<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>show_id</th>
      <th>type</th>
      <th>title</th>
      <th>director</th>
      <th>cast</th>
      <th>country</th>
      <th>date_added</th>
      <th>release_year</th>
      <th>rating</th>
      <th>duration</th>
      <th>listed_in</th>
      <th>description</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>s1</td>
      <td>Movie</td>
      <td>Dick Johnson Is Dead</td>
      <td>Kirsten Johnson</td>
      <td>NaN</td>
      <td>United States</td>
      <td>2021-09-25 00:00:00</td>
      <td>2020</td>
      <td>PG-13</td>
      <td>90 min</td>
      <td>Documentaries</td>
      <td>As her father nears the end of his life, filmm...</td>
    </tr>
    <tr>
      <th>1</th>
      <td>s2</td>
      <td>TV Show</td>
      <td>Blood &amp; Water</td>
      <td>NaN</td>
      <td>Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...</td>
      <td>South Africa</td>
      <td>2021-09-24 00:00:00</td>
      <td>2021</td>
      <td>TV-MA</td>
      <td>2 Seasons</td>
      <td>International TV Shows, TV Dramas, TV Mysteries</td>
      <td>After crossing paths at a party, a Cape Town t...</td>
    </tr>
    <tr>
      <th>2</th>
      <td>s3</td>
      <td>TV Show</td>
      <td>Ganglands</td>
      <td>Julien Leclercq</td>
      <td>Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...</td>
      <td>NaN</td>
      <td>2021-09-24 00:00:00</td>
      <td>2021</td>
      <td>TV-MA</td>
      <td>1 Season</td>
      <td>Crime TV Shows, International TV Shows, TV Act...</td>
      <td>To protect his family from a powerful drug lor...</td>
    </tr>
    <tr>
      <th>3</th>
      <td>s4</td>
      <td>TV Show</td>
      <td>Jailbirds New Orleans</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>2021-09-24 00:00:00</td>
      <td>2021</td>
      <td>TV-MA</td>
      <td>1 Season</td>
      <td>Docuseries, Reality TV</td>
      <td>Feuds, flirtations and toilet talk go down amo...</td>
    </tr>
    <tr>
      <th>4</th>
      <td>s5</td>
      <td>TV Show</td>
      <td>Kota Factory</td>
      <td>NaN</td>
      <td>Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...</td>
      <td>India</td>
      <td>2021-09-24 00:00:00</td>
      <td>2021</td>
      <td>TV-MA</td>
      <td>2 Seasons</td>
      <td>International TV Shows, Romantic TV Shows, TV ...</td>
      <td>In a city of coaching centers known to train I...</td>
    </tr>
  </tbody>
</table>
</div>

  show_id     type                  title         director  \
0      s1    Movie   Dick Johnson Is Dead  Kirsten Johnson   
1      s2  TV Show          Blood & Water              NaN   
2      s3  TV Show              Ganglands  Julien Leclercq   
3      s4  TV Show  Jailbirds New Orleans              NaN   
4      s5  TV Show           Kota Factory              NaN   

                                                cast        country  \
0                                                NaN  United States   
1  Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   
2  Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi...            NaN   
3                                                NaN            NaN   
4  Mayur More, Jitendra Kumar, Ranjan Raj, Alam K...          India   

            date_added  release_year rating   duration  \
0  2021-09-25 00:00:00          2020  PG-13     90 min   
1  2021-09-24 00:00:00          2021  TV-MA  2 Seasons   
2  2021-09-24 00:00:00          2021  TV-MA   1 Season   
3  2021-09-24 00:00:00          2021  TV-MA   1 Season   
4  2021-09-24 00:00:00          2021  TV-MA  2 Seasons   

                                           listed_in  \
0                                      Documentaries   
1    International TV Shows, TV Dramas, TV Mysteries   
2  Crime TV Shows, International TV Shows, TV Act...   
3                             Docuseries, Reality TV   
4  International TV Shows, Romantic TV Shows, TV ...   

                                         description  
0  As her father nears the end of his life, filmm...  
1  After crossing paths at a party, a Cape Town t...  
2  To protect his family from a powerful drug lor...  
3  Feuds, flirtations and toilet talk go down amo...  
4  In a city of coaching centers known to train I...  

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Genre</th>
      <th>Count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>International Movies</td>
      <td>2752</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Dramas</td>
      <td>2427</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Comedies</td>
      <td>1674</td>
    </tr>
    <tr>
      <th>3</th>
      <td>International TV Shows</td>
      <td>1351</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Documentaries</td>
      <td>869</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Action &amp; Adventure</td>
      <td>859</td>
    </tr>
    <tr>
      <th>6</th>
      <td>TV Dramas</td>
      <td>763</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Independent Movies</td>
      <td>756</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Children &amp; Family Movies</td>
      <td>641</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Romantic Movies</td>
      <td>616</td>
    </tr>
    <tr>
      <th>10</th>
      <td>TV Comedies</td>
      <td>581</td>
    </tr>
    <tr>
      <th>11</th>
      <td>Thrillers</td>
      <td>577</td>
    </tr>
    <tr>
      <th>12</th>
      <td>Crime TV Shows</td>
      <td>470</td>
    </tr>
    <tr>
      <th>13</th>
      <td>Kids' TV</td>
      <td>451</td>
    </tr>
    <tr>
      <th>14</th>
      <td>Docuseries</td>
      <td>395</td>
    </tr>
    <tr>
      <th>15</th>
      <td>Music &amp; Musicals</td>
      <td>375</td>
    </tr>
    <tr>
      <th>16</th>
      <td>Romantic TV Shows</td>
      <td>370</td>
    </tr>
    <tr>
      <th>17</th>
      <td>Horror Movies</td>
      <td>357</td>
    </tr>
    <tr>
      <th>18</th>
      <td>Stand-Up Comedy</td>
      <td>343</td>
    </tr>
    <tr>
      <th>19</th>
      <td>Reality TV</td>
      <td>255</td>
    </tr>
    <tr>
      <th>20</th>
      <td>British TV Shows</td>
      <td>253</td>
    </tr>
    <tr>
      <th>21</th>
      <td>Sci-Fi &amp; Fantasy</td>
      <td>243</td>
    </tr>
    <tr>
      <th>22</th>
      <td>Sports Movies</td>
      <td>219</td>
    </tr>
    <tr>
      <th>23</th>
      <td>Anime Series</td>
      <td>176</td>
    </tr>
    <tr>
      <th>24</th>
      <td>Spanish-Language TV Shows</td>
      <td>174</td>
    </tr>
    <tr>
      <th>25</th>
      <td>TV Action &amp; Adventure</td>
      <td>168</td>
    </tr>
    <tr>
      <th>26</th>
      <td>Korean TV Shows</td>
      <td>151</td>
    </tr>
    <tr>
      <th>27</th>
      <td>Classic Movies</td>
      <td>116</td>
    </tr>
    <tr>
      <th>28</th>
      <td>LGBTQ Movies</td>
      <td>102</td>
    </tr>
    <tr>
      <th>29</th>
      <td>TV Mysteries</td>
      <td>98</td>
    </tr>
    <tr>
      <th>30</th>
      <td>Science &amp; Nature TV</td>
      <td>92</td>
    </tr>
    <tr>
      <th>31</th>
      <td>TV Sci-Fi &amp; Fantasy</td>
      <td>84</td>
    </tr>
    <tr>
      <th>32</th>
      <td>TV Horror</td>
      <td>75</td>
    </tr>
    <tr>
      <th>33</th>
      <td>Cult Movies</td>
      <td>71</td>
    </tr>
    <tr>
      <th>34</th>
      <td>Anime Features</td>
      <td>71</td>
    </tr>
    <tr>
      <th>35</th>
      <td>Teen TV Shows</td>
      <td>69</td>
    </tr>
    <tr>
      <th>36</th>
      <td>Faith &amp; Spirituality</td>
      <td>65</td>
    </tr>
    <tr>
      <th>37</th>
      <td>TV Thrillers</td>
      <td>57</td>
    </tr>
    <tr>
      <th>38</th>
      <td>Movies</td>
      <td>57</td>
    </tr>
    <tr>
      <th>39</th>
      <td>Stand-Up Comedy &amp; Talk Shows</td>
      <td>56</td>
    </tr>
    <tr>
      <th>40</th>
      <td>Classic &amp; Cult TV</td>
      <td>28</td>
    </tr>
    <tr>
      <th>41</th>
      <td>TV Shows</td>
      <td>16</td>
    </tr>
  </tbody>
</table>
</div>

                           Genre  Count
0           International Movies   2752
1                         Dramas   2427
2                       Comedies   1674
3         International TV Shows   1351
4                  Documentaries    869
5             Action & Adventure    859
6                      TV Dramas    763
7             Independent Movies    756
8       Children & Family Movies    641
9                Romantic Movies    616
10                   TV Comedies    581
11                     Thrillers    577
12                Crime TV Shows    470
13                      Kids' TV    451
14                    Docuseries    395
15              Music & Musicals    375
16             Romantic TV Shows    370
17                 Horror Movies    357
18               Stand-Up Comedy    343
19                    Reality TV    255
20              British TV Shows    253
21              Sci-Fi & Fantasy    243
22                 Sports Movies    219
23                  Anime Series    176
24     Spanish-Language TV Shows    174
25         TV Action & Adventure    168
26               Korean TV Shows    151
27                Classic Movies    116
28                  LGBTQ Movies    102
29                  TV Mysteries     98
30           Science & Nature TV     92
31           TV Sci-Fi & Fantasy     84
32                     TV Horror     75
33                   Cult Movies     71
34                Anime Features     71
35                 Teen TV Shows     69
36          Faith & Spirituality     65
37                  TV Thrillers     57
38                        Movies     57
39  Stand-Up Comedy & Talk Shows     56
40             Classic & Cult TV     28
41                      TV Shows     16

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Year</th>
      <th>Count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1925</td>
      <td>1</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1942</td>
      <td>2</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1943</td>
      <td>3</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1944</td>
      <td>3</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1945</td>
      <td>4</td>
    </tr>
    <tr>
      <th>...</th>
      <td>...</td>
      <td>...</td>
    </tr>
    <tr>
      <th>69</th>
      <td>2017</td>
      <td>1032</td>
    </tr>
    <tr>
      <th>70</th>
      <td>2018</td>
      <td>1147</td>
    </tr>
    <tr>
      <th>71</th>
      <td>2019</td>
      <td>1030</td>
    </tr>
    <tr>
      <th>72</th>
      <td>2020</td>
      <td>953</td>
    </tr>
    <tr>
      <th>73</th>
      <td>2021</td>
      <td>592</td>
    </tr>
  </tbody>
</table>
<p>74 rows × 2 columns</p>
</div>

    Year  Count
0   1925      1
1   1942      2
2   1943      3
3   1944      3
4   1945      4
..   ...    ...
69  2017   1032
70  2018   1147
71  2019   1030
72  2020    953
73  2021    592

[74 rows x 2 columns]

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Rating</th>
      <th>Count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>TV-MA</td>
      <td>3207</td>
    </tr>
    <tr>
      <th>1</th>
      <td>TV-14</td>
      <td>2160</td>
    </tr>
    <tr>
      <th>2</th>
      <td>TV-PG</td>
      <td>863</td>
    </tr>
    <tr>
      <th>3</th>
      <td>R</td>
      <td>799</td>
    </tr>
    <tr>
      <th>4</th>
      <td>PG-13</td>
      <td>490</td>
    </tr>
    <tr>
      <th>5</th>
      <td>TV-Y7</td>
      <td>334</td>
    </tr>
    <tr>
      <th>6</th>
      <td>TV-Y</td>
      <td>307</td>
    </tr>
    <tr>
      <th>7</th>
      <td>PG</td>
      <td>287</td>
    </tr>
    <tr>
      <th>8</th>
      <td>TV-G</td>
      <td>220</td>
    </tr>
    <tr>
      <th>9</th>
      <td>NR</td>
      <td>80</td>
    </tr>
    <tr>
      <th>10</th>
      <td>G</td>
      <td>41</td>
    </tr>
    <tr>
      <th>11</th>
      <td>TV-Y7-FV</td>
      <td>6</td>
    </tr>
    <tr>
      <th>12</th>
      <td>NC-17</td>
      <td>3</td>
    </tr>
    <tr>
      <th>13</th>
      <td>UR</td>
      <td>3</td>
    </tr>
    <tr>
      <th>14</th>
      <td>74 min</td>
      <td>1</td>
    </tr>
    <tr>
      <th>15</th>
      <td>84 min</td>
      <td>1</td>
    </tr>
    <tr>
      <th>16</th>
      <td>66 min</td>
      <td>1</td>
    </tr>
  </tbody>
</table>
</div>

      Rating  Count
0      TV-MA   3207
1      TV-14   2160
2      TV-PG    863
3          R    799
4      PG-13    490
5      TV-Y7    334
6       TV-Y    307
7         PG    287
8       TV-G    220
9         NR     80
10         G     41
11  TV-Y7-FV      6
12     NC-17      3
13        UR      3
14    74 min      1
15    84 min      1
16    66 min      1

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Country</th>
      <th>Count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>United States</td>
      <td>2818</td>
    </tr>
    <tr>
      <th>1</th>
      <td>India</td>
      <td>972</td>
    </tr>
    <tr>
      <th>2</th>
      <td>United Kingdom</td>
      <td>419</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Japan</td>
      <td>245</td>
    </tr>
    <tr>
      <th>4</th>
      <td>South Korea</td>
      <td>199</td>
    </tr>
    <tr>
      <th>...</th>
      <td>...</td>
      <td>...</td>
    </tr>
    <tr>
      <th>743</th>
      <td>Mexico, United States, Spain, Colombia</td>
      <td>1</td>
    </tr>
    <tr>
      <th>744</th>
      <td>Canada, Norway</td>
      <td>1</td>
    </tr>
    <tr>
      <th>745</th>
      <td>Finland, Germany, Belgium</td>
      <td>1</td>
    </tr>
    <tr>
      <th>746</th>
      <td>Argentina, United States, Mexico</td>
      <td>1</td>
    </tr>
    <tr>
      <th>747</th>
      <td>United Kingdom, United States, Germany, Denmar...</td>
      <td>1</td>
    </tr>
  </tbody>
</table>
<p>748 rows × 2 columns</p>
</div>

                                               Country  Count
0                                        United States   2818
1                                                India    972
2                                       United Kingdom    419
3                                                Japan    245
4                                          South Korea    199
..                                                 ...    ...
743             Mexico, United States, Spain, Colombia      1
744                                     Canada, Norway      1
745                          Finland, Germany, Belgium      1
746                   Argentina, United States, Mexico      1
747  United Kingdom, United States, Germany, Denmar...      1

[748 rows x 2 columns]

<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Director</th>
      <th>Count</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Rajiv Chilaka</td>
      <td>19</td>
    </tr>
    <tr>
      <th>1</th>
      <td>RaÃºl Campos, Jan Suter</td>
      <td>18</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Suhas Kadav</td>
      <td>16</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Marcus Raboy</td>
      <td>16</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Jay Karas</td>
      <td>14</td>
    </tr>
    <tr>
      <th>...</th>
      <td>...</td>
      <td>...</td>
    </tr>
    <tr>
      <th>4523</th>
      <td>Eric Bross</td>
      <td>1</td>
    </tr>
    <tr>
      <th>4524</th>
      <td>Will Eisenberg</td>
      <td>1</td>
    </tr>
    <tr>
      <th>4525</th>
      <td>Marina Seresesky</td>
      <td>1</td>
    </tr>
    <tr>
      <th>4526</th>
      <td>Kenny Leon</td>
      <td>1</td>
    </tr>
    <tr>
      <th>4527</th>
      <td>Luke Snellin</td>
      <td>1</td>
    </tr>
  </tbody>
</table>
<p>4528 rows × 2 columns</p>
</div>

                     Director  Count
0               Rajiv Chilaka     19
1     RaÃºl Campos, Jan Suter     18
2                 Suhas Kadav     16
3                Marcus Raboy     16
4                   Jay Karas     14
...                       ...    ...
4523               Eric Bross      1
4524           Will Eisenberg      1
4525         Marina Seresesky      1
4526               Kenny Leon      1
4527             Luke Snellin      1

[4528 rows x 2 columns]

Analysis of Popular Genres on Netflix with Graphical Representation

What are the most popular genres on Netflix?

Show with graph

Can you show the trend of new releases over the years?

What are the most popular ratings on Netflix?

Which countries have produced the most content on Netflix over the years?

change the map diagram

What are the most popular directors on Netflix?

show with line graph

How does the distribution of movies vs. TV shows on Netflix vary by year? (Show line graph)