Parte1-ETL.ipynb

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      "source": [
        "#importamos las librerias \n",
        "import pandas as pd\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OR3LEygSdhtg"
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      "source": [
        "#abrimos los csv y los colocamos dentro de un dataframe\n",
        "\n",
        "#el csv de amazon\n",
        "amazon=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/amazon_prime_titles.csv')\n",
        "\n",
        "#el csv de amazon\n",
        "disney=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/disney_plus_titles.csv')\n",
        "\n",
        "#el csv de amazon\n",
        "hulu=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/hulu_titles.csv')\n",
        "\n",
        "#el csv de amazon\n",
        "netflix=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/netflix_titles.csv')\n"
      ]
    },
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              "  show_id     type                 title         director  \\\n",
              "0      s1    Movie  Dick Johnson Is Dead  Kirsten Johnson   \n",
              "1      s2  TV Show         Blood & Water              NaN   \n",
              "\n",
              "                                                cast        country  \\\n",
              "0                                                NaN  United States   \n",
              "1  Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban...   South Africa   \n",
              "\n",
              "           date_added  release_year rating   duration  \\\n",
              "0  September 25, 2021          2020  PG-13     90 min   \n",
              "1  September 24, 2021          2021  TV-MA  2 Seasons   \n",
              "\n",
              "                                         listed_in  \\\n",
              "0                                    Documentaries   \n",
              "1  International TV Shows, TV Dramas, TV Mysteries   \n",
              "\n",
              "                                         description  \n",
              "0  As her father nears the end of his life, filmm...  \n",
              "1  After crossing paths at a party, a Cape Town t...  "
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              "      <th>show_id</th>\n",
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      ],
      "source": [
        "# se pone head solo para comprobar que están bien los datos\n",
        "netflix.head(2)\n"
      ]
    },
    {
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      "execution_count": null,
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      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 9668 entries, 0 to 9667\n",
            "Data columns (total 12 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   show_id       9668 non-null   object\n",
            " 1   type          9668 non-null   object\n",
            " 2   title         9668 non-null   object\n",
            " 3   director      7586 non-null   object\n",
            " 4   cast          8435 non-null   object\n",
            " 5   country       672 non-null    object\n",
            " 6   date_added    155 non-null    object\n",
            " 7   release_year  9668 non-null   int64 \n",
            " 8   rating        9331 non-null   object\n",
            " 9   duration      9668 non-null   object\n",
            " 10  listed_in     9668 non-null   object\n",
            " 11  description   9668 non-null   object\n",
            "dtypes: int64(1), object(11)\n",
            "memory usage: 906.5+ KB\n"
          ]
        }
      ],
      "source": [
        "#con info() nos da tanto nulos, como el tipo de variables y el tamaño del df\n",
        "amazon.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "M5c5M5hiA455"
      },
      "outputs": [],
      "source": [
        "#Se realiza la concatenación para el campo de id, para tener la informacion \n",
        "#de que plataforma viene cada uno de los datos \n",
        "\n",
        "amazon['id']='a'+amazon.show_id\n",
        "\n",
        "disney['id']='d'+disney.show_id\n",
        "\n",
        "hulu['id']='h'+hulu.show_id\n",
        "\n",
        "netflix['id']='n'+netflix.show_id"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#revisando en la columna de rating se observa que \n",
        "#hay un error porque ademas de colocar la claseificacion, tiene duracion\n",
        "hulu.rating.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C_hfBRXj231H",
        "outputId": "ddf0f1e4-691e-4b8b-a973-5b9807484808"
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      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['TV-MA', nan, 'PG-13', 'R', 'TV-14', 'PG', 'TV-PG', 'NOT RATED',\n",
              "       'G', 'TV-G', '2 Seasons', 'TV-Y', '93 min', '4 Seasons', 'TV-Y7',\n",
              "       '136 min', '91 min', '85 min', '98 min', '89 min', '94 min',\n",
              "       '86 min', '3 Seasons', '121 min', '88 min', '101 min', '1 Season',\n",
              "       '83 min', '100 min', '95 min', '92 min', '96 min', '109 min',\n",
              "       '99 min', '75 min', '87 min', '67 min', '104 min', '107 min',\n",
              "       '84 min', '103 min', '105 min', '119 min', '114 min', '82 min',\n",
              "       '90 min', '130 min', '110 min', '80 min', '6 Seasons', '97 min',\n",
              "       '111 min', '81 min', '49 min', '45 min', '41 min', '73 min',\n",
              "       '40 min', '36 min', '39 min', '34 min', '47 min', '65 min',\n",
              "       '37 min', '78 min', '102 min', '129 min', '115 min', '112 min',\n",
              "       'NR', '61 min', '106 min', '76 min', '77 min', '79 min', '157 min',\n",
              "       '28 min', '64 min', '7 min', '5 min', '6 min', '127 min',\n",
              "       '142 min', '108 min', '57 min', '118 min', '116 min', '12 Seasons',\n",
              "       '71 min'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para corregir se divide en dos columnas una que tenga los datos que comienzan con numeros y la otra con los demas valores"
      ],
      "metadata": {
        "id": "N5uWpq6JJusd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#se divide de la columna rating aquellos valores que contiene números con los que tienen la\n",
        "#correcta clasificación, y los que son nan se dejan nan en ambas columnas \n",
        "hulu[['noesrating','ratingbien']] = hulu.apply(lambda x: [x.rating, 0] if  x.rating == x.rating and x.rating[0].isdigit() \n",
        "                                            else [0, x.rating] if x.rating == x.rating\n",
        "                                            else [np.nan, np.nan], axis=1, result_type='expand')"
      ],
      "metadata": {
        "id": "3H-UcTAV4SbU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#se compruba que valores tiene la columna no es rating\n",
        "hulu.noesrating.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AT4IxyO48VaG",
        "outputId": "4cab55fa-fae6-4bf3-d4ee-05124bf1cb0e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, nan, '2 Seasons', '93 min', '4 Seasons', '136 min', '91 min',\n",
              "       '85 min', '98 min', '89 min', '94 min', '86 min', '3 Seasons',\n",
              "       '121 min', '88 min', '101 min', '1 Season', '83 min', '100 min',\n",
              "       '95 min', '92 min', '96 min', '109 min', '99 min', '75 min',\n",
              "       '87 min', '67 min', '104 min', '107 min', '84 min', '103 min',\n",
              "       '105 min', '119 min', '114 min', '82 min', '90 min', '130 min',\n",
              "       '110 min', '80 min', '6 Seasons', '97 min', '111 min', '81 min',\n",
              "       '49 min', '45 min', '41 min', '73 min', '40 min', '36 min',\n",
              "       '39 min', '34 min', '47 min', '65 min', '37 min', '78 min',\n",
              "       '102 min', '129 min', '115 min', '112 min', '61 min', '106 min',\n",
              "       '76 min', '77 min', '79 min', '157 min', '28 min', '64 min',\n",
              "       '7 min', '5 min', '6 min', '127 min', '142 min', '108 min',\n",
              "       '57 min', '118 min', '116 min', '12 Seasons', '71 min'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#se compruba que valores tiene la columna ratingbien\n",
        "hulu.ratingbien.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z8Gxu7ff5kLe",
        "outputId": "cfcfcca2-e524-4080-f4a9-24185a6ff165"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['TV-MA', nan, 'PG-13', 'R', 'TV-14', 'PG', 'TV-PG', 'NOT RATED',\n",
              "       'G', 'TV-G', 0, 'TV-Y', 'TV-Y7', 'NR'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Entonces con la columna \"no es rating\"que contiene la duración de las peliculas o tv shows por lo que podemos \"rellenar\" la columna que es la correcta."
      ],
      "metadata": {
        "id": "cp7T_-nTKPnk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#Revisamos si hay valores sin \"rellenar\" en la columna de duración\n",
        "#Los nan en duration son de 479\n",
        "hulu.duration.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RYyJZ3mEDdro",
        "outputId": "58dead9a-eefe-4ed0-c195-50e5d53c0b40"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "479"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# con los valores de la comulumna de no es rating se rellenan los faltantes\n",
        "# en la columna de Duration  \n",
        "hulu.duration = hulu.duration.fillna(hulu.noesrating)"
      ],
      "metadata": {
        "id": "jueMqqO8-juE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Como comprobacion revisamos de nuevo los nan\n",
        "#Los nan en duration despues del relleno son 106\n",
        "hulu.duration.isna().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8-_1o8BZ-1ml",
        "outputId": "5818cc7a-83a8-41dd-d86a-275a0bd7abb3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "106"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# reemplazar los valores de rating por los ya separados\n",
        "hulu.rating=hulu.ratingbien\n",
        "\n",
        "# reemplazo los valores 0 de la rating por NaN\n",
        "hulu.rating = np.where(hulu.rating==0, np.nan, hulu.rating)"
      ],
      "metadata": {
        "id": "2Iq393tKDxbp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#elimino las columnas inecesarias\n",
        "hulu.drop(columns=['noesrating','ratingbien'], inplace=True)"
      ],
      "metadata": {
        "id": "VZjexw_LFu1s"
      },
      "execution_count": null,
      "outputs": []
    },
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      "cell_type": "code",
      "source": [
        "hulu.head(2)"
      ],
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        "id": "vqv2pScsGNsI",
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                           title director  cast country  \\\n",
              "0      s1  Movie  Ricky Velez: Here's Everything      NaN   NaN     NaN   \n",
              "1      s2  Movie                    Silent Night      NaN   NaN     NaN   \n",
              "\n",
              "         date_added  release_year rating duration               listed_in  \\\n",
              "0  October 24, 2021          2021  TV-MA        0        Comedy, Stand Up   \n",
              "1  October 23, 2021          2020    NaN   94 min  Crime, Drama, Thriller   \n",
              "\n",
              "                                         description   id  \n",
              "0  ​Comedian Ricky Velez bares it all with his ho...  hs1  \n",
              "1  Mark, a low end South London hitman recently r...  hs2  "
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              "      <th>show_id</th>\n",
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              "      <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",
              "      <th>id</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>s1</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Ricky Velez: Here's Everything</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>October 24, 2021</td>\n",
              "      <td>2021</td>\n",
              "      <td>TV-MA</td>\n",
              "      <td>0</td>\n",
              "      <td>Comedy, Stand Up</td>\n",
              "      <td>​Comedian Ricky Velez bares it all with his ho...</td>\n",
              "      <td>hs1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>s2</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Silent Night</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>October 23, 2021</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>94 min</td>\n",
              "      <td>Crime, Drama, Thriller</td>\n",
              "      <td>Mark, a low end South London hitman recently r...</td>\n",
              "      <td>hs2</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ed5dbe23-c3c4-425a-be4b-667d1d49970c')\"\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se tiene el mismo problema en netflix por lo que se procede a realizar los mismos pasos"
      ],
      "metadata": {
        "id": "Cxt5_LqCIRLd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#hay error en el campo de rating en el data de netflix\n",
        "netflix.rating.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yF_L1D4sIXFX",
        "outputId": "d0403423-9fe4-4d01-dc7a-15461e9e9ddb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['PG-13', 'TV-MA', 'PG', 'TV-14', 'TV-PG', 'TV-Y', 'TV-Y7', 'R',\n",
              "       'TV-G', 'G', 'NC-17', '74 min', '84 min', '66 min', 'NR', nan,\n",
              "       'TV-Y7-FV', 'UR'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#se divide de la columna rating aquellos valores que contiene numeros con los que tienen la\n",
        "#correcta clasificacion, y los que son nan se dejan nan en ambas columnas \n",
        "netflix[['noesrating','ratingbien']] = netflix.apply(lambda x: [x.rating, 0] if  x.rating == x.rating and x.rating[0].isdigit() \n",
        "                                            else [0, x.rating] if x.rating == x.rating\n",
        "                                            else [np.nan, np.nan], axis=1, result_type='expand')\n",
        "\n",
        "\n",
        "# con los valores de la comulumna de no es rating se rellenan los faltantes\n",
        "# en la columna de Duration  \n",
        "netflix.duration = netflix.duration.fillna(netflix.noesrating)\n",
        "\n",
        "# reemplazar los valores de rating por los ya separados\n",
        "netflix.rating=netflix.ratingbien\n",
        "\n",
        "# reemplazo los valores 0 de la rating por NaN\n",
        "netflix.rating = np.where(netflix.rating==0, np.nan, netflix.rating)\n",
        "\n",
        "#elimino las columnas inecesarias\n",
        "netflix.drop(columns=['noesrating','ratingbien'], inplace=True)"
      ],
      "metadata": {
        "id": "COYBuSH8Ifew"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
        },
        "id": "fUHW8tdzFEZt",
        "outputId": "7c310fa2-c677-45f2-8d68-0c31cc3c80a4"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                 title      director  \\\n",
              "0      s1  Movie   The Grand Seduction  Don McKellar   \n",
              "1      s2  Movie  Take Care Good Night  Girish Joshi   \n",
              "\n",
              "                                               cast country      date_added  \\\n",
              "0    Brendan Gleeson, Taylor Kitsch, Gordon Pinsent  Canada  March 30, 2021   \n",
              "1  Mahesh Manjrekar, Abhay Mahajan, Sachin Khedekar   India  March 30, 2021   \n",
              "\n",
              "   release_year rating duration             listed_in  \\\n",
              "0          2014    NaN  113 min         Comedy, Drama   \n",
              "1          2018    13+  110 min  Drama, International   \n",
              "\n",
              "                                         description   id  \n",
              "0  A small fishing village must procure a local d...  as1  \n",
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              "  </tbody>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-92ef5616-8150-461f-bb97-80e18f3338db')\"\n",
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              "\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-92ef5616-8150-461f-bb97-80e18f3338db');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "amazon.head(2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O-6p1_FhtH42",
        "outputId": "bee65cde-87b7-4774-b3a7-d0ae0ac44bae"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "22998"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "amazon.shape[0]+ disney.shape[0]+hulu.shape[0]+netflix.shape[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JpDdXg0wtbWr",
        "outputId": "15fd6135-f68d-4aa1-f686-2eb437cf152b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22998, 13)"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "# se concatenan los data de todas las plataformas y se cambia el index\n",
        "plataformas = pd.concat([amazon, disney, hulu, netflix], ignore_index=True, sort=False )\n",
        "plataformas.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 208
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        "id": "Ei_YJkE0u6mC",
        "outputId": "51472089-e7ce-46e0-a35f-34a58c93b587"
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        {
          "output_type": "execute_result",
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            "text/plain": [
              "  show_id   type                 title      director  \\\n",
              "0      s1  Movie   The Grand Seduction  Don McKellar   \n",
              "1      s2  Movie  Take Care Good Night  Girish Joshi   \n",
              "\n",
              "                                               cast country      date_added  \\\n",
              "0    Brendan Gleeson, Taylor Kitsch, Gordon Pinsent  Canada  March 30, 2021   \n",
              "1  Mahesh Manjrekar, Abhay Mahajan, Sachin Khedekar   India  March 30, 2021   \n",
              "\n",
              "   release_year rating duration             listed_in  \\\n",
              "0          2014    NaN  113 min         Comedy, Drama   \n",
              "1          2018    13+  110 min  Drama, International   \n",
              "\n",
              "                                         description   id  \n",
              "0  A small fishing village must procure a local d...  as1  \n",
              "1  A Metro Family decides to fight a Cyber Crimin...  as2  "
            ],
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              "      <td>Take Care Good Night</td>\n",
              "      <td>Girish Joshi</td>\n",
              "      <td>Mahesh Manjrekar, Abhay Mahajan, Sachin Khedekar</td>\n",
              "      <td>India</td>\n",
              "      <td>March 30, 2021</td>\n",
              "      <td>2018</td>\n",
              "      <td>13+</td>\n",
              "      <td>110 min</td>\n",
              "      <td>Drama, International</td>\n",
              "      <td>A Metro Family decides to fight a Cyber Crimin...</td>\n",
              "      <td>as2</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "plataformas.head(2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VLmCH3KyvKj8",
        "outputId": "86365a4f-8481-4755-e8e5-be1930504171"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "show_id             0\n",
              "type                0\n",
              "title               0\n",
              "director         8259\n",
              "cast             5321\n",
              "country         11499\n",
              "date_added       9554\n",
              "release_year        0\n",
              "rating           1159\n",
              "duration          106\n",
              "listed_in           0\n",
              "description         4\n",
              "id                  0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "plataformas.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qESLPmOzvXuN"
      },
      "outputs": [],
      "source": [
        "#Cambiar datos nulos por 'G'\n",
        "plataformas.rating.fillna('G', inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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        "colab": {
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          "height": 274
        },
        "id": "X_9NCukFv5PM",
        "outputId": "0434ae24-a37d-4ff1-e54a-31a1a32f666b"
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              "  show_id   type                 title      director  \\\n",
              "0      s1  Movie   The Grand Seduction  Don McKellar   \n",
              "1      s2  Movie  Take Care Good Night  Girish Joshi   \n",
              "2      s3  Movie  Secrets of Deception   Josh Webber   \n",
              "\n",
              "                                                cast        country  \\\n",
              "0     Brendan Gleeson, Taylor Kitsch, Gordon Pinsent         Canada   \n",
              "1   Mahesh Manjrekar, Abhay Mahajan, Sachin Khedekar          India   \n",
              "2  Tom Sizemore, Lorenzo Lamas, Robert LaSardo, R...  United States   \n",
              "\n",
              "       date_added  release_year rating duration                listed_in  \\\n",
              "0  March 30, 2021          2014      G  113 min            Comedy, Drama   \n",
              "1  March 30, 2021          2018    13+  110 min     Drama, International   \n",
              "2  March 30, 2021          2017      G   74 min  Action, Drama, Suspense   \n",
              "\n",
              "                                         description   id  \n",
              "0  A small fishing village must procure a local d...  as1  \n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "#revisando los cambios en rating\n",
        "plataformas.head(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ek78HYhUv99G",
        "outputId": "6a35471f-bc5f-4aee-cdfd-4a898b51e8f5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['G', '13+', 'ALL', '18+', 'R', 'TV-Y', 'TV-Y7', 'NR', '16+',\n",
              "       'TV-PG', '7+', 'TV-14', 'TV-NR', 'TV-G', 'PG-13', 'TV-MA', 'PG',\n",
              "       'NC-17', 'UNRATED', '16', 'AGES_16_', 'AGES_18_', 'ALL_AGES',\n",
              "       'NOT_RATE', 'TV-Y7-FV', 'NOT RATED', 'UR'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ],
      "source": [
        "#se comprueba que los valores en la columna de rating están correctos después de las transformaciones\n",
        "plataformas.rating.unique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "65OkxQPJxL2Y",
        "outputId": "1124796d-3e75-4cad-c0b4-2a964f498827"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 22998 entries, 0 to 22997\n",
            "Data columns (total 13 columns):\n",
            " #   Column        Non-Null Count  Dtype \n",
            "---  ------        --------------  ----- \n",
            " 0   show_id       22998 non-null  object\n",
            " 1   type          22998 non-null  object\n",
            " 2   title         22998 non-null  object\n",
            " 3   director      14739 non-null  object\n",
            " 4   cast          17677 non-null  object\n",
            " 5   country       11499 non-null  object\n",
            " 6   date_added    13444 non-null  object\n",
            " 7   release_year  22998 non-null  int64 \n",
            " 8   rating        22998 non-null  object\n",
            " 9   duration      22892 non-null  object\n",
            " 10  listed_in     22998 non-null  object\n",
            " 11  description   22994 non-null  object\n",
            " 12  id            22998 non-null  object\n",
            "dtypes: int64(1), object(12)\n",
            "memory usage: 2.3+ MB\n"
          ]
        }
      ],
      "source": [
        "plataformas.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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          "data": {
            "text/plain": [
              "      show_id     type        title         director  \\\n",
              "22993   s8803    Movie       Zodiac    David Fincher   \n",
              "22994   s8804  TV Show  Zombie Dumb              NaN   \n",
              "22995   s8805    Movie   Zombieland  Ruben Fleischer   \n",
              "22996   s8806    Movie         Zoom     Peter Hewitt   \n",
              "22997   s8807    Movie       Zubaan      Mozez Singh   \n",
              "\n",
              "                                                    cast        country  \\\n",
              "22993  Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...  United States   \n",
              "22994                                                NaN            NaN   \n",
              "22995  Jesse Eisenberg, Woody Harrelson, Emma Stone, ...  United States   \n",
              "22996  Tim Allen, Courteney Cox, Chevy Chase, Kate Ma...  United States   \n",
              "22997  Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan...          India   \n",
              "\n",
              "      date_added  release_year rating   duration  \\\n",
              "22993 2019-11-20          2007      R    158 min   \n",
              "22994 2019-07-01          2018  TV-Y7  2 Seasons   \n",
              "22995 2019-11-01          2009      R     88 min   \n",
              "22996 2020-01-11          2006     PG     88 min   \n",
              "22997 2019-03-02          2015  TV-14    111 min   \n",
              "\n",
              "                                            listed_in  \\\n",
              "22993                  Cult Movies, Dramas, Thrillers   \n",
              "22994          Kids' TV, Korean TV Shows, TV Comedies   \n",
              "22995                         Comedies, Horror Movies   \n",
              "22996              Children & Family Movies, Comedies   \n",
              "22997  Dramas, International Movies, Music & Musicals   \n",
              "\n",
              "                                             description      id  \n",
              "22993  A political cartoonist, a crime reporter and a...  ns8803  \n",
              "22994  While living alone in a spooky town, a young g...  ns8804  \n",
              "22995  Looking to survive in a world taken over by zo...  ns8805  \n",
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              "      <th>22993</th>\n",
              "      <td>s8803</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zodiac</td>\n",
              "      <td>David Fincher</td>\n",
              "      <td>Mark Ruffalo, Jake Gyllenhaal, Robert Downey J...</td>\n",
              "      <td>United States</td>\n",
              "      <td>2019-11-20</td>\n",
              "      <td>2007</td>\n",
              "      <td>R</td>\n",
              "      <td>158 min</td>\n",
              "      <td>Cult Movies, Dramas, Thrillers</td>\n",
              "      <td>A political cartoonist, a crime reporter and a...</td>\n",
              "      <td>ns8803</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22994</th>\n",
              "      <td>s8804</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>2019-07-01</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",
              "      <td>ns8804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22995</th>\n",
              "      <td>s8805</td>\n",
              "      <td>Movie</td>\n",
              "      <td>Zombieland</td>\n",
              "      <td>Ruben Fleischer</td>\n",
              "      <td>Jesse Eisenberg, Woody Harrelson, Emma Stone, ...</td>\n",
              "      <td>United States</td>\n",
              "      <td>2019-11-01</td>\n",
              "      <td>2009</td>\n",
              "      <td>R</td>\n",
              "      <td>88 min</td>\n",
              "      <td>Comedies, Horror Movies</td>\n",
              "      <td>Looking to survive in a world taken over by zo...</td>\n",
              "      <td>ns8805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22996</th>\n",
              "      <td>s8806</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>2020-01-11</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",
              "      <td>ns8806</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22997</th>\n",
              "      <td>s8807</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>2019-03-02</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",
              "      <td>ns8807</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7302b68d-83b8-43d2-bd6a-b5c0d2f76aee')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #D2E3FC;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-7302b68d-83b8-43d2-bd6a-b5c0d2f76aee button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7302b68d-83b8-43d2-bd6a-b5c0d2f76aee');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ],
      "source": [
        "#haciendo el cambio de fecha como strig a y-m-d\n",
        "plataformas.date_added=pd.to_datetime(plataformas.date_added)\n",
        "plataformas.tail()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0BTGD6Sh_WT5"
      },
      "outputs": [],
      "source": [
        "#se cambia a minusculas todos los string\n",
        "columnas_a_cambiar=['type',\t'title', 'director', 'cast', 'country', 'rating', 'duration', 'listed_in', 'description']\n",
        "#la lambda nos ayuda a declarar una funcion que en este caso es poner en minusculas\n",
        "plataformas[columnas_a_cambiar] = plataformas[columnas_a_cambiar].apply(lambda x: x.str.lower())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 240
        },
        "id": "g5r9SAv4BsOI",
        "outputId": "0b8d742c-e05d-426f-e235-430d7f748372"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                 title      director  \\\n",
              "0      s1  movie   the grand seduction  don mckellar   \n",
              "1      s2  movie  take care good night  girish joshi   \n",
              "2      s3  movie  secrets of deception   josh webber   \n",
              "\n",
              "                                                cast        country  \\\n",
              "0     brendan gleeson, taylor kitsch, gordon pinsent         canada   \n",
              "1   mahesh manjrekar, abhay mahajan, sachin khedekar          india   \n",
              "2  tom sizemore, lorenzo lamas, robert lasardo, r...  united states   \n",
              "\n",
              "  date_added  release_year rating duration                listed_in  \\\n",
              "0 2021-03-30          2014      g  113 min            comedy, drama   \n",
              "1 2021-03-30          2018    13+  110 min     drama, international   \n",
              "2 2021-03-30          2017      g   74 min  action, drama, suspense   \n",
              "\n",
              "                                         description   id  \n",
              "0  a small fishing village must procure a local d...  as1  \n",
              "1  a metro family decides to fight a cyber crimin...  as2  \n",
              "2  after a man discovers his wife is cheating on ...  as3  "
            ],
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <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",
              "      <th>id</th>\n",
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              "      <td>s1</td>\n",
              "      <td>movie</td>\n",
              "      <td>the grand seduction</td>\n",
              "      <td>don mckellar</td>\n",
              "      <td>brendan gleeson, taylor kitsch, gordon pinsent</td>\n",
              "      <td>canada</td>\n",
              "      <td>2021-03-30</td>\n",
              "      <td>2014</td>\n",
              "      <td>g</td>\n",
              "      <td>113 min</td>\n",
              "      <td>comedy, drama</td>\n",
              "      <td>a small fishing village must procure a local d...</td>\n",
              "      <td>as1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>s2</td>\n",
              "      <td>movie</td>\n",
              "      <td>take care good night</td>\n",
              "      <td>girish joshi</td>\n",
              "      <td>mahesh manjrekar, abhay mahajan, sachin khedekar</td>\n",
              "      <td>india</td>\n",
              "      <td>2021-03-30</td>\n",
              "      <td>2018</td>\n",
              "      <td>13+</td>\n",
              "      <td>110 min</td>\n",
              "      <td>drama, international</td>\n",
              "      <td>a metro family decides to fight a cyber crimin...</td>\n",
              "      <td>as2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>s3</td>\n",
              "      <td>movie</td>\n",
              "      <td>secrets of deception</td>\n",
              "      <td>josh webber</td>\n",
              "      <td>tom sizemore, lorenzo lamas, robert lasardo, r...</td>\n",
              "      <td>united states</td>\n",
              "      <td>2021-03-30</td>\n",
              "      <td>2017</td>\n",
              "      <td>g</td>\n",
              "      <td>74 min</td>\n",
              "      <td>action, drama, suspense</td>\n",
              "      <td>after a man discovers his wife is cheating on ...</td>\n",
              "      <td>as3</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e64321fa-a3cf-426d-9b0f-1e389e7e4460')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-e64321fa-a3cf-426d-9b0f-1e389e7e4460 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-e64321fa-a3cf-426d-9b0f-1e389e7e4460');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "#revision de los cambios\n",
        "plataformas.head(3)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se hace un cambio en la columna de duracion, a partir de ella se crearan dos, una duration_int que contendrá solo los números y otra duration_type con el tipo de duracion, min, season or seasons"
      ],
      "metadata": {
        "id": "IDvvp-iO2-v_"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BRj_agAPNxnY",
        "outputId": "85d48ccf-7e2e-4ba0-ad70-d370ce30c339"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['113 min', '110 min', '74 min', '69 min', '45 min', '52 min',\n",
              "       '98 min', '131 min', '87 min', '92 min', '88 min', '93 min',\n",
              "       '94 min', '46 min', '96 min', '1 season', '104 min', '62 min',\n",
              "       '50 min', '3 seasons', '2 seasons', '86 min', '36 min', '37 min',\n",
              "       '103 min', '9 min', '18 min', '14 min', '20 min', '19 min',\n",
              "       '22 min', '60 min', '6 min', '54 min', '5 min', '84 min',\n",
              "       '126 min', '125 min', '109 min', '89 min', '85 min', '56 min',\n",
              "       '40 min', '111 min', '33 min', '34 min', '95 min', '99 min',\n",
              "       '78 min', '4 seasons', '77 min', '55 min', '53 min', '115 min',\n",
              "       '58 min', '49 min', '135 min', '91 min', '64 min', '59 min',\n",
              "       '48 min', '122 min', '90 min', '102 min', '65 min', '114 min',\n",
              "       '136 min', '70 min', '138 min', '100 min', '480 min', '4 min',\n",
              "       '30 min', '152 min', '68 min', '57 min', '7 seasons', '31 min',\n",
              "       '151 min', '149 min', '9 seasons', '141 min', '121 min', '79 min',\n",
              "       '140 min', '51 min', '106 min', '75 min', '27 min', '107 min',\n",
              "       '108 min', '38 min', '157 min', '43 min', '118 min', '139 min',\n",
              "       '6 seasons', '112 min', '15 min', '72 min', '5 seasons', '116 min',\n",
              "       '142 min', '71 min', '42 min', '81 min', '32 min', '66 min',\n",
              "       '127 min', '159 min', '67 min', '29 min', '132 min', '101 min',\n",
              "       '164 min', '73 min', '61 min', '80 min', '83 min', '44 min',\n",
              "       '120 min', '26 min', '97 min', '23 min', '105 min', '82 min',\n",
              "       '11 min', '148 min', '161 min', '123 min', '29 seasons', '0 min',\n",
              "       '124 min', '143 min', '35 min', '47 min', '170 min', '19 seasons',\n",
              "       '3 min', '146 min', '601 min', '24 min', '21 seasons', '154 min',\n",
              "       '128 min', '133 min', '153 min', '119 min', '63 min', '169 min',\n",
              "       '174 min', '144 min', '7 min', '137 min', '76 min', '39 min',\n",
              "       '8 seasons', '12 seasons', '134 min', '163 min', '1 min',\n",
              "       '145 min', '162 min', '41 min', '147 min', '155 min', '117 min',\n",
              "       '167 min', '11 seasons', '28 min', '25 min', '180 min', '2 min',\n",
              "       '541 min', '240 min', '129 min', '178 min', '171 min', '21 min',\n",
              "       '172 min', '173 min', '10 min', '166 min', '160 min', '130 min',\n",
              "       '479 min', '13 min', '8 min', '10 seasons', '17 min', '16 min',\n",
              "       '158 min', '183 min', '12 min', '14 seasons', '150 min', '481 min',\n",
              "       '181 min', '156 min', '540 min', '177 min', '550 min', '485 min',\n",
              "       '176 min', '193 min', '165 min', '175 min', '188 min', '187 min',\n",
              "       '168 min', '190 min', '185 min', '209 min', '192 min', '182 min',\n",
              "       '207 min', '269 min', '15 seasons', '191 min', '32 seasons',\n",
              "       '16 seasons', nan, '23 seasons', '20 seasons', '13 seasons',\n",
              "       '17 seasons', '30 seasons', '22 seasons', '25 seasons',\n",
              "       '34 seasons', '26 seasons', '229 min', '189 min', '273 min',\n",
              "       '204 min', '212 min', '224 min', '203 min', '194 min', '233 min',\n",
              "       '237 min', '230 min', '195 min', '253 min', '208 min', '186 min',\n",
              "       '312 min', '214 min', '179 min', '200 min', '196 min', '228 min',\n",
              "       '205 min', '201 min'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ],
      "source": [
        "plataformas.duration.unique()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plataformas.duration.dtype"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SEFWVhD5ZbHQ",
        "outputId": "c109f711-a3a6-43be-d321-1b6dd52480a6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('O')"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se usa la funcion de lambda para poder hacer ese split"
      ],
      "metadata": {
        "id": "pQLLqd8D3S1W"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plataformas[['duration_int', 'duration_type']] = plataformas.apply(lambda x: [np.nan, np.nan] if pd.isna(x.duration) or x.duration.strip() == ''\n",
        "                                                           else [int(x.duration.split(' ')[0]), x.duration.split(' ')[1]] if 'min' not in x.duration\n",
        "                                                           else [int(x.duration.replace('min', '').strip()), 'min'], axis=1, result_type='expand')\n"
      ],
      "metadata": {
        "id": "_nV674X0XXfv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#comprobacion de las columnas creadas\n",
        "plataformas.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 330
        },
        "id": "vSgftv8A5eB0",
        "outputId": "95cdd2b2-e021-46ca-8eb0-30c2f6460fdc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                 title      director  \\\n",
              "0      s1  movie   the grand seduction  don mckellar   \n",
              "1      s2  movie  take care good night  girish joshi   \n",
              "\n",
              "                                               cast country date_added  \\\n",
              "0    brendan gleeson, taylor kitsch, gordon pinsent  canada 2021-03-30   \n",
              "1  mahesh manjrekar, abhay mahajan, sachin khedekar   india 2021-03-30   \n",
              "\n",
              "   release_year rating duration             listed_in  \\\n",
              "0          2014      g  113 min         comedy, drama   \n",
              "1          2018    13+  110 min  drama, international   \n",
              "\n",
              "                                         description   id  duration_int  \\\n",
              "0  a small fishing village must procure a local d...  as1         113.0   \n",
              "1  a metro family decides to fight a cyber crimin...  as2         110.0   \n",
              "\n",
              "  duration_type  \n",
              "0           min  \n",
              "1           min  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-22a53d72-c218-4856-bcad-3ce6e8325084\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>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",
              "      <th>id</th>\n",
              "      <th>duration_int</th>\n",
              "      <th>duration_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>s1</td>\n",
              "      <td>movie</td>\n",
              "      <td>the grand seduction</td>\n",
              "      <td>don mckellar</td>\n",
              "      <td>brendan gleeson, taylor kitsch, gordon pinsent</td>\n",
              "      <td>canada</td>\n",
              "      <td>2021-03-30</td>\n",
              "      <td>2014</td>\n",
              "      <td>g</td>\n",
              "      <td>113 min</td>\n",
              "      <td>comedy, drama</td>\n",
              "      <td>a small fishing village must procure a local d...</td>\n",
              "      <td>as1</td>\n",
              "      <td>113.0</td>\n",
              "      <td>min</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>s2</td>\n",
              "      <td>movie</td>\n",
              "      <td>take care good night</td>\n",
              "      <td>girish joshi</td>\n",
              "      <td>mahesh manjrekar, abhay mahajan, sachin khedekar</td>\n",
              "      <td>india</td>\n",
              "      <td>2021-03-30</td>\n",
              "      <td>2018</td>\n",
              "      <td>13+</td>\n",
              "      <td>110 min</td>\n",
              "      <td>drama, international</td>\n",
              "      <td>a metro family decides to fight a cyber crimin...</td>\n",
              "      <td>as2</td>\n",
              "      <td>110.0</td>\n",
              "      <td>min</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-22a53d72-c218-4856-bcad-3ce6e8325084')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
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              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-22a53d72-c218-4856-bcad-3ce6e8325084 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-22a53d72-c218-4856-bcad-3ce6e8325084');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#una comprobacion de la columna de type\n",
        "plataformas.duration_type.unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jWPgPiU35j5H",
        "outputId": "8caef33d-af8d-4aec-ed6a-3247c439ff91"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['min', 'season', 'seasons', nan], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 346
        },
        "id": "FAYy1dT3lgAb",
        "outputId": "9c17253a-29c1-48ae-a4ef-966d324f0d62"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      show_id   type                                              title  \\\n",
              "11118      s1  movie                     ricky velez: here's everything   \n",
              "11130     s13  movie  out of the shadows: the man behind the steele ...   \n",
              "11133     s16  movie  showtime championship boxing: lopez vs. salido...   \n",
              "\n",
              "      director cast country date_added  release_year rating duration  \\\n",
              "11118      NaN  NaN     NaN 2021-10-24          2021  tv-ma      NaN   \n",
              "11130      NaN  NaN     NaN 2021-10-18          2021      g      NaN   \n",
              "11133      NaN  NaN     NaN 2021-10-16          2011      g      NaN   \n",
              "\n",
              "              listed_in                                        description  \\\n",
              "11118  comedy, stand up  ​comedian ricky velez bares it all with his ho...   \n",
              "11130              news  george stephanopoulos sits down with former mi...   \n",
              "11133            sports  juan manuel lopez vs. orlando salido for the w...   \n",
              "\n",
              "         id  duration_int duration_type  \n",
              "11118   hs1           NaN           NaN  \n",
              "11130  hs13           NaN           NaN  \n",
              "11133  hs16           NaN           NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d3b22313-f96e-4f81-86be-e72a37ffa369\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>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",
              "      <th>id</th>\n",
              "      <th>duration_int</th>\n",
              "      <th>duration_type</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>11118</th>\n",
              "      <td>s1</td>\n",
              "      <td>movie</td>\n",
              "      <td>ricky velez: here's everything</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2021-10-24</td>\n",
              "      <td>2021</td>\n",
              "      <td>tv-ma</td>\n",
              "      <td>NaN</td>\n",
              "      <td>comedy, stand up</td>\n",
              "      <td>​comedian ricky velez bares it all with his ho...</td>\n",
              "      <td>hs1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11130</th>\n",
              "      <td>s13</td>\n",
              "      <td>movie</td>\n",
              "      <td>out of the shadows: the man behind the steele ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2021-10-18</td>\n",
              "      <td>2021</td>\n",
              "      <td>g</td>\n",
              "      <td>NaN</td>\n",
              "      <td>news</td>\n",
              "      <td>george stephanopoulos sits down with former mi...</td>\n",
              "      <td>hs13</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11133</th>\n",
              "      <td>s16</td>\n",
              "      <td>movie</td>\n",
              "      <td>showtime championship boxing: lopez vs. salido...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2021-10-16</td>\n",
              "      <td>2011</td>\n",
              "      <td>g</td>\n",
              "      <td>NaN</td>\n",
              "      <td>sports</td>\n",
              "      <td>juan manuel lopez vs. orlando salido for the w...</td>\n",
              "      <td>hs16</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d3b22313-f96e-4f81-86be-e72a37ffa369')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-d3b22313-f96e-4f81-86be-e72a37ffa369 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d3b22313-f96e-4f81-86be-e72a37ffa369');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ],
      "source": [
        "null_rows = plataformas[plataformas[\"duration\"].isnull()]\n",
        "null_rows.head(3)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Datos de las plataformas y los detalles de las peliculas  🌸"
      ],
      "metadata": {
        "id": "ZBC8cA-Z-nUV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#para guardar a csv\n",
        "#plataformas.to_csv('/content/drive/MyDrive/plataformas.csv') "
      ],
      "metadata": {
        "id": "zl3SvwKdOea7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#para guardar a csv\n",
        "plataformas.to_parquet('/content/drive/MyDrive/plataformas.parquet', index=False) "
      ],
      "metadata": {
        "id": "N7qL8QPrOBR7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plataformas.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4FBxOIUSPYIy",
        "outputId": "8d1551d2-a9b9-43cf-ff30-6a20f82fd505"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 22998 entries, 0 to 22997\n",
            "Data columns (total 15 columns):\n",
            " #   Column         Non-Null Count  Dtype         \n",
            "---  ------         --------------  -----         \n",
            " 0   show_id        22998 non-null  object        \n",
            " 1   type           22998 non-null  object        \n",
            " 2   title          22998 non-null  object        \n",
            " 3   director       14739 non-null  object        \n",
            " 4   cast           17677 non-null  object        \n",
            " 5   country        11499 non-null  object        \n",
            " 6   date_added     13444 non-null  datetime64[ns]\n",
            " 7   release_year   22998 non-null  int64         \n",
            " 8   rating         22998 non-null  object        \n",
            " 9   duration       22811 non-null  object        \n",
            " 10  listed_in      22998 non-null  object        \n",
            " 11  description    22994 non-null  object        \n",
            " 12  id             22998 non-null  object        \n",
            " 13  duration_int   22811 non-null  float64       \n",
            " 14  duration_type  22811 non-null  object        \n",
            "dtypes: datetime64[ns](1), float64(1), int64(1), object(12)\n",
            "memory usage: 2.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "u1DJlG62-tuG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plataformas.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NB828HNGA1gu",
        "outputId": "0d8bba78-a1c7-4127-a0bf-a0df3263f1a7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22998, 15)"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Vamos con los 8 datos donde vienen los ratings\n"
      ],
      "metadata": {
        "id": "F5G393a-cnP2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#abrimos los csv de raiting y los colocamos a un dataframe\n",
        "\n",
        "df1=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/1.csv')\n",
        "df2=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/2.csv')\n",
        "df3=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/3.csv')\n",
        "df4=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/4.csv')\n",
        "df5=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/5.csv')\n",
        "df6=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/6.csv')\n",
        "df7=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/7.csv')\n",
        "df8=pd.read_csv('/content/drive/MyDrive/MLOpsReviews/ratings/8.csv')"
      ],
      "metadata": {
        "id": "I6q-QduyctbE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# se concatenan los data del rating\n",
        "ratingTotal = pd.concat([df1, df2, df3, df4, df5, df6, df7, df8], ignore_index=True, sort=False )\n",
        "ratingTotal.head(3)"
      ],
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   userId  rating   timestamp movieId\n",
              "0       1     1.0  1425941529   as680\n",
              "1       1     4.5  1425942435  ns2186\n",
              "2       1     5.0  1425941523  hs2381"
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            ]
          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#la union de los datas con los rating nos da un dataframe de \n",
        "ratingTotal.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zMO1Zu9A33Ve",
        "outputId": "9fe942da-5aad-49b6-d5b0-64b410443d3d"
      },
      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(11024289, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
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    {
      "cell_type": "code",
      "source": [
        "# se obtienen 124 duplicados\n",
        "ratingTotal.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qvYD8hoPk4-7",
        "outputId": "09ec2313-b35b-48b6-e039-6f1b580af006"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "124"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#se eliminan los duplicates\n",
        "ratingTotal.drop_duplicates(inplace=True)"
      ],
      "metadata": {
        "id": "GNzdlUuepazc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#comprobando que se elimino\n",
        "ratingTotal.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "N85EHvalmEIL",
        "outputId": "71e54e13-a51a-4436-a267-fb635a39ef48"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#cambio el formato de la columna 'timestamp' a fecha sin la opcion de hora\n",
        "ratingTotal.timestamp = pd.to_datetime(ratingTotal.timestamp, unit='s').dt.strftime('%Y - %m - %d')\n",
        "#Pasamos a formato fecha\n",
        "ratingTotal.timestamp = pd.to_datetime(ratingTotal.timestamp)"
      ],
      "metadata": {
        "id": "pCj5TYJPiAnc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#comprobacion del cambio\n",
        "ratingTotal.head(3)"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 143
        },
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   userId  rating  timestamp movieId\n",
              "0       1     1.0 2015-03-09   as680\n",
              "1       1     4.5 2015-03-09  ns2186\n",
              "2       1     5.0 2015-03-09  hs2381"
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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          },
          "metadata": {},
          "execution_count": 47
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Se hace un cambio en el nombre, ya que los datos que muestra en la columna de rating se consideran como el score que el usuario le da a la pelicula o tv show que vio"
      ],
      "metadata": {
        "id": "fSetB2M54om8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ratingTotal.rename( columns = { \"rating\": \"score\"}, inplace=True)"
      ],
      "metadata": {
        "id": "hgxnhIxv-Ygu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Este dataframe se usará para el ML junto con la info de plataformas 👀"
      ],
      "metadata": {
        "id": "b1z5vM5-_j11"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#una comprobacion del cambio\n",
        "ratingTotal.head(3)"
      ],
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          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "Rc2xEG36-kcC",
        "outputId": "c01e76b1-87ca-4c41-a5e8-5f82ca84a246"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   userId  score  timestamp movieId\n",
              "0       1    1.0 2015-03-09   as680\n",
              "1       1    4.5 2015-03-09  ns2186\n",
              "2       1    5.0 2015-03-09  hs2381"
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            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#para guardar a csv de plataformas con la informacion del score promedio \n",
        "ratingTotal.to_parquet('/content/drive/MyDrive/rating.parquet', index=False) "
      ],
      "metadata": {
        "id": "Xv1Eu47SID_K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "Para hacer una union entre el csv de plataformas y la de usuarios, se hace un merge con estos nuevos datos pero con el score promedio, por lo que se hace una agrupacion "
      ],
      "metadata": {
        "id": "XfTmpZzS5AHB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#hacemos una prueba para ver como quedará \n",
        "ratingPorPromedio = ratingTotal.groupby('movieId')['score'].mean()\n",
        "\n",
        "#se muestra un dataframe muy crudo con dos columnas uno con el movieID como index y otra columna con el promedio \n",
        "ratingPorPromedio.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aQs6sF7t_seL",
        "outputId": "01889110-bc2c-432e-de0f-49f0bc121d7e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "movieId\n",
              "as1      3.467131\n",
              "as10     3.439571\n",
              "as100    3.609302\n",
              "Name: score, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Hago un dataframe con la media, el score y redondeo a dos decimales\n",
        "sacandoPromedio = ratingTotal.groupby('movieId')['score'].mean().round(2).to_frame()\n",
        "\n",
        "#renombro la columna de moviId, para que quede como el indice y reseteo los datos\n",
        "sacandoPromedio = sacandoPromedio.rename_axis('movieId').reset_index()\n",
        "\n",
        "# Ahora en la columna que tiene el movieID le cambio el nombre\n",
        "sacandoPromedio.rename( columns = { \"movieId\": \"id\"}, inplace=True)\n",
        "\n",
        "#Comprobacion de los pasos \n",
        "sacandoPromedio.head(3)\n"
      ],
      "metadata": {
        "id": "LUhiZaNoJXL-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "outputId": "328f85c7-eada-4d62-e03d-25b8392f5388"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      id  score\n",
              "0    as1   3.47\n",
              "1   as10   3.44\n",
              "2  as100   3.61"
            ],
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              "      <td>3.61</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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            ]
          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#revisamos las dimensiones de este dataframa\n",
        "sacandoPromedio.shape"
      ],
      "metadata": {
        "id": "NxwYeeMqfA2Z",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0d692062-33f2-4f4c-b8b2-c316b40df46e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22998, 2)"
            ]
          },
          "metadata": {},
          "execution_count": 53
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Tenemos la misma cantidad de rows en el dataframe que tiene el promedio del score de las peliculas y el dataframe donde estan las plataformas y los detalles de las peliculas"
      ],
      "metadata": {
        "id": "WzySTg9j9EI1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Ahora si hacemos el marge con la base de datos de plataforma y con la base de datos que tienen los promedios"
      ],
      "metadata": {
        "id": "ROkmaC8rOITP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plataformasConScore = plataformas.merge(sacandoPromedio, on='id')\n",
        "plataformasConScore.head(3)"
      ],
      "metadata": {
        "id": "fTg3as-AOPm6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "outputId": "2f814dd6-332f-48f4-dedb-3c43f367f182"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                 title      director  \\\n",
              "0      s1  movie   the grand seduction  don mckellar   \n",
              "1      s2  movie  take care good night  girish joshi   \n",
              "2      s3  movie  secrets of deception   josh webber   \n",
              "\n",
              "                                                cast        country  \\\n",
              "0     brendan gleeson, taylor kitsch, gordon pinsent         canada   \n",
              "1   mahesh manjrekar, abhay mahajan, sachin khedekar          india   \n",
              "2  tom sizemore, lorenzo lamas, robert lasardo, r...  united states   \n",
              "\n",
              "  date_added  release_year rating duration                listed_in  \\\n",
              "0 2021-03-30          2014      g  113 min            comedy, drama   \n",
              "1 2021-03-30          2018    13+  110 min     drama, international   \n",
              "2 2021-03-30          2017      g   74 min  action, drama, suspense   \n",
              "\n",
              "                                         description   id  duration_int  \\\n",
              "0  a small fishing village must procure a local d...  as1         113.0   \n",
              "1  a metro family decides to fight a cyber crimin...  as2         110.0   \n",
              "2  after a man discovers his wife is cheating on ...  as3          74.0   \n",
              "\n",
              "  duration_type  score  \n",
              "0           min   3.47  \n",
              "1           min   3.55  \n",
              "2           min   3.50  "
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              "      <td>action, drama, suspense</td>\n",
              "      <td>after a man discovers his wife is cheating on ...</td>\n",
              "      <td>as3</td>\n",
              "      <td>74.0</td>\n",
              "      <td>min</td>\n",
              "      <td>3.50</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-835862e5-224a-4a59-952a-c989d52eb313')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      </button>\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-835862e5-224a-4a59-952a-c989d52eb313 button.colab-df-convert');\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-835862e5-224a-4a59-952a-c989d52eb313');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plataformasConScore.shape"
      ],
      "metadata": {
        "id": "ff-qp-AxPC0m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "be5d8179-ba65-4613-e021-8d3f746dd1b6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22998, 16)"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Agregare una columna donde se especifique la plataforma para poder hacer consultas más sencillas"
      ],
      "metadata": {
        "id": "T2ymszee9m9-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#agrego una columna de plataformas porque hay una consulta que necesita\n",
        "plataformasConScore['platform'] = plataformasConScore.id.apply(lambda x: 'amazon prime' if 'a' in x \n",
        "                                                                 else 'disney plus' if 'd' in x\n",
        "                                                                 else 'hulu' if 'h' in x\n",
        "                                                                 else 'netflix')"
      ],
      "metadata": {
        "id": "MKh4L3FETuUN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plataformasConScore.platform.value_counts()"
      ],
      "metadata": {
        "id": "LCf8pEuQVC5j",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2096bf27-8da8-4289-95d4-07d4c1f4590a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "amazon prime    9668\n",
              "netflix         8807\n",
              "hulu            3073\n",
              "disney plus     1450\n",
              "Name: platform, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "9YMYbMXq-hOE"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Pasamos la data a un csv para posteriormente realizar consultas 🌸"
      ],
      "metadata": {
        "id": "w4-vLyTzPHDM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#para guardar a csv de plataformas con la informacion del score promedio \n",
        "#plataformasConScore.to_csv('/content/drive/MyDrive/plataformasConScore.csv', index=False) "
      ],
      "metadata": {
        "id": "62_rX1W-PPTu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plataformasConScore.to_parquet('/content/drive/MyDrive/plataformasConScore.parquet', index=False) "
      ],
      "metadata": {
        "id": "UXIqd4DZQWx3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n"
      ],
      "metadata": {
        "id": "wTp5Wrnl-fXk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "# Union de la informacion de las plataformas con los datos por usuario y sus calificaciones\n"
      ],
      "metadata": {
        "id": "UOLiSsgV-Kr8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#se hacen algunos cambios (revisar texto 👀) para que se pueda hacer el merge con los datos de plataformas\n",
        "ratingTotal.rename( columns = { \"movieId\": \"id\"}, inplace=True)\n",
        "ratingTotal.head(3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "3FFUQtCcfw9F",
        "outputId": "532af18c-22a1-4790-b855-929c875522d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   userId  score  timestamp      id\n",
              "0       1    1.0 2015-03-09   as680\n",
              "1       1    4.5 2015-03-09  ns2186\n",
              "2       1    5.0 2015-03-09  hs2381"
            ],
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              "      <th></th>\n",
              "      <th>userId</th>\n",
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              "      <td>ns2186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2015-03-09</td>\n",
              "      <td>hs2381</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f81ae62e-a55d-42fb-b9d7-46fc52db14cd')\"\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f81ae62e-a55d-42fb-b9d7-46fc52db14cd button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f81ae62e-a55d-42fb-b9d7-46fc52db14cd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ratingTotal.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tQmvsZiGgBEy",
        "outputId": "07926976-feb3-4fcb-9060-d71c00264445"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(11024165, 4)"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plataformas.shape"
      ],
      "metadata": {
        "id": "xepjiEpvyBHw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f73aa073-ae93-40cb-a242-e6344eb535ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(22998, 15)"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Merge con plataformas y con los usarios y el rating usando el id\n",
        "plataformasUsuarioRating = plataformas.merge(ratingTotal, on='id')"
      ],
      "metadata": {
        "id": "VZf-pU0WVdHQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#revisando el resultado\n",
        "plataformasUsuarioRating.head(2)"
      ],
      "metadata": {
        "id": "zdl0xxlRgbM0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "outputId": "937e071f-1bad-441a-efd4-f1d269906a33"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  show_id   type                title      director  \\\n",
              "0      s1  movie  the grand seduction  don mckellar   \n",
              "1      s1  movie  the grand seduction  don mckellar   \n",
              "\n",
              "                                             cast country date_added  \\\n",
              "0  brendan gleeson, taylor kitsch, gordon pinsent  canada 2021-03-30   \n",
              "1  brendan gleeson, taylor kitsch, gordon pinsent  canada 2021-03-30   \n",
              "\n",
              "   release_year rating duration      listed_in  \\\n",
              "0          2014      g  113 min  comedy, drama   \n",
              "1          2014      g  113 min  comedy, drama   \n",
              "\n",
              "                                         description   id  duration_int  \\\n",
              "0  a small fishing village must procure a local d...  as1         113.0   \n",
              "1  a small fishing village must procure a local d...  as1         113.0   \n",
              "\n",
              "  duration_type  userId  score  timestamp  \n",
              "0           min     543    5.0 2003-07-30  \n",
              "1           min     595    3.0 1996-08-13  "
            ],
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              "      <th>0</th>\n",
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              "      <td>the grand seduction</td>\n",
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              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-19ff1a79-6565-4ddd-98a9-1e19b0b76180')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-19ff1a79-6565-4ddd-98a9-1e19b0b76180 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-19ff1a79-6565-4ddd-98a9-1e19b0b76180');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#cantidad de rows y columnas\n",
        "plataformasUsuarioRating.shape"
      ],
      "metadata": {
        "id": "VA29RoUsgjHT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a43a08dd-8cbc-4ed4-b75a-83ff39c117e3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(11024165, 18)"
            ]
          },
          "metadata": {},
          "execution_count": 65
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#un poco mas de info del data\n",
        "plataformasUsuarioRating.info()"
      ],
      "metadata": {
        "id": "N-MMzVpL3wlE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a372c58c-fcf7-4792-dc9d-93228d4d80b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 11024165 entries, 0 to 11024164\n",
            "Data columns (total 18 columns):\n",
            " #   Column         Dtype         \n",
            "---  ------         -----         \n",
            " 0   show_id        object        \n",
            " 1   type           object        \n",
            " 2   title          object        \n",
            " 3   director       object        \n",
            " 4   cast           object        \n",
            " 5   country        object        \n",
            " 6   date_added     datetime64[ns]\n",
            " 7   release_year   int64         \n",
            " 8   rating         object        \n",
            " 9   duration       object        \n",
            " 10  listed_in      object        \n",
            " 11  description    object        \n",
            " 12  id             object        \n",
            " 13  duration_int   float64       \n",
            " 14  duration_type  object        \n",
            " 15  userId         int64         \n",
            " 16  score          float64       \n",
            " 17  timestamp      datetime64[ns]\n",
            "dtypes: datetime64[ns](2), float64(2), int64(2), object(12)\n",
            "memory usage: 1.6+ GB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Data que se usará para ML 🌸"
      ],
      "metadata": {
        "id": "vtLJqvVPBbqE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#para guardar a csv \n",
        "#plataformasUsuarioRating.to_csv('plataformasUsuarioRating.csv', index=False) "
      ],
      "metadata": {
        "id": "hf-57XQLg2Cy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#tambien lo guardaré en formato parquet\n",
        "plataformasUsuarioRating.to_parquet('/content/drive/MyDrive/plataformasUsuarioRating.parquet', index=False) "
      ],
      "metadata": {
        "id": "iZox-6aaBk2M"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "<p align=\"center\">\n",
        "<img src = \"https://media.tenor.com/sDhhANV9qroAAAAC/por-fin.gif\" width=20%>\n",
        "</p>"
      ],
      "metadata": {
        "id": "Ba4NJGtLGwbd"
      }
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "mount_file_id": "1zvNhdS1OllH4MNGOyW8wt3bYENXBGNyb",
      "authorship_tag": "ABX9TyPUyI8EBROx7D1TRo/DOQH3"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}