TIkaqpqdGAAQO0du1ahYWFNdepAACAFqxVPYcolHgOEUKF5xABQOCuyOcQAQAANAUCEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA67Xo5xABaJ2PZeBRAQBaG1aIAACA9QhEAADAegQiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKxHIAIAANYjEAEAAOsRiAAAgPUIRAAAwHoEIgAAYD0CEQAAsB6BCAAAWI9ABAAArEcgAgAA1iMQAQAA6xGIAACA9cJD3QCAK0/nea+GuoVL9tGioaFuAUAIsUIEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAezyECAPHsJMB2rBABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiP2+4BoJXiUQFA8LBCBAAArEcgAgAA1iMQAQAA63ENEQCg2XDdE1oqAhEAAN+iNYa41ijUwdOqj8yefvpppaamqk2bNsrIyNCf//znULcEAABaAGsC0csvv6ysrCwtWLBA+/bt049//GP99Kc/1bFjx0LdGgAACDFrAlFubq4mTZqkX/ziF7r++uu1fPlypaSkaOXKlaFuDQAAhJgV1xDV1dWpqKhI8+bN8xvPzMxUYWHhed9TW1ur2tpa57XP55MkVVZWBr2/htozQT8mAACtSVP8ff374xpjvrXOikD06aefqr6+XsnJyX7jycnJKisrO+97cnJy9OijjzYaT0lJaZIeAQCwmXt50x6/qqpKbrf7gvutCERfc7lcfq+NMY3GvjZ//nzNnDnTed3Q0KDPP/9cCQkJF3zPpaqsrFRKSoqOHz+u+Pj4oBwTF8Z8Nx/muvkw182HuW4+wZxrY4yqqqrk9Xq/tc6KQJSYmKiwsLBGq0Hl5eWNVo2+FhUVpaioKL+xq6++ukn6i4+P5z+uZsR8Nx/muvkw182HuW4+wZrrb1sZ+poVF1VHRkYqIyND+fn5fuP5+fnq3bt3iLoCAAAthRUrRJI0c+ZMjRs3Tj179tStt96qVatW6dixY5oyZUqoWwMAACFmTSAaNWqUPvvsMz322GMqLS1Venq6XnvtNXXq1ClkPUVFRemRRx5p9NEcmgbz3XyY6+bDXDcf5rr5hGKuXea77kMDAAC4wllxDREAAMC3IRABAADrEYgAAID1CEQAAMB6BKIQevrpp5Wamqo2bdooIyNDf/7zn0PdUquSk5OjW265RXFxcUpKStJdd92lw4cP+9UYY7Rw4UJ5vV5FR0erX79+OnTokF9NbW2tpk+frsTERMXGxmr48OE6ceJEc55Kq5OTkyOXy6WsrCxnjLkOnpMnT2rs2LFKSEhQTEyMfvCDH6ioqMjZz1wHx7lz5/Twww8rNTVV0dHR6tKlix577DE1NDQ4Ncx14N566y3deeed8nq9crlc+sMf/uC3P1hzW1FRoXHjxsntdsvtdmvcuHH64osvLr1hg5DIy8szERER5rnnnjPvvfeemTFjhomNjTVHjx4NdWutxuDBg82aNWvMwYMHTXFxsRk6dKjp2LGjqa6udmoWLVpk4uLizO9//3tz4MABM2rUKNO+fXtTWVnp1EyZMsVce+21Jj8/3+zdu9f079/ffP/73zfnzp0LxWm1eLt27TKdO3c2N910k5kxY4YzzlwHx+eff246depk7rvvPvPOO++YkpISs3XrVvO3v/3NqWGug+Pxxx83CQkJ5n/+539MSUmJeeWVV8w//MM/mOXLlzs1zHXgXnvtNbNgwQLz+9//3kgymzZt8tsfrLm94447THp6uiksLDSFhYUmPT3dDBs27JL7JRCFyA9/+EMzZcoUv7Fu3bqZefPmhaij1q+8vNxIMgUFBcYYYxoaGozH4zGLFi1yar788kvjdrvNM888Y4wx5osvvjAREREmLy/PqTl58qS56qqrzBtvvNG8J9AKVFVVmbS0NJOfn2/69u3rBCLmOnjmzp1r+vTpc8H9zHXwDB061EycONFvbMSIEWbs2LHGGOY6mL4ZiII1t++9956RZN5++22nZufOnUaS+etf/3pJPfKRWQjU1dWpqKhImZmZfuOZmZkqLCwMUVetn8/nkyS1a9dOklRSUqKysjK/eY6KilLfvn2deS4qKtLZs2f9arxer9LT0/ldnMcDDzygoUOHauDAgX7jzHXwbN68WT179tTPf/5zJSUlqUePHnruueec/cx18PTp00dvvvmmjhw5Iknav3+/duzYoSFDhkhirptSsOZ2586dcrvd6tWrl1Pzox/9SG63+5Ln35onVbckn376qerr6xt9sWxycnKjL6DFxTHGaObMmerTp4/S09MlyZnL883z0aNHnZrIyEi1bdu2UQ2/C395eXkqKirSnj17Gu1jroPnww8/1MqVKzVz5kz9y7/8i3bt2qUHH3xQUVFRGj9+PHMdRHPnzpXP51O3bt0UFham+vp6PfHEE7r33nsl8e+6KQVrbsvKypSUlNTo+ElJSZc8/wSiEHK5XH6vjTGNxnBxpk2bpnfffVc7duxotC+QeeZ34e/48eOaMWOGtmzZojZt2lywjrm+fA0NDerZs6eys7MlST169NChQ4e0cuVKjR8/3qljri/fyy+/rPXr12vDhg268cYbVVxcrKysLHm9Xk2YMMGpY66bTjDm9nz1gcw/H5mFQGJiosLCwhql1/Ly8kZpGd9t+vTp2rx5s7Zv364OHTo44x6PR5K+dZ49Ho/q6upUUVFxwRp8tXRdXl6ujIwMhYeHKzw8XAUFBXrqqacUHh7uzBVzffnat2+vG264wW/s+uuv17FjxyTx7zqYfvWrX2nevHm655571L17d40bN04PPfSQcnJyJDHXTSlYc+vxePTxxx83Ov4nn3xyyfNPIAqByMhIZWRkKD8/3288Pz9fvXv3DlFXrY8xRtOmTdPGjRu1bds2paam+u1PTU2Vx+Pxm+e6ujoVFBQ485yRkaGIiAi/mtLSUh08eJDfxd8ZMGCADhw4oOLiYmfr2bOnxowZo+LiYnXp0oW5DpLbbrut0eMjjhw54nwRNf+ug+fMmTO66ir/P4NhYWHObffMddMJ1tzeeuut8vl82rVrl1PzzjvvyOfzXfr8X9Il2Aiar2+7X716tXnvvfdMVlaWiY2NNR999FGoW2s1/vmf/9m43W7zv//7v6a0tNTZzpw549QsWrTIuN1us3HjRnPgwAFz7733nve2zg4dOpitW7eavXv3mp/85CfcMnsR/v4uM2OY62DZtWuXCQ8PN0888YR5//33zYsvvmhiYmLM+vXrnRrmOjgmTJhgrr32Wue2+40bN5rExEQzZ84cp4a5DlxVVZXZt2+f2bdvn5FkcnNzzb59+5zHywRrbu+44w5z0003mZ07d5qdO3ea7t27c9t9a/Ob3/zGdOrUyURGRpqbb77ZuV0cF0fSebc1a9Y4NQ0NDeaRRx4xHo/HREVFmdtvv90cOHDA7zg1NTVm2rRppl27diY6OtoMGzbMHDt2rJnPpvX5ZiBiroPnj3/8o0lPTzdRUVGmW7duZtWqVX77mevgqKysNDNmzDAdO3Y0bdq0MV26dDELFiwwtbW1Tg1zHbjt27ef9/+jJ0yYYIwJ3tx+9tlnZsyYMSYuLs7ExcWZMWPGmIqKikvu12WMMZe40gUAAHBF4RoiAABgPQIRAACwHoEIAABYj0AEAACsRyACAADWIxABAADrEYgAAID1CEQAAMB6BCIAAGA9AhEAALAegQgAAFiPQAQAAKz3/95tYrZBYd8HAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ted.query('comments<1000').comments.plot(kind='hist') #method 1 query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "b4407676",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ted[ted.comments<1000].comments.plot(kind='box') #method 2 x-axis:index | y-axis:values of comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a3286983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ted.loc[ted.comments<1000,'comments'].plot(kind='hist',bins=20) #method 3 loc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1cb86fbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot the number of talks that took place each year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "97d3c60f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "812     TEDGlobal 2010\n",
       "1011    TEDGlobal 2011\n",
       "1971           TED2015\n",
       "957     TEDActive 2011\n",
       "1533       TEDMED 2013\n",
       "965            TED2011\n",
       "17             TED2006\n",
       "2261         TEDSummit\n",
       "1479       TEDxCaltech\n",
       "1469           TED2013\n",
       "Name: event, dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.event.sample(10) # 10 random events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "808e5d52",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted['film_datetime']=pd.to_datetime(ted.film_date,unit='s')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "5857e26d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>event</th>\n",
       "      <th>film_datetime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2232</th>\n",
       "      <td>TED@BCG Paris</td>\n",
       "      <td>2016-05-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1742</th>\n",
       "      <td>TEDxUMKC</td>\n",
       "      <td>2013-09-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1097</th>\n",
       "      <td>TEDSalon NY2011</td>\n",
       "      <td>2011-11-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>TEDxSanDiego</td>\n",
       "      <td>2011-12-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2218</th>\n",
       "      <td>TED2016</td>\n",
       "      <td>2016-02-16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                event film_datetime\n",
       "2232    TED@BCG Paris    2016-05-18\n",
       "1742         TEDxUMKC    2013-09-09\n",
       "1097  TEDSalon NY2011    2011-11-09\n",
       "1269     TEDxSanDiego    2011-12-03\n",
       "2218          TED2016    2016-02-16"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted[['event','film_datetime']].sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "f901110c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "comments                       int64\n",
       "description                   object\n",
       "duration                       int64\n",
       "event                         object\n",
       "film_date                      int64\n",
       "languages                      int64\n",
       "main_speaker                  object\n",
       "name                          object\n",
       "num_speaker                    int64\n",
       "published_date                 int64\n",
       "ratings                       object\n",
       "related_talks                 object\n",
       "speaker_occupation            object\n",
       "tags                          object\n",
       "title                         object\n",
       "url                           object\n",
       "views                          int64\n",
       "comments_per_view            float64\n",
       "views_per_comment            float64\n",
       "film_datetime         datetime64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "6d201d70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ted.film_datetime.dt.year.value_counts().sort_index().plot(kind='line')  # day time datatype | dt.dayofyear sort index values y-axis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "6712d62e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2017-08-27 00:00:00')"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.film_datetime.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "da28ebab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            ted2006\n",
       "1            ted2006\n",
       "2            ted2006\n",
       "3            ted2006\n",
       "4            ted2006\n",
       "            ...     \n",
       "2545         ted2017\n",
       "2546         ted2017\n",
       "2547         ted2017\n",
       "2548    tedxmilehigh\n",
       "2549         ted2017\n",
       "Name: event, Length: 2550, dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.event.str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3dec4c0d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# What were the best events in TED history to attend?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "567a14bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TED2014    84\n",
       "TED2009    83\n",
       "TED2016    77\n",
       "TED2013    77\n",
       "TED2015    75\n",
       "Name: event, dtype: int64"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.event.value_counts().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "83a487b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TEDxNorrkoping</th>\n",
       "      <td>1</td>\n",
       "      <td>6569493.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEDxCreativeCoast</th>\n",
       "      <td>1</td>\n",
       "      <td>8444981.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEDxBloomington</th>\n",
       "      <td>2</td>\n",
       "      <td>9484259.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEDxHouston</th>\n",
       "      <td>2</td>\n",
       "      <td>16140250.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEDxPuget Sound</th>\n",
       "      <td>1</td>\n",
       "      <td>34309432.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   count        mean\n",
       "event                               \n",
       "TEDxNorrkoping         1   6569493.0\n",
       "TEDxCreativeCoast      1   8444981.0\n",
       "TEDxBloomington        2   9484259.5\n",
       "TEDxHouston            2  16140250.5\n",
       "TEDxPuget Sound        1  34309432.0"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.groupby('event').views.agg(['count','mean']).sort_values('mean').tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "8befa844",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>sum</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TED2006</th>\n",
       "      <td>45</td>\n",
       "      <td>3.274345e+06</td>\n",
       "      <td>147345533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TED2015</th>\n",
       "      <td>75</td>\n",
       "      <td>2.011017e+06</td>\n",
       "      <td>150826305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEDGlobal 2013</th>\n",
       "      <td>66</td>\n",
       "      <td>2.584163e+06</td>\n",
       "      <td>170554736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TED2014</th>\n",
       "      <td>84</td>\n",
       "      <td>2.072874e+06</td>\n",
       "      <td>174121423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TED2013</th>\n",
       "      <td>77</td>\n",
       "      <td>2.302700e+06</td>\n",
       "      <td>177307937</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                count          mean        sum\n",
       "event                                         \n",
       "TED2006            45  3.274345e+06  147345533\n",
       "TED2015            75  2.011017e+06  150826305\n",
       "TEDGlobal 2013     66  2.584163e+06  170554736\n",
       "TED2014            84  2.072874e+06  174121423\n",
       "TED2013            77  2.302700e+06  177307937"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.groupby('event').views.agg(['count','mean','sum']).sort_values('sum').tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ae3e2ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Unpack the ratings data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "ad7e8b6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [{'id': 7, 'name': 'Funny', 'count': 19645}, {...\n",
       "1    [{'id': 7, 'name': 'Funny', 'count': 544}, {'i...\n",
       "2    [{'id': 7, 'name': 'Funny', 'count': 964}, {'i...\n",
       "3    [{'id': 3, 'name': 'Courageous', 'count': 760}...\n",
       "4    [{'id': 9, 'name': 'Ingenious', 'count': 3202}...\n",
       "Name: ratings, dtype: object"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "29d99784",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"[{'id': 7, 'name': 'Funny', 'count': 19645}, {'id': 1, 'name': 'Beautiful', 'count': 4573}, {'id': 9, 'name': 'Ingenious', 'count': 6073}, {'id': 3, 'name': 'Courageous', 'count': 3253}, {'id': 11, 'name': 'Longwinded', 'count': 387}, {'id': 2, 'name': 'Confusing', 'count': 242}, {'id': 8, 'name': 'Informative', 'count': 7346}, {'id': 22, 'name': 'Fascinating', 'count': 10581}, {'id': 21, 'name': 'Unconvincing', 'count': 300}, {'id': 24, 'name': 'Persuasive', 'count': 10704}, {'id': 23, 'name': 'Jaw-dropping', 'count': 4439}, {'id': 25, 'name': 'OK', 'count': 1174}, {'id': 26, 'name': 'Obnoxious', 'count': 209}, {'id': 10, 'name': 'Inspiring', 'count': 24924}]\""
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.loc[0,'ratings'] # row 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "261ae8fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast #abstract syntax tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "f49d3e45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ast.literal_eval('[1,2,3]') # stingifed | type list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "b4100e9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 7, 'name': 'Funny', 'count': 19645},\n",
       " {'id': 1, 'name': 'Beautiful', 'count': 4573},\n",
       " {'id': 9, 'name': 'Ingenious', 'count': 6073},\n",
       " {'id': 3, 'name': 'Courageous', 'count': 3253},\n",
       " {'id': 11, 'name': 'Longwinded', 'count': 387},\n",
       " {'id': 2, 'name': 'Confusing', 'count': 242},\n",
       " {'id': 8, 'name': 'Informative', 'count': 7346},\n",
       " {'id': 22, 'name': 'Fascinating', 'count': 10581},\n",
       " {'id': 21, 'name': 'Unconvincing', 'count': 300},\n",
       " {'id': 24, 'name': 'Persuasive', 'count': 10704},\n",
       " {'id': 23, 'name': 'Jaw-dropping', 'count': 4439},\n",
       " {'id': 25, 'name': 'OK', 'count': 1174},\n",
       " {'id': 26, 'name': 'Obnoxious', 'count': 209},\n",
       " {'id': 10, 'name': 'Inspiring', 'count': 24924}]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ast.literal_eval(ted.ratings[0]) #strigified list to list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "df2d4827",
   "metadata": {},
   "outputs": [],
   "source": [
    "def str_to_list(ratings_str):\n",
    "    return ast.literal_eval(ratings_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "53ebf6b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 7, 'name': 'Funny', 'count': 19645},\n",
       " {'id': 1, 'name': 'Beautiful', 'count': 4573},\n",
       " {'id': 9, 'name': 'Ingenious', 'count': 6073},\n",
       " {'id': 3, 'name': 'Courageous', 'count': 3253},\n",
       " {'id': 11, 'name': 'Longwinded', 'count': 387},\n",
       " {'id': 2, 'name': 'Confusing', 'count': 242},\n",
       " {'id': 8, 'name': 'Informative', 'count': 7346},\n",
       " {'id': 22, 'name': 'Fascinating', 'count': 10581},\n",
       " {'id': 21, 'name': 'Unconvincing', 'count': 300},\n",
       " {'id': 24, 'name': 'Persuasive', 'count': 10704},\n",
       " {'id': 23, 'name': 'Jaw-dropping', 'count': 4439},\n",
       " {'id': 25, 'name': 'OK', 'count': 1174},\n",
       " {'id': 26, 'name': 'Obnoxious', 'count': 209},\n",
       " {'id': 10, 'name': 'Inspiring', 'count': 24924}]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str_to_list(ted.ratings[0]) #keyword check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "364bc3d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [{'id': 7, 'name': 'Funny', 'count': 19645}, {...\n",
       "1    [{'id': 7, 'name': 'Funny', 'count': 544}, {'i...\n",
       "2    [{'id': 7, 'name': 'Funny', 'count': 964}, {'i...\n",
       "3    [{'id': 3, 'name': 'Courageous', 'count': 760}...\n",
       "4    [{'id': 9, 'name': 'Ingenious', 'count': 3202}...\n",
       "Name: ratings, dtype: object"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.ratings.apply(ast.literal_eval).head()  # str_to_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "1ce7db3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted['ratings_list']=ted.ratings.apply(lambda x: ast.literal_eval(x)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "a676f740",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'id': 7, 'name': 'Funny', 'count': 19645},\n",
       " {'id': 1, 'name': 'Beautiful', 'count': 4573},\n",
       " {'id': 9, 'name': 'Ingenious', 'count': 6073},\n",
       " {'id': 3, 'name': 'Courageous', 'count': 3253},\n",
       " {'id': 11, 'name': 'Longwinded', 'count': 387},\n",
       " {'id': 2, 'name': 'Confusing', 'count': 242},\n",
       " {'id': 8, 'name': 'Informative', 'count': 7346},\n",
       " {'id': 22, 'name': 'Fascinating', 'count': 10581},\n",
       " {'id': 21, 'name': 'Unconvincing', 'count': 300},\n",
       " {'id': 24, 'name': 'Persuasive', 'count': 10704},\n",
       " {'id': 23, 'name': 'Jaw-dropping', 'count': 4439},\n",
       " {'id': 25, 'name': 'OK', 'count': 1174},\n",
       " {'id': 26, 'name': 'Obnoxious', 'count': 209},\n",
       " {'id': 10, 'name': 'Inspiring', 'count': 24924}]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.ratings_list[0]  # type series of list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "2fd3b086",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "comments                       int64\n",
       "description                   object\n",
       "duration                       int64\n",
       "event                         object\n",
       "film_date                      int64\n",
       "languages                      int64\n",
       "main_speaker                  object\n",
       "name                          object\n",
       "num_speaker                    int64\n",
       "published_date                 int64\n",
       "ratings                       object\n",
       "related_talks                 object\n",
       "speaker_occupation            object\n",
       "tags                          object\n",
       "title                         object\n",
       "url                           object\n",
       "views                          int64\n",
       "comments_per_view            float64\n",
       "views_per_comment            float64\n",
       "film_datetime         datetime64[ns]\n",
       "ratings_list                  object\n",
       "dtype: object"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b72084e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Count the total number of ratings received by each talk--store new column named 'num_ratings'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "d9a98bd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93850"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(ted.ratings_list[0]) ['count'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "bab1b3a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_num_ratings(list_of_dicts):\n",
    "    num=0\n",
    "    for d in list_of_dicts:\n",
    "        num=num+d['count']\n",
    "    return num"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "06c4514c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "93850"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "get_num_ratings(ted.ratings_list[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "52972d24",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted['num_ratings']=ted.ratings_list.apply(get_num_ratings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "0d87aafa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     2550.000000\n",
       "mean      2436.408235\n",
       "std       4226.795631\n",
       "min         68.000000\n",
       "25%        870.750000\n",
       "50%       1452.500000\n",
       "75%       2506.750000\n",
       "max      93850.000000\n",
       "Name: num_ratings, dtype: float64"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.num_ratings.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3ec2a36a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Which occupations deliver the funniest TED talks on average?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "fbe674c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    [{'id': 7, 'name': 'Funny', 'count': 19645}, {...\n",
       "1    [{'id': 7, 'name': 'Funny', 'count': 544}, {'i...\n",
       "2    [{'id': 7, 'name': 'Funny', 'count': 964}, {'i...\n",
       "3    [{'id': 3, 'name': 'Courageous', 'count': 760}...\n",
       "4    [{'id': 9, 'name': 'Ingenious', 'count': 3202}...\n",
       "Name: ratings_list, dtype: object"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# step1:count the number of funny ratings\n",
    "ted.ratings_list.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "b2cc3dc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True    2550\n",
       "Name: ratings, dtype: int64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.ratings.str.contains('Funny').value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "84f45440",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_funny_ratings(list_of_dicts):\n",
    "    for d in list_of_dicts:\n",
    "        if d['name']=='Funny':\n",
    "            return d['count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "68fa159b",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted['funny_ratings']=ted.ratings_list.apply(get_funny_ratings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "25e077e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    19645\n",
       "1      544\n",
       "2      964\n",
       "3       59\n",
       "4     1390\n",
       "Name: funny_ratings, dtype: int64"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.funny_ratings.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "eb21cd37",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted['funny_rate']=ted.funny_ratings /ted.num_ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "da6a1ca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1849                       Science humorist\n",
       "337                                Comedian\n",
       "124     Performance poet, multimedia artist\n",
       "315                                  Expert\n",
       "1168             Social energy entrepreneur\n",
       "1468                          Ornithologist\n",
       "595                  Comedian, voice artist\n",
       "1534                         Cartoon editor\n",
       "97                                 Satirist\n",
       "2297                          Actor, writer\n",
       "568                                Comedian\n",
       "675                          Data scientist\n",
       "21                     Humorist, web artist\n",
       "194                                Jugglers\n",
       "2273                    Comedian and writer\n",
       "2114                    Comedian and writer\n",
       "173                                Investor\n",
       "747                                Comedian\n",
       "1398                               Comedian\n",
       "685             Actor, comedian, playwright\n",
       "Name: speaker_occupation, dtype: object"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# step2\n",
    "ted.sort_values('funny_rate').speaker_occupation.tail(20) #funny talks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "66024a2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step3:Analyze the funny rate by occupation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "a4ff67cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "speaker_occupation\n",
       "Comedian                       0.512457\n",
       "Actor, writer                  0.515152\n",
       "Actor, comedian, playwright    0.558107\n",
       "Jugglers                       0.566828\n",
       "Comedian and writer            0.602085\n",
       "Name: funny_rate, dtype: float64"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.groupby('speaker_occupation').funny_rate.mean().sort_values().tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "2de7f7d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count       2544\n",
       "unique      1458\n",
       "top       Writer\n",
       "freq          45\n",
       "Name: speaker_occupation, dtype: object"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted.speaker_occupation.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "94f71992",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Step4: Focus on occupations that are well-represented in data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "ee764a7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "occupation_counts=ted.speaker_occupation.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "66efb2a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "top_occupations=occupation_counts[occupation_counts>=5].index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "f1f4ca46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.indexes.base.Index"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(top_occupations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "82a4cfcf",
   "metadata": {},
   "outputs": [],
   "source": [
    "ted_top_occupations=ted[ted.speaker_occupation.isin(top_occupations)]  #filter in top_occupations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "229b5fa9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(786, 24)"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted_top_occupations.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "be99c734",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "speaker_occupation\n",
       "Surgeon                                       0.002465\n",
       "Physician                                     0.004515\n",
       "Photojournalist                               0.004908\n",
       "Investor and advocate for moral leadership    0.005198\n",
       "Photographer                                  0.007152\n",
       "                                                ...   \n",
       "Data scientist                                0.184076\n",
       "Producer                                      0.202531\n",
       "Singer/songwriter                             0.252205\n",
       "Performance poet, multimedia artist           0.306468\n",
       "Comedian                                      0.512457\n",
       "Name: funny_rate, Length: 68, dtype: float64"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ted_top_occupations.groupby('speaker_occupation').funny_rate.mean().sort_values() #least funny with least as from 5 "
   ]
  }
 ],
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