Clase 5 - Ejercicios de tarea completos (con mapa y gráficos).ipynb

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      "name": " Ejercicios Clase 5",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hXlGMvi_RQu_"
      },
      "source": [
        "**Ejercicio grupal**:\n",
        "\n",
        "Importar el dataset (está compartido en git) en Google colab.\n",
        "\n",
        "Mostrar:\n",
        "- ¿Cuantas películas se lanzaron en 2019?\n",
        "- ¿Cuantas películas se lanzaron entre 2017 y 2018?\n",
        "- ¿Qué cantidad de películas hay publicadas?\n",
        "- ¿Cuántos shows de televisión hay publicados?\n",
        "\n",
        "Plus:\n",
        "- Un gráfico de barras con la cantidad de películas lanzadas por año\n",
        "- Gráficos con países de origen\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eSd9L4zeTAkv"
      },
      "source": [
        "Importar el dataset (está compartido en git) en Google colab."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        "outputId": "0148cd37-d882-4da7-9b6c-aaf9c6b3b913"
      },
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv(\"https://raw.githubusercontent.com/manquintana/taller_programacion_2_uade/master/Datasets/clase_5%20-%20netflix_titles.csv\")\n",
        "df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>João Miguel, Bianca Comparato, Michel Gomes, R...</td>\n",
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              "      <td>Jorge Michel Grau</td>\n",
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              "      <td>2016</td>\n",
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              "      <td>2008</td>\n",
              "      <td>PG-13</td>\n",
              "      <td>123 min</td>\n",
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              "2         s3  ...  When an army recruit is found dead, his fellow...\n",
              "3         s4  ...  In a postapocalyptic world, rag-doll robots hi...\n",
              "4         s5  ...  A brilliant group of students become card-coun...\n",
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              "\n",
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    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QLtMjrDQUgGU"
      },
      "source": [
        "**¿Cuántas películas se lanzaron en 2019?:**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 658
        },
        "id": "XZ860d1FUjgL",
        "outputId": "84e50422-8ab1-42fd-ec75-f0012ca0b529"
      },
      "source": [
        "peliculas_2019 = df[(df[\"type\"] == \"Movie\") & (df[\"release_year\"] == 2019) ]\n",
        "print (f\"En 2019 se lanzaron {len(peliculas_2019)} peliculas\")\n",
        "peliculas_2019"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "En 2019 se lanzaron 582 peliculas\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
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              "      <td>Helen Mirren, Gengher Gatti</td>\n",
              "      <td>Italy</td>\n",
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              "      <td>2019</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>95 min</td>\n",
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              "      <td>In this documentary, South African rapper Nast...</td>\n",
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              "      <td>Sam Dunn</td>\n",
              "      <td>NaN</td>\n",
              "      <td>United Kingdom, Canada, United States</td>\n",
              "      <td>March 1, 2020</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>90 min</td>\n",
              "      <td>Documentaries, Music &amp; Musicals</td>\n",
              "      <td>This documentary delves into the mystique behi...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
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              "8         s9  ...  When a doctor goes missing, his psychiatrist w...\n",
              "14       s15  ...  Stranded when the Earth is suddenly destroyed ...\n",
              "18       s19  ...  On India's Independence Day, a zany mishap in ...\n",
              "28       s29  ...  Through her diary, Anne Frank's story is retol...\n",
              "...      ...  ...                                                ...\n",
              "7654   s7655  ...  When a major drug deal goes sour, the queen of...\n",
              "7658   s7659  ...  For the 50th anniversary of the legendary Wood...\n",
              "7739   s7740  ...  Bumbling through politics, a billionaire busin...\n",
              "7784   s7785  ...  In this documentary, South African rapper Nast...\n",
              "7786   s7787  ...  This documentary delves into the mystique behi...\n",
              "\n",
              "[582 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7LBM7irgX6Tw"
      },
      "source": [
        "**¿Cuantas películas se lanzaron entre 2017 y 2018?:**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 606
        },
        "id": "ZJ8JBnCaYC4k",
        "outputId": "43c1013c-5046-440d-82a9-d85ff1baa837"
      },
      "source": [
        "\n",
        "lanzamientos =df[(df['release_year']>2016) & (df['release_year']<2019)] \n",
        "peliculas_2017_2018 = lanzamientos[lanzamientos['type'] == \"Movie\"]\n",
        "print (f\"Entre 2017 y 2018 se lanzaron {len(peliculas_2017_2018)} peliculas\")\n",
        "peliculas_2017_2018\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Entre 2017 y 2018 se lanzaron 1478 peliculas\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>show_id</th>\n",
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              "      <th>title</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>s11</td>\n",
              "      <td>Movie</td>\n",
              "      <td>1922</td>\n",
              "      <td>Zak Hilditch</td>\n",
              "      <td>Thomas Jane, Molly Parker, Dylan Schmid, Kaitl...</td>\n",
              "      <td>United States</td>\n",
              "      <td>October 20, 2017</td>\n",
              "      <td>2017</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>103 min</td>\n",
              "      <td>Dramas, Thrillers</td>\n",
              "      <td>A farmer pens a confession admitting to his wi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>s14</td>\n",
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              "      <td>2,215</td>\n",
              "      <td>Nottapon Boonprakob</td>\n",
              "      <td>Artiwara Kongmalai</td>\n",
              "      <td>Thailand</td>\n",
              "      <td>March 1, 2019</td>\n",
              "      <td>2018</td>\n",
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              "      <td>89 min</td>\n",
              "      <td>Documentaries, International Movies, Sports Mo...</td>\n",
              "      <td>This intimate documentary follows rock star Ar...</td>\n",
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              "      <td>s18</td>\n",
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              "      <td>Paul Greengrass</td>\n",
              "      <td>Anders Danielsen Lie, Jon Øigarden, Jonas Stra...</td>\n",
              "      <td>Norway, Iceland, United States</td>\n",
              "      <td>October 10, 2018</td>\n",
              "      <td>2018</td>\n",
              "      <td>R</td>\n",
              "      <td>144 min</td>\n",
              "      <td>Dramas, Thrillers</td>\n",
              "      <td>After devastating terror attacks in Norway, a ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>s20</td>\n",
              "      <td>Movie</td>\n",
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              "      <td>Lee Dixon, Ian Wright, Paul Merson</td>\n",
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              "      <td>May 16, 2018</td>\n",
              "      <td>2017</td>\n",
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              "      <td>87 min</td>\n",
              "      <td>Sports Movies</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>s21</td>\n",
              "      <td>Movie</td>\n",
              "      <td>​​Kuch Bheege Alfaaz</td>\n",
              "      <td>Onir</td>\n",
              "      <td>Geetanjali Thapa, Zain Khan Durrani, Shray Rai...</td>\n",
              "      <td>India</td>\n",
              "      <td>September 1, 2018</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>110 min</td>\n",
              "      <td>Dramas, Independent Movies, International Movies</td>\n",
              "      <td>After accidentally connecting over the Interne...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7751</th>\n",
              "      <td>s7752</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Yucatán</td>\n",
              "      <td>Daniel Monzón</td>\n",
              "      <td>Luis Tosar, Rodrigo de la Serna, Joan Pera, St...</td>\n",
              "      <td>Spain</td>\n",
              "      <td>February 15, 2019</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>130 min</td>\n",
              "      <td>Comedies, International Movies</td>\n",
              "      <td>Competing con artists attempt to creatively an...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7764</th>\n",
              "      <td>s7765</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zero</td>\n",
              "      <td>Aanand Rai</td>\n",
              "      <td>Shah Rukh Khan, Anushka Sharma, Katrina Kaif, ...</td>\n",
              "      <td>India</td>\n",
              "      <td>May 21, 2019</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>159 min</td>\n",
              "      <td>Comedies, Dramas, International Movies</td>\n",
              "      <td>Through his relationships with two wildly diff...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7765</th>\n",
              "      <td>s7766</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zero Hour</td>\n",
              "      <td>Robert O. Peters</td>\n",
              "      <td>Richard Mofe-Damijo, Alex Ekubo, Ali Nuhu, Rah...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>December 13, 2019</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>89 min</td>\n",
              "      <td>International Movies, Thrillers</td>\n",
              "      <td>After his father passes, the heir to a retail ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7771</th>\n",
              "      <td>s7772</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zion</td>\n",
              "      <td>Floyd Russ</td>\n",
              "      <td>Zion Clark</td>\n",
              "      <td>United States</td>\n",
              "      <td>August 10, 2018</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>12 min</td>\n",
              "      <td>Documentaries, Sports Movies</td>\n",
              "      <td>Born without legs and stuck in foster care for...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7780</th>\n",
              "      <td>s7781</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zoo</td>\n",
              "      <td>Shlok Sharma</td>\n",
              "      <td>Shashank Arora, Shweta Tripathi, Rahul Kumar, ...</td>\n",
              "      <td>India</td>\n",
              "      <td>July 1, 2018</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>94 min</td>\n",
              "      <td>Dramas, Independent Movies, International Movies</td>\n",
              "      <td>A drug dealer starts having doubts about his t...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1478 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     show_id  ...                                        description\n",
              "10       s11  ...  A farmer pens a confession admitting to his wi...\n",
              "13       s14  ...  This intimate documentary follows rock star Ar...\n",
              "17       s18  ...  After devastating terror attacks in Norway, a ...\n",
              "19       s20  ...  Mixing old footage with interviews, this is th...\n",
              "20       s21  ...  After accidentally connecting over the Interne...\n",
              "...      ...  ...                                                ...\n",
              "7751   s7752  ...  Competing con artists attempt to creatively an...\n",
              "7764   s7765  ...  Through his relationships with two wildly diff...\n",
              "7765   s7766  ...  After his father passes, the heir to a retail ...\n",
              "7771   s7772  ...  Born without legs and stuck in foster care for...\n",
              "7780   s7781  ...  A drug dealer starts having doubts about his t...\n",
              "\n",
              "[1478 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eWre3sNwxEKW"
      },
      "source": [
        "**¿Qué cantidad de películas hay publicadas?**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 710
        },
        "id": "_tHvIhJ4xaU3",
        "outputId": "a0bb926f-5e6f-424a-d33e-1d7755557ed7"
      },
      "source": [
        "peliculas = df[df[\"type\"] == \"Movie\"]\n",
        "print (f\"Hay {len(peliculas)} peliculas publicadas\")\n",
        "peliculas"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Hay 5377 peliculas publicadas\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>s2</td>\n",
              "      <td>Movie</td>\n",
              "      <td>7:19</td>\n",
              "      <td>Jorge Michel Grau</td>\n",
              "      <td>Demián Bichir, Héctor Bonilla, Oscar Serrano, ...</td>\n",
              "      <td>Mexico</td>\n",
              "      <td>December 23, 2016</td>\n",
              "      <td>2016</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>93 min</td>\n",
              "      <td>Dramas, International Movies</td>\n",
              "      <td>After a devastating earthquake hits Mexico Cit...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>s3</td>\n",
              "      <td>Movie</td>\n",
              "      <td>23:59</td>\n",
              "      <td>Gilbert Chan</td>\n",
              "      <td>Tedd Chan, Stella Chung, Henley Hii, Lawrence ...</td>\n",
              "      <td>Singapore</td>\n",
              "      <td>December 20, 2018</td>\n",
              "      <td>2011</td>\n",
              "      <td>R</td>\n",
              "      <td>78 min</td>\n",
              "      <td>Horror Movies, International Movies</td>\n",
              "      <td>When an army recruit is found dead, his fellow...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>s4</td>\n",
              "      <td>Movie</td>\n",
              "      <td>9</td>\n",
              "      <td>Shane Acker</td>\n",
              "      <td>Elijah Wood, John C. Reilly, Jennifer Connelly...</td>\n",
              "      <td>United States</td>\n",
              "      <td>November 16, 2017</td>\n",
              "      <td>2009</td>\n",
              "      <td>PG-13</td>\n",
              "      <td>80 min</td>\n",
              "      <td>Action &amp; Adventure, Independent Movies, Sci-Fi...</td>\n",
              "      <td>In a postapocalyptic world, rag-doll robots hi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>s5</td>\n",
              "      <td>Movie</td>\n",
              "      <td>21</td>\n",
              "      <td>Robert Luketic</td>\n",
              "      <td>Jim Sturgess, Kevin Spacey, Kate Bosworth, Aar...</td>\n",
              "      <td>United States</td>\n",
              "      <td>January 1, 2020</td>\n",
              "      <td>2008</td>\n",
              "      <td>PG-13</td>\n",
              "      <td>123 min</td>\n",
              "      <td>Dramas</td>\n",
              "      <td>A brilliant group of students become card-coun...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>s7</td>\n",
              "      <td>Movie</td>\n",
              "      <td>122</td>\n",
              "      <td>Yasir Al Yasiri</td>\n",
              "      <td>Amina Khalil, Ahmed Dawood, Tarek Lotfy, Ahmed...</td>\n",
              "      <td>Egypt</td>\n",
              "      <td>June 1, 2020</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>95 min</td>\n",
              "      <td>Horror Movies, International Movies</td>\n",
              "      <td>After an awful accident, a couple admitted to ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7781</th>\n",
              "      <td>s7782</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zoom</td>\n",
              "      <td>Peter Hewitt</td>\n",
              "      <td>Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...</td>\n",
              "      <td>United States</td>\n",
              "      <td>January 11, 2020</td>\n",
              "      <td>2006</td>\n",
              "      <td>PG</td>\n",
              "      <td>88 min</td>\n",
              "      <td>Children &amp; Family Movies, Comedies</td>\n",
              "      <td>Dragged from civilian life, a former superhero...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7782</th>\n",
              "      <td>s7783</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zozo</td>\n",
              "      <td>Josef Fares</td>\n",
              "      <td>Imad Creidi, Antoinette Turk, Elias Gergi, Car...</td>\n",
              "      <td>Sweden, Czech Republic, United Kingdom, Denmar...</td>\n",
              "      <td>October 19, 2020</td>\n",
              "      <td>2005</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>99 min</td>\n",
              "      <td>Dramas, International Movies</td>\n",
              "      <td>When Lebanon's Civil War deprives Zozo of his ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7783</th>\n",
              "      <td>s7784</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zubaan</td>\n",
              "      <td>Mozez Singh</td>\n",
              "      <td>Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...</td>\n",
              "      <td>India</td>\n",
              "      <td>March 2, 2019</td>\n",
              "      <td>2015</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>111 min</td>\n",
              "      <td>Dramas, International Movies, Music &amp; Musicals</td>\n",
              "      <td>A scrappy but poor boy worms his way into a ty...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7784</th>\n",
              "      <td>s7785</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zulu Man in Japan</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Nasty C</td>\n",
              "      <td>NaN</td>\n",
              "      <td>September 25, 2020</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>44 min</td>\n",
              "      <td>Documentaries, International Movies, Music &amp; M...</td>\n",
              "      <td>In this documentary, South African rapper Nast...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7786</th>\n",
              "      <td>s7787</td>\n",
              "      <td>Movie</td>\n",
              "      <td>ZZ TOP: THAT LITTLE OL' BAND FROM TEXAS</td>\n",
              "      <td>Sam Dunn</td>\n",
              "      <td>NaN</td>\n",
              "      <td>United Kingdom, Canada, United States</td>\n",
              "      <td>March 1, 2020</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>90 min</td>\n",
              "      <td>Documentaries, Music &amp; Musicals</td>\n",
              "      <td>This documentary delves into the mystique behi...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5377 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     show_id  ...                                        description\n",
              "1         s2  ...  After a devastating earthquake hits Mexico Cit...\n",
              "2         s3  ...  When an army recruit is found dead, his fellow...\n",
              "3         s4  ...  In a postapocalyptic world, rag-doll robots hi...\n",
              "4         s5  ...  A brilliant group of students become card-coun...\n",
              "6         s7  ...  After an awful accident, a couple admitted to ...\n",
              "...      ...  ...                                                ...\n",
              "7781   s7782  ...  Dragged from civilian life, a former superhero...\n",
              "7782   s7783  ...  When Lebanon's Civil War deprives Zozo of his ...\n",
              "7783   s7784  ...  A scrappy but poor boy worms his way into a ty...\n",
              "7784   s7785  ...  In this documentary, South African rapper Nast...\n",
              "7786   s7787  ...  This documentary delves into the mystique behi...\n",
              "\n",
              "[5377 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n50FB_Hl2UEx"
      },
      "source": [
        "**¿Cuántos shows de televisión hay publicados?:**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 832
        },
        "id": "rjrSFdXf2aNB",
        "outputId": "3f8422e3-dc05-4c92-d3b6-b7597cd84055"
      },
      "source": [
        "tv_shows = df[df[\"type\"] == \"TV Show\"]\n",
        "print (f\"Hay {len(tv_shows)} shows de televisión publicados\")\n",
        "tv_shows"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Hay 2410 shows de televisión publicados\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "        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>show_id</th>\n",
              "      <th>type</th>\n",
              "      <th>title</th>\n",
              "      <th>director</th>\n",
              "      <th>cast</th>\n",
              "      <th>country</th>\n",
              "      <th>date_added</th>\n",
              "      <th>release_year</th>\n",
              "      <th>rating</th>\n",
              "      <th>duration</th>\n",
              "      <th>listed_in</th>\n",
              "      <th>description</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>s1</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>3%</td>\n",
              "      <td>NaN</td>\n",
              "      <td>João Miguel, Bianca Comparato, Michel Gomes, R...</td>\n",
              "      <td>Brazil</td>\n",
              "      <td>August 14, 2020</td>\n",
              "      <td>2020</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>4 Seasons</td>\n",
              "      <td>International TV Shows, TV Dramas, TV Sci-Fi &amp;...</td>\n",
              "      <td>In a future where the elite inhabit an island ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>s6</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>46</td>\n",
              "      <td>Serdar Akar</td>\n",
              "      <td>Erdal Beşikçioğlu, Yasemin Allen, Melis Birkan...</td>\n",
              "      <td>Turkey</td>\n",
              "      <td>July 1, 2017</td>\n",
              "      <td>2016</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>International TV Shows, TV Dramas, TV Mysteries</td>\n",
              "      <td>A genetics professor experiments with a treatm...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>s12</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>1983</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Robert Więckiewicz, Maciej Musiał, Michalina O...</td>\n",
              "      <td>Poland, United States</td>\n",
              "      <td>November 30, 2018</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>Crime TV Shows, International TV Shows, TV Dramas</td>\n",
              "      <td>In this dark alt-history thriller, a naïve law...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>s13</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>1994</td>\n",
              "      <td>Diego Enrique Osorno</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mexico</td>\n",
              "      <td>May 17, 2019</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>Crime TV Shows, Docuseries, International TV S...</td>\n",
              "      <td>Archival video and new interviews examine Mexi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>s17</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Feb-09</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Shahd El Yaseen, Shaila Sabt, Hala, Hanadi Al-...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>March 20, 2019</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-14</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>International TV Shows, TV Dramas</td>\n",
              "      <td>As a psychology professor faces Alzheimer's, h...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7767</th>\n",
              "      <td>s7768</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Zindagi Gulzar Hai</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Sanam Saeed, Fawad Khan, Ayesha Omer, Mehreen ...</td>\n",
              "      <td>Pakistan</td>\n",
              "      <td>December 15, 2016</td>\n",
              "      <td>2012</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>International TV Shows, Romantic TV Shows, TV ...</td>\n",
              "      <td>Strong-willed, middle-class Kashaf and carefre...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7775</th>\n",
              "      <td>s7776</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Zoids Wild</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Kensho Ono, Takahiro Sakurai, Mikako Komatsu, ...</td>\n",
              "      <td>Japan</td>\n",
              "      <td>August 14, 2020</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-Y7</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>Anime Series, Kids' TV</td>\n",
              "      <td>A quest for freedom and legendary treasure beg...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7777</th>\n",
              "      <td>s7778</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Zombie Dumb</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>July 1, 2019</td>\n",
              "      <td>2018</td>\n",
              "      <td>TV-Y7</td>\n",
              "      <td>2 Seasons</td>\n",
              "      <td>Kids' TV, Korean TV Shows, TV Comedies</td>\n",
              "      <td>While living alone in a spooky town, a young g...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7779</th>\n",
              "      <td>s7780</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Zona Rosa</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Manu NNa, Ana Julia Yeyé, Ray Contreras, Pablo...</td>\n",
              "      <td>Mexico</td>\n",
              "      <td>November 26, 2019</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>International TV Shows, Spanish-Language TV Sh...</td>\n",
              "      <td>An assortment of talent takes the stage for a ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7785</th>\n",
              "      <td>s7786</td>\n",
              "      <td>TV Show</td>\n",
              "      <td>Zumbo's Just Desserts</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Adriano Zumbo, Rachel Khoo</td>\n",
              "      <td>Australia</td>\n",
              "      <td>October 31, 2020</td>\n",
              "      <td>2019</td>\n",
              "      <td>TV-PG</td>\n",
              "      <td>1 Season</td>\n",
              "      <td>International TV Shows, Reality TV</td>\n",
              "      <td>Dessert wizard Adriano Zumbo looks for the nex...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2410 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     show_id  ...                                        description\n",
              "0         s1  ...  In a future where the elite inhabit an island ...\n",
              "5         s6  ...  A genetics professor experiments with a treatm...\n",
              "11       s12  ...  In this dark alt-history thriller, a naïve law...\n",
              "12       s13  ...  Archival video and new interviews examine Mexi...\n",
              "16       s17  ...  As a psychology professor faces Alzheimer's, h...\n",
              "...      ...  ...                                                ...\n",
              "7767   s7768  ...  Strong-willed, middle-class Kashaf and carefre...\n",
              "7775   s7776  ...  A quest for freedom and legendary treasure beg...\n",
              "7777   s7778  ...  While living alone in a spooky town, a young g...\n",
              "7779   s7780  ...  An assortment of talent takes the stage for a ...\n",
              "7785   s7786  ...  Dessert wizard Adriano Zumbo looks for the nex...\n",
              "\n",
              "[2410 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hOQEHYYn3_aQ"
      },
      "source": [
        "Gráfico de barras con la cantidad de películas lanzadas por año"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "SzSa9BPl9KPx",
        "outputId": "ce5a4752-b67e-4f0c-8afe-6e30f0e0b376"
      },
      "source": [
        "peliculas = df[df[\"type\"] == \"Movie\"]\n",
        "peliculas\n",
        "\n",
        "pelis_ordenadas =peliculas.groupby([\"release_year\"]).size().reset_index(name=\"cantidad\")\n",
        "pelis_ordenadas\n",
        "\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>release_year</th>\n",
              "      <th>cantidad</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1942</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1943</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1944</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1945</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1946</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>2017</td>\n",
              "      <td>744</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68</th>\n",
              "      <td>2018</td>\n",
              "      <td>734</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>69</th>\n",
              "      <td>2019</td>\n",
              "      <td>582</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>2020</td>\n",
              "      <td>411</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>71</th>\n",
              "      <td>2021</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>72 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    release_year  cantidad\n",
              "0           1942         2\n",
              "1           1943         3\n",
              "2           1944         3\n",
              "3           1945         3\n",
              "4           1946         1\n",
              "..           ...       ...\n",
              "67          2017       744\n",
              "68          2018       734\n",
              "69          2019       582\n",
              "70          2020       411\n",
              "71          2021        12\n",
              "\n",
              "[72 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 674
        },
        "id": "nGyGW9S0ekLw",
        "outputId": "55153cd0-ffa2-4b27-8865-cbada3f50043"
      },
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "barras=sns.catplot( x=\"release_year\", y=\"cantidad\", kind=\"bar\", data= pelis_ordenadas, height=10, aspect=20/10)\n",
        "barras.set_xticklabels(rotation=90)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.FacetGrid at 0x7f0833267750>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "RNAOoc6RiY66",
        "outputId": "7ae02376-3949-4416-d5a0-7a687e831cc7"
      },
      "source": [
        "histograma= sns.lineplot(x=\"release_year\", y=\"cantidad\",  data=pelis_ordenadas, color=\"blue\")\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 2426.4x595.44 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CLLkyaH2lpCr"
      },
      "source": [
        "Gráficos con países de origen"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "x-fehoy9pUrx",
        "outputId": "48a9cf75-c0cb-4c4a-be6c-7515a9e4b997"
      },
      "source": [
        "pelis_clean= peliculas.dropna()\n",
        "pelis_clean = pelis_clean.groupby([\"country\"]).size().reset_index(name=\"cantidad_peliculas\")\n",
        "pelis_clean\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>country</th>\n",
              "      <th>cantidad_peliculas</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Argentina, Brazil, France, Poland, Germany, De...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Argentina, Chile</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Argentina, Chile, Peru</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Argentina, France</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>531</th>\n",
              "      <td>Uruguay, Guatemala</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>532</th>\n",
              "      <td>Uruguay, Spain, Mexico</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>533</th>\n",
              "      <td>Venezuela</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>534</th>\n",
              "      <td>Vietnam</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>535</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>536 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                               country  cantidad_peliculas\n",
              "0                                            Argentina                  31\n",
              "1    Argentina, Brazil, France, Poland, Germany, De...                   1\n",
              "2                                     Argentina, Chile                   1\n",
              "3                               Argentina, Chile, Peru                   1\n",
              "4                                    Argentina, France                   1\n",
              "..                                                 ...                 ...\n",
              "531                                 Uruguay, Guatemala                   1\n",
              "532                             Uruguay, Spain, Mexico                   1\n",
              "533                                          Venezuela                   1\n",
              "534                                            Vietnam                   5\n",
              "535                                           Zimbabwe                   1\n",
              "\n",
              "[536 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wfilgv3RxYjX",
        "outputId": "88af915a-e271-42df-93ad-dd1e0d495c3b"
      },
      "source": [
        "!pip install pycountry"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting pycountry\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/76/73/6f1a412f14f68c273feea29a6ea9b9f1e268177d32e0e69ad6790d306312/pycountry-20.7.3.tar.gz (10.1MB)\n",
            "\u001b[K     |████████████████████████████████| 10.1MB 9.8MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: pycountry\n",
            "  Building wheel for pycountry (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pycountry: filename=pycountry-20.7.3-py2.py3-none-any.whl size=10746863 sha256=a1eb9aec4c772d3fce5af0d283784f9d33f37f01674bc3564637a98a8010a4f5\n",
            "  Stored in directory: /root/.cache/pip/wheels/33/4e/a6/be297e6b83567e537bed9df4a93f8590ec01c1acfbcd405348\n",
            "Successfully built pycountry\n",
            "Installing collected packages: pycountry\n",
            "Successfully installed pycountry-20.7.3\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "ldH5px733GPV",
        "outputId": "2f487580-57fe-41dd-f06f-78735ede596e"
      },
      "source": [
        "import pycountry\n",
        "def c_alpha_3(pais):\n",
        "  try:\n",
        "    return pycountry.countries.get(name=pais).alpha_3\n",
        "  except:\n",
        "    return None\n",
        "pelis_clean[\"código\"] = pelis_clean[\"país\"].apply(lambda x :c_alpha_3(x))   \n",
        "pelis_clean=pelis_clean.dropna()\n",
        "#pelis_clean=pelis_clean.groupby([\"código\"]).()\n",
        "pelis_clean\n",
        "\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>país</th>\n",
              "      <th>código</th>\n",
              "      <th>cantidad_peliculas</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Argentina</td>\n",
              "      <td>ARG</td>\n",
              "      <td>45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Australia</td>\n",
              "      <td>AUS</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Austria</td>\n",
              "      <td>AUT</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Bangladesh</td>\n",
              "      <td>BGD</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Belgium</td>\n",
              "      <td>BEL</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>United Arab Emirates</td>\n",
              "      <td>ARE</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>GBR</td>\n",
              "      <td>289</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>United States</td>\n",
              "      <td>USA</td>\n",
              "      <td>1853</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>Uruguay</td>\n",
              "      <td>URY</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>ZWE</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>64 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                    país código  cantidad_peliculas\n",
              "0              Argentina    ARG                  45\n",
              "1              Australia    AUS                  49\n",
              "2                Austria    AUT                   5\n",
              "3             Bangladesh    BGD                   2\n",
              "4                Belgium    BEL                   5\n",
              "..                   ...    ...                 ...\n",
              "59  United Arab Emirates    ARE                  17\n",
              "60        United Kingdom    GBR                 289\n",
              "61         United States    USA                1853\n",
              "62               Uruguay    URY                   7\n",
              "63              Zimbabwe    ZWE                   1\n",
              "\n",
              "[64 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1CwDtNSVfYzA"
      },
      "source": [
        "pelis_clean= pelis_clean.groupby([\"país\", \"código\"], as_index=False).sum()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "sHOCKeJdgSw6",
        "outputId": "6c4ec107-2f3b-4ed3-8ce7-531547bb05c4"
      },
      "source": [
        "import plotly.express as px\n",
        "fig= px.choropleth(pelis_clean, locations=\"código\", color=\"cantidad_peliculas\", hover_name=\"país\",  color_continuous_scale=px.colors.sequential.Pinkyl )\n",
        "fig.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
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              "            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>\n",
              "                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
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