Movies_Notebook.ipynb

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      "id": "major-backing",
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        "id": "major-backing"
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      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "prepared-edgar",
      "metadata": {
        "id": "prepared-edgar"
      },
      "source": [
        "### Data Assessing"
      ]
    },
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      "execution_count": null,
      "id": "complicated-stick",
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        "id": "complicated-stick"
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      "source": [
        "# load Movies data\n",
        "\n",
        "data = pd.read_csv(\"/content/Movies.csv\", index_col = False)"
      ]
    },
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime  \n",
              "0   46998772.0        Warner Bros.    146.0  \n",
              "1   58853106.0   Columbia Pictures    104.0  \n",
              "2  538375067.0           Lucasfilm    124.0  \n",
              "3   83453539.0  Paramount Pictures     88.0  \n",
              "4   39846344.0      Orion Pictures     98.0  "
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              "      <td>1980</td>\n",
              "      <td>June 20, 1980 (United States)</td>\n",
              "      <td>8.7</td>\n",
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              "      <td>538375067.0</td>\n",
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              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 25, 1980 (United States)</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 7668 entries, 0 to 7667\n",
            "Data columns (total 15 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   name      7668 non-null   object \n",
            " 1   rating    7591 non-null   object \n",
            " 2   genre     7668 non-null   object \n",
            " 3   year      7668 non-null   int64  \n",
            " 4   released  7666 non-null   object \n",
            " 5   score     7665 non-null   float64\n",
            " 6   votes     7665 non-null   float64\n",
            " 7   director  7668 non-null   object \n",
            " 8   writer    7665 non-null   object \n",
            " 9   star      7667 non-null   object \n",
            " 10  country   7665 non-null   object \n",
            " 11  budget    5497 non-null   float64\n",
            " 12  gross     7479 non-null   float64\n",
            " 13  company   7651 non-null   object \n",
            " 14  runtime   7664 non-null   float64\n",
            "dtypes: float64(5), int64(1), object(9)\n",
            "memory usage: 898.7+ KB\n"
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime  \n",
              "0   46998772.0        Warner Bros.    146.0  \n",
              "1   58853106.0   Columbia Pictures    104.0  \n",
              "2  538375067.0           Lucasfilm    124.0  \n",
              "3   83453539.0  Paramount Pictures     88.0  \n",
              "4   39846344.0      Orion Pictures     98.0  "
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              "      <td>The Shining</td>\n",
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              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
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              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
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              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
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              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
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              "      <td>Brian Doyle-Murray</td>\n",
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              "  </svg>\n",
              "      </button>\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
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              "\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
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              "          document.querySelector('#df-50049062-d749-44fe-898f-429f58a0b6a2 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-50049062-d749-44fe-898f-429f58a0b6a2');\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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ],
      "source": [
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "missing-agreement",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "missing-agreement",
        "outputId": "85cf94df-e454-4e04-a2e2-dc1b4507d750"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              year        score         votes        budget         gross  \\\n",
              "count  7668.000000  7665.000000  7.665000e+03  5.497000e+03  7.479000e+03   \n",
              "mean   2000.405451     6.390411  8.810850e+04  3.558988e+07  7.850054e+07   \n",
              "std      11.153508     0.968842  1.633238e+05  4.145730e+07  1.657251e+08   \n",
              "min    1980.000000     1.900000  7.000000e+00  3.000000e+03  3.090000e+02   \n",
              "25%    1991.000000     5.800000  9.100000e+03  1.000000e+07  4.532056e+06   \n",
              "50%    2000.000000     6.500000  3.300000e+04  2.050000e+07  2.020576e+07   \n",
              "75%    2010.000000     7.100000  9.300000e+04  4.500000e+07  7.601669e+07   \n",
              "max    2020.000000     9.300000  2.400000e+06  3.560000e+08  2.847246e+09   \n",
              "\n",
              "           runtime  \n",
              "count  7664.000000  \n",
              "mean    107.261613  \n",
              "std      18.581247  \n",
              "min      55.000000  \n",
              "25%      95.000000  \n",
              "50%     104.000000  \n",
              "75%     116.000000  \n",
              "max     366.000000  "
            ],
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              "      <th></th>\n",
              "      <th>year</th>\n",
              "      <th>score</th>\n",
              "      <th>votes</th>\n",
              "      <th>budget</th>\n",
              "      <th>gross</th>\n",
              "      <th>runtime</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>7668.000000</td>\n",
              "      <td>7665.000000</td>\n",
              "      <td>7.665000e+03</td>\n",
              "      <td>5.497000e+03</td>\n",
              "      <td>7.479000e+03</td>\n",
              "      <td>7664.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>2000.405451</td>\n",
              "      <td>6.390411</td>\n",
              "      <td>8.810850e+04</td>\n",
              "      <td>3.558988e+07</td>\n",
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              "      <td>107.261613</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>11.153508</td>\n",
              "      <td>0.968842</td>\n",
              "      <td>1.633238e+05</td>\n",
              "      <td>4.145730e+07</td>\n",
              "      <td>1.657251e+08</td>\n",
              "      <td>18.581247</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1980.000000</td>\n",
              "      <td>1.900000</td>\n",
              "      <td>7.000000e+00</td>\n",
              "      <td>3.000000e+03</td>\n",
              "      <td>3.090000e+02</td>\n",
              "      <td>55.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1991.000000</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>9.100000e+03</td>\n",
              "      <td>1.000000e+07</td>\n",
              "      <td>4.532056e+06</td>\n",
              "      <td>95.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>2000.000000</td>\n",
              "      <td>6.500000</td>\n",
              "      <td>3.300000e+04</td>\n",
              "      <td>2.050000e+07</td>\n",
              "      <td>2.020576e+07</td>\n",
              "      <td>104.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2010.000000</td>\n",
              "      <td>7.100000</td>\n",
              "      <td>9.300000e+04</td>\n",
              "      <td>4.500000e+07</td>\n",
              "      <td>7.601669e+07</td>\n",
              "      <td>116.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2020.000000</td>\n",
              "      <td>9.300000</td>\n",
              "      <td>2.400000e+06</td>\n",
              "      <td>3.560000e+08</td>\n",
              "      <td>2.847246e+09</td>\n",
              "      <td>366.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "              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",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b6b5f6f7-6d5b-4477-82ad-259e5b829d01 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-b6b5f6f7-6d5b-4477-82ad-259e5b829d01');\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",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 125
        }
      ],
      "source": [
        "data.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "arctic-tradition",
      "metadata": {
        "id": "arctic-tradition"
      },
      "source": [
        "# data cleaning"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "wanted-enlargement",
      "metadata": {
        "id": "wanted-enlargement"
      },
      "source": [
        "###### incorrect data type, missing data, duplicate data"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "continuous-radio",
      "metadata": {
        "id": "continuous-radio"
      },
      "source": [
        "### Missing Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "selective-pointer",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "selective-pointer",
        "outputId": "24bead72-33c0-47f7-e18b-0c3a3045ac77"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0\n",
              "rating        77\n",
              "genre          0\n",
              "year           0\n",
              "released       2\n",
              "score          3\n",
              "votes          3\n",
              "director       0\n",
              "writer         3\n",
              "star           1\n",
              "country        3\n",
              "budget      2171\n",
              "gross        189\n",
              "company       17\n",
              "runtime        4\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 126
        }
      ],
      "source": [
        "#Check for Null Values\n",
        "\n",
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "governmental-taylor",
      "metadata": {
        "id": "governmental-taylor"
      },
      "outputs": [],
      "source": [
        "# Using mode to fill null values\n",
        "\n",
        "rating_mode = data['rating'].mode()[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "arctic-victory",
      "metadata": {
        "id": "arctic-victory"
      },
      "outputs": [],
      "source": [
        "data['rating'].fillna(rating_mode, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "civil-athens",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "civil-athens",
        "outputId": "8ad00714-a43f-4408-e39f-48c139b22dba"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0\n",
              "rating         0\n",
              "genre          0\n",
              "year           0\n",
              "released       2\n",
              "score          3\n",
              "votes          3\n",
              "director       0\n",
              "writer         3\n",
              "star           1\n",
              "country        3\n",
              "budget      2171\n",
              "gross        189\n",
              "company       17\n",
              "runtime        4\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 129
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## first we will deal with missing values in released column\n",
        "## split released column to two columns: released_year and released_country\n",
        "## and after that append the two columns inside our data"
      ],
      "metadata": {
        "id": "Hifn6eS2Mlg9"
      },
      "id": "Hifn6eS2Mlg9"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "alert-senior",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "alert-senior",
        "outputId": "5c9249d4-53f5-4675-d2a7-b461ac5801de"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    February 14, 1986 (United States)\n",
              "1         May 17, 2019 (United States)\n",
              "2      October 4, 1991 (United States)\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 130
        }
      ],
      "source": [
        "data['released'].mode()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "objective-horizon",
      "metadata": {
        "id": "objective-horizon"
      },
      "outputs": [],
      "source": [
        "# Drop null values\n",
        "\n",
        "data.dropna(subset=['released'], axis = 0, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['released'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VLYeGjFifogI",
        "outputId": "bc81945a-7c9d-41f1-9bcf-378d16b6d2a8"
      },
      "id": "VLYeGjFifogI",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['June 13, 1980 (United States)', 'July 2, 1980 (United States)',\n",
              "       'June 20, 1980 (United States)', ...,\n",
              "       'October 23, 2020 (United States)', 'April 27, 2020 (Cameroon)',\n",
              "       'August 19, 2020 (United States)'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 132
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['released'].count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lxzMo4NdKggd",
        "outputId": "71a2afb0-bb85-4219-ad16-53a4628faadf"
      },
      "id": "lxzMo4NdKggd",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "7666"
            ]
          },
          "metadata": {},
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# split released column to two columns and assign names to new columns\n",
        "\n",
        "df = data['released'].str.split(\"(\", expand=True)\n",
        "df_columns = [\"released_date\",\"released_country\"]\n",
        "df.columns = df_columns"
      ],
      "metadata": {
        "id": "9YHT9CA4o0lR"
      },
      "id": "9YHT9CA4o0lR",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.count()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3hXguPQ1LHz7",
        "outputId": "2c2953cf-d3d6-4ed1-b9ca-caae1c357e16"
      },
      "id": "3hXguPQ1LHz7",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "released_date       7666\n",
              "released_country    7666\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 135
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.count()"
      ],
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              "name        7666\n",
              "rating      7666\n",
              "genre       7666\n",
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              "score       7663\n",
              "votes       7663\n",
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              "country     7665\n",
              "budget      5497\n",
              "gross       7479\n",
              "company     7651\n",
              "runtime     7664\n",
              "dtype: int64"
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          "execution_count": 136
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime  \n",
              "0   46998772.0        Warner Bros.    146.0  \n",
              "1   58853106.0   Columbia Pictures    104.0  \n",
              "2  538375067.0           Lucasfilm    124.0  \n",
              "3   83453539.0  Paramount Pictures     88.0  \n",
              "4   39846344.0      Orion Pictures     98.0  "
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          },
          "metadata": {},
          "execution_count": 137
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# add released_year column to our data\n",
        "\n",
        "data['released_date'] = df['released_date']"
      ],
      "metadata": {
        "id": "2fEe6jewL9wa"
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      "id": "2fEe6jewL9wa",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# add released_country column to our data\n",
        "\n",
        "data['released_country'] = df['released_country']"
      ],
      "metadata": {
        "id": "UFC8EpgrMJ58"
      },
      "id": "UFC8EpgrMJ58",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# also let's remove \")\" from released_country column\n",
        "\n",
        "data['released_country'] = data['released_country'].str.slice(stop = -1)"
      ],
      "metadata": {
        "id": "0FXuYq8zXk-4"
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      "id": "0FXuYq8zXk-4",
      "execution_count": null,
      "outputs": []
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    {
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        "\n",
        "data.shape"
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          "base_uri": "https://localhost:8080/"
        },
        "id": "i0SzrDZNMNKo",
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      "id": "i0SzrDZNMNKo",
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          "data": {
            "text/plain": [
              "(7666, 17)"
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          "metadata": {},
          "execution_count": 141
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime   released_date released_country  \n",
              "0   46998772.0        Warner Bros.    146.0  June 13, 1980     United States  \n",
              "1   58853106.0   Columbia Pictures    104.0   July 2, 1980     United States  \n",
              "2  538375067.0           Lucasfilm    124.0  June 20, 1980     United States  \n",
              "3   83453539.0  Paramount Pictures     88.0   July 2, 1980     United States  \n",
              "4   39846344.0      Orion Pictures     98.0  July 25, 1980     United States  "
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              "      <td>1980</td>\n",
              "      <td>June 20, 1980 (United States)</td>\n",
              "      <td>8.7</td>\n",
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              "      <td>Irvin Kershner</td>\n",
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              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
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              "      <td>June 20, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
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              "      <td>PG</td>\n",
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              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
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              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>July 2, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 25, 1980 (United States)</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>July 25, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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          },
          "metadata": {},
          "execution_count": 142
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "challenging-monte",
      "metadata": {
        "id": "challenging-monte",
        "outputId": "ff0cea1c-073b-421d-d113-8b87d8feb158",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  3\n",
              "votes                  3\n",
              "director               0\n",
              "writer                 3\n",
              "star                   1\n",
              "country                1\n",
              "budget              2169\n",
              "gross                187\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 143
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "eight-doctrine",
      "metadata": {
        "id": "eight-doctrine"
      },
      "outputs": [],
      "source": [
        "mean_score =round(data['score'].mean(),1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "tutorial-giant",
      "metadata": {
        "id": "tutorial-giant"
      },
      "outputs": [],
      "source": [
        "# Using mean to fill null values\n",
        "\n",
        "data['score'].fillna(mean_score, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "revised-vertex",
      "metadata": {
        "scrolled": true,
        "id": "revised-vertex",
        "outputId": "d4321fdc-9d76-49bf-fbb2-db69cdc54872",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  0\n",
              "votes                  3\n",
              "director               0\n",
              "writer                 3\n",
              "star                   1\n",
              "country                1\n",
              "budget              2169\n",
              "gross                187\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 146
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "naked-cleaning",
      "metadata": {
        "id": "naked-cleaning"
      },
      "outputs": [],
      "source": [
        "mean_votes =round(data['votes'].mean(),2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "creative-belgium",
      "metadata": {
        "id": "creative-belgium"
      },
      "outputs": [],
      "source": [
        "# Using mean to fill null values\n",
        "\n",
        "data['votes'].fillna(mean_votes, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "knowing-algebra",
      "metadata": {
        "id": "knowing-algebra",
        "outputId": "afffa8d4-e34b-410a-9142-9f3780a29f82",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  0\n",
              "votes                  0\n",
              "director               0\n",
              "writer                 3\n",
              "star                   1\n",
              "country                1\n",
              "budget              2169\n",
              "gross                187\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 149
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "dangerous-fields",
      "metadata": {
        "id": "dangerous-fields"
      },
      "outputs": [],
      "source": [
        "#Drop Null Values\n",
        "\n",
        "data.dropna(subset=['writer'], axis = 0, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "supported-crisis",
      "metadata": {
        "id": "supported-crisis",
        "outputId": "e1505683-2825-4d0a-a2ba-74e0c7d319d8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  0\n",
              "votes                  0\n",
              "director               0\n",
              "writer                 0\n",
              "star                   1\n",
              "country                1\n",
              "budget              2166\n",
              "gross                187\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 151
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "seventh-surge",
      "metadata": {
        "id": "seventh-surge"
      },
      "outputs": [],
      "source": [
        "#Drop Null Values\n",
        "\n",
        "data.dropna(subset=['star'], axis = 0, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "reduced-importance",
      "metadata": {
        "id": "reduced-importance",
        "outputId": "0f159443-50cb-4b46-a011-4e9a67a1d3a8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  0\n",
              "votes                  0\n",
              "director               0\n",
              "writer                 0\n",
              "star                   0\n",
              "country                1\n",
              "budget              2166\n",
              "gross                186\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 153
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "composite-chuck",
      "metadata": {
        "id": "composite-chuck"
      },
      "outputs": [],
      "source": [
        "#Drop Null Values\n",
        "\n",
        "data.dropna(subset=['country'], axis = 0, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "sexual-scholar",
      "metadata": {
        "id": "sexual-scholar",
        "outputId": "b427ecef-a16e-42e2-e8e2-516ec84c5e4a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                   0\n",
              "rating                 0\n",
              "genre                  0\n",
              "year                   0\n",
              "released               0\n",
              "score                  0\n",
              "votes                  0\n",
              "director               0\n",
              "writer                 0\n",
              "star                   0\n",
              "country                0\n",
              "budget              2166\n",
              "gross                186\n",
              "company               15\n",
              "runtime                2\n",
              "released_date          0\n",
              "released_country       0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 155
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "internal-nursing",
      "metadata": {
        "id": "internal-nursing",
        "outputId": "2854cd81-e962-4714-cc65-d439f90762db",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime   released_date released_country  \n",
              "0   46998772.0        Warner Bros.    146.0  June 13, 1980     United States  \n",
              "1   58853106.0   Columbia Pictures    104.0   July 2, 1980     United States  \n",
              "2  538375067.0           Lucasfilm    124.0  June 20, 1980     United States  \n",
              "3   83453539.0  Paramount Pictures     88.0   July 2, 1980     United States  \n",
              "4   39846344.0      Orion Pictures     98.0  July 25, 1980     United States  "
            ],
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              "\n",
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              "<style scoped>\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>name</th>\n",
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              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Shining</td>\n",
              "      <td>R</td>\n",
              "      <td>Drama</td>\n",
              "      <td>1980</td>\n",
              "      <td>June 13, 1980 (United States)</td>\n",
              "      <td>8.4</td>\n",
              "      <td>927000.0</td>\n",
              "      <td>Stanley Kubrick</td>\n",
              "      <td>Stephen King</td>\n",
              "      <td>Jack Nicholson</td>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>19000000.0</td>\n",
              "      <td>46998772.0</td>\n",
              "      <td>Warner Bros.</td>\n",
              "      <td>146.0</td>\n",
              "      <td>June 13, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The Blue Lagoon</td>\n",
              "      <td>R</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
              "      <td>Henry De Vere Stacpoole</td>\n",
              "      <td>Brooke Shields</td>\n",
              "      <td>United States</td>\n",
              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>July 2, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>June 20, 1980 (United States)</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
              "      <td>Mark Hamill</td>\n",
              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>June 20, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>July 2, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 25, 1980 (United States)</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>July 25, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-64651644-ce13-4c6d-88fc-9f037b282c68')\"\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-64651644-ce13-4c6d-88fc-9f037b282c68 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-64651644-ce13-4c6d-88fc-9f037b282c68');\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": 156
        }
      ],
      "source": [
        "data.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "clinical-curtis",
      "metadata": {
        "id": "clinical-curtis",
        "outputId": "bdbac33b-5909-47e1-8663-1f05eabf70d8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    5.495000e+03\n",
              "mean     3.560232e+07\n",
              "std      4.145971e+07\n",
              "min      3.000000e+03\n",
              "25%      1.000000e+07\n",
              "50%      2.050000e+07\n",
              "75%      4.500000e+07\n",
              "max      3.560000e+08\n",
              "Name: budget, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 157
        }
      ],
      "source": [
        "# some information about budget column to descide how we will manage Null Values here\n",
        "\n",
        "data['budget'].describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "prostate-chapter",
      "metadata": {
        "id": "prostate-chapter",
        "outputId": "4c10bc2e-0e89-4c69-8435-dd3e16e0806f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "39.41765241128298"
            ]
          },
          "metadata": {},
          "execution_count": 158
        }
      ],
      "source": [
        "(data['budget'].isnull().sum() / data['budget'].count()) * 100"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "blank-moses",
      "metadata": {
        "id": "blank-moses"
      },
      "source": [
        "we found that 40% of this column is null values and we descide to fill null values"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "nasty-indiana",
      "metadata": {
        "id": "nasty-indiana"
      },
      "source": [
        "after that we will check if there is outliers in this column to descide if we will use mean or median to fill null values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "olive-sample",
      "metadata": {
        "id": "olive-sample",
        "outputId": "a32b1c2c-7f1f-4e6b-bd89-5f0f02e9f0bc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3000.0"
            ]
          },
          "metadata": {},
          "execution_count": 159
        }
      ],
      "source": [
        "data['budget'].min()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "temporal-oxide",
      "metadata": {
        "id": "temporal-oxide",
        "outputId": "ffe52f18-f489-45ee-dff0-03bdb610de13",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "356000000.0"
            ]
          },
          "metadata": {},
          "execution_count": 160
        }
      ],
      "source": [
        "data['budget'].max()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "closing-buffalo",
      "metadata": {
        "id": "closing-buffalo",
        "outputId": "b78fc767-3d5c-4bc8-8ddc-d57cdaa2bc3a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "35602315.899727024"
            ]
          },
          "metadata": {},
          "execution_count": 161
        }
      ],
      "source": [
        "data['budget'].mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "vertical-palmer",
      "metadata": {
        "id": "vertical-palmer",
        "outputId": "ea3aea60-afe3-4249-e593-df82bfec3e43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "data['budget'].plot(kind = 'hist', figsize = (8,8));"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "precise-theology",
      "metadata": {
        "id": "precise-theology",
        "outputId": "fbbc0a23-ec5f-4f45-e101-c625fc1b75ad",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 494
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": 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USqVkZkqlUtzLGKgghDEQgUwmo2w2q87OThUKBXV2diqbzRLIQIXgMjUQgVQqpc7OTq1fv36sbevWrdq4caMGBgYCVgbEhd8ZAxEzMxUKBc2dO3es7dChQ6qtrVWo/wYAMWLOGIhYMplUNpud0JbNZpVMJgNVBGA8whiIQGtrqzZs2CAzG3ts2LBBra2toUsDIMIYiML9998vafRy9fjnI+0AwiKMgQjs3btXzc3NGhkZkbtrZGREzc3N2rt3b+jSAIgwBqJx7733HvMYQDiEMRCJyy+//JjHAMIhjIEI1NfXa+fOnVqxYoVefPFFrVixQjt37lR9fX3o0gCIG0UAUXj++ed1+umna+fOnXrb294mSVq0aJGef/75wJUBkBgZA1Ho7u7WggUL9Nhjj+nw4cN67LHHtGDBAnV3d4cuDYDYgQuIQmNjo7q6urRq1aqxtlwup0wmo127dgWsDIgLO3ABEevt7dW+ffvU2NioRCKhxsZG7du3T729vaFLAyDmjIEovO1tb1N7e7u+/e1va+XKlcrn87rqqqvG5o8BhEUYA5E4cOCAPvrRj6pYLKqmpkbV1dU6/fTTQ5cFQFymBqLwwgsvaGBgQIsWLZI0upJ6YGBAL7zwQuDKAEiEMRCNtrY2vfTSS3J3vfTSS2prawtdEoASwhiIgLvr4YcfVi6XU7FYVC6X08MPP8y9jIEKwZwxEIFkMqkVK1Yok8mot7dX6XR6bDcuAOExMgYi0Nraqrvvvltr167Va6+9prVr1+ruu+/mfsZAhWDTDyAS5513np555pmx43e/+916+umnA1YExIdNP4CIZTIZ7d69W2eccYbMTGeccYZ2796tTCYTujQAIoyBKGSzWS1cuFDd3d0aHBxUd3e3Fi5cqGw2G7o0ACKMgSgMDQ2ppaVFmUxGqVRKmUxGLS0tGhoaCl0aALGaGojGbbfdpvvuu29sO8zLLrssdEkASghjIAJVVVU6cOCArrzySr388st661vfqgMHDqiqiotjQCXgLxGIwMjIiCSpr69PIyMj6uvrm9AOICzCGIhAMpnUlVdeqXPOOUdVVVU655xzdOWVVyqZTIYuDYAIYyAKhw8f1o4dO9TV1aWBgQF1dXVpx44dOnz4cOjSAIg5YyAK5557rj75yU9O2A7zqquu0ve+973QpQHQNEbGZlZvZjkze9bMdpvZF6boY2b2DTPbY2ZPm9mfz0y5AE5ER0eH7rrrrgkj47vuuksdHR2hSwOgaWyHaWZnSjrT3X9lZqdJekLSJ9392XF9LpGUkXSJpA9I+rq7f+BY38t2mMDsMrM/aeOuTcDsOuHtMN39RXf/Ven1a5J6JZ01qdulkr7po34uaWEpxAFUgPFB/NWvfnXKdgDhvKEFXGbWIOm9kn4x6a2zJO0dd7xPfxrYAAJzd33xi19kRAxUmGmHsZnNk3SfpP/i7gdP5GRmts7Mesys58jvHAHMjvEj4qmOAYQzrVsomlmNpB9I+qG7b53i/f8h6XF37y4d/0bSBe5+1DuXM2cMzJ4jl6PH/71P1QZgZp3wnLGN/sVuk9Q7VRCXPCDpM6VV1R+U9OqxghhAGGY29gBQOaZzmXqFpL+SdKGZPVV6XGJmbWbWVurzkKTfStoj6VZJfzMz5QI4Eddcc80bagcwu6Z1mXomcJkamD2pVEqdnZ1av379WNvWrVu1ceNGDQwMBKwMiMvRLlMTxkAEzEyFQkFz584dazt06JBqa2uZMwZm0QnPGQN480smk8pmsxPastksN4oAKgR7UwMRaG1tVXt7uySpra1N2WxW7e3tamtrO84nAcwGLlMDkZg3b54KhcLYcW1trV5//fWAFQHx4TI1ELGzzz5bhUJBzc3N+t3vfqfm5mYVCgWdffbZoUsDIMIYiMLevXvV3NysHTt26Mwzz9SOHTvU3NysvXv3Hv/DAGYcYQxE4t577z3mMYBwCGMgEpdffvkxjwGEQxgDEaivr9fOnTu1YsUKvfjii1qxYoV27typ+vr60KUBEKupgWhMtR81G34As4vV1EDE5s2bJ0lqaGjQnj171NDQMKEdQFiEMRCBQqGgxYsXq7a2VsuWLVNtba0WL1484XfHAMIhjIFIpFIpdXV1aWBgQF1dXUqlUqFLAlDCdphAJIrFolatWiVJWrVqlYrFYuCKABxBGAOR+P3vfz/lIi4A4XGZGojA0UKYcAYqA2EMROBoP2Hip01AZSCMgYhUVVVNeAZQGfiLBCLyox/9SIcPH9aPfvSj0KUAGIcFXEBEPvKRj2hkZISRMVBh+IsEIjIyMjLhGUBlIIyByNx5552hSwAwCWEMRObTn/506BIATEIYA5FYvXq1li9frqqqKi1fvlyrV68OXRKAEhZwAZG455579Nhjj2nlypXK5/O68MILQ5cEoIQwBiJCAAOVicvUAAAERhgDkaipqZG7jz1qampClwSghDAGIpHL5Y55DCAcwhiIxJF7GR/tGEA4hDEQiWKxqDlz5mjHjh2aM2eOisVi6JIAlLCaGoiAu8vMVCwWtXLlygntAMJjZAxEIJVKSZLOOOMM9fb26owzzpjQDiAswhiIwODgoObPn6/Fixdr+fLlWrx4sebPn6/BwcHQpQEQYQxEo6qqSoVCQZJUKBS4jSJQQfhrBCJx8OBBbd++XQMDA9q+fbsOHjwYuiQAJSzgAiIxMjLCdphAhWJkDABAYIQxEJEtW7aoUChoy5YtoUsBMA5hDERi7ty56urq0rx589TV1aW5c+eGLglACWEMROLQoUOqra2Vmam2tlaHDh0KXRKAEsIYiMizzz6rhx56SM8++2zoUgCMQxgDEbjrrrskjW5/efHFF49tg3mkHUBYhDEQgdtvv12SVFdXp6qqKtXV1U1oBxAWYQxE4NFHH9XVV1+t/v5+DQ8Pq7+/X1dffbUeffTR0KUBkGSh7trS1NTkPT09Qc4NxMbMdODAAS1YsGCs7dVXX9XChQu5cxMwi8zsCXdvmtzOyBiIgJnp+uuvn9B2/fXXy8wCVQRgvOOGsZltN7OXzWzXUd6/wMxeNbOnSo8vlb9MACfjoosu0s033ywzG3vcfPPNuuiii0KXBkDT25v6dkk3SvrmMfr8zN3/siwVASi7Rx555A21A5hdxx0Zu/tPJfXPQi0AZlgymZzwDKAylGvO+ENm9msze9jMlh+tk5mtM7MeM+vp6+sr06kBTFdnZ6cKhYI6OztDlwJgnGmtpjazBkk/cPfGKd6bL2nE3V83s0skfd3d33W872Q1NTB7jizUGv/3PlUbgJk1Y6up3f2gu79eev2QpBozW3yy3wug/MxMn/rUp1hFDVSYkw5jM1tqpb9sM3t/6TtfOdnvBVA+4+eI77nnninbAYRz3NXUZtYt6QJJi81sn6QvS6qRJHfPSrpc0tVmNiTpD5KucK57ARVleHhYklRVVSV3l5lpZGRkrB1AWMcNY3dfc5z3b9ToT58AVKihoSGZmRKJhIrFoqqrq+XuGhoaCl0aALEDFxCNtrY2LVu2TFVVVVq2bJna2tpClwSgZDqbfgA4BWSzWf34xz/WypUrlc/n9eEPfzh0SQBKGBkDkXB3rV27Vs8//7zWrl3LT5qACsLIGIiAmcnd9dxzz+md73znhHYA4TEyBiJwtFEwo2OgMhDGQESWLl2qqqoqLV26NHQpAMYhjIFIVFdX66WXXtLIyIheeuklVVczSwVUCsIYiMTQ0JC2bNmiQqGgLVu28BtjoIJM60YRM4EbRQCz51gLtZg3BmbPjN0oAgAAnBzCGIhITU3NhGcAlYEwBiJSLBYnPAOoDIQxEJFEIjHhGUBlIIyByDz++OOhSwAwCT80BCIyPDysCy64IHQZACZhZAxEhv2ogcpDGAOR4XfFQOUhjAEACIwwBiLS0NAgM1NDQ0PoUgCMwwIuICLPPffchGcAlYGRMQAAgRHGQETY9AOoTIQxAACBEcZAROrr61VVVaX6+vrQpQAYhwVcQERYwAVUJkbGQASWL1/+htoBzC7CGIjA7t27x17feeedU7YDCIcwBiKyfPlyfeYzn2FEDFQYwhiIxOc+97ljHgMIhzAGInHTTTepUCjI3VUoFHTTTTeFLglACaupgYiwmhqoTIyMAQAIjDAGIlFbWyt3H3vU1taGLglACWEMRGJoaEhz5syRmWnOnDkaGhoKXRKAEuaMgUgMDg6qqmr0/7+Hh4dVLBYDVwTgCEbGQERGRkYmPAOoDIQxAACBEcYAAARGGAMROTJnfOQZQGXgLxKICHPGQGUijIGI1NXVycxUV1cXuhQA4/DTJiAi+/fvn/AMoDIwMgYAIDDCGIhIIpGY8AygMhDGQESGh4cnPAOoDIQxAACBHTeMzWy7mb1sZruO8r6Z2TfMbI+ZPW1mf17+MgGUQyKR0OOPP85laqDCTGdkfLuki4/x/sckvav0WCfp5pMvC8BMGB4e1gUXXMBlaqDCHDeM3f2nkvqP0eVSSd/0UT+XtNDMzixXgQAAnOrKMWd8lqS94473ldoAAMA0zOoCLjNbZ2Y9ZtbT19c3m6cGAKBilSOMX5BUP+747aW2P+Hut7h7k7s3LVmypAynBgDgza8cYfyApM+UVlV/UNKr7v5iGb4XwAxYtWpV6BIATHLcvanNrFvSBZIWm9k+SV+WVCNJ7p6V9JCkSyTtkXRI0n+aqWIBSA3XPXhSn8/lcmX5vue+9vGTqgPAH5m7BzlxU1OT9/T0BDk3EJvTTz9d/f39qq6u1tDQ0NjzokWL9Morr4QuD4iGmT3h7k2T29mBC4jAjTfeqPnz58vMJElmpvnz5+vGG28MXBkAiTAGorBmzRpls1ktW7ZMsiotW7ZM2WxWa9asCV0aAHGZGohOw3UPMt8LBMJlagAAKhRhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAAQ2rTA2s4vN7DdmtsfMrpvi/c+aWZ+ZPVV6/OfylwoAwKmp+ngdzCwh6SZJF0naJ+mXZvaAuz87qevd7n7NDNQIAMApbToj4/dL2uPuv3X3w5K+I+nSmS0LAIB4TCeMz5K0d9zxvlLbZJeZ2dNmdq+Z1ZelOgAAIlCuBVzfl9Tg7udJelTSHVN1MrN1ZtZjZj19fX1lOjUAAG9u0wnjFySNH+m+vdQ2xt1fcffB0uFtkt431Re5+y3u3uTuTUuWLDmRegEAOOVMJ4x/KeldZvZnZjZH0hWSHhjfwczOHHf4CUm95SsRAIBT23FXU7v7kJldI+mHkhKStrv7bjP7iqQed39A0ufN7BOShiT1S/rsDNYMAMAp5bhhLEnu/pCkhya1fWnc6+slXV/e0gAAiMO0whhAebznhkf06h+KoctQw3UPhi5BC95So19/+d+HLgOoCIQxMIte/UNRz33t46HLqAiV8D8EQKVgb2oAAAIjjAEACIwwBgAgMMIYAIDACGMAAAIjjAEACIwwBgAgMMIYAIDACGMAAAIjjAEACIwwBgAgMMIYAIDACGMAAAIjjAEACIwwBgAgMMIYAIDACGMAAAIjjAEACIwwBgAgMMIYAIDACGMAAAIjjAEACIwwBgAgMMIYAIDACGMAAAKrDl0AEJPT0tfp3XdcF7qMinBaWpI+HroMoCIQxsAseq33a3ruawSQJDVc92DoEoCKwWVqAAACI4wBAAiMMAYAIDDCGACAwAhjAAACI4wBAAiMMAYAIDDCGACAwAhjAAACI4wBAAiM7TCBWcY2kKMWvKUmdAlAxSCMgVlUCftSN1z3YEXUAeCPuEwNAEBghDEAAIERxgAABEYYAwAQGGEMAEBg0wpjM7vYzH5jZnvM7Lop3k+a2d2l939hZg3lLhQAgFPVccPYzBKSbptTYLUAAAO9SURBVJL0MUnnSlpjZudO6tYiab+7v1PS30vaXO5CAQA4VU1nZPx+SXvc/bfufljSdyRdOqnPpZLuKL2+V9KHzczKVyYAAKeu6YTxWZL2jjveV2qbso+7D0l6VdLp5SgQAIBT3azuwGVm6yStk6Szzz57Nk8NnDLKsZ1mOb6DXbyA8plOGL8gqX7c8dtLbVP12Wdm1ZIWSHpl8he5+y2SbpGkpqYmP5GCgdgRgsCpZzqXqX8p6V1m9mdmNkfSFZIemNTnAUl/XXp9uaTH3J2wBQBgGo47Mnb3ITO7RtIPJSUkbXf33Wb2FUk97v6ApG2SvmVmeyT1azSwAQDANExrztjdH5L00KS2L417PSBpdXlLAwAgDuzABQBAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARGGAMAEBhhDABAYIQxAACBEcYAAARm7h7mxGZ9kv4lyMmBuC2W9K+hiwAi9W/cfcnkxmBhDCAMM+tx96bQdQD4Iy5TAwAQGGEMAEBghDEQn1tCFwBgIuaMAQAIjJExAACBEcbAm4yZNZjZrpP4/HNmtvgEP/tJMzv3RM8NYGqEMYA34pOSCGOgzAhj4M2p2sy+bWa9Znavmc0dP+I1syYze7z0+nQze8TMdpvZbZLsyJeY2X8zs9+YWd7Mus3sb0vt7zCzfzSzJ8zsZ2Z2jpk1S/qEpL8zs6fM7B2z/88GTk2EMfDm9G8l/YO7pyUdlPQ3x+j7ZUl5d18u6X9JOluSzOzfSbpM0nskfUzS+I1AbpGUcff3Sfrb0rl2SnpA0rXufr67/78y/5uAaFWHLgDACdnr7jtKr++U9Plj9P0LSf9Rktz9QTPbX2pfIel+dx+QNGBm35ckM5snqVnSPWZjg+hkmesHMA5hDLw5Tf5Noksa0h+vdqVO4rurJB1w9/NP4jsAvAFcpgbenM42sw+VXl8pKS/pOUnvK7VdNq7vT0t9ZGYfk1RXat8h6T+YWao0Gv5LSXL3g5L+2cxWlz5jZvae0mdek3TajPyLgIgRxsCb028kfc7MejUarjdLukHS182sR9LwuL43SPoLM9ut0cvVz0uSu/9So3PAT0t6WNIzkl4tfeYqSS1m9mtJuyVdWmr/jqRrzexJFnAB5cMOXEDEzGyeu79uZnM1OoJe5+6/Cl0XEBvmjIG43VLaxCMl6Q6CGAiDkTEAAIExZwwAQGCEMQAAgRHGAAAERhgDABAYYQwAQGCEMQAAgf1/j1zLH7iuUwYAAAAASUVORK5CYII=\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "data['budget'].plot(kind = 'box', figsize = (8,8));"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "exposed-peace",
      "metadata": {
        "id": "exposed-peace"
      },
      "source": [
        "Budget column has outliers so we will use median"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "matched-dispatch",
      "metadata": {
        "id": "matched-dispatch"
      },
      "outputs": [],
      "source": [
        "median_budget = data['budget'].median()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "israeli-cookbook",
      "metadata": {
        "id": "israeli-cookbook",
        "outputId": "f06834fb-9130-427f-84e5-042a274e8288",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "20500000.0"
            ]
          },
          "metadata": {},
          "execution_count": 165
        }
      ],
      "source": [
        "median_budget"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "clear-lecture",
      "metadata": {
        "id": "clear-lecture"
      },
      "outputs": [],
      "source": [
        "# Fill null values with median\n",
        "\n",
        "data['budget'].fillna(median_budget, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "nasty-collins",
      "metadata": {
        "id": "nasty-collins",
        "outputId": "964bf62c-0456-4db5-a814-357928d039f3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                  0\n",
              "rating                0\n",
              "genre                 0\n",
              "year                  0\n",
              "released              0\n",
              "score                 0\n",
              "votes                 0\n",
              "director              0\n",
              "writer                0\n",
              "star                  0\n",
              "country               0\n",
              "budget                0\n",
              "gross               186\n",
              "company              15\n",
              "runtime               2\n",
              "released_date         0\n",
              "released_country      0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 167
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "popular-sword",
      "metadata": {
        "id": "popular-sword"
      },
      "source": [
        "How to deal with Gross Column?\n",
        "fillna with median or mean>"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "civilian-dealing",
      "metadata": {
        "id": "civilian-dealing"
      },
      "source": [
        "we will check if there is outliers in this column to descide if we will use mean or median to fill null values"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "hindu-macedonia",
      "metadata": {
        "id": "hindu-macedonia",
        "outputId": "de9b44d2-8b8b-4966-c277-7c8f09763a45",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "78509817.05685619"
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ],
      "source": [
        "data['gross'].mean()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "radical-accused",
      "metadata": {
        "id": "radical-accused",
        "outputId": "b98dd173-78ef-4d40-dd5e-aaa3261608ad",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "20208496.0"
            ]
          },
          "metadata": {},
          "execution_count": 169
        }
      ],
      "source": [
        "data['gross'].median()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "retained-driver",
      "metadata": {
        "id": "retained-driver",
        "outputId": "430e2e84-dc84-43d7-8ae4-69614f7c2e3f",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    7.475000e+03\n",
              "mean     7.850982e+07\n",
              "std      1.657516e+08\n",
              "min      3.090000e+02\n",
              "25%      4.549607e+06\n",
              "50%      2.020850e+07\n",
              "75%      7.601669e+07\n",
              "max      2.847246e+09\n",
              "Name: gross, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 170
        }
      ],
      "source": [
        "data['gross'].describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "extensive-involvement",
      "metadata": {
        "id": "extensive-involvement",
        "outputId": "b376d3cf-0242-48f1-9e13-0a4a7f60a869",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 512
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877ca59910>"
            ]
          },
          "metadata": {},
          "execution_count": 171
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "data['gross'].plot(kind = 'box', figsize = (8,8))"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "normal-clearing",
      "metadata": {
        "id": "normal-clearing"
      },
      "source": [
        "so we use median as there are outliers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "medium-harmony",
      "metadata": {
        "id": "medium-harmony"
      },
      "outputs": [],
      "source": [
        "median_gross = round(data['gross'].median(),2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "finite-renewal",
      "metadata": {
        "id": "finite-renewal"
      },
      "outputs": [],
      "source": [
        "# Fill null values with median\n",
        "\n",
        "data['gross'].fillna(median_gross, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "worthy-mumbai",
      "metadata": {
        "id": "worthy-mumbai",
        "outputId": "afa3a8b3-8c05-4c27-ce8f-250a4c3747f6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                 0\n",
              "rating               0\n",
              "genre                0\n",
              "year                 0\n",
              "released             0\n",
              "score                0\n",
              "votes                0\n",
              "director             0\n",
              "writer               0\n",
              "star                 0\n",
              "country              0\n",
              "budget               0\n",
              "gross                0\n",
              "company             15\n",
              "runtime              2\n",
              "released_date        0\n",
              "released_country     0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 174
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "political-davis",
      "metadata": {
        "id": "political-davis",
        "outputId": "f4898ca2-85f7-401d-accf-8acea6b01620",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2380"
            ]
          },
          "metadata": {},
          "execution_count": 175
        }
      ],
      "source": [
        "data['company'].nunique()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "blond-missouri",
      "metadata": {
        "id": "blond-missouri"
      },
      "outputs": [],
      "source": [
        "# Drop Null Values\n",
        "\n",
        "data.dropna(subset = ['company'], axis = 0, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "nearby-measure",
      "metadata": {
        "id": "nearby-measure",
        "outputId": "5d74683b-ab01-4b8c-97a2-906157138c4c",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                0\n",
              "rating              0\n",
              "genre               0\n",
              "year                0\n",
              "released            0\n",
              "score               0\n",
              "votes               0\n",
              "director            0\n",
              "writer              0\n",
              "star                0\n",
              "country             0\n",
              "budget              0\n",
              "gross               0\n",
              "company             0\n",
              "runtime             2\n",
              "released_date       0\n",
              "released_country    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 177
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "adapted-progressive",
      "metadata": {
        "id": "adapted-progressive"
      },
      "outputs": [],
      "source": [
        "mean_runtime = round(data['runtime'].mean())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "swedish-salon",
      "metadata": {
        "id": "swedish-salon"
      },
      "outputs": [],
      "source": [
        "# Fill Null Values\n",
        "\n",
        "data['runtime'].fillna(mean_runtime, inplace = True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "sustained-language",
      "metadata": {
        "id": "sustained-language",
        "outputId": "36cee6f8-4738-403c-ac5c-025e163c3de6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name                0\n",
              "rating              0\n",
              "genre               0\n",
              "year                0\n",
              "released            0\n",
              "score               0\n",
              "votes               0\n",
              "director            0\n",
              "writer              0\n",
              "star                0\n",
              "country             0\n",
              "budget              0\n",
              "gross               0\n",
              "company             0\n",
              "runtime             0\n",
              "released_date       0\n",
              "released_country    0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 180
        }
      ],
      "source": [
        "data.isnull().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "occupational-matter",
      "metadata": {
        "id": "occupational-matter"
      },
      "source": [
        "### Duplicated Rows"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "architectural-sender",
      "metadata": {
        "id": "architectural-sender",
        "outputId": "330fe8a1-92ae-42e8-f739-bde4257825b1",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 181
        }
      ],
      "source": [
        "# Check if there are any duplicated rows\n",
        "\n",
        "data.duplicated().sum()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "greek-torture",
      "metadata": {
        "id": "greek-torture"
      },
      "source": [
        "there is no duplicated rows "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "3a3OjDuKPzfS",
        "outputId": "ef8cb102-fed0-4640-ae3f-b12ec6308f1d"
      },
      "id": "3a3OjDuKPzfS",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime   released_date released_country  \n",
              "0   46998772.0        Warner Bros.    146.0  June 13, 1980     United States  \n",
              "1   58853106.0   Columbia Pictures    104.0   July 2, 1980     United States  \n",
              "2  538375067.0           Lucasfilm    124.0  June 20, 1980     United States  \n",
              "3   83453539.0  Paramount Pictures     88.0   July 2, 1980     United States  \n",
              "4   39846344.0      Orion Pictures     98.0  July 25, 1980     United States  "
            ],
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              "      <th>name</th>\n",
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              "      <th>0</th>\n",
              "      <td>The Shining</td>\n",
              "      <td>R</td>\n",
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              "      <td>1980</td>\n",
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              "      <td>8.4</td>\n",
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              "      <td>The Blue Lagoon</td>\n",
              "      <td>R</td>\n",
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              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
              "      <td>Henry De Vere Stacpoole</td>\n",
              "      <td>Brooke Shields</td>\n",
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              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>July 2, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>June 20, 1980 (United States)</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
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              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>June 20, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>July 2, 1980</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>July 25, 1980 (United States)</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>July 25, 1980</td>\n",
              "      <td>United States</td>\n",
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              "    .colab-df-container {\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",
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          },
          "metadata": {},
          "execution_count": 182
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2hEzU-FBP5Ah",
        "outputId": "f3d2a2cd-0413-4865-e8b7-fcd2912ef43e"
      },
      "id": "2hEzU-FBP5Ah",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7646 entries, 0 to 7667\n",
            "Data columns (total 17 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   name              7646 non-null   object \n",
            " 1   rating            7646 non-null   object \n",
            " 2   genre             7646 non-null   object \n",
            " 3   year              7646 non-null   int64  \n",
            " 4   released          7646 non-null   object \n",
            " 5   score             7646 non-null   float64\n",
            " 6   votes             7646 non-null   float64\n",
            " 7   director          7646 non-null   object \n",
            " 8   writer            7646 non-null   object \n",
            " 9   star              7646 non-null   object \n",
            " 10  country           7646 non-null   object \n",
            " 11  budget            7646 non-null   float64\n",
            " 12  gross             7646 non-null   float64\n",
            " 13  company           7646 non-null   object \n",
            " 14  runtime           7646 non-null   float64\n",
            " 15  released_date     7646 non-null   object \n",
            " 16  released_country  7646 non-null   object \n",
            "dtypes: float64(5), int64(1), object(11)\n",
            "memory usage: 1.1+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "released year has incorrect data type, It should be datetime no object, so let's convert column data type"
      ],
      "metadata": {
        "id": "qOfqgqawQK45"
      },
      "id": "qOfqgqawQK45"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "rapid-glenn",
      "metadata": {
        "id": "rapid-glenn"
      },
      "outputs": [],
      "source": [
        "# change data type of Start Time column to be datetime type\n",
        "\n",
        "data['released_date'] = pd.to_datetime(data['released_date'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "linear-scotland",
      "metadata": {
        "id": "linear-scotland",
        "outputId": "247efd4f-cdbb-4826-d29c-82f78822989b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7646 entries, 0 to 7667\n",
            "Data columns (total 17 columns):\n",
            " #   Column            Non-Null Count  Dtype         \n",
            "---  ------            --------------  -----         \n",
            " 0   name              7646 non-null   object        \n",
            " 1   rating            7646 non-null   object        \n",
            " 2   genre             7646 non-null   object        \n",
            " 3   year              7646 non-null   int64         \n",
            " 4   released          7646 non-null   object        \n",
            " 5   score             7646 non-null   float64       \n",
            " 6   votes             7646 non-null   float64       \n",
            " 7   director          7646 non-null   object        \n",
            " 8   writer            7646 non-null   object        \n",
            " 9   star              7646 non-null   object        \n",
            " 10  country           7646 non-null   object        \n",
            " 11  budget            7646 non-null   float64       \n",
            " 12  gross             7646 non-null   float64       \n",
            " 13  company           7646 non-null   object        \n",
            " 14  runtime           7646 non-null   float64       \n",
            " 15  released_date     7646 non-null   datetime64[ns]\n",
            " 16  released_country  7646 non-null   object        \n",
            "dtypes: datetime64[ns](1), float64(5), int64(1), object(10)\n",
            "memory usage: 1.1+ MB\n"
          ]
        }
      ],
      "source": [
        "data.info()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Okay, after cleaning our data let's start explore data and find some patterns that could help us in our data model"
      ],
      "metadata": {
        "id": "cTMP2tfcQuOZ"
      },
      "id": "cTMP2tfcQuOZ"
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "id": "-frE88MITTKJ",
        "outputId": "0c4f1ed4-7aaa-411c-8e3b-f33c594f8c4c"
      },
      "id": "-frE88MITTKJ",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "                        released  score      votes         director  \\\n",
              "0  June 13, 1980 (United States)    8.4   927000.0  Stanley Kubrick   \n",
              "1   July 2, 1980 (United States)    5.8    65000.0   Randal Kleiser   \n",
              "2  June 20, 1980 (United States)    8.7  1200000.0   Irvin Kershner   \n",
              "3   July 2, 1980 (United States)    7.7   221000.0     Jim Abrahams   \n",
              "4  July 25, 1980 (United States)    7.3   108000.0     Harold Ramis   \n",
              "\n",
              "                    writer            star         country      budget  \\\n",
              "0             Stephen King  Jack Nicholson  United Kingdom  19000000.0   \n",
              "1  Henry De Vere Stacpoole  Brooke Shields   United States   4500000.0   \n",
              "2           Leigh Brackett     Mark Hamill   United States  18000000.0   \n",
              "3             Jim Abrahams     Robert Hays   United States   3500000.0   \n",
              "4       Brian Doyle-Murray     Chevy Chase   United States   6000000.0   \n",
              "\n",
              "         gross             company  runtime released_date released_country  \n",
              "0   46998772.0        Warner Bros.    146.0    1980-06-13    United States  \n",
              "1   58853106.0   Columbia Pictures    104.0    1980-07-02    United States  \n",
              "2  538375067.0           Lucasfilm    124.0    1980-06-20    United States  \n",
              "3   83453539.0  Paramount Pictures     88.0    1980-07-02    United States  \n",
              "4   39846344.0      Orion Pictures     98.0    1980-07-25    United States  "
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              "      <td>The Shining</td>\n",
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              "      <td>1980</td>\n",
              "      <td>July 2, 1980 (United States)</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
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              "      <th>4</th>\n",
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              "      <td>1980</td>\n",
              "      <td>July 25, 1980 (United States)</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "released column is not useful now so we can drop it"
      ],
      "metadata": {
        "id": "99t05xa7Tkr5"
      },
      "id": "99t05xa7Tkr5"
    },
    {
      "cell_type": "code",
      "source": [
        "# drop released column\n",
        "\n",
        "data.drop(labels= \"released\",axis = 1, inplace = True)"
      ],
      "metadata": {
        "id": "k32uyt40Tf2g"
      },
      "id": "k32uyt40Tf2g",
      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
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        "data.info()"
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        "id": "myIK5B8lTVyj",
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      },
      "id": "myIK5B8lTVyj",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 7646 entries, 0 to 7667\n",
            "Data columns (total 16 columns):\n",
            " #   Column            Non-Null Count  Dtype         \n",
            "---  ------            --------------  -----         \n",
            " 0   name              7646 non-null   object        \n",
            " 1   rating            7646 non-null   object        \n",
            " 2   genre             7646 non-null   object        \n",
            " 3   year              7646 non-null   int64         \n",
            " 4   score             7646 non-null   float64       \n",
            " 5   votes             7646 non-null   float64       \n",
            " 6   director          7646 non-null   object        \n",
            " 7   writer            7646 non-null   object        \n",
            " 8   star              7646 non-null   object        \n",
            " 9   country           7646 non-null   object        \n",
            " 10  budget            7646 non-null   float64       \n",
            " 11  gross             7646 non-null   float64       \n",
            " 12  company           7646 non-null   object        \n",
            " 13  runtime           7646 non-null   float64       \n",
            " 14  released_date     7646 non-null   datetime64[ns]\n",
            " 15  released_country  7646 non-null   object        \n",
            "dtypes: datetime64[ns](1), float64(5), int64(1), object(9)\n",
            "memory usage: 1015.5+ KB\n"
          ]
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    {
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        "data.head()"
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      "id": "UHV1o8HOUEA9",
      "execution_count": null,
      "outputs": [
        {
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              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "   score      votes         director                   writer            star  \\\n",
              "0    8.4   927000.0  Stanley Kubrick             Stephen King  Jack Nicholson   \n",
              "1    5.8    65000.0   Randal Kleiser  Henry De Vere Stacpoole  Brooke Shields   \n",
              "2    8.7  1200000.0   Irvin Kershner           Leigh Brackett     Mark Hamill   \n",
              "3    7.7   221000.0     Jim Abrahams             Jim Abrahams     Robert Hays   \n",
              "4    7.3   108000.0     Harold Ramis       Brian Doyle-Murray     Chevy Chase   \n",
              "\n",
              "          country      budget        gross             company  runtime  \\\n",
              "0  United Kingdom  19000000.0   46998772.0        Warner Bros.    146.0   \n",
              "1   United States   4500000.0   58853106.0   Columbia Pictures    104.0   \n",
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              "4   United States   6000000.0   39846344.0      Orion Pictures     98.0   \n",
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              "  released_date released_country  \n",
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              "1    1980-07-02    United States  \n",
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              "      <th>2</th>\n",
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              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
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              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>1980-06-20</td>\n",
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              "      <th>3</th>\n",
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              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
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              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>R</td>\n",
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              "      <td>1980</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
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              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
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              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5782d3ee-640c-4569-89f3-7774f0b62b8a')\"\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-5782d3ee-640c-4569-89f3-7774f0b62b8a 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-5782d3ee-640c-4569-89f3-7774f0b62b8a');\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": 189
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data['rating'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Twbt76eOUHie",
        "outputId": "7ad88aab-7f42-4ae4-c25a-9bec5bd33f2a"
      },
      "id": "Twbt76eOUHie",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['R', 'PG', 'G', 'Not Rated', 'NC-17', 'Approved', 'TV-PG', 'PG-13',\n",
              "       'Unrated', 'X', 'TV-MA', 'TV-14'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 190
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q1) find the most five rating for movies"
      ],
      "metadata": {
        "id": "FzIfbOoIVZue"
      },
      "id": "FzIfbOoIVZue"
    },
    {
      "cell_type": "code",
      "source": [
        "most_five_rating =data['rating'].value_counts().head()"
      ],
      "metadata": {
        "id": "cFHrXn_GVYjY"
      },
      "id": "cFHrXn_GVYjY",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "most_five_rating"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lgKruvgDWUa3",
        "outputId": "203620ec-cc4e-460d-a4c4-5187b1545605"
      },
      "id": "lgKruvgDWUa3",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "R            3760\n",
              "PG-13        2111\n",
              "PG           1249\n",
              "Not Rated     282\n",
              "G             153\n",
              "Name: rating, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 192
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "most_five_rating.sort_values().plot(kind = \"barh\", figsize = (9,9))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 556
        },
        "id": "ChvSxSWmUu7Z",
        "outputId": "f346716a-cfcb-4aa4-b700-aa5a3d8ea6fa"
      },
      "id": "ChvSxSWmUu7Z",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877ca20c90>"
            ]
          },
          "metadata": {},
          "execution_count": 193
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q2) the most common movie star"
      ],
      "metadata": {
        "id": "TZt9s7GvWpeH"
      },
      "id": "TZt9s7GvWpeH"
    },
    {
      "cell_type": "code",
      "source": [
        "common_movie_star =data['star'].value_counts().head()"
      ],
      "metadata": {
        "id": "IY9hn-CMUz9O"
      },
      "id": "IY9hn-CMUz9O",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "common_movie_star"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6EVFVBHaXN3Q",
        "outputId": "9a4e5721-ae4c-48b3-bd4f-c2a6c4dd852f"
      },
      "id": "6EVFVBHaXN3Q",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Nicolas Cage         43\n",
              "Robert De Niro       41\n",
              "Tom Hanks            41\n",
              "Denzel Washington    37\n",
              "Tom Cruise           34\n",
              "Name: star, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 195
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q3) most common release country "
      ],
      "metadata": {
        "id": "zKR9KeRAZ4l1"
      },
      "id": "zKR9KeRAZ4l1"
    },
    {
      "cell_type": "code",
      "source": [
        "data['released_country'].unique()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wp8VXV8RW5nc",
        "outputId": "43d4938a-ad6c-4f7f-96f4-ebf89a81fd4e"
      },
      "id": "Wp8VXV8RW5nc",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['United States', 'Australia', 'Japan', 'Ireland', 'Argentina',\n",
              "       'Soviet Union', 'United Kingdom', 'Sweden', 'France', 'Canada',\n",
              "       'Brazil', 'South Korea', 'West Germany', 'Italy', 'Denmark',\n",
              "       'Netherlands', 'Uruguay', 'Hong Kong', 'Taiwan', 'Yugoslavia',\n",
              "       'Spain', 'Finland', 'South Africa', 'Philippines', 'Portugal',\n",
              "       'Mexico', 'Germany', 'New Zealand', 'Iran', 'Greece', 'Singapore',\n",
              "       'Poland', 'India', 'Federal Republic of Yugoslavia', 'Iceland',\n",
              "       'Belgium', 'Israel', 'Hungary', 'China', 'Russia', 'Norway',\n",
              "       'Austria', 'Thailand', 'Puerto Rico', 'Turkey', 'Romania',\n",
              "       'Czech Republic', 'Latvia', 'Indonesia', 'Bahrain', 'Kazakhstan',\n",
              "       'Malaysia', 'Croatia', 'Bulgaria', 'Lebanon',\n",
              "       'United Arab Emirates', 'Ukraine', 'Bahamas', 'Kuwait', 'Vietnam',\n",
              "       'Cameroon'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 196
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "most_common_release_country =data['released_country'].value_counts().head()"
      ],
      "metadata": {
        "id": "-26EtuEwZU-R"
      },
      "id": "-26EtuEwZU-R",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "most_common_release_country.plot(kind ='bar', figsize= (9,9))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 627
        },
        "id": "OKbdH0GAXUrg",
        "outputId": "cc2b0e1a-b33e-4a3e-ff21-3cd0a17b9021"
      },
      "id": "OKbdH0GAXUrg",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877c99f850>"
            ]
          },
          "metadata": {},
          "execution_count": 198
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x648 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "show every country with budget mean and gross mean"
      ],
      "metadata": {
        "id": "Ls8XGQB4pAhG"
      },
      "id": "Ls8XGQB4pAhG"
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby('released_country')['budget','gross'].agg(np.mean)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 492
        },
        "id": "P0QOzs5hZnfo",
        "outputId": "9026ff8b-7ae6-4ae8-f2d3-dfcb6dc3eb68"
      },
      "id": "P0QOzs5hZnfo",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        budget         gross\n",
              "released_country                            \n",
              "Argentina         1.329231e+07  8.210161e+06\n",
              "Australia         1.575844e+07  4.678544e+06\n",
              "Austria           1.000000e+07  4.025990e+05\n",
              "Bahamas           1.200000e+07  1.456675e+06\n",
              "Bahrain           1.900000e+07  3.676533e+06\n",
              "...                        ...           ...\n",
              "United States     3.345258e+07  8.648115e+07\n",
              "Uruguay           2.050000e+07  3.438900e+05\n",
              "Vietnam           2.050000e+07  5.756185e+06\n",
              "West Germany      2.050000e+07  3.626271e+06\n",
              "Yugoslavia        2.050000e+07  2.020850e+07\n",
              "\n",
              "[61 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-209b90b1-f44b-4dcf-b342-cc0f31c57885\">\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>budget</th>\n",
              "      <th>gross</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>released_country</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Argentina</th>\n",
              "      <td>1.329231e+07</td>\n",
              "      <td>8.210161e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>1.575844e+07</td>\n",
              "      <td>4.678544e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Austria</th>\n",
              "      <td>1.000000e+07</td>\n",
              "      <td>4.025990e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahamas</th>\n",
              "      <td>1.200000e+07</td>\n",
              "      <td>1.456675e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Bahrain</th>\n",
              "      <td>1.900000e+07</td>\n",
              "      <td>3.676533e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>United States</th>\n",
              "      <td>3.345258e+07</td>\n",
              "      <td>8.648115e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Uruguay</th>\n",
              "      <td>2.050000e+07</td>\n",
              "      <td>3.438900e+05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Vietnam</th>\n",
              "      <td>2.050000e+07</td>\n",
              "      <td>5.756185e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>West Germany</th>\n",
              "      <td>2.050000e+07</td>\n",
              "      <td>3.626271e+06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Yugoslavia</th>\n",
              "      <td>2.050000e+07</td>\n",
              "      <td>2.020850e+07</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>61 rows × 2 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-209b90b1-f44b-4dcf-b342-cc0f31c57885')\"\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-209b90b1-f44b-4dcf-b342-cc0f31c57885 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-209b90b1-f44b-4dcf-b342-cc0f31c57885');\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": 199
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q4) genres with high score rate\n",
        "\n"
      ],
      "metadata": {
        "id": "TdG3gYnkpR2h"
      },
      "id": "TdG3gYnkpR2h"
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby('genre')['score'].mean().sort_values().plot(kind = 'bar', figsize = (12,12))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 774
        },
        "id": "HI2xEF65nu4z",
        "outputId": "f66d768f-e6e1-4c8b-b4c0-f962d6c78acd"
      },
      "id": "HI2xEF65nu4z",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877c926410>"
            ]
          },
          "metadata": {},
          "execution_count": 200
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "_I69VN2qn20p",
        "outputId": "325c173f-6330-43cd-ae1e-9bb4293933e9"
      },
      "id": "_I69VN2qn20p",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "   score      votes         director                   writer            star  \\\n",
              "0    8.4   927000.0  Stanley Kubrick             Stephen King  Jack Nicholson   \n",
              "1    5.8    65000.0   Randal Kleiser  Henry De Vere Stacpoole  Brooke Shields   \n",
              "2    8.7  1200000.0   Irvin Kershner           Leigh Brackett     Mark Hamill   \n",
              "3    7.7   221000.0     Jim Abrahams             Jim Abrahams     Robert Hays   \n",
              "4    7.3   108000.0     Harold Ramis       Brian Doyle-Murray     Chevy Chase   \n",
              "\n",
              "          country      budget        gross             company  runtime  \\\n",
              "0  United Kingdom  19000000.0   46998772.0        Warner Bros.    146.0   \n",
              "1   United States   4500000.0   58853106.0   Columbia Pictures    104.0   \n",
              "2   United States  18000000.0  538375067.0           Lucasfilm    124.0   \n",
              "3   United States   3500000.0   83453539.0  Paramount Pictures     88.0   \n",
              "4   United States   6000000.0   39846344.0      Orion Pictures     98.0   \n",
              "\n",
              "  released_date released_country  \n",
              "0    1980-06-13    United States  \n",
              "1    1980-07-02    United States  \n",
              "2    1980-06-20    United States  \n",
              "3    1980-07-02    United States  \n",
              "4    1980-07-25    United States  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0e97e7c4-d9cd-4513-8001-c39da5d29df5\">\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>name</th>\n",
              "      <th>rating</th>\n",
              "      <th>genre</th>\n",
              "      <th>year</th>\n",
              "      <th>score</th>\n",
              "      <th>votes</th>\n",
              "      <th>director</th>\n",
              "      <th>writer</th>\n",
              "      <th>star</th>\n",
              "      <th>country</th>\n",
              "      <th>budget</th>\n",
              "      <th>gross</th>\n",
              "      <th>company</th>\n",
              "      <th>runtime</th>\n",
              "      <th>released_date</th>\n",
              "      <th>released_country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Shining</td>\n",
              "      <td>R</td>\n",
              "      <td>Drama</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.4</td>\n",
              "      <td>927000.0</td>\n",
              "      <td>Stanley Kubrick</td>\n",
              "      <td>Stephen King</td>\n",
              "      <td>Jack Nicholson</td>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>19000000.0</td>\n",
              "      <td>46998772.0</td>\n",
              "      <td>Warner Bros.</td>\n",
              "      <td>146.0</td>\n",
              "      <td>1980-06-13</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The Blue Lagoon</td>\n",
              "      <td>R</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>1980</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
              "      <td>Henry De Vere Stacpoole</td>\n",
              "      <td>Brooke Shields</td>\n",
              "      <td>United States</td>\n",
              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
              "      <td>Mark Hamill</td>\n",
              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>1980-06-20</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
              "      <td>United States</td>\n",
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          },
          "metadata": {},
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q5) the most five years in Released movies with the highest gross"
      ],
      "metadata": {
        "id": "qm8I2kL-4OpY"
      },
      "id": "qm8I2kL-4OpY"
    },
    {
      "cell_type": "code",
      "source": [
        " Years_with_highest_gross = data.groupby('year')['gross'].sum().to_frame().sort_values('gross', ascending = False)"
      ],
      "metadata": {
        "id": "yv84iZzH41hQ"
      },
      "id": "yv84iZzH41hQ",
      "execution_count": null,
      "outputs": []
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    {
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        "Years_with_highest_gross.head(5)"
      ],
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      "id": "C2cMIjXU4-AO",
      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             gross\n",
              "year              \n",
              "2019  3.042033e+10\n",
              "2016  2.893884e+10\n",
              "2017  2.848525e+10\n",
              "2018  2.808529e+10\n",
              "2015  2.676622e+10"
            ],
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              "      <th>gross</th>\n",
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      "source": [
        "Years_with_highest_gross.plot(kind = 'bar', figsize = (11,11))"
      ],
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        "id": "RCVNbxg26pHm",
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      "execution_count": null,
      "outputs": [
        {
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          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877c85c390>"
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        {
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          "data": {
            "text/plain": [
              "<Figure size 792x792 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.groupby('year')['budget'].sum().plot(kind = 'line', figsize= (12,12))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 743
        },
        "id": "HP8GpWkM7yLk",
        "outputId": "0eba225a-9148-4b1f-84b6-c628c6a98117"
      },
      "id": "HP8GpWkM7yLk",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877c6d6f50>"
            ]
          },
          "metadata": {},
          "execution_count": 205
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "MYp8O-le6QFN",
        "outputId": "dcc31e0b-a2ad-405b-8416-5aa5349cd8c7"
      },
      "id": "MYp8O-le6QFN",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "   score      votes         director                   writer            star  \\\n",
              "0    8.4   927000.0  Stanley Kubrick             Stephen King  Jack Nicholson   \n",
              "1    5.8    65000.0   Randal Kleiser  Henry De Vere Stacpoole  Brooke Shields   \n",
              "2    8.7  1200000.0   Irvin Kershner           Leigh Brackett     Mark Hamill   \n",
              "3    7.7   221000.0     Jim Abrahams             Jim Abrahams     Robert Hays   \n",
              "4    7.3   108000.0     Harold Ramis       Brian Doyle-Murray     Chevy Chase   \n",
              "\n",
              "          country      budget        gross             company  runtime  \\\n",
              "0  United Kingdom  19000000.0   46998772.0        Warner Bros.    146.0   \n",
              "1   United States   4500000.0   58853106.0   Columbia Pictures    104.0   \n",
              "2   United States  18000000.0  538375067.0           Lucasfilm    124.0   \n",
              "3   United States   3500000.0   83453539.0  Paramount Pictures     88.0   \n",
              "4   United States   6000000.0   39846344.0      Orion Pictures     98.0   \n",
              "\n",
              "  released_date released_country  \n",
              "0    1980-06-13    United States  \n",
              "1    1980-07-02    United States  \n",
              "2    1980-06-20    United States  \n",
              "3    1980-07-02    United States  \n",
              "4    1980-07-25    United States  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b1bbf46b-9071-4db1-b340-cf74f5b16991\">\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>name</th>\n",
              "      <th>rating</th>\n",
              "      <th>genre</th>\n",
              "      <th>year</th>\n",
              "      <th>score</th>\n",
              "      <th>votes</th>\n",
              "      <th>director</th>\n",
              "      <th>writer</th>\n",
              "      <th>star</th>\n",
              "      <th>country</th>\n",
              "      <th>budget</th>\n",
              "      <th>gross</th>\n",
              "      <th>company</th>\n",
              "      <th>runtime</th>\n",
              "      <th>released_date</th>\n",
              "      <th>released_country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Shining</td>\n",
              "      <td>R</td>\n",
              "      <td>Drama</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.4</td>\n",
              "      <td>927000.0</td>\n",
              "      <td>Stanley Kubrick</td>\n",
              "      <td>Stephen King</td>\n",
              "      <td>Jack Nicholson</td>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>19000000.0</td>\n",
              "      <td>46998772.0</td>\n",
              "      <td>Warner Bros.</td>\n",
              "      <td>146.0</td>\n",
              "      <td>1980-06-13</td>\n",
              "      <td>United States</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The Blue Lagoon</td>\n",
              "      <td>R</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>1980</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
              "      <td>Henry De Vere Stacpoole</td>\n",
              "      <td>Brooke Shields</td>\n",
              "      <td>United States</td>\n",
              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
              "      <td>Mark Hamill</td>\n",
              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>1980-06-20</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
              "      <td>United States</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 206
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Q6) the most popular five movie star"
      ],
      "metadata": {
        "id": "3YGuzUNi7IVu"
      },
      "id": "3YGuzUNi7IVu"
    },
    {
      "cell_type": "code",
      "source": [
        "popular_movie_star = data['star'].value_counts().to_frame().head(5)"
      ],
      "metadata": {
        "id": "KVGQYUGQ7Q6M"
      },
      "id": "KVGQYUGQ7Q6M",
      "execution_count": null,
      "outputs": []
    },
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        "popular_movie_star"
      ],
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      "id": "GfoW7LfL691X",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   star\n",
              "Nicolas Cage         43\n",
              "Robert De Niro       41\n",
              "Tom Hanks            41\n",
              "Denzel Washington    37\n",
              "Tom Cruise           34"
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    {
      "cell_type": "markdown",
      "source": [
        "Q7) most released company for movies"
      ],
      "metadata": {
        "id": "RGoLAS2T_9AG"
      },
      "id": "RGoLAS2T_9AG"
    },
    {
      "cell_type": "code",
      "source": [
        "movies_company = data['company'].value_counts().to_frame().sort_values('company', ascending = False).head(10)"
      ],
      "metadata": {
        "id": "hfqdm8q9AF-U"
      },
      "id": "hfqdm8q9AF-U",
      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
      "source": [
        "movies_company"
      ],
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        "id": "v2eXEkuy853q",
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      "id": "v2eXEkuy853q",
      "execution_count": null,
      "outputs": [
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            "text/plain": [
              "                           company\n",
              "Universal Pictures             377\n",
              "Warner Bros.                   334\n",
              "Columbia Pictures              332\n",
              "Paramount Pictures             320\n",
              "Twentieth Century Fox          240\n",
              "New Line Cinema                174\n",
              "Touchstone Pictures            132\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ec86ec77-0651-429a-8d84-cad7ee16c243');\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": 210
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "movies_company.sort_values('company', ascending = True).plot(kind = 'barh', figsize = (12,12))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 718
        },
        "id": "APvZTQdSArKK",
        "outputId": "15be5ce0-1791-47dc-9c79-d7008fcbeb70"
      },
      "id": "APvZTQdSArKK",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f877c6d6310>"
            ]
          },
          "metadata": {},
          "execution_count": 211
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x864 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 337
        },
        "id": "u-4kkQPKAzQV",
        "outputId": "c30035ba-e554-4ed3-9dfe-f39a44c1ff46"
      },
      "id": "u-4kkQPKAzQV",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "   score      votes         director                   writer            star  \\\n",
              "0    8.4   927000.0  Stanley Kubrick             Stephen King  Jack Nicholson   \n",
              "1    5.8    65000.0   Randal Kleiser  Henry De Vere Stacpoole  Brooke Shields   \n",
              "2    8.7  1200000.0   Irvin Kershner           Leigh Brackett     Mark Hamill   \n",
              "3    7.7   221000.0     Jim Abrahams             Jim Abrahams     Robert Hays   \n",
              "4    7.3   108000.0     Harold Ramis       Brian Doyle-Murray     Chevy Chase   \n",
              "\n",
              "          country      budget        gross             company  runtime  \\\n",
              "0  United Kingdom  19000000.0   46998772.0        Warner Bros.    146.0   \n",
              "1   United States   4500000.0   58853106.0   Columbia Pictures    104.0   \n",
              "2   United States  18000000.0  538375067.0           Lucasfilm    124.0   \n",
              "3   United States   3500000.0   83453539.0  Paramount Pictures     88.0   \n",
              "4   United States   6000000.0   39846344.0      Orion Pictures     98.0   \n",
              "\n",
              "  released_date released_country  \n",
              "0    1980-06-13    United States  \n",
              "1    1980-07-02    United States  \n",
              "2    1980-06-20    United States  \n",
              "3    1980-07-02    United States  \n",
              "4    1980-07-25    United States  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-eb6d5f7e-037b-4d1b-a740-bb19756797f4\">\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>name</th>\n",
              "      <th>rating</th>\n",
              "      <th>genre</th>\n",
              "      <th>year</th>\n",
              "      <th>score</th>\n",
              "      <th>votes</th>\n",
              "      <th>director</th>\n",
              "      <th>writer</th>\n",
              "      <th>star</th>\n",
              "      <th>country</th>\n",
              "      <th>budget</th>\n",
              "      <th>gross</th>\n",
              "      <th>company</th>\n",
              "      <th>runtime</th>\n",
              "      <th>released_date</th>\n",
              "      <th>released_country</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>The Shining</td>\n",
              "      <td>R</td>\n",
              "      <td>Drama</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.4</td>\n",
              "      <td>927000.0</td>\n",
              "      <td>Stanley Kubrick</td>\n",
              "      <td>Stephen King</td>\n",
              "      <td>Jack Nicholson</td>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>19000000.0</td>\n",
              "      <td>46998772.0</td>\n",
              "      <td>Warner Bros.</td>\n",
              "      <td>146.0</td>\n",
              "      <td>1980-06-13</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
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              "      <td>R</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>1980</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
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              "      <td>Brooke Shields</td>\n",
              "      <td>United States</td>\n",
              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
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              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
              "      <td>Mark Hamill</td>\n",
              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>1980-06-20</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
              "      <td>United States</td>\n",
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    {
      "cell_type": "markdown",
      "source": [
        "Q8) the most popular writers"
      ],
      "metadata": {
        "id": "oPxhUNcEBYZS"
      },
      "id": "oPxhUNcEBYZS"
    },
    {
      "cell_type": "code",
      "source": [
        "popular_writers =data['writer'].value_counts().to_frame().sort_values('writer', ascending = False).head()"
      ],
      "metadata": {
        "id": "2bxrMOpgBVO_"
      },
      "id": "2bxrMOpgBVO_",
      "execution_count": null,
      "outputs": []
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      "cell_type": "code",
      "source": [
        "popular_writers.sort_values('writer', ascending = False)"
      ],
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        "colab": {
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          "height": 206
        },
        "id": "ctFDcUNfBpey",
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      "id": "ctFDcUNfBpey",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     writer\n",
              "Woody Allen              37\n",
              "Stephen King             31\n",
              "Luc Besson               26\n",
              "John Hughes              25\n",
              "William Shakespeare      15"
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    {
      "cell_type": "markdown",
      "source": [
        "Q9) best runtime for movie"
      ],
      "metadata": {
        "id": "9XteclGDGhP8"
      },
      "id": "9XteclGDGhP8"
    },
    {
      "cell_type": "code",
      "source": [
        "round(data['runtime'].mean(),0)"
      ],
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        "id": "mmANINvHGpE-",
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "107.0"
            ]
          },
          "metadata": {},
          "execution_count": 215
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "round(data['runtime'].median(),0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Rue3fZ-QGpQS",
        "outputId": "de972819-c6ef-423d-a69e-def0a53fbc55"
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      "id": "Rue3fZ-QGpQS",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "104.0"
            ]
          },
          "metadata": {},
          "execution_count": 216
        }
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    {
      "cell_type": "code",
      "source": [
        "data['runtime'].describe()"
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          "base_uri": "https://localhost:8080/"
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      "id": "27sbrWucHdZ9",
      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    7646.000000\n",
              "mean      107.293225\n",
              "std        18.571885\n",
              "min        63.000000\n",
              "25%        95.000000\n",
              "50%       104.000000\n",
              "75%       116.000000\n",
              "max       366.000000\n",
              "Name: runtime, dtype: float64"
            ]
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          "metadata": {},
          "execution_count": 217
        }
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    {
      "cell_type": "markdown",
      "source": [
        "# so after all of that questions we can assume that the characteristics of profitable movie could be:\n",
        "\n",
        "### \n",
        "\n",
        "1.   movie to be released in United States\n",
        "2.   movie to be Musical or Comedy will be more attractive to people\n",
        "3.   the best release company for movies are Universal Pictures, Warner Bros, Columbia Pictures, or Paramount Pictures \n",
        "4.   Woody Allen is the best writer for you movie\n",
        "5.   Try have a rate = R\n",
        "6.   released year between 2015 to 2019\n",
        "6.   the best runtime to be between 104 to 107\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "kTomLdUsCNi7"
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      "id": "kTomLdUsCNi7"
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    {
      "cell_type": "code",
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      "id": "8FSEEnUqB-jP",
      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             name rating      genre  year  \\\n",
              "0                                     The Shining      R      Drama  1980   \n",
              "1                                 The Blue Lagoon      R  Adventure  1980   \n",
              "2  Star Wars: Episode V - The Empire Strikes Back     PG     Action  1980   \n",
              "3                                       Airplane!     PG     Comedy  1980   \n",
              "4                                      Caddyshack      R     Comedy  1980   \n",
              "\n",
              "   score      votes         director                   writer            star  \\\n",
              "0    8.4   927000.0  Stanley Kubrick             Stephen King  Jack Nicholson   \n",
              "1    5.8    65000.0   Randal Kleiser  Henry De Vere Stacpoole  Brooke Shields   \n",
              "2    8.7  1200000.0   Irvin Kershner           Leigh Brackett     Mark Hamill   \n",
              "3    7.7   221000.0     Jim Abrahams             Jim Abrahams     Robert Hays   \n",
              "4    7.3   108000.0     Harold Ramis       Brian Doyle-Murray     Chevy Chase   \n",
              "\n",
              "          country      budget        gross             company  runtime  \\\n",
              "0  United Kingdom  19000000.0   46998772.0        Warner Bros.    146.0   \n",
              "1   United States   4500000.0   58853106.0   Columbia Pictures    104.0   \n",
              "2   United States  18000000.0  538375067.0           Lucasfilm    124.0   \n",
              "3   United States   3500000.0   83453539.0  Paramount Pictures     88.0   \n",
              "4   United States   6000000.0   39846344.0      Orion Pictures     98.0   \n",
              "\n",
              "  released_date released_country  \n",
              "0    1980-06-13    United States  \n",
              "1    1980-07-02    United States  \n",
              "2    1980-06-20    United States  \n",
              "3    1980-07-02    United States  \n",
              "4    1980-07-25    United States  "
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              "      <td>Stanley Kubrick</td>\n",
              "      <td>Stephen King</td>\n",
              "      <td>Jack Nicholson</td>\n",
              "      <td>United Kingdom</td>\n",
              "      <td>19000000.0</td>\n",
              "      <td>46998772.0</td>\n",
              "      <td>Warner Bros.</td>\n",
              "      <td>146.0</td>\n",
              "      <td>1980-06-13</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>The Blue Lagoon</td>\n",
              "      <td>R</td>\n",
              "      <td>Adventure</td>\n",
              "      <td>1980</td>\n",
              "      <td>5.8</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Randal Kleiser</td>\n",
              "      <td>Henry De Vere Stacpoole</td>\n",
              "      <td>Brooke Shields</td>\n",
              "      <td>United States</td>\n",
              "      <td>4500000.0</td>\n",
              "      <td>58853106.0</td>\n",
              "      <td>Columbia Pictures</td>\n",
              "      <td>104.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Star Wars: Episode V - The Empire Strikes Back</td>\n",
              "      <td>PG</td>\n",
              "      <td>Action</td>\n",
              "      <td>1980</td>\n",
              "      <td>8.7</td>\n",
              "      <td>1200000.0</td>\n",
              "      <td>Irvin Kershner</td>\n",
              "      <td>Leigh Brackett</td>\n",
              "      <td>Mark Hamill</td>\n",
              "      <td>United States</td>\n",
              "      <td>18000000.0</td>\n",
              "      <td>538375067.0</td>\n",
              "      <td>Lucasfilm</td>\n",
              "      <td>124.0</td>\n",
              "      <td>1980-06-20</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Airplane!</td>\n",
              "      <td>PG</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.7</td>\n",
              "      <td>221000.0</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Jim Abrahams</td>\n",
              "      <td>Robert Hays</td>\n",
              "      <td>United States</td>\n",
              "      <td>3500000.0</td>\n",
              "      <td>83453539.0</td>\n",
              "      <td>Paramount Pictures</td>\n",
              "      <td>88.0</td>\n",
              "      <td>1980-07-02</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Caddyshack</td>\n",
              "      <td>R</td>\n",
              "      <td>Comedy</td>\n",
              "      <td>1980</td>\n",
              "      <td>7.3</td>\n",
              "      <td>108000.0</td>\n",
              "      <td>Harold Ramis</td>\n",
              "      <td>Brian Doyle-Murray</td>\n",
              "      <td>Chevy Chase</td>\n",
              "      <td>United States</td>\n",
              "      <td>6000000.0</td>\n",
              "      <td>39846344.0</td>\n",
              "      <td>Orion Pictures</td>\n",
              "      <td>98.0</td>\n",
              "      <td>1980-07-25</td>\n",
              "      <td>United States</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b9b6e2fb-8fab-4d04-bc3c-4768ed83efe0')\"\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",
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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",
              "    }\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",
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              "    .colab-df-convert:hover {\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b9b6e2fb-8fab-4d04-bc3c-4768ed83efe0');\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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 218
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Now let's create our tables so we can use it to create dashboard using power bi"
      ],
      "metadata": {
        "id": "8n5ivJ4GRzdF"
      },
      "id": "8n5ivJ4GRzdF"
    },
    {
      "cell_type": "code",
      "source": [
        "gross_budget = data.loc[:,['released_date','budget', 'gross']]"
      ],
      "metadata": {
        "id": "F93OUNwQU52F"
      },
      "id": "F93OUNwQU52F",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "gross_budget = gross_budget.to_csv('gross_budget.csv')"
      ],
      "metadata": {
        "id": "Hmob9Pn-GRT0"
      },
      "id": "Hmob9Pn-GRT0",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "movies_rating = data.loc[:,['name','released_date','rating','votes','score']]"
      ],
      "metadata": {
        "id": "Idz0IeZARxYJ"
      },
      "id": "Idz0IeZARxYJ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "movies_rating = movies_rating.to_csv('movies_rating.csv')"
      ],
      "metadata": {
        "id": "Fl01X0idRxjo"
      },
      "id": "Fl01X0idRxjo",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "movies_details = data.loc[:,['name','director', 'writer','star','company','genre','released_date','released_country','runtime']]"
      ],
      "metadata": {
        "id": "0yNCaZUOXQ32"
      },
      "id": "0yNCaZUOXQ32",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "movies_details = movies_details.to_csv('movies_details.csv')"
      ],
      "metadata": {
        "id": "_Ka2uwIPYhfT"
      },
      "id": "_Ka2uwIPYhfT",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fact_gross_budget = data.groupby('year')['gross','budget'].sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BY7FHgMx320a",
        "outputId": "2ae78cad-19a6-4c44-f96d-9d9598e83db7"
      },
      "id": "BY7FHgMx320a",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fact_gross_budget = fact_gross_budget.to_csv('fact_gross_budget.csv')"
      ],
      "metadata": {
        "id": "HAWRNp6K4CA5"
      },
      "id": "HAWRNp6K4CA5",
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
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      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8.5"
    },
    "colab": {
      "name": "Movies Notebook.ipynb",
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}