Movie_Based_Recommendation_Project.ipynb

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                  "Recommended Movie Names-  \n",
                  "1:Edge, The (1997)\n",
                  "William Shakespeare's Romeo and Juliet (1996)\n",
                  "Star Trek: The Wrath of Khan (1982)\n",
                  "Dumbo (1941)\n"
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        "<a href=\"https://colab.research.google.com/github/SACHINSIROHI47/DataScience_with_Python_Programming_Project/blob/main/Movie_Based_Recommendation_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "# **Recommendation Project**\n",
        "\n",
        "These recommendations suggest strategies to address issues identified through a study. They are based on research findings and other relevant information."
      ],
      "metadata": {
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)"
      ],
      "metadata": {
        "id": "n7GgG9MFzhWR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#import Library\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "metadata": {
        "id": "ZU09iUwgzlC9"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Load data\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "aBzoA7rL3GcK",
        "outputId": "e706f6ca-4fcd-4858-fd2a-478368fdc294"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-00bc516a-a929-4cd6-ac45-7ddd2e7799ba\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-00bc516a-a929-4cd6-ac45-7ddd2e7799ba\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving dataset.csv to dataset.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colName=['user_id','item_id','rating','timestamp']\n",
        "df=pd.read_csv('dataset.csv',sep='\\t',names=colName)\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "TeiZPPZj3os5",
        "outputId": "05a1c11a-0192-4903-a3c8-d3ecea851601"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   user_id  item_id  rating  timestamp\n",
              "0        0       50       5  881250949\n",
              "1        0      172       5  881250949\n",
              "2        0      133       1  881250949\n",
              "3      196      242       3  881250949\n",
              "4      186      302       3  891717742"
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              "        const element = document.querySelector('#df-638b0ecd-9375-48cd-8b08-17a2302730a1');\n",
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              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "        element.innerHTML = '';\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Load movies data\n",
        "from google.colab import files\n",
        "uploaded = files.upload()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 73
        },
        "id": "mQqyBn5Z5Xv1",
        "outputId": "6b818560-74b5-4b78-b26c-d98da7d5286d"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-90a13fe7-c4c9-4199-9a4e-95bebd3ac8e6\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-90a13fe7-c4c9-4199-9a4e-95bebd3ac8e6\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving movieIdTitles.csv to movieIdTitles.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Load Movie Titles\n",
        "movie_titles=pd.read_csv('movieIdTitles.csv')\n",
        "movie_titles.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "ZDevMHn-5jus",
        "outputId": "21acd293-46a6-407e-ad92-58c7ccaaf8c9"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   item_id              title\n",
              "0        1   Toy Story (1995)\n",
              "1        2   GoldenEye (1995)\n",
              "2        3  Four Rooms (1995)\n",
              "3        4  Get Shorty (1995)\n",
              "4        5     Copycat (1995)"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d909a4c0-16eb-4c76-b354-18b93a9a8c9c\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>item_id</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>GoldenEye (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Four Rooms (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Get Shorty (1995)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Copycat (1995)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d909a4c0-16eb-4c76-b354-18b93a9a8c9c')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-d909a4c0-16eb-4c76-b354-18b93a9a8c9c 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-d909a4c0-16eb-4c76-b354-18b93a9a8c9c');\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",
              "\n",
              "\n",
              "<div id=\"df-e4218b5b-3dd5-4c51-945b-7c202f0e898e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e4218b5b-3dd5-4c51-945b-7c202f0e898e')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e4218b5b-3dd5-4c51-945b-7c202f0e898e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "movie_titles",
              "summary": "{\n  \"name\": \"movie_titles\",\n  \"rows\": 1682,\n  \"fields\": [\n    {\n      \"column\": \"item_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 485,\n        \"min\": 1,\n        \"max\": 1682,\n        \"num_unique_values\": 1682,\n        \"samples\": [\n          1394,\n          744,\n          1606\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Madame Butterfly (1995)\",\n          \"Wrong Trousers, The (1993)\",\n          \"Breaking the Waves (1996)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Merge the dataset\n",
        "df=pd.merge(df,movie_titles,on='item_id')\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "u1xMy4Ms6bym",
        "outputId": "e98fff50-5349-413a-cbc0-56f98442ab51"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   user_id  item_id  rating  timestamp             title\n",
              "0        0       50       5  881250949  Star Wars (1977)\n",
              "1      290       50       5  880473582  Star Wars (1977)\n",
              "2       79       50       4  891271545  Star Wars (1977)\n",
              "3        2       50       5  888552084  Star Wars (1977)\n",
              "4        8       50       5  879362124  Star Wars (1977)"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5f0a3193-9fac-436d-af15-15e10d366059\" 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",
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              "    <tr style=\"text-align: right;\">\n",
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              "      <td>880473582</td>\n",
              "      <td>Star Wars (1977)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>79</td>\n",
              "      <td>50</td>\n",
              "      <td>4</td>\n",
              "      <td>891271545</td>\n",
              "      <td>Star Wars (1977)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>50</td>\n",
              "      <td>5</td>\n",
              "      <td>888552084</td>\n",
              "      <td>Star Wars (1977)</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>879362124</td>\n",
              "      <td>Star Wars (1977)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5f0a3193-9fac-436d-af15-15e10d366059')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-5f0a3193-9fac-436d-af15-15e10d366059 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-5f0a3193-9fac-436d-af15-15e10d366059');\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",
              "\n",
              "\n",
              "<div id=\"df-8a8ecae4-e6c5-4901-becd-8561acb71383\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8a8ecae4-e6c5-4901-becd-8561acb71383')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
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              "\n",
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              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8a8ecae4-e6c5-4901-becd-8561acb71383 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#EDA (Exploatory Data Analysis)\n",
        "#groupby title for rating\n",
        "ratings=pd.DataFrame(df.groupby('title')['rating'].mean().sort_values(ascending=False))\n",
        "ratings.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "MxuU0liv6A4o",
        "outputId": "26cacfea-63e8-4d0c-bdd3-da0e97444a96"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                            rating\n",
              "title                                             \n",
              "They Made Me a Criminal (1939)                 5.0\n",
              "Marlene Dietrich: Shadow and Light (1996)      5.0\n",
              "Saint of Fort Washington, The (1993)           5.0\n",
              "Someone Else's America (1995)                  5.0\n",
              "Star Kid (1997)                                5.0"
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              "\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "    80% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "ratings",
              "summary": "{\n  \"name\": \"ratings\",\n  \"rows\": 1664,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Cowboy Way, The (1994)\",\n          \"I Don't Want to Talk About It (De eso no se habla) (1993)\",\n          \"In the Name of the Father (1993)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7804112593703867,\n        \"min\": 1.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          2.803921568627451,\n          3.4184782608695654,\n          3.227722772277228\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#groupby and count the rating\n",
        "df.groupby('title')['rating'].count().sort_values(ascending=False).head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "id": "VbjwO-4r70Mh",
        "outputId": "859e6d2b-588d-412f-b609-c5c2717f6515"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title\n",
              "Star Wars (1977)             584\n",
              "Contact (1997)               509\n",
              "Fargo (1996)                 508\n",
              "Return of the Jedi (1983)    507\n",
              "Liar Liar (1997)             485\n",
              "Name: rating, dtype: int64"
            ],
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              "</div><br><label><b>dtype:</b> int64</label>"
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "#find mean for rating\n",
        "ratings=pd.DataFrame(df.groupby('title')['rating'].mean())\n",
        "ratings.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
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        "id": "7rP5I-lm9SCy",
        "outputId": "a6ba8f61-b111-47ee-bced-b927daa08619"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             rating\n",
              "title                              \n",
              "'Til There Was You (1997)  2.333333\n",
              "1-900 (1994)               2.600000\n",
              "101 Dalmatians (1996)      2.908257\n",
              "12 Angry Men (1957)        4.344000\n",
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              "      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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-35974b40-cb87-454c-9c77-fe5d055d2c38 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-35974b40-cb87-454c-9c77-fe5d055d2c38');\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",
              "\n",
              "\n",
              "<div id=\"df-96cb33c7-4489-4d44-9663-7e0361b38048\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-96cb33c7-4489-4d44-9663-7e0361b38048')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-96cb33c7-4489-4d44-9663-7e0361b38048 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "ratings",
              "summary": "{\n  \"name\": \"ratings\",\n  \"rows\": 1664,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Tainted (1998)\",\n          \"Big Bully (1996)\",\n          \"Boys, Les (1997)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7804112593703867,\n        \"min\": 1.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          3.143835616438356,\n          2.125,\n          4.23121387283237\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ratings['numOfRatings'] = pd.DataFrame(df.groupby('title')['rating'].count())\n",
        "ratings.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "p2_qr2cXpZ40",
        "outputId": "6403dac9-af2a-45ec-ffee-23d09cd65f6b"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             rating  numOfRatings\n",
              "title                                            \n",
              "'Til There Was You (1997)  2.333333             9\n",
              "1-900 (1994)               2.600000             5\n",
              "101 Dalmatians (1996)      2.908257           109\n",
              "12 Angry Men (1957)        4.344000           125\n",
              "187 (1997)                 3.024390            41"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c4d6a1e7-9fd9-4dc1-9375-fe3e9282b36a\" class=\"colab-df-container\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "      <th>rating</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>'Til There Was You (1997)</th>\n",
              "      <td>2.333333</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1-900 (1994)</th>\n",
              "      <td>2.600000</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <td>2.908257</td>\n",
              "      <td>109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <td>4.344000</td>\n",
              "      <td>125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187 (1997)</th>\n",
              "      <td>3.024390</td>\n",
              "      <td>41</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-c4d6a1e7-9fd9-4dc1-9375-fe3e9282b36a 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-c4d6a1e7-9fd9-4dc1-9375-fe3e9282b36a');\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",
              "\n",
              "\n",
              "<div id=\"df-8e61918f-c661-4f10-a65e-d93fca75d188\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8e61918f-c661-4f10-a65e-d93fca75d188')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-8e61918f-c661-4f10-a65e-d93fca75d188 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "ratings",
              "summary": "{\n  \"name\": \"ratings\",\n  \"rows\": 1664,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Tainted (1998)\",\n          \"Big Bully (1996)\",\n          \"Boys, Les (1997)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7804112593703867,\n        \"min\": 1.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          3.143835616438356,\n          2.125,\n          4.23121387283237\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"numOfRatings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 80,\n        \"min\": 1,\n        \"max\": 584,\n        \"num_unique_values\": 273,\n        \"samples\": [\n          32,\n          24,\n          86\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (10,4))\n",
        "ratings['numOfRatings'].hist(bins = 70)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "SSGCjmubp57_",
        "outputId": "6337fb52-559d-4953-cb73-83c32da596e3"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x400 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize = (10,4))\n",
        "ratings['rating'].hist(bins = 70)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "g-TRrKl8qD-0",
        "outputId": "2cc6ed08-184a-455d-caa0-ded01c582bd8"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x400 with 1 Axes>"
            ],
            "image/png": 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5Wrt2rXJycrRw4cJolwMAAAAAkmwIP08//bTWrl2r733vezp//rxycnL03e9+Vw8//HBwzAMPPKD29natWLFCra2tuv3227Vr1y6lpaVFuxwAAAAAkGRD+BkxYoSqqqpUVVXV6xiHw6F169Zp3bp10b57AAAAAOhR1L/zAwAAAADxiPADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIQ2NdQLKYXLFb3k5Hn2PeWz9/kKoBAAAA0BUrPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABghKGxLgAAAMAE161+LeSya4iljdOkyRW75e10BLe/t37+YJcGGIOVHwAAAABGIPwAAAAAMAIfewMA4K90/WhSb/hoEgAkHlZ+AAAAABiB8AMAAADACLaEn//93//V17/+dY0ePVrDhg3TTTfdpMOHDwevtyxLDz/8sLKzszVs2DAVFRXp9OnTdpQCAAAAAJJsCD8fffSRZsyYIafTqd/+9rf67//+b/3rv/6rrr766uCYjRs3avPmzaqpqdGhQ4c0fPhwFRcX6/Lly9EuBwAAAAAk2XDCgw0bNig3N1dbt24NbsvLywv+3bIsVVVV6aGHHtKCBQskSS+88IIyMzO1Y8cOLVmyJNolAQAAAED0w8+vfvUrFRcX66tf/ar279+vT33qU/re976n++67T5J05swZNTc3q6ioKHibkSNHqqCgQAcPHuwx/Hi9Xnm93uBlj8cjSfL5fPL5fNE+hIgE7t+VYoU9FuEL9Ize2YP+2o8e28uO52DXkP73Fcn+EhnzN7q6zq3AvO06f+l3dDB/7RVP/Y2kBodlWeE9y4cpLS1NklReXq6vfvWramho0KpVq1RTU6OSkhIdOHBAM2bM0Llz55SdnR283eLFi+VwOPTyyy9322dFRYUqKyu7ba+trVV6eno0ywcAAACQQDo6OrR06VK1tbXJ7Xb3OTbq4Sc1NVVTp07VgQMHgtv+8R//UQ0NDTp48OCAwk9PKz+5ubn605/+1O8B2s3n86murk5rD6fI63f0OfZERfEgVZU8Av2dM2eOnE5nrMtJOvTXfvTYXnY8B0+u2B3WOBOe05m/0dV1brlSLD061d9t/powtwYD89de8dRfj8eja665JqzwE/WPvWVnZ+uzn/1syLaJEyfq3//93yVJWVlZkqSWlpaQ8NPS0qL8/Pwe9+lyueRyubptdzqdMW92gNfvkLez7/9446XWRBRPj3Uyor/2o8f2iuZzcH/7iXR/8a6vH3V1DbG0cZr0ucf3qunxLw5iVcmpt7nVdf4my9yKFzz/2ise+hvJ/Uf9bG8zZsxQU1NTyLY//OEPuvbaayX95eQHWVlZ2rNnT/B6j8ejQ4cOqbCwMNrlAAAAAIAkG1Z+7r//fk2fPl3//M//rMWLF+vtt9/Wc889p+eee06S5HA4VFZWpscee0w33HCD8vLytHbtWuXk5GjhwoXRLgcAAAAAJNkQfm677TZt375da9as0bp165SXl6eqqiotW7YsOOaBBx5Qe3u7VqxYodbWVt1+++3atWtX8GQJAAAAABBtUQ8/kvTFL35RX/xi758NdjgcWrdundatW2fH3QMAAABAN7aEHwAAEJm+Tjzw195bP9/mSgAgeUX9hAcAAAAAEI8IPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADACP3IKAEASCvdHUwHAJKz8AAAAADACKz+AQbq+E+waYmnjNGlyxW55Ox3B7e+tnz/YpQEwTLgrUzwfAYgmVn4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIzAqa4BAEDU8OOqAOIZKz8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEbgVNcAAAxAuKd0fm/9fJsrQaR47ABzsfIDAAAAwAis/ACADQLvLLuGWNo4TZpcsVveTke3cbF6Z5l3vgcPP/o5OOgzgHCw8gMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBE44QEAJBG+9A0AQO9Y+QEAAABgBFZ+AABAv1hVBJAMbF/5Wb9+vRwOh8rKyoLbLl++rNLSUo0ePVpXXXWVFi1apJaWFrtLAQAAAGAwW8NPQ0ODnn32WU2ZMiVk+/33369f//rXevXVV7V//36dO3dOX/nKV+wsBQAAAIDhbAs/ly5d0rJly/Rv//Zvuvrqq4Pb29ra9NOf/lSbNm3SnXfeqVtvvVVbt27VgQMH9NZbb9lVDgAAAADD2fadn9LSUs2fP19FRUV67LHHgtsbGxvl8/lUVFQU3DZhwgSNGzdOBw8e1Oc///lu+/J6vfJ6vcHLHo9HkuTz+eTz+ew6hLAE7t+VYoU9FuEL9IzeRYdrSOg8DczbrvOXfl+5QK9763FAtHvd9TG+UvE+F+x4Do52D6NtMI+jv/k7GGL5uNn975PnYHvxGsJe8dTfSGpwWJYV9WeLl156SY8//rgaGhqUlpammTNnKj8/X1VVVaqtrdW9994bEmYkadq0aZo1a5Y2bNjQbX8VFRWqrKzstr22tlbp6enRLh8AAABAgujo6NDSpUvV1tYmt9vd59ior/ycPXtWq1atUl1dndLS0qKyzzVr1qi8vDx42ePxKDc3V3Pnzu33AO3m8/lUV1entYdT5PU7+hx7oqJ4kKpKHoH+zpkzR06nM9blJLzJFbtDLrtSLD061d9t/jJXr1yg1731OCDave76GF+peJ8LkTwHJ4twH5NozIX+5u9gGMzjHeh9h4vn4MHFawh7xVN/A58KC0fUw09jY6POnz+vW265Jbits7NT9fX12rJli3bv3q2PP/5Yra2tGjVqVHBMS0uLsrKyetyny+WSy+Xqtt3pdMa82QFev0Pezr7/Y4iXWhNRPD3Wiay3Odp1/tLrK9e11709R0S71/09D0UqUeZCOM/BySLcxySa/Yhlf2NxvJHed7h4Do4NXkPYKx76G8n9Rz38zJ49W8ePHw/Zdu+992rChAl68MEHlZubK6fTqT179mjRokWSpKamJn3wwQcqLCyMdjkAAAAAIMmG8DNixAhNnjw5ZNvw4cM1evTo4Pbly5ervLxcGRkZcrvd+v73v6/CwsIeT3YAAAAAANFg29ne+vLUU08pJSVFixYtktfrVXFxsX784x/HohQAQB+uW/1aWOPeWz/f5koAALhygxJ+9u3bF3I5LS1N1dXVqq6uHoy7BwAAAAD7fuQUAAAAAOIJ4QcAAACAEWLynR8AQHLhu0GwS7hzCwDCwcoPAAAAACOw8gMAAHAFWJ0CEgcrPwAAAACMQPgBAAAAYAQ+9gYA4gv7ALrj42xA8mHlBwAAAIARCD8AAAAAjED4AQAAAGAEvvMDABg0kXyHgu9X9YzvoQDAwLHyAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMMLQWBcAAOjfdatfi3UJAOJMuM8L762fb3MlQOJg5QcAAACAEVj5ARBXeCcTAADYhZUfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMwAkPAAAA4gintgfsw8oPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGiHr4eeKJJ3TbbbdpxIgRGjNmjBYuXKimpqaQMZcvX1ZpaalGjx6tq666SosWLVJLS0u0SwEAAACAoKiHn/3796u0tFRvvfWW6urq5PP5NHfuXLW3twfH3H///fr1r3+tV199Vfv379e5c+f0la98JdqlAAAAAEBQ1E91vWvXrpDL27Zt05gxY9TY2Ki/+7u/U1tbm37605+qtrZWd955pyRp69atmjhxot566y19/vOfj3ZJABC3OKUtAACDx/bf+Wlra5MkZWRkSJIaGxvl8/lUVFQUHDNhwgSNGzdOBw8e7DH8eL1eeb3e4GWPxyNJ8vl88vl8dpbfr8D9u1KssMcifIGe0bvocA0JnaeBedt1/say311r7E20a4z2/Qb211uP0b9weh3JczAix/y112D119T/Q3kNYa946m8kNTgsy7LtX5zf79eXvvQltba26o033pAk1dbW6t577w0JM5I0bdo0zZo1Sxs2bOi2n4qKClVWVnbbXltbq/T0dHuKBwAAABD3Ojo6tHTpUrW1tcntdvc51taVn9LSUp04cSIYfAZqzZo1Ki8vD172eDzKzc3V3Llz+z1Au/l8PtXV1Wnt4RR5/Y4+x56oKB6kqpJHoL9z5syR0+mMdTkJb3LF7pDLrhRLj071d5u/sZyrXWvsTbRrDPd+I9Vbj9G/cB7jSJ6DETnmr70Gq7+mvv7gNYS94qm/gU+FhcO28LNy5Urt3LlT9fX1Gjt2bHB7VlaWPv74Y7W2tmrUqFHB7S0tLcrKyupxXy6XSy6Xq9t2p9MZ82YHeP0OeTv7fuKKl1oTUTw91omstznadf7a0evwv9sS3guAaNfY37/fK95/GM8RCBXJY0x/7UV/7WV3f03//5PXEPaKh/5Gcv9RP9ubZVlauXKltm/frr179yovLy/k+ltvvVVOp1N79uwJbmtqatIHH3ygwsLCaJcDAAAAAJJsWPkpLS1VbW2tfvnLX2rEiBFqbm6WJI0cOVLDhg3TyJEjtXz5cpWXlysjI0Nut1vf//73VVhYyJneAAAAANgm6uHnmWeekSTNnDkzZPvWrVv1rW99S5L01FNPKSUlRYsWLZLX61VxcbF+/OMfR7sUAAAAAAiKevgJ5+RxaWlpqq6uVnV1dbTvHgAAAAB6ZPvv/ABALPEjogAAICDqJzwAAAAAgHhE+AEAAABgBMIPAAAAACMQfgAAAAAYgRMeAEhInMgAAKIr3OfV99bPt7kSwD6s/AAAAAAwAis/AAAASYyVcuD/Y+UHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjcMIDAEBcCudL2q4hljZOG4RiAABJgZUfAAAAAEZg5Qdxobd3eAPv6k6u2C1vp4MfVgMAIMb4MVQkMlZ+AAAAABiBlR8AAAAAQcn8nUtWfgAAAAAYgZUfIAb4vDQAAMDgY+UHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjcMIDGC3eTzwQ7/VJ4dcIAAAQa6z8AAAAADACKz9AEmD1BQAAoH+s/AAAAAAwAuEHAAAAgBH42BsAAACiLton7Yn0I96uIZY2TpMmV+yWt9Mx4PtFcmHlBwAAAIARWPlBiEQ4tXI4on0CgGTpCwAAgMlY+QEAAABgBFZ+gChKllNOJ8txAAAA/DVWfgAAAAAYgfADAAAAwAh87M0QfIwJAADEI16jYDDFdOWnurpa1113ndLS0lRQUKC33347luUAAAAASGIxW/l5+eWXVV5erpqaGhUUFKiqqkrFxcVqamrSmDFjYlVWXIjkHZB4P7Uy7+YAAIBExs9dJJeYhZ9Nmzbpvvvu07333itJqqmp0Wuvvabnn39eq1evDhnr9Xrl9XqDl9va2iRJFy5ckM/nG7yie+Dz+dTR0aGhvhR1+rv/evBf+/Of/xzWPod+0h72/duxz3i636F+Sx0d/mB/Y3W8yaprfxF99Nhe9Nde9Nde9Nde/fU32q8pwt1fIgjnmAP9/fOf/yyn0zkIVfXu4sWLkiTLsvod67DCGRVlH3/8sdLT0/WLX/xCCxcuDG4vKSlRa2urfvnLX4aMr6ioUGVl5SBXCQAAACBRnD17VmPHju1zTExWfv70pz+ps7NTmZmZIdszMzP1P//zP93Gr1mzRuXl5cHLfr9fFy5c0OjRo+VwxPadEo/Ho9zcXJ09e1ZutzumtSQj+msv+ms/emwv+msv+msv+msv+muveOqvZVm6ePGicnJy+h2bEGd7c7lccrlcIdtGjRoVm2J64Xa7Y/7AJzP6ay/6az96bC/6ay/6ay/6ay/6a6946e/IkSPDGheTs71dc801GjJkiFpaWkK2t7S0KCsrKxYlAQAAAEhyMQk/qampuvXWW7Vnz57gNr/frz179qiwsDAWJQEAAABIcjH72Ft5eblKSko0depUTZs2TVVVVWpvbw+e/S1RuFwuPfLII90+lofooL/2or/2o8f2or/2or/2or/2or/2StT+xuRsbwFbtmzRv/zLv6i5uVn5+fnavHmzCgoKYlUOAAAAgCQW0/ADAAAAAIMlJt/5AQAAAIDBRvgBAAAAYATCDwAAAAAjEH4AAAAAGIHw04/6+nrdfffdysnJkcPh0I4dO/q9zb59+3TLLbfI5XLpM5/5jLZt22Z7nYkq0v7u27dPDoej25/m5ubBKTjBPPHEE7rttts0YsQIjRkzRgsXLlRTU1O/t3v11Vc1YcIEpaWl6aabbtJvfvObQag28Qykv9u2bes2f9PS0gap4sTyzDPPaMqUKcFfDy8sLNRvf/vbPm/D3A1fpP1l7g7c+vXr5XA4VFZW1uc45u/AhdNj5nD4KioquvVqwoQJfd4mUeYv4acf7e3tuvnmm1VdXR3W+DNnzmj+/PmaNWuWjh07prKyMn3nO9/R7t27ba40MUXa34CmpiZ9+OGHwT9jxoyxqcLEtn//fpWWluqtt95SXV2dfD6f5s6dq/b29l5vc+DAAX3ta1/T8uXLdfToUS1cuFALFy7UiRMnBrHyxDCQ/kqS2+0Omb/vv//+IFWcWMaOHav169ersbFRhw8f1p133qkFCxbo5MmTPY5n7kYm0v5KzN2BaGho0LPPPqspU6b0OY75O3Dh9lhiDkdi0qRJIb164403eh2bUPPXQtgkWdu3b+9zzAMPPGBNmjQpZNs999xjFRcX21hZcginv7///e8tSdZHH300KDUlm/Pnz1uSrP379/c6ZvHixdb8+fNDthUUFFjf/e537S4v4YXT361bt1ojR44cvKKSzNVXX2395Cc/6fE65u6V66u/zN3IXbx40brhhhusuro664477rBWrVrV61jm78BE0mPmcPgeeeQR6+abbw57fCLNX1Z+ouzgwYMqKioK2VZcXKyDBw/GqKLklJ+fr+zsbM2ZM0dvvvlmrMtJGG1tbZKkjIyMXscwhwcunP5K0qVLl3TttdcqNze333fa8RednZ166aWX1N7ersLCwh7HMHcHLpz+SszdSJWWlmr+/Pnd5mVPmL8DE0mPJeZwJE6fPq2cnBx9+tOf1rJly/TBBx/0OjaR5u/QWBeQbJqbm5WZmRmyLTMzUx6PR//3f/+nYcOGxaiy5JCdna2amhpNnTpVXq9XP/nJTzRz5kwdOnRIt9xyS6zLi2t+v19lZWWaMWOGJk+e3Ou43uYw36vqW7j9HT9+vJ5//nlNmTJFbW1tevLJJzV9+nSdPHlSY8eOHcSKE8Px48dVWFioy5cv66qrrtL27dv12c9+tsexzN3IRdJf5m5kXnrpJR05ckQNDQ1hjWf+Ri7SHjOHw1dQUKBt27Zp/Pjx+vDDD1VZWam//du/1YkTJzRixIhu4xNp/hJ+kFDGjx+v8ePHBy9Pnz5d7777rp566in97Gc/i2Fl8a+0tFQnTpzo8zO7GLhw+1tYWBjyzvr06dM1ceJEPfvss3r00UftLjPhjB8/XseOHVNbW5t+8YtfqKSkRPv37+/1BToiE0l/mbvhO3v2rFatWqW6ujq+UG+TgfSYORy+efPmBf8+ZcoUFRQU6Nprr9Urr7yi5cuXx7CyK0f4ibKsrCy1tLSEbGtpaZHb7WbVxybTpk3jBX0/Vq5cqZ07d6q+vr7fd7d6m8NZWVl2lpjQIulvV06nU5/73Of0zjvv2FRdYktNTdVnPvMZSdKtt96qhoYG/ehHP9Kzzz7bbSxzN3KR9Lcr5m7vGhsbdf78+ZBPJHR2dqq+vl5btmyR1+vVkCFDQm7D/I3MQHrcFXM4fKNGjdKNN97Ya68Saf7ynZ8oKyws1J49e0K21dXV9fkZalyZY8eOKTs7O9ZlxCXLsrRy5Upt375de/fuVV5eXr+3YQ6HbyD97aqzs1PHjx9nDofJ7/fL6/X2eB1z98r11d+umLu9mz17to4fP65jx44F/0ydOlXLli3TsWPHenxRzvyNzEB63BVzOHyXLl3Su+++22uvEmr+xvqMC/Hu4sWL1tGjR62jR49akqxNmzZZR48etd5//33Lsixr9erV1je+8Y3g+D/+8Y9Wenq69cMf/tA6deqUVV1dbQ0ZMsTatWtXrA4hrkXa36eeesrasWOHdfr0aev48ePWqlWrrJSUFOt3v/tdrA4hrv3DP/yDNXLkSGvfvn3Whx9+GPzT0dERHPONb3zDWr16dfDym2++aQ0dOtR68sknrVOnTlmPPPKI5XQ6rePHj8fiEOLaQPpbWVlp7d6923r33XetxsZGa8mSJVZaWpp18uTJWBxCXFu9erW1f/9+68yZM9Z//dd/WatXr7YcDof1+uuvW5bF3L1SkfaXuXtlup6JjPkbff31mDkcvh/84AfWvn37rDNnzlhvvvmmVVRUZF1zzTXW+fPnLctK7PlL+OlH4NTKXf+UlJRYlmVZJSUl1h133NHtNvn5+VZqaqr16U9/2tq6deug150oIu3vhg0brOuvv95KS0uzMjIyrJkzZ1p79+6NTfEJoKfeSgqZk3fccUew3wGvvPKKdeONN1qpqanWpEmTrNdee21wC08QA+lvWVmZNW7cOCs1NdXKzMy07rrrLuvIkSODX3wC+Pa3v21de+21VmpqqvU3f/M31uzZs4MvzC2LuXulIu0vc/fKdH1hzvyNvv56zBwO3z333GNlZ2dbqamp1qc+9Snrnnvusd55553g9Yk8fx2WZVmDt84EAAAAALHBd34AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABG+H/X9rYIiR3T7wAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sns.jointplot(x='rating', y='numOfRatings', data = ratings, alpha = 0.5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 625
        },
        "id": "HhOMFtJYqJRF",
        "outputId": "42f5076d-a845-40ee-81a1-fa7d9e28c959"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.JointGrid at 0x78248fd1c0a0>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**Create the Recommendation System**\n",
        "Create a matrix that has the user ids on one access and the movie title on another axis. Each cell will then consist of the rating the user gave to that movie. Note there will be a lot of NaN values, because most people have not seen most of the movies."
      ],
      "metadata": {
        "id": "ujYYPKzdqTjk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "moviemat = df.pivot_table(index='user_id',columns='title',values='rating')\n",
        "moviemat.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        },
        "id": "QP31YiUJqPpY",
        "outputId": "b05edb63-d129-4b29-c9fb-c98d054b9bfa"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "title    'Til There Was You (1997)  1-900 (1994)  101 Dalmatians (1996)  \\\n",
              "user_id                                                                   \n",
              "0                              NaN           NaN                    NaN   \n",
              "1                              NaN           NaN                    2.0   \n",
              "2                              NaN           NaN                    NaN   \n",
              "3                              NaN           NaN                    NaN   \n",
              "4                              NaN           NaN                    NaN   \n",
              "\n",
              "title    12 Angry Men (1957)  187 (1997)  2 Days in the Valley (1996)  \\\n",
              "user_id                                                                 \n",
              "0                        NaN         NaN                          NaN   \n",
              "1                        5.0         NaN                          NaN   \n",
              "2                        NaN         NaN                          NaN   \n",
              "3                        NaN         2.0                          NaN   \n",
              "4                        NaN         NaN                          NaN   \n",
              "\n",
              "title    20,000 Leagues Under the Sea (1954)  2001: A Space Odyssey (1968)  \\\n",
              "user_id                                                                      \n",
              "0                                        NaN                           NaN   \n",
              "1                                        3.0                           4.0   \n",
              "2                                        NaN                           NaN   \n",
              "3                                        NaN                           NaN   \n",
              "4                                        NaN                           NaN   \n",
              "\n",
              "title    3 Ninjas: High Noon At Mega Mountain (1998)  39 Steps, The (1935)  \\\n",
              "user_id                                                                      \n",
              "0                                                NaN                   NaN   \n",
              "1                                                NaN                   NaN   \n",
              "2                                                1.0                   NaN   \n",
              "3                                                NaN                   NaN   \n",
              "4                                                NaN                   NaN   \n",
              "\n",
              "title    ...  Yankee Zulu (1994)  Year of the Horse (1997)  \\\n",
              "user_id  ...                                                 \n",
              "0        ...                 NaN                       NaN   \n",
              "1        ...                 NaN                       NaN   \n",
              "2        ...                 NaN                       NaN   \n",
              "3        ...                 NaN                       NaN   \n",
              "4        ...                 NaN                       NaN   \n",
              "\n",
              "title    You So Crazy (1994)  Young Frankenstein (1974)  Young Guns (1988)  \\\n",
              "user_id                                                                      \n",
              "0                        NaN                        NaN                NaN   \n",
              "1                        NaN                        5.0                3.0   \n",
              "2                        NaN                        NaN                NaN   \n",
              "3                        NaN                        NaN                NaN   \n",
              "4                        NaN                        NaN                NaN   \n",
              "\n",
              "title    Young Guns II (1990)  Young Poisoner's Handbook, The (1995)  \\\n",
              "user_id                                                                \n",
              "0                         NaN                                    NaN   \n",
              "1                         NaN                                    NaN   \n",
              "2                         NaN                                    NaN   \n",
              "3                         NaN                                    NaN   \n",
              "4                         NaN                                    NaN   \n",
              "\n",
              "title    Zeus and Roxanne (1997)  unknown  Á köldum klaka (Cold Fever) (1994)  \n",
              "user_id                                                                        \n",
              "0                            NaN      NaN                                 NaN  \n",
              "1                            NaN      4.0                                 NaN  \n",
              "2                            NaN      NaN                                 NaN  \n",
              "3                            NaN      NaN                                 NaN  \n",
              "4                            NaN      NaN                                 NaN  \n",
              "\n",
              "[5 rows x 1664 columns]"
            ],
            "text/html": [
              "\n",
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              "      <th>title</th>\n",
              "      <th>'Til There Was You (1997)</th>\n",
              "      <th>1-900 (1994)</th>\n",
              "      <th>101 Dalmatians (1996)</th>\n",
              "      <th>12 Angry Men (1957)</th>\n",
              "      <th>187 (1997)</th>\n",
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              "      <th>2001: A Space Odyssey (1968)</th>\n",
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              "      <th>39 Steps, The (1935)</th>\n",
              "      <th>...</th>\n",
              "      <th>Yankee Zulu (1994)</th>\n",
              "      <th>Year of the Horse (1997)</th>\n",
              "      <th>You So Crazy (1994)</th>\n",
              "      <th>Young Frankenstein (1974)</th>\n",
              "      <th>Young Guns (1988)</th>\n",
              "      <th>Young Guns II (1990)</th>\n",
              "      <th>Young Poisoner's Handbook, The (1995)</th>\n",
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              "      <td>...</td>\n",
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              "      buttonEl.style.display =\n",
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              "        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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              "  .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
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              "\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "    90% {\n",
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              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "    (() => {\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "\n",
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "moviemat"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Most Rated Movies with their Average Ratings\n",
        "ratings.sort_values('numOfRatings', ascending = False).head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 394
        },
        "id": "7m3Od1j8qX2J",
        "outputId": "aa63b9e4-7b09-4fc6-f35a-b8b7b4b34fc9"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                 rating  numOfRatings\n",
              "title                                                \n",
              "Star Wars (1977)               4.359589           584\n",
              "Contact (1997)                 3.803536           509\n",
              "Fargo (1996)                   4.155512           508\n",
              "Return of the Jedi (1983)      4.007890           507\n",
              "Liar Liar (1997)               3.156701           485\n",
              "English Patient, The (1996)    3.656965           481\n",
              "Scream (1996)                  3.441423           478\n",
              "Toy Story (1995)               3.878319           452\n",
              "Air Force One (1997)           3.631090           431\n",
              "Independence Day (ID4) (1996)  3.438228           429"
            ],
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"ratings\",\n  \"rows\": 10,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"Air Force One (1997)\",\n          \"Contact (1997)\",\n          \"English Patient, The (1996)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3634727729966799,\n        \"min\": 3.156701030927835,\n        \"max\": 4.359589041095891,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          3.6310904872389793,\n          3.8035363457760316,\n          3.656964656964657\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"numOfRatings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 45,\n        \"min\": 429,\n        \"max\": 584,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          431,\n          509,\n          481\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Now we will create a correlation matrix of every movie with every other movie on user ratings. We will then use that correlation matrix to find top matches that relates the best for a particular movie (having atleast 100 ratings) and the result obtained (recommended movies) will then be added to the ratings dataframe of every movie. Those whose matches could not be obtained using correlation, their value will be converted to \"-\""
      ],
      "metadata": {
        "id": "3SRro1NHq97f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for i in ratings.index:\n",
        "    movieUserRatings = moviemat[i]\n",
        "    similarToThatMovie = moviemat.corrwith(movieUserRatings)\n",
        "    corr_toMovie = pd.DataFrame(similarToThatMovie, columns = ['Correlation'])\n",
        "    corr_toMovie.dropna(inplace = True)\n",
        "    corr_toMovie = corr_toMovie.join(ratings['numOfRatings'])\n",
        "    result = corr_toMovie[corr_toMovie['numOfRatings'] > 100].sort_values('Correlation', ascending = False).head()\n",
        "    if result['numOfRatings'].count() >= 5:\n",
        "        print(i)\n",
        "        ratings.loc[i, 'FirstMovieRecommendation'] = result.iloc[1:2].index.values[0]\n",
        "        ratings.loc[i, 'SecondMovieRecommendation'] = result.iloc[2:3].index.values[0]\n",
        "        ratings.loc[i, 'ThirdMovieRecommendation'] = result.iloc[3:4].index.values[0]\n",
        "        ratings.loc[i, 'FourthMovieRecommendation'] = result.iloc[4:5].index.values[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oLMhj0ezq6t7",
        "outputId": "d67d5a2f-c262-4a5e-95ff-e3c5783b1805"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "'Til There Was You (1997)\n",
            "1-900 (1994)\n",
            "101 Dalmatians (1996)\n",
            "12 Angry Men (1957)\n",
            "187 (1997)\n",
            "2 Days in the Valley (1996)\n",
            "20,000 Leagues Under the Sea (1954)\n",
            "2001: A Space Odyssey (1968)\n",
            "39 Steps, The (1935)\n",
            "8 1/2 (1963)\n",
            "8 Heads in a Duffel Bag (1997)\n",
            "8 Seconds (1994)\n",
            "A Chef in Love (1996)\n",
            "Above the Rim (1994)\n",
            "Absolute Power (1997)\n",
            "Abyss, The (1989)\n",
            "Ace Ventura: Pet Detective (1994)\n",
            "Ace Ventura: When Nature Calls (1995)\n",
            "Across the Sea of Time (1995)\n",
            "Addams Family Values (1993)\n",
            "Addicted to Love (1997)\n",
            "Addiction, The (1995)\n",
            "Adventures of Pinocchio, The (1996)\n",
            "Adventures of Priscilla, Queen of the Desert, The (1994)\n",
            "Adventures of Robin Hood, The (1938)\n",
            "Affair to Remember, An (1957)\n",
            "African Queen, The (1951)\n",
            "Afterglow (1997)\n",
            "Age of Innocence, The (1993)\n",
            "Air Bud (1997)\n",
            "Air Force One (1997)\n",
            "Air Up There, The (1994)\n",
            "Airheads (1994)\n",
            "Akira (1988)\n",
            "Aladdin (1992)\n",
            "Aladdin and the King of Thieves (1996)\n",
            "Alaska (1996)\n",
            "Albino Alligator (1996)\n",
            "Alice in Wonderland (1951)\n",
            "Alien (1979)\n",
            "Alien 3 (1992)\n",
            "Alien: Resurrection (1997)\n",
            "Aliens (1986)\n",
            "All About Eve (1950)\n",
            "All Dogs Go to Heaven 2 (1996)\n",
            "Alphaville (1965)\n",
            "Amadeus (1984)\n",
            "Amateur (1994)\n",
            "Amazing Panda Adventure, The (1995)\n",
            "American Buffalo (1996)\n",
            "American Dream (1990)\n",
            "American President, The (1995)\n",
            "American Strays (1996)\n",
            "American Werewolf in London, An (1981)\n",
            "American in Paris, An (1951)\n",
            "Amistad (1997)\n",
            "Amityville 3-D (1983)\n",
            "Amityville Curse, The (1990)\n",
            "Amityville Horror, The (1979)\n",
            "Amityville II: The Possession (1982)\n",
            "Amos & Andrew (1993)\n",
            "An Unforgettable Summer (1994)\n",
            "Anaconda (1997)\n",
            "Anastasia (1997)\n",
            "Andre (1994)\n",
            "Angel Baby (1995)\n",
            "Angel and the Badman (1947)\n",
            "Angels and Insects (1995)\n",
            "Angels in the Outfield (1994)\n",
            "Angus (1995)\n",
            "Anna (1996)\n",
            "Anna Karenina (1997)\n",
            "Anne Frank Remembered (1995)\n",
            "Annie Hall (1977)\n",
            "Another Stakeout (1993)\n",
            "Antonia's Line (1995)\n",
            "Aparajito (1956)\n",
            "Apartment, The (1960)\n",
            "Apocalypse Now (1979)\n",
            "Apollo 13 (1995)\n",
            "Apostle, The (1997)\n",
            "Apple Dumpling Gang, The (1975)\n",
            "April Fool's Day (1986)\n",
            "Apt Pupil (1998)\n",
            "Aristocats, The (1970)\n",
            "Army of Darkness (1993)\n",
            "Around the World in 80 Days (1956)\n",
            "Arrival, The (1996)\n",
            "Arsenic and Old Lace (1944)\n",
            "As Good As It Gets (1997)\n",
            "Assassins (1995)\n",
            "Assignment, The (1997)\n",
            "Associate, The (1996)\n",
            "Audrey Rose (1977)\n",
            "Austin Powers: International Man of Mystery (1997)\n",
            "Awfully Big Adventure, An (1995)\n",
            "Ayn Rand: A Sense of Life (1997)\n",
            "B*A*P*S (1997)\n",
            "Babe (1995)\n",
            "Baby-Sitters Club, The (1995)\n",
            "Babysitter, The (1995)\n",
            "Back to the Future (1985)\n",
            "Backbeat (1993)\n",
            "Bad Boys (1995)\n",
            "Bad Company (1995)\n",
            "Bad Girls (1994)\n",
            "Bad Moon (1996)\n",
            "Bad Taste (1987)\n",
            "Ballad of Narayama, The (Narayama Bushiko) (1958)\n",
            "Balto (1995)\n",
            "Bananas (1971)\n",
            "Band Wagon, The (1953)\n",
            "Barb Wire (1996)\n",
            "Barbarella (1968)\n",
            "Barcelona (1994)\n",
            "Basic Instinct (1992)\n",
            "Basketball Diaries, The (1995)\n",
            "Basquiat (1996)\n",
            "Bastard Out of Carolina (1996)\n",
            "Batman & Robin (1997)\n",
            "Batman (1989)\n",
            "Batman Forever (1995)\n",
            "Batman Returns (1992)\n",
            "Bean (1997)\n",
            "Beans of Egypt, Maine, The (1994)\n",
            "Beat the Devil (1954)\n",
            "Beautician and the Beast, The (1997)\n",
            "Beautiful Girls (1996)\n",
            "Beautiful Thing (1996)\n",
            "Beauty and the Beast (1991)\n",
            "Beavis and Butt-head Do America (1996)\n",
            "Bed of Roses (1996)\n",
            "Bedknobs and Broomsticks (1971)\n",
            "Before Sunrise (1995)\n",
            "Before and After (1996)\n",
            "Before the Rain (Pred dozhdot) (1994)\n",
            "Being Human (1993)\n",
            "Being There (1979)\n",
            "Believers, The (1987)\n",
            "Belle de jour (1967)\n",
            "Ben-Hur (1959)\n",
            "Benny & Joon (1993)\n",
            "Bent (1997)\n",
            "Best Men (1997)\n",
            "Best of the Best 3: No Turning Back (1995)\n",
            "Better Off Dead... (1985)\n",
            "Beverly Hillbillies, The (1993)\n",
            "Beverly Hills Cop III (1994)\n",
            "Beverly Hills Ninja (1997)\n",
            "Bewegte Mann, Der (1994)\n",
            "Beyond Rangoon (1995)\n",
            "Bhaji on the Beach (1993)\n",
            "Big Blue, The (Grand bleu, Le) (1988)\n",
            "Big Bully (1996)\n",
            "Big Green, The (1995)\n",
            "Big Lebowski, The (1998)\n",
            "Big Night (1996)\n",
            "Big Sleep, The (1946)\n",
            "Big Squeeze, The (1996)\n",
            "Billy Madison (1995)\n",
            "Bio-Dome (1996)\n",
            "Birdcage, The (1996)\n",
            "Birds, The (1963)\n",
            "Bitter Moon (1992)\n",
            "Bitter Sugar (Azucar Amargo) (1996)\n",
            "Black Beauty (1994)\n",
            "Black Sheep (1996)\n",
            "Blade Runner (1982)\n",
            "Blink (1994)\n",
            "Bliss (1997)\n",
            "Blob, The (1958)\n",
            "Blood & Wine (1997)\n",
            "Blood Beach (1981)\n",
            "Blood For Dracula (Andy Warhol's Dracula) (1974)\n",
            "Bloodsport 2 (1995)\n",
            "Blown Away (1994)\n",
            "Blue Angel, The (Blaue Engel, Der) (1930)\n",
            "Blue Chips (1994)\n",
            "Blue Sky (1994)\n",
            "Blue in the Face (1995)\n",
            "Blues Brothers 2000 (1998)\n",
            "Blues Brothers, The (1980)\n",
            "Bob Roberts (1992)\n",
            "Body Parts (1991)\n",
            "Body Snatcher, The (1945)\n",
            "Body Snatchers (1993)\n",
            "Bogus (1996)\n",
            "Bonheur, Le (1965)\n",
            "Bonnie and Clyde (1967)\n",
            "Boogie Nights (1997)\n",
            "Boomerang (1992)\n",
            "Boot, Das (1981)\n",
            "Booty Call (1997)\n",
            "Bottle Rocket (1996)\n",
            "Bound (1996)\n",
            "Boxing Helena (1993)\n",
            "Boy's Life 2 (1997)\n",
            "Boys (1996)\n",
            "Boys Life (1995)\n",
            "Boys of St. Vincent, The (1993)\n",
            "Boys on the Side (1995)\n",
            "Boys, Les (1997)\n",
            "Brady Bunch Movie, The (1995)\n",
            "Braindead (1992)\n",
            "Bram Stoker's Dracula (1992)\n",
            "Brassed Off (1996)\n",
            "Braveheart (1995)\n",
            "Brazil (1985)\n",
            "Bread and Chocolate (Pane e cioccolata) (1973)\n",
            "Breakdown (1997)\n",
            "Breakfast at Tiffany's (1961)\n",
            "Breaking the Waves (1996)\n",
            "Bride of Frankenstein (1935)\n",
            "Bridge on the River Kwai, The (1957)\n",
            "Bridges of Madison County, The (1995)\n",
            "Bringing Up Baby (1938)\n",
            "Broken Arrow (1996)\n",
            "Broken English (1996)\n",
            "Bronx Tale, A (1993)\n",
            "Brother Minister: The Assassination of Malcolm X (1994)\n",
            "Brothers McMullen, The (1995)\n",
            "Browning Version, The (1994)\n",
            "Buddy (1997)\n",
            "Bulletproof (1996)\n",
            "Bullets Over Broadway (1994)\n",
            "Burnt By the Sun (1994)\n",
            "Burnt Offerings (1976)\n",
            "Bushwhacked (1995)\n",
            "Butch Cassidy and the Sundance Kid (1969)\n",
            "Bye Bye, Love (1995)\n",
            "C'est arrivé près de chez vous (1992)\n",
            "Cabin Boy (1994)\n",
            "Cable Guy, The (1996)\n",
            "Calendar Girl (1993)\n",
            "Canadian Bacon (1994)\n",
            "Candidate, The (1972)\n",
            "Candyman (1992)\n",
            "Candyman: Farewell to the Flesh (1995)\n",
            "Cape Fear (1962)\n",
            "Cape Fear (1991)\n",
            "Captives (1994)\n",
            "Career Girls (1997)\n",
            "Carlito's Way (1993)\n",
            "Carmen Miranda: Bananas Is My Business (1994)\n",
            "Caro Diario (Dear Diary) (1994)\n",
            "Carpool (1996)\n",
            "Carrie (1976)\n",
            "Carried Away (1996)\n",
            "Carrington (1995)\n",
            "Casablanca (1942)\n",
            "Casino (1995)\n",
            "Casper (1995)\n",
            "Castle Freak (1995)\n",
            "Cat People (1982)\n",
            "Cat on a Hot Tin Roof (1958)\n",
            "Cats Don't Dance (1997)\n",
            "Catwalk (1995)\n",
            "Caught (1996)\n",
            "Celluloid Closet, The (1995)\n",
            "Celtic Pride (1996)\n",
            "Cement Garden, The (1993)\n",
            "Cemetery Man (Dellamorte Dellamore) (1994)\n",
            "Chain Reaction (1996)\n",
            "Chairman of the Board (1998)\n",
            "Chamber, The (1996)\n",
            "Charade (1963)\n",
            "Chasers (1994)\n",
            "Chasing Amy (1997)\n",
            "Children of the Corn: The Gathering (1996)\n",
            "Children of the Revolution (1996)\n",
            "Chinatown (1974)\n",
            "Christmas Carol, A (1938)\n",
            "Chungking Express (1994)\n",
            "Ciao, Professore! (1993)\n",
            "Cinderella (1950)\n",
            "Cinema Paradiso (1988)\n",
            "Circle of Friends (1995)\n",
            "Citizen Kane (1941)\n",
            "Citizen Ruth (1996)\n",
            "City Hall (1996)\n",
            "City Slickers II: The Legend of Curly's Gold (1994)\n",
            "City of Angels (1998)\n",
            "City of Industry (1997)\n",
            "City of Lost Children, The (1995)\n",
            "Clean Slate (1994)\n",
            "Clean Slate (Coup de Torchon) (1981)\n",
            "Clear and Present Danger (1994)\n",
            "Clerks (1994)\n",
            "Client, The (1994)\n",
            "Cliffhanger (1993)\n",
            "Clockers (1995)\n",
            "Clockwork Orange, A (1971)\n",
            "Close Shave, A (1995)\n",
            "Clueless (1995)\n",
            "Cobb (1994)\n",
            "Cold Comfort Farm (1995)\n",
            "Collectionneuse, La (1967)\n",
            "Colonel Chabert, Le (1994)\n",
            "Color of Night (1994)\n",
            "Commandments (1997)\n",
            "Con Air (1997)\n",
            "Conan the Barbarian (1981)\n",
            "Condition Red (1995)\n",
            "Coneheads (1993)\n",
            "Congo (1995)\n",
            "Conspiracy Theory (1997)\n",
            "Contact (1997)\n",
            "Contempt (Mépris, Le) (1963)\n",
            "Convent, The (Convento, O) (1995)\n",
            "Cook the Thief His Wife & Her Lover, The (1989)\n",
            "Cool Hand Luke (1967)\n",
            "Cool Runnings (1993)\n",
            "Cop Land (1997)\n",
            "Cops and Robbersons (1994)\n",
            "Copycat (1995)\n",
            "Corrina, Corrina (1994)\n",
            "Cosi (1996)\n",
            "Country Life (1994)\n",
            "Courage Under Fire (1996)\n",
            "Cowboy Way, The (1994)\n",
            "Craft, The (1996)\n",
            "Crash (1996)\n",
            "Crimson Tide (1995)\n",
            "Critical Care (1997)\n",
            "Cronos (1992)\n",
            "Crooklyn (1994)\n",
            "Crossfire (1947)\n",
            "Crossing Guard, The (1995)\n",
            "Crow, The (1994)\n",
            "Crow: City of Angels, The (1996)\n",
            "Crows and Sparrows (1949)\n",
            "Crucible, The (1996)\n",
            "Crumb (1994)\n",
            "Cry, the Beloved Country (1995)\n",
            "Crying Game, The (1992)\n",
            "Curdled (1996)\n",
            "Cure, The (1995)\n",
            "Cutthroat Island (1995)\n",
            "Cyrano de Bergerac (1990)\n",
            "D3: The Mighty Ducks (1996)\n",
            "Dances with Wolves (1990)\n",
            "Dangerous Beauty (1998)\n",
            "Dangerous Ground (1997)\n",
            "Dangerous Minds (1995)\n",
            "Daniel Defoe's Robinson Crusoe (1996)\n",
            "Dante's Peak (1997)\n",
            "Dark City (1998)\n",
            "Dave (1993)\n",
            "Davy Crockett, King of the Wild Frontier (1955)\n",
            "Day the Earth Stood Still, The (1951)\n",
            "Day the Sun Turned Cold, The (Tianguo niezi) (1994)\n",
            "Daylight (1996)\n",
            "Days of Thunder (1990)\n",
            "Daytrippers, The (1996)\n",
            "Dazed and Confused (1993)\n",
            "Dead Man (1995)\n",
            "Dead Man Walking (1995)\n",
            "Dead Poets Society (1989)\n",
            "Dead Presidents (1995)\n",
            "Dear God (1996)\n",
            "Death and the Maiden (1994)\n",
            "Deceiver (1997)\n",
            "Deconstructing Harry (1997)\n",
            "Deep Rising (1998)\n",
            "Deer Hunter, The (1978)\n",
            "Delicatessen (1991)\n",
            "Delta of Venus (1994)\n",
            "Demolition Man (1993)\n",
            "Denise Calls Up (1995)\n",
            "Designated Mourner, The (1997)\n",
            "Desperado (1995)\n",
            "Desperate Measures (1998)\n",
            "Devil in a Blue Dress (1995)\n",
            "Devil's Advocate, The (1997)\n",
            "Devil's Own, The (1997)\n",
            "Diabolique (1996)\n",
            "Dial M for Murder (1954)\n",
            "Die Hard (1988)\n",
            "Die Hard 2 (1990)\n",
            "Die Hard: With a Vengeance (1995)\n",
            "Die xue shuang xiong (Killer, The) (1989)\n",
            "Dingo (1992)\n",
            "Dirty Dancing (1987)\n",
            "Disclosure (1994)\n",
            "Diva (1981)\n",
            "Dolores Claiborne (1994)\n",
            "Don Juan DeMarco (1995)\n",
            "Don't Be a Menace to South Central While Drinking Your Juice in the Hood (1996)\n",
            "Donnie Brasco (1997)\n",
            "Doom Generation, The (1995)\n",
            "Doors, The (1991)\n",
            "Double Happiness (1994)\n",
            "Double Team (1997)\n",
            "Double vie de Véronique, La (Double Life of Veronique, The) (1991)\n",
            "Down Periscope (1996)\n",
            "Down by Law (1986)\n",
            "Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1963)\n",
            "Dracula: Dead and Loving It (1995)\n",
            "Dragonheart (1996)\n",
            "Dream Man (1995)\n",
            "Dream With the Fishes (1997)\n",
            "Drop Dead Fred (1991)\n",
            "Drop Zone (1994)\n",
            "Drunks (1995)\n",
            "Duck Soup (1933)\n",
            "Dumb & Dumber (1994)\n",
            "Dumbo (1941)\n",
            "Dunston Checks In (1996)\n",
            "Duoluo tianshi (1995)\n",
            "E.T. the Extra-Terrestrial (1982)\n",
            "East of Eden (1955)\n",
            "Eat Drink Man Woman (1994)\n",
            "Ed (1996)\n",
            "Ed Wood (1994)\n",
            "Ed's Next Move (1996)\n",
            "Eddie (1996)\n",
            "Edge, The (1997)\n",
            "Emma (1996)\n",
            "Empire Strikes Back, The (1980)\n",
            "Enchanted April (1991)\n",
            "Endless Summer 2, The (1994)\n",
            "Enfer, L' (1994)\n",
            "English Patient, The (1996)\n",
            "Englishman Who Went Up a Hill, But Came Down a Mountain, The (1995)\n",
            "Eraser (1996)\n",
            "Escape from L.A. (1996)\n",
            "Escape from New York (1981)\n",
            "Escape to Witch Mountain (1975)\n",
            "Eve's Bayou (1997)\n",
            "Even Cowgirls Get the Blues (1993)\n",
            "Evening Star, The (1996)\n",
            "Event Horizon (1997)\n",
            "Everest (1998)\n",
            "Everyone Says I Love You (1996)\n",
            "Evil Dead II (1987)\n",
            "Evita (1996)\n",
            "Excess Baggage (1997)\n",
            "Executive Decision (1996)\n",
            "Exit to Eden (1994)\n",
            "Exotica (1994)\n",
            "Extreme Measures (1996)\n",
            "Eye for an Eye (1996)\n",
            "Face/Off (1997)\n",
            "Faces (1968)\n",
            "Fair Game (1995)\n",
            "FairyTale: A True Story (1997)\n",
            "Faithful (1996)\n",
            "Fall (1997)\n",
            "Fallen (1998)\n",
            "Family Thing, A (1996)\n",
            "Fan, The (1996)\n",
            "Fantasia (1940)\n",
            "Far From Home: The Adventures of Yellow Dog (1995)\n",
            "Farewell My Concubine (1993)\n",
            "Farewell to Arms, A (1932)\n",
            "Fargo (1996)\n",
            "Farinelli: il castrato (1994)\n",
            "Fast, Cheap & Out of Control (1997)\n",
            "Faster Pussycat! Kill! Kill! (1965)\n",
            "Fatal Instinct (1993)\n",
            "Father of the Bride (1950)\n",
            "Father of the Bride Part II (1995)\n",
            "Fathers' Day (1997)\n",
            "Faust (1994)\n",
            "Fausto (1993)\n",
            "Fear (1996)\n",
            "Fear of a Black Hat (1993)\n",
            "Fearless (1993)\n",
            "Feast of July (1995)\n",
            "Feeling Minnesota (1996)\n",
            "Female Perversions (1996)\n",
            "Field of Dreams (1989)\n",
            "Fierce Creatures (1997)\n",
            "Fifth Element, The (1997)\n",
            "Fille seule, La (A Single Girl) (1995)\n",
            "Fire Down Below (1997)\n",
            "Firestorm (1998)\n",
            "Firm, The (1993)\n",
            "First Kid (1996)\n",
            "First Knight (1995)\n",
            "First Wives Club, The (1996)\n",
            "Fish Called Wanda, A (1988)\n",
            "Fled (1996)\n",
            "Flesh and Bone (1993)\n",
            "Flintstones, The (1994)\n",
            "Flipper (1996)\n",
            "Flirt (1995)\n",
            "Flirting With Disaster (1996)\n",
            "Flower of My Secret, The (Flor de mi secreto, La) (1995)\n",
            "Flubber (1997)\n",
            "Fluke (1995)\n",
            "Fly Away Home (1996)\n",
            "Fog, The (1980)\n",
            "Fools Rush In (1997)\n",
            "For Ever Mozart (1996)\n",
            "For Love or Money (1993)\n",
            "For Richer or Poorer (1997)\n",
            "For Whom the Bell Tolls (1943)\n",
            "For the Moment (1994)\n",
            "Forbidden Christ, The (Cristo proibito, Il) (1950)\n",
            "Forbidden Planet (1956)\n",
            "Foreign Correspondent (1940)\n",
            "Forget Paris (1995)\n",
            "Forrest Gump (1994)\n",
            "Four Days in September (1997)\n",
            "Four Rooms (1995)\n",
            "Four Weddings and a Funeral (1994)\n",
            "Fox and the Hound, The (1981)\n",
            "Foxfire (1996)\n",
            "Frankie Starlight (1995)\n",
            "Free Willy (1993)\n",
            "Free Willy 2: The Adventure Home (1995)\n",
            "Free Willy 3: The Rescue (1997)\n",
            "Freeway (1996)\n",
            "French Kiss (1995)\n",
            "French Twist (Gazon maudit) (1995)\n",
            "Fresh (1994)\n",
            "Friday (1995)\n",
            "Fried Green Tomatoes (1991)\n",
            "Frighteners, The (1996)\n",
            "Frisk (1995)\n",
            "From Dusk Till Dawn (1996)\n",
            "Fugitive, The (1993)\n",
            "Full Metal Jacket (1987)\n",
            "Full Monty, The (1997)\n",
            "Full Speed (1996)\n",
            "Funeral, The (1996)\n",
            "Funny Face (1957)\n",
            "G.I. Jane (1997)\n",
            "Gabbeh (1996)\n",
            "Game, The (1997)\n",
            "Gandhi (1982)\n",
            "Gang Related (1997)\n",
            "Garden of Finzi-Contini, The (Giardino dei Finzi-Contini, Il) (1970)\n",
            "Gaslight (1944)\n",
            "Gattaca (1997)\n",
            "Gay Divorcee, The (1934)\n",
            "George of the Jungle (1997)\n",
            "Georgia (1995)\n",
            "Germinal (1993)\n",
            "Geronimo: An American Legend (1993)\n",
            "Get Shorty (1995)\n",
            "Get on the Bus (1996)\n",
            "Getaway, The (1994)\n",
            "Getting Even with Dad (1994)\n",
            "Ghost (1990)\n",
            "Ghost and Mrs. Muir, The (1947)\n",
            "Ghost and the Darkness, The (1996)\n",
            "Ghost in the Shell (Kokaku kidotai) (1995)\n",
            "Ghosts of Mississippi (1996)\n",
            "Giant (1956)\n",
            "Gigi (1958)\n",
            "Gilligan's Island: The Movie (1998)\n",
            "Girl 6 (1996)\n",
            "Glass Shield, The (1994)\n",
            "Glengarry Glen Ross (1992)\n",
            "Glimmer Man, The (1996)\n",
            "Glory (1989)\n",
            "Go Fish (1994)\n",
            "Godfather, The (1972)\n",
            "Godfather: Part II, The (1974)\n",
            "Gold Diggers: The Secret of Bear Mountain (1995)\n",
            "Golden Earrings (1947)\n",
            "GoldenEye (1995)\n",
            "Gone Fishin' (1997)\n",
            "Gone with the Wind (1939)\n",
            "Good Man in Africa, A (1994)\n",
            "Good Will Hunting (1997)\n",
            "Good, The Bad and The Ugly, The (1966)\n",
            "GoodFellas (1990)\n",
            "Goofy Movie, A (1995)\n",
            "Grace of My Heart (1996)\n",
            "Graduate, The (1967)\n",
            "Grand Day Out, A (1992)\n",
            "Grass Harp, The (1995)\n",
            "Grateful Dead (1995)\n",
            "Grease (1978)\n",
            "Grease 2 (1982)\n",
            "Great Dictator, The (1940)\n",
            "Great Escape, The (1963)\n",
            "Great Expectations (1998)\n",
            "Great Race, The (1965)\n",
            "Great White Hype, The (1996)\n",
            "Gridlock'd (1997)\n",
            "Grifters, The (1990)\n",
            "Grosse Fatigue (1994)\n",
            "Grosse Pointe Blank (1997)\n",
            "Groundhog Day (1993)\n",
            "Grumpier Old Men (1995)\n",
            "Guantanamera (1994)\n",
            "Guilty as Sin (1993)\n",
            "Gumby: The Movie (1995)\n",
            "Hackers (1995)\n",
            "Half Baked (1998)\n",
            "Halloween: The Curse of Michael Myers (1995)\n",
            "Hamlet (1996)\n",
            "Happy Gilmore (1996)\n",
            "Hard Eight (1996)\n",
            "Hard Rain (1998)\n",
            "Hard Target (1993)\n",
            "Harlem (1993)\n",
            "Harold and Maude (1971)\n",
            "Harriet the Spy (1996)\n",
            "Hate (Haine, La) (1995)\n",
            "Haunted World of Edward D. Wood Jr., The (1995)\n",
            "Head Above Water (1996)\n",
            "Hear My Song (1991)\n",
            "Hearts and Minds (1996)\n",
            "Heat (1995)\n",
            "Heathers (1989)\n",
            "Heaven & Earth (1993)\n",
            "Heaven's Prisoners (1996)\n",
            "Heavenly Creatures (1994)\n",
            "Heavy (1995)\n",
            "Heavy Metal (1981)\n",
            "Heavyweights (1994)\n",
            "Heidi Fleiss: Hollywood Madam (1995) \n",
            "Hellraiser: Bloodline (1996)\n",
            "Henry V (1989)\n",
            "Herbie Rides Again (1974)\n",
            "Hercules (1997)\n",
            "Hideaway (1995)\n",
            "High Noon (1952)\n",
            "High School High (1996)\n",
            "Higher Learning (1995)\n",
            "Highlander (1986)\n",
            "Highlander III: The Sorcerer (1994)\n",
            "His Girl Friday (1940)\n",
            "Hollow Reed (1996)\n",
            "Home Alone (1990)\n",
            "Home Alone 3 (1997)\n",
            "Home for the Holidays (1995)\n",
            "Homeward Bound II: Lost in San Francisco (1996)\n",
            "Homeward Bound: The Incredible Journey (1993)\n",
            "Hoodlum (1997)\n",
            "Hoop Dreams (1994)\n",
            "Horse Whisperer, The (1998)\n",
            "Horseman on the Roof, The (Hussard sur le toit, Le) (1995)\n",
            "Hot Shots! Part Deux (1993)\n",
            "Hotel de Love (1996)\n",
            "Hour of the Pig, The (1993)\n",
            "House Arrest (1996)\n",
            "House Party 3 (1994)\n",
            "House of Yes, The (1997)\n",
            "House of the Spirits, The (1993)\n",
            "Houseguest (1994)\n",
            "How to Be a Player (1997)\n",
            "How to Make an American Quilt (1995)\n",
            "Howling, The (1981)\n",
            "Hudsucker Proxy, The (1994)\n",
            "Hugo Pool (1997)\n",
            "Hunchback of Notre Dame, The (1996)\n",
            "Hunt for Red October, The (1990)\n",
            "Hunted, The (1995)\n",
            "Hurricane Streets (1998)\n",
            "I Can't Sleep (J'ai pas sommeil) (1994)\n",
            "I Know What You Did Last Summer (1997)\n",
            "I Like It Like That (1994)\n",
            "I Love Trouble (1994)\n",
            "I Shot Andy Warhol (1996)\n",
            "I'll Do Anything (1994)\n",
            "I'm Not Rappaport (1996)\n",
            "I.Q. (1994)\n",
            "Ice Storm, The (1997)\n",
            "If Lucy Fell (1996)\n",
            "Ill Gotten Gains (1997)\n",
            "Immortal Beloved (1994)\n",
            "In & Out (1997)\n",
            "In Love and War (1996)\n",
            "In the Army Now (1994)\n",
            "In the Bleak Midwinter (1995)\n",
            "In the Company of Men (1997)\n",
            "In the Line of Duty 2 (1987)\n",
            "In the Line of Fire (1993)\n",
            "In the Mouth of Madness (1995)\n",
            "In the Name of the Father (1993)\n",
            "In the Realm of the Senses (Ai no corrida) (1976)\n",
            "Incognito (1997)\n",
            "Independence Day (ID4) (1996)\n",
            "Indian Summer (1996)\n",
            "Indian in the Cupboard, The (1995)\n",
            "Indiana Jones and the Last Crusade (1989)\n",
            "Infinity (1996)\n",
            "Inkwell, The (1994)\n",
            "Innocent Sleep, The (1995)\n",
            "Innocents, The (1961)\n",
            "Inspector General, The (1949)\n",
            "Interview with the Vampire (1994)\n",
            "Inventing the Abbotts (1997)\n",
            "Island of Dr. Moreau, The (1996)\n",
            "It Could Happen to You (1994)\n",
            "It Happened One Night (1934)\n",
            "It Takes Two (1995)\n",
            "It's My Party (1995)\n",
            "It's a Wonderful Life (1946)\n",
            "Jack (1996)\n",
            "Jack and Sarah (1995)\n",
            "Jackal, The (1997)\n",
            "Jackie Brown (1997)\n",
            "Jackie Chan's First Strike (1996)\n",
            "Jade (1995)\n",
            "James and the Giant Peach (1996)\n",
            "Jane Eyre (1996)\n",
            "Jason's Lyric (1994)\n",
            "Jaws (1975)\n",
            "Jaws 2 (1978)\n",
            "Jaws 3-D (1983)\n",
            "Jean de Florette (1986)\n",
            "Jefferson in Paris (1995)\n",
            "Jeffrey (1995)\n",
            "Jerky Boys, The (1994)\n",
            "Jerry Maguire (1996)\n",
            "Jimmy Hollywood (1994)\n",
            "Jingle All the Way (1996)\n",
            "Joe's Apartment (1996)\n",
            "Johnny 100 Pesos (1993)\n",
            "Johnny Mnemonic (1995)\n",
            "Journey of August King, The (1995)\n",
            "Joy Luck Club, The (1993)\n",
            "Jude (1996)\n",
            "Judge Dredd (1995)\n",
            "Judgment Night (1993)\n",
            "Jumanji (1995)\n",
            "Jungle Book, The (1994)\n",
            "Jungle2Jungle (1997)\n",
            "Junior (1994)\n",
            "Jurassic Park (1993)\n",
            "Juror, The (1996)\n",
            "Jury Duty (1995)\n",
            "Just Cause (1995)\n",
            "Kalifornia (1993)\n",
            "Kama Sutra: A Tale of Love (1996)\n",
            "Kansas City (1996)\n",
            "Kaspar Hauser (1993)\n",
            "Kazaam (1996)\n",
            "Keys to Tulsa (1997)\n",
            "Kicked in the Head (1997)\n",
            "Kicking and Screaming (1995)\n",
            "Kid in King Arthur's Court, A (1995)\n",
            "Kids (1995)\n",
            "Kids in the Hall: Brain Candy (1996)\n",
            "Killer (Bulletproof Heart) (1994)\n",
            "Killing Fields, The (1984)\n",
            "Killing Zoe (1994)\n",
            "Kim (1950)\n",
            "King of the Hill (1993)\n",
            "Kingpin (1996)\n",
            "Kiss Me, Guido (1997)\n",
            "Kiss of Death (1995)\n",
            "Kiss the Girls (1997)\n",
            "Kissed (1996)\n",
            "Kolya (1996)\n",
            "Koyaanisqatsi (1983)\n",
            "Kull the Conqueror (1997)\n",
            "Kundun (1997)\n",
            "L.A. Confidential (1997)\n",
            "Ladybird Ladybird (1994)\n",
            "Lamerica (1994)\n",
            "Land Before Time III: The Time of the Great Giving (1995) (V)\n",
            "Larger Than Life (1996)\n",
            "Lassie (1994)\n",
            "Last Action Hero (1993)\n",
            "Last Dance (1996)\n",
            "Last Klezmer: Leopold Kozlowski, His Life and Music, The (1995)\n",
            "Last Man Standing (1996)\n",
            "Last Summer in the Hamptons (1995)\n",
            "Last Supper, The (1995)\n",
            "Last Time I Committed Suicide, The (1997)\n",
            "Last Time I Saw Paris, The (1954)\n",
            "Last of the Mohicans, The (1992)\n",
            "Late Bloomers (1996)\n",
            "Laura (1944)\n",
            "Lawnmower Man 2: Beyond Cyberspace (1996)\n",
            "Lawnmower Man, The (1992)\n",
            "Lawrence of Arabia (1962)\n",
            "Lay of the Land, The (1997)\n",
            "Leading Man, The (1996)\n",
            "Leave It to Beaver (1997)\n",
            "Leaving Las Vegas (1995)\n",
            "Legal Deceit (1997)\n",
            "Legends of the Fall (1994)\n",
            "Letter From Death Row, A (1998)\n",
            "Liar Liar (1997)\n",
            "Life Less Ordinary, A (1997)\n",
            "Life with Mikey (1993)\n",
            "Lightning Jack (1994)\n",
            "Like Water For Chocolate (Como agua para chocolate) (1992)\n",
            "Line King: Al Hirschfeld, The (1996)\n",
            "Lion King, The (1994)\n",
            "Little Big League (1994)\n",
            "Little Buddha (1993)\n",
            "Little Lord Fauntleroy (1936)\n",
            "Little Odessa (1994)\n",
            "Little Princess, A (1995)\n",
            "Little Princess, The (1939)\n",
            "Little Rascals, The (1994)\n",
            "Little Women (1994)\n",
            "Live Nude Girls (1995)\n",
            "Living in Oblivion (1995)\n",
            "Loaded (1994)\n",
            "Local Hero (1983)\n",
            "Loch Ness (1995)\n",
            "Locusts, The (1997)\n",
            "Lone Star (1996)\n",
            "Long Kiss Goodnight, The (1996)\n",
            "Looking for Richard (1996)\n",
            "Lord of Illusions (1995)\n",
            "Losing Chase (1996)\n",
            "Losing Isaiah (1995)\n",
            "Lost Highway (1997)\n",
            "Lost Horizon (1937)\n",
            "Lost World: Jurassic Park, The (1997)\n",
            "Lost in Space (1998)\n",
            "Love & Human Remains (1993)\n",
            "Love Affair (1994)\n",
            "Love Bug, The (1969)\n",
            "Love Jones (1997)\n",
            "Love Serenade (1996)\n",
            "Love and Death on Long Island (1997)\n",
            "Love and Other Catastrophes (1996)\n",
            "Love and a .45 (1994)\n",
            "Love in the Afternoon (1957)\n",
            "Love! Valour! Compassion! (1997)\n",
            "Lover's Knot (1996)\n",
            "Low Down Dirty Shame, A (1994)\n",
            "M (1931)\n",
            "M*A*S*H (1970)\n",
            "M. Butterfly (1993)\n",
            "Ma vie en rose (My Life in Pink) (1997)\n",
            "Machine, The (1994)\n",
            "Mad City (1997)\n",
            "Mad Love (1995)\n",
            "Madame Butterfly (1995)\n",
            "Made in America (1993)\n",
            "Madness of King George, The (1994)\n",
            "Madonna: Truth or Dare (1991)\n",
            "Magic Hour, The (1998)\n",
            "Magnificent Seven, The (1954)\n",
            "Major Payne (1994)\n",
            "Malice (1993)\n",
            "Mallrats (1995)\n",
            "Maltese Falcon, The (1941)\n",
            "Man Who Knew Too Little, The (1997)\n",
            "Man Who Would Be King, The (1975)\n",
            "Man Without a Face, The (1993)\n",
            "Man in the Iron Mask, The (1998)\n",
            "Man of No Importance, A (1994)\n",
            "Man of the House (1995)\n",
            "Man of the Year (1995)\n",
            "Manchurian Candidate, The (1962)\n",
            "Manhattan (1979)\n",
            "Manhattan Murder Mystery (1993)\n",
            "Manny & Lo (1996)\n",
            "Manon of the Spring (Manon des sources) (1986)\n",
            "Margaret's Museum (1995)\n",
            "Mark of Zorro, The (1940)\n",
            "Marked for Death (1990)\n",
            "Mars Attacks! (1996)\n",
            "Marvin's Room (1996)\n",
            "Mary Poppins (1964)\n",
            "Mary Reilly (1996)\n",
            "Mary Shelley's Frankenstein (1994)\n",
            "Mask, The (1994)\n",
            "MatchMaker, The (1997)\n",
            "Matilda (1996)\n",
            "Maverick (1994)\n",
            "Maximum Risk (1996)\n",
            "Maya Lin: A Strong Clear Vision (1994)\n",
            "Maybe, Maybe Not (Bewegte Mann, Der) (1994)\n",
            "McHale's Navy (1997)\n",
            "Mediterraneo (1991)\n",
            "Meet John Doe (1941)\n",
            "Meet Me in St. Louis (1944)\n",
            "Meet Wally Sparks (1997)\n",
            "Men With Guns (1997)\n",
            "Men in Black (1997)\n",
            "Men of Means (1998)\n",
            "Menace II Society (1993)\n",
            "Mercury Rising (1998)\n",
            "Metisse (Café au Lait) (1993)\n",
            "Metro (1997)\n",
            "Miami Rhapsody (1995)\n",
            "Michael (1996)\n",
            "Michael Collins (1996)\n",
            "Microcosmos: Le peuple de l'herbe (1996)\n",
            "Midnight Dancers (Sibak) (1994)\n",
            "Midnight in the Garden of Good and Evil (1997)\n",
            "Mighty Aphrodite (1995)\n",
            "Mighty Morphin Power Rangers: The Movie (1995)\n",
            "Milk Money (1994)\n",
            "Miller's Crossing (1990)\n",
            "Mimic (1997)\n",
            "Mina Tannenbaum (1994)\n",
            "Miracle on 34th Street (1994)\n",
            "Mirror Has Two Faces, The (1996)\n",
            "Mission: Impossible (1996)\n",
            "Misérables, Les (1995)\n",
            "Mixed Nuts (1994)\n",
            "Moll Flanders (1996)\n",
            "Mondo (1996)\n",
            "Money Talks (1997)\n",
            "Money Train (1995)\n",
            "Month by the Lake, A (1995)\n",
            "Monty Python and the Holy Grail (1974)\n",
            "Monty Python's Life of Brian (1979)\n",
            "Moonlight and Valentino (1995)\n",
            "Mortal Kombat (1995)\n",
            "Mortal Kombat: Annihilation (1997)\n",
            "Mother (1996)\n",
            "Mother Night (1996)\n",
            "Mouse Hunt (1997)\n",
            "Mr. Holland's Opus (1995)\n",
            "Mr. Jones (1993)\n",
            "Mr. Magoo (1997)\n",
            "Mr. Smith Goes to Washington (1939)\n",
            "Mr. Wrong (1996)\n",
            "Mrs. Brown (Her Majesty, Mrs. Brown) (1997)\n",
            "Mrs. Dalloway (1997)\n",
            "Mrs. Doubtfire (1993)\n",
            "Mrs. Parker and the Vicious Circle (1994)\n",
            "Mrs. Winterbourne (1996)\n",
            "Much Ado About Nothing (1993)\n",
            "Mulholland Falls (1996)\n",
            "Multiplicity (1996)\n",
            "Muppet Treasure Island (1996)\n",
            "Murder at 1600 (1997)\n",
            "Murder in the First (1995)\n",
            "Murder, My Sweet (1944)\n",
            "Muriel's Wedding (1994)\n",
            "Mute Witness (1994)\n",
            "My Best Friend's Wedding (1997)\n",
            "My Crazy Life (Mi vida loca) (1993)\n",
            "My Fair Lady (1964)\n",
            "My Family (1995)\n",
            "My Favorite Season (1993)\n",
            "My Favorite Year (1982)\n",
            "My Fellow Americans (1996)\n",
            "My Left Foot (1989)\n",
            "My Life and Times With Antonin Artaud (En compagnie d'Antonin Artaud) (1993)\n",
            "My Life as a Dog (Mitt liv som hund) (1985)\n",
            "My Man Godfrey (1936)\n",
            "My Own Private Idaho (1991)\n",
            "Mystery Science Theater 3000: The Movie (1996)\n",
            "Nadja (1994)\n",
            "Naked (1993)\n",
            "Naked Gun 33 1/3: The Final Insult (1994)\n",
            "Naked in New York (1994)\n",
            "National Lampoon's Senior Trip (1995)\n",
            "Natural Born Killers (1994)\n",
            "Nell (1994)\n",
            "Nelly & Monsieur Arnaud (1995)\n",
            "Neon Bible, The (1995)\n",
            "Net, The (1995)\n",
            "NeverEnding Story III, The (1994)\n",
            "New Jersey Drive (1995)\n",
            "New York Cop (1996)\n",
            "Newton Boys, The (1998)\n",
            "Next Karate Kid, The (1994)\n",
            "Nick of Time (1995)\n",
            "Nico Icon (1995)\n",
            "Night Falls on Manhattan (1997)\n",
            "Night Flier (1997)\n",
            "Night of the Living Dead (1968)\n",
            "Night on Earth (1991)\n",
            "Nightmare Before Christmas, The (1993)\n",
            "Nightmare on Elm Street, A (1984)\n",
            "Nightwatch (1997)\n",
            "Nikita (La Femme Nikita) (1990)\n",
            "Nil By Mouth (1997)\n",
            "Nina Takes a Lover (1994)\n",
            "Nine Months (1995)\n",
            "Ninotchka (1939)\n",
            "Nixon (1995)\n",
            "No Escape (1994)\n",
            "Nobody's Fool (1994)\n",
            "North (1994)\n",
            "North by Northwest (1959)\n",
            "Nosferatu (Nosferatu, eine Symphonie des Grauens) (1922)\n",
            "Nosferatu a Venezia (1986)\n",
            "Nothing to Lose (1994)\n",
            "Notorious (1946)\n",
            "Now and Then (1995)\n",
            "Nowhere (1997)\n",
            "Nutty Professor, The (1996)\n",
            "Nénette et Boni (1996)\n",
            "Of Human Bondage (1934)\n",
            "Of Love and Shadows (1994)\n",
            "Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)\n",
            "Old Man and the Sea, The (1958)\n",
            "Old Yeller (1957)\n",
            "Oliver & Company (1988)\n",
            "Omen, The (1976)\n",
            "On Golden Pond (1981)\n",
            "Once Upon a Time in America (1984)\n",
            "Once Upon a Time in the West (1969)\n",
            "Once Upon a Time... When We Were Colored (1995)\n",
            "Once Were Warriors (1994)\n",
            "One Fine Day (1996)\n",
            "One Flew Over the Cuckoo's Nest (1975)\n",
            "One Night Stand (1997)\n",
            "Only You (1994)\n",
            "Open Season (1996)\n",
            "Operation Dumbo Drop (1995)\n",
            "Original Gangstas (1996)\n",
            "Orlando (1993)\n",
            "Oscar & Lucinda (1997)\n",
            "Othello (1995)\n",
            "Out to Sea (1997)\n",
            "Outbreak (1995)\n",
            "Outlaw, The (1943)\n",
            "Pagemaster, The (1994)\n",
            "Pallbearer, The (1996)\n",
            "Palmetto (1998)\n",
            "Palookaville (1996)\n",
            "Panther (1995)\n",
            "Paper, The (1994)\n",
            "Paradise Lost: The Child Murders at Robin Hood Hills (1996)\n",
            "Paradise Road (1997)\n",
            "Parent Trap, The (1961)\n",
            "Paris Is Burning (1990)\n",
            "Paris, France (1993)\n",
            "Paris, Texas (1984)\n",
            "Party Girl (1995)\n",
            "Passion Fish (1992)\n",
            "Pather Panchali (1955)\n",
            "Paths of Glory (1957)\n",
            "Patton (1970)\n",
            "Peacemaker, The (1997)\n",
            "Penny Serenade (1941)\n",
            "People vs. Larry Flynt, The (1996)\n",
            "Perez Family, The (1995)\n",
            "Perfect Candidate, A (1996)\n",
            "Perfect World, A (1993)\n",
            "Persuasion (1995)\n",
            "Pest, The (1997)\n",
            "Pete's Dragon (1977)\n",
            "Phantom, The (1996)\n",
            "Phantoms (1998)\n",
            "Phat Beach (1996)\n",
            "Phenomenon (1996)\n",
            "Philadelphia (1993)\n",
            "Philadelphia Story, The (1940)\n",
            "Piano, The (1993)\n",
            "Picnic (1955)\n",
            "Picture Bride (1995)\n",
            "Picture Perfect (1997)\n",
            "Pie in the Sky (1995)\n",
            "Pillow Book, The (1995)\n",
            "Pink Floyd - The Wall (1982)\n",
            "Pinocchio (1940)\n",
            "Platoon (1986)\n",
            "Playing God (1997)\n",
            "Pocahontas (1995)\n",
            "Poetic Justice (1993)\n",
            "Poison Ivy II (1995)\n",
            "Pollyanna (1960)\n",
            "Pompatus of Love, The (1996)\n",
            "Ponette (1996)\n",
            "Portrait of a Lady, The (1996)\n",
            "Postino, Il (1994)\n",
            "Postman, The (1997)\n",
            "Powder (1995)\n",
            "Preacher's Wife, The (1996)\n",
            "Pretty Woman (1990)\n",
            "Price Above Rubies, A (1998)\n",
            "Priest (1994)\n",
            "Primal Fear (1996)\n",
            "Primary Colors (1998)\n",
            "Princess Bride, The (1987)\n",
            "Princess Caraboo (1994)\n",
            "Prisoner of the Mountains (Kavkazsky Plennik) (1996)\n",
            "Private Benjamin (1980)\n",
            "Private Parts (1997)\n",
            "Professional, The (1994)\n",
            "Program, The (1993)\n",
            "Promesse, La (1996)\n",
            "Prophecy II, The (1998)\n",
            "Prophecy, The (1995)\n",
            "Psycho (1960)\n",
            "Pulp Fiction (1994)\n",
            "Pump Up the Volume (1990)\n",
            "Purple Noon (1960)\n",
            "Pushing Hands (1992)\n",
            "Pyromaniac's Love Story, A (1995)\n",
            "Queen Margot (Reine Margot, La) (1994)\n",
            "Quest, The (1996)\n",
            "Quick and the Dead, The (1995)\n",
            "Quiet Man, The (1952)\n",
            "Quiet Room, The (1996)\n",
            "Quiz Show (1994)\n",
            "Race the Sun (1996)\n",
            "Radioland Murders (1994)\n",
            "Raging Bull (1980)\n",
            "Raiders of the Lost Ark (1981)\n",
            "Rainmaker, The (1997)\n",
            "Raise the Red Lantern (1991)\n",
            "Raising Arizona (1987)\n",
            "Ran (1985)\n",
            "Ransom (1996)\n",
            "Ready to Wear (Pret-A-Porter) (1994)\n",
            "Real Genius (1985)\n",
            "Reality Bites (1994)\n",
            "Rear Window (1954)\n",
            "Rebecca (1940)\n",
            "Rebel Without a Cause (1955)\n",
            "Reckless (1995)\n",
            "Red Corner (1997)\n",
            "Red Firecracker, Green Firecracker (1994)\n",
            "Red Rock West (1992)\n",
            "Ref, The (1994)\n",
            "Relative Fear (1994)\n",
            "Relic, The (1997)\n",
            "Remains of the Day, The (1993)\n",
            "Renaissance Man (1994)\n",
            "Rendezvous in Paris (Rendez-vous de Paris, Les) (1995)\n",
            "Rent-a-Kid (1995)\n",
            "Replacement Killers, The (1998)\n",
            "Reservoir Dogs (1992)\n",
            "Restoration (1995)\n",
            "Return of Martin Guerre, The (Retour de Martin Guerre, Le) (1982)\n",
            "Return of the Jedi (1983)\n",
            "Return of the Pink Panther, The (1974)\n",
            "Rhyme & Reason (1997)\n",
            "Rich Man's Wife, The (1996)\n",
            "Richard III (1995)\n",
            "Richie Rich (1994)\n",
            "Ridicule (1996)\n",
            "Right Stuff, The (1983)\n",
            "Rising Sun (1993)\n",
            "River Wild, The (1994)\n",
            "Road to Wellville, The (1994)\n",
            "Rob Roy (1995)\n",
            "Robert A. Heinlein's The Puppet Masters (1994)\n",
            "Robin Hood: Men in Tights (1993)\n",
            "Robin Hood: Prince of Thieves (1991)\n",
            "Robocop 3 (1993)\n",
            "Rock, The (1996)\n",
            "Rocket Man (1997)\n",
            "Roman Holiday (1953)\n",
            "Romeo Is Bleeding (1993)\n",
            "Romper Stomper (1992)\n",
            "Romy and Michele's High School Reunion (1997)\n",
            "Room with a View, A (1986)\n",
            "Roommates (1995)\n",
            "Roseanna's Grave (For Roseanna) (1997)\n",
            "Rosencrantz and Guildenstern Are Dead (1990)\n",
            "Rosewood (1997)\n",
            "Rough Magic (1995)\n",
            "Ruby in Paradise (1993)\n",
            "Rudy (1993)\n",
            "Ruling Class, The (1972)\n",
            "Rumble in the Bronx (1995)\n",
            "Run of the Country, The (1995)\n",
            "S.F.W. (1994)\n",
            "Sabrina (1954)\n",
            "Sabrina (1995)\n",
            "Safe (1995)\n",
            "Safe Passage (1994)\n",
            "Saint, The (1997)\n",
            "Salut cousin! (1996)\n",
            "Santa Clause, The (1994)\n",
            "Savage Nights (Nuits fauves, Les) (1992)\n",
            "Scarlet Letter, The (1926)\n",
            "Scarlet Letter, The (1995)\n",
            "Schindler's List (1993)\n",
            "Schizopolis (1996)\n",
            "Scout, The (1994)\n",
            "Scream (1996)\n",
            "Scream 2 (1997)\n",
            "Screamers (1995)\n",
            "Search for One-eye Jimmy, The (1996)\n",
            "Searching for Bobby Fischer (1993)\n",
            "Second Jungle Book: Mowgli & Baloo, The (1997)\n",
            "Secret Adventures of Tom Thumb, The (1993)\n",
            "Secret Agent, The (1996)\n",
            "Secret Garden, The (1993)\n",
            "Secret of Roan Inish, The (1994)\n",
            "Secrets & Lies (1996)\n",
            "Selena (1997)\n",
            "Sense and Sensibility (1995)\n",
            "Senseless (1998)\n",
            "Serial Mom (1994)\n",
            "Set It Off (1996)\n",
            "Seven (Se7en) (1995)\n",
            "Seven Years in Tibet (1997)\n",
            "Seventh Seal, The (Sjunde inseglet, Det) (1957)\n",
            "Sex, Lies, and Videotape (1989)\n",
            "Sexual Life of the Belgians, The (1994)\n",
            "Sgt. Bilko (1996)\n",
            "Shadow Conspiracy (1997)\n",
            "Shadow, The (1994)\n",
            "Shadowlands (1993)\n",
            "Shaggy Dog, The (1959)\n",
            "Shall We Dance? (1937)\n",
            "Shall We Dance? (1996)\n",
            "Shallow Grave (1994)\n",
            "Shanghai Triad (Yao a yao yao dao waipo qiao) (1995)\n",
            "Shawshank Redemption, The (1994)\n",
            "She's So Lovely (1997)\n",
            "She's the One (1996)\n",
            "Shiloh (1997)\n",
            "Shine (1996)\n",
            "Shining, The (1980)\n",
            "Shooter, The (1995)\n",
            "Shooting Fish (1997)\n",
            "Short Cuts (1993)\n",
            "Show, The (1995)\n",
            "Showgirls (1995)\n",
            "Silence of the Lambs, The (1991)\n",
            "Simple Twist of Fate, A (1994)\n",
            "Simple Wish, A (1997)\n",
            "Singin' in the Rain (1952)\n",
            "Sirens (1994)\n",
            "Six Degrees of Separation (1993)\n",
            "Sixth Man, The (1997)\n",
            "Sleeper (1973)\n",
            "Sleepers (1996)\n",
            "Sleepless in Seattle (1993)\n",
            "Sliding Doors (1998)\n",
            "Sling Blade (1996)\n",
            "Slingshot, The (1993)\n",
            "Sliver (1993)\n",
            "Smile Like Yours, A (1997)\n",
            "Smilla's Sense of Snow (1997)\n",
            "Smoke (1995)\n",
            "Sneakers (1992)\n",
            "Snow White and the Seven Dwarfs (1937)\n",
            "So Dear to My Heart (1949)\n",
            "So I Married an Axe Murderer (1993)\n",
            "Solo (1996)\n",
            "Some Folks Call It a Sling Blade (1993)\n",
            "Some Kind of Wonderful (1987)\n",
            "Some Like It Hot (1959)\n",
            "Some Mother's Son (1996)\n",
            "Something to Talk About (1995)\n",
            "Somewhere in Time (1980)\n",
            "Son in Law (1993)\n",
            "Sophie's Choice (1982)\n",
            "Soul Food (1997)\n",
            "Sound of Music, The (1965)\n",
            "Space Jam (1996)\n",
            "Spanking the Monkey (1994)\n",
            "Spawn (1997)\n",
            "Specialist, The (1994)\n",
            "Species (1995)\n",
            "Speechless (1994)\n",
            "Speed (1994)\n",
            "Speed 2: Cruise Control (1997)\n",
            "Spellbound (1945)\n",
            "Sphere (1998)\n",
            "Spice World (1997)\n",
            "Spirits of the Dead (Tre passi nel delirio) (1968)\n",
            "Spitfire Grill, The (1996)\n",
            "Spy Hard (1996)\n",
            "Squeeze (1996)\n",
            "Stag (1997)\n",
            "Stalingrad (1993)\n",
            "Stalker (1979)\n",
            "Stand by Me (1986)\n",
            "Star Maker, The (Uomo delle stelle, L') (1995)\n",
            "Star Maps (1997)\n",
            "Star Trek III: The Search for Spock (1984)\n",
            "Star Trek IV: The Voyage Home (1986)\n",
            "Star Trek V: The Final Frontier (1989)\n",
            "Star Trek VI: The Undiscovered Country (1991)\n",
            "Star Trek: First Contact (1996)\n",
            "Star Trek: Generations (1994)\n",
            "Star Trek: The Motion Picture (1979)\n",
            "Star Trek: The Wrath of Khan (1982)\n",
            "Star Wars (1977)\n",
            "Stargate (1994)\n",
            "Stars Fell on Henrietta, The (1995)\n",
            "Starship Troopers (1997)\n",
            "Steal Big, Steal Little (1995)\n",
            "Stealing Beauty (1996)\n",
            "Steel (1997)\n",
            "Stephen King's The Langoliers (1995)\n",
            "Sting, The (1973)\n",
            "Stonewall (1995)\n",
            "Story of Xinghua, The (1993)\n",
            "Strange Days (1995)\n",
            "Stranger in the House (1997)\n",
            "Stranger, The (1994)\n",
            "Strawberry and Chocolate (Fresa y chocolate) (1993)\n",
            "Street Fighter (1994)\n",
            "Streetcar Named Desire, A (1951)\n",
            "Strictly Ballroom (1992)\n",
            "Striking Distance (1993)\n",
            "Stripes (1981)\n",
            "Striptease (1996)\n",
            "Stuart Saves His Family (1995)\n",
            "Stupids, The (1996)\n",
            "SubUrbia (1997)\n",
            "Substance of Fire, The (1996)\n",
            "Substitute, The (1996)\n",
            "Sudden Death (1995)\n",
            "Sudden Manhattan (1996)\n",
            "Sum of Us, The (1994)\n",
            "Sunset Blvd. (1950)\n",
            "Sunset Park (1996)\n",
            "Super Mario Bros. (1993)\n",
            "Supercop (1992)\n",
            "Surviving Picasso (1996)\n",
            "Surviving the Game (1994)\n",
            "Suture (1993)\n",
            "Swan Princess, The (1994)\n",
            "Sweet Hereafter, The (1997)\n",
            "Swept from the Sea (1997)\n",
            "Swimming with Sharks (1995)\n",
            "Swingers (1996)\n",
            "Swiss Family Robinson (1960)\n",
            "Switchback (1997)\n",
            "Switchblade Sisters (1975)\n",
            "Sword in the Stone, The (1963)\n",
            "Tales From the Crypt Presents: Demon Knight (1995)\n",
            "Tales from the Crypt Presents: Bordello of Blood (1996)\n",
            "Tales from the Hood (1995)\n",
            "Talking About Sex (1994)\n",
            "Tango Lesson, The (1997)\n",
            "Tank Girl (1995)\n",
            "Taxi Driver (1976)\n",
            "Telling Lies in America (1997)\n",
            "Temptress Moon (Feng Yue) (1996)\n",
            "Terminal Velocity (1994)\n",
            "Terminator 2: Judgment Day (1991)\n",
            "Terminator, The (1984)\n",
            "Tetsuo II: Body Hammer (1992)\n",
            "That Darn Cat! (1965)\n",
            "That Darn Cat! (1997)\n",
            "That Old Feeling (1997)\n",
            "That Thing You Do! (1996)\n",
            "The Deadly Cure (1996)\n",
            "The Innocent (1994)\n",
            "Theodore Rex (1995)\n",
            "Thieves (Voleurs, Les) (1996)\n",
            "Thin Blue Line, The (1988)\n",
            "Thin Line Between Love and Hate, A (1996)\n",
            "Thin Man, The (1934)\n",
            "Things to Do in Denver when You're Dead (1995)\n",
            "Thinner (1996)\n",
            "Third Man, The (1949)\n",
            "Thirty-Two Short Films About Glenn Gould (1993)\n",
            "This Is Spinal Tap (1984)\n",
            "Thousand Acres, A (1997)\n",
            "Three Caballeros, The (1945)\n",
            "Three Colors: Blue (1993)\n",
            "Three Colors: Red (1994)\n",
            "Three Colors: White (1994)\n",
            "Three Musketeers, The (1993)\n",
            "Three Wishes (1995)\n",
            "Threesome (1994)\n",
            "Tie Me Up! Tie Me Down! (1990)\n",
            "Tie That Binds, The (1995)\n",
            "Time Tracers (1995)\n",
            "Time to Kill, A (1996)\n",
            "Timecop (1994)\n",
            "Tin Cup (1996)\n",
            "Tin Drum, The (Blechtrommel, Die) (1979)\n",
            "Tin Men (1987)\n",
            "Titanic (1997)\n",
            "To Be or Not to Be (1942)\n",
            "To Catch a Thief (1955)\n",
            "To Die For (1995)\n",
            "To Gillian on Her 37th Birthday (1996)\n",
            "To Have, or Not (1995)\n",
            "To Kill a Mockingbird (1962)\n",
            "To Live (Huozhe) (1994)\n",
            "To Wong Foo, Thanks for Everything! Julie Newmar (1995)\n",
            "Tom & Viv (1994)\n",
            "Tom and Huck (1995)\n",
            "Tombstone (1993)\n",
            "Tommy Boy (1995)\n",
            "Tomorrow Never Dies (1997)\n",
            "Top Gun (1986)\n",
            "Top Hat (1935)\n",
            "Total Eclipse (1995)\n",
            "Touch (1997)\n",
            "Touch of Evil (1958)\n",
            "Tough and Deadly (1995)\n",
            "Toy Story (1995)\n",
            "Trainspotting (1996)\n",
            "Transformers: The Movie, The (1986)\n",
            "Traveller (1997)\n",
            "Treasure of the Sierra Madre, The (1948)\n",
            "Trees Lounge (1996)\n",
            "Trial and Error (1997)\n",
            "Trial by Jury (1994)\n",
            "Trigger Effect, The (1996)\n",
            "True Crime (1995)\n",
            "True Lies (1994)\n",
            "True Romance (1993)\n",
            "Truman Show, The (1998)\n",
            "Trust (1990)\n",
            "Truth About Cats & Dogs, The (1996)\n",
            "Truth or Consequences, N.M. (1997)\n",
            "Turbo: A Power Rangers Movie (1997)\n",
            "Turbulence (1997)\n",
            "Turning, The (1992)\n",
            "Twelfth Night (1996)\n",
            "Twelve Monkeys (1995)\n",
            "Twilight (1998)\n",
            "Twin Town (1997)\n",
            "Twisted (1996)\n",
            "Twister (1996)\n",
            "Two Bits (1995)\n",
            "Two Deaths (1995)\n",
            "Two Much (1996)\n",
            "Two if by Sea (1996)\n",
            "Two or Three Things I Know About Her (1966)\n",
            "U Turn (1997)\n",
            "U.S. Marshalls (1998)\n",
            "Ulee's Gold (1997)\n",
            "Umbrellas of Cherbourg, The (Parapluies de Cherbourg, Les) (1964)\n",
            "Unbearable Lightness of Being, The (1988)\n",
            "Under Siege (1992)\n",
            "Under Siege 2: Dark Territory (1995)\n",
            "Underground (1995)\n",
            "Underneath, The (1995)\n",
            "Underworld (1997)\n",
            "Unforgettable (1996)\n",
            "Unforgiven (1992)\n",
            "Unhook the Stars (1996)\n",
            "Unstrung Heroes (1995)\n",
            "Until the End of the World (Bis ans Ende der Welt) (1991)\n",
            "Unzipped (1995)\n",
            "Up Close and Personal (1996)\n",
            "Up in Smoke (1978)\n",
            "Usual Suspects, The (1995)\n",
            "Vampire in Brooklyn (1995)\n",
            "Van, The (1996)\n",
            "Vanya on 42nd Street (1994)\n",
            "Vegas Vacation (1997)\n",
            "Vermin (1998)\n",
            "Vertigo (1958)\n",
            "Very Brady Sequel, A (1996)\n",
            "Victor/Victoria (1982)\n",
            "Village of the Damned (1995)\n",
            "Virtuosity (1995)\n",
            "Visitors, The (Visiteurs, Les) (1993)\n",
            "Volcano (1997)\n",
            "Wag the Dog (1997)\n",
            "Waiting for Guffman (1996)\n",
            "Waiting to Exhale (1995)\n",
            "Walk in the Clouds, A (1995)\n",
            "Walkabout (1971)\n",
            "Walking Dead, The (1995)\n",
            "Walking and Talking (1996)\n",
            "Wallace & Gromit: The Best of Aardman Animation (1996)\n",
            "War Room, The (1993)\n",
            "War, The (1994)\n",
            "Warriors of Virtue (1997)\n",
            "Washington Square (1997)\n",
            "Waterworld (1995)\n",
            "Wedding Gift, The (1994)\n",
            "Wedding Singer, The (1998)\n",
            "Weekend at Bernie's (1989)\n",
            "Welcome To Sarajevo (1997)\n",
            "Welcome to the Dollhouse (1995)\n",
            "Wes Craven's New Nightmare (1994)\n",
            "What Happened Was... (1994)\n",
            "What's Eating Gilbert Grape (1993)\n",
            "What's Love Got to Do with It (1993)\n",
            "When Harry Met Sally... (1989)\n",
            "When Night Is Falling (1995)\n",
            "When We Were Kings (1996)\n",
            "When a Man Loves a Woman (1994)\n",
            "When the Cats Away (Chacun cherche son chat) (1996)\n",
            "While You Were Sleeping (1995)\n",
            "White Balloon, The (1995)\n",
            "White Man's Burden (1995)\n",
            "White Squall (1996)\n",
            "Whole Wide World, The (1996)\n",
            "Widows' Peak (1994)\n",
            "Wild America (1997)\n",
            "Wild Bill (1995)\n",
            "Wild Bunch, The (1969)\n",
            "Wild Reeds (1994)\n",
            "Wild Things (1998)\n",
            "William Shakespeare's Romeo and Juliet (1996)\n",
            "Willy Wonka and the Chocolate Factory (1971)\n",
            "Wings of Desire (1987)\n",
            "Wings of the Dove, The (1997)\n",
            "Winnie the Pooh and the Blustery Day (1968)\n",
            "Winter Guest, The (1997)\n",
            "Wishmaster (1997)\n",
            "With Honors (1994)\n",
            "Withnail and I (1987)\n",
            "Wizard of Oz, The (1939)\n",
            "Wolf (1994)\n",
            "Women, The (1939)\n",
            "Wonderful, Horrible Life of Leni Riefenstahl, The (1993)\n",
            "Wonderland (1997)\n",
            "Wooden Man's Bride, The (Wu Kui) (1994)\n",
            "World of Apu, The (Apur Sansar) (1959)\n",
            "Wrong Trousers, The (1993)\n",
            "Wyatt Earp (1994)\n",
            "Year of the Horse (1997)\n",
            "Young Frankenstein (1974)\n",
            "Young Guns (1988)\n",
            "Young Guns II (1990)\n",
            "Young Poisoner's Handbook, The (1995)\n",
            "Zeus and Roxanne (1997)\n",
            "unknown\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Check the result of data\n",
        "ratings.head()"
      ],
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        },
        "id": "kwMKWrZPxZuY",
        "outputId": "30368ef6-0eaa-4274-a44e-37cc10c60517"
      },
      "execution_count": 32,
      "outputs": [
        {
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          "data": {
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              "                             rating  numOfRatings FirstMovieRecommendation  \\\n",
              "title                                                                        \n",
              "'Til There Was You (1997)  2.333333             9         Edge, The (1997)   \n",
              "1-900 (1994)               2.600000             5   Full Monty, The (1997)   \n",
              "101 Dalmatians (1996)      2.908257           109    Murder at 1600 (1997)   \n",
              "12 Angry Men (1957)        4.344000           125       Ulee's Gold (1997)   \n",
              "187 (1997)                 3.024390            41          Maverick (1994)   \n",
              "\n",
              "                                               SecondMovieRecommendation  \\\n",
              "title                                                                      \n",
              "'Til There Was You (1997)  William Shakespeare's Romeo and Juliet (1996)   \n",
              "1-900 (1994)                                            Crow, The (1994)   \n",
              "101 Dalmatians (1996)                      Miracle on 34th Street (1994)   \n",
              "12 Angry Men (1957)                                   Rear Window (1954)   \n",
              "187 (1997)                                    Conan the Barbarian (1981)   \n",
              "\n",
              "                                      ThirdMovieRecommendation  \\\n",
              "title                                                            \n",
              "'Til There Was You (1997)  Star Trek: The Wrath of Khan (1982)   \n",
              "1-900 (1994)                             Ice Storm, The (1997)   \n",
              "101 Dalmatians (1996)                       Being There (1979)   \n",
              "12 Angry Men (1957)                Seven Years in Tibet (1997)   \n",
              "187 (1997)                       Magnificent Seven, The (1954)   \n",
              "\n",
              "                                FourthMovieRecommendation  \n",
              "title                                                      \n",
              "'Til There Was You (1997)                    Dumbo (1941)  \n",
              "1-900 (1994)                           Hoop Dreams (1994)  \n",
              "101 Dalmatians (1996)      Remains of the Day, The (1993)  \n",
              "12 Angry Men (1957)                         Clerks (1994)  \n",
              "187 (1997)                          Cool Hand Luke (1967)  "
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            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "ratings",
              "summary": "{\n  \"name\": \"ratings\",\n  \"rows\": 1664,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Tainted (1998)\",\n          \"Big Bully (1996)\",\n          \"Boys, Les (1997)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7804112593703867,\n        \"min\": 1.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          3.143835616438356,\n          2.125,\n          4.23121387283237\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"numOfRatings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 80,\n        \"min\": 1,\n        \"max\": 584,\n        \"num_unique_values\": 273,\n        \"samples\": [\n          32,\n          24,\n          86\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"FirstMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 297,\n        \"samples\": [\n          \"Ben-Hur (1959)\",\n          \"Reservoir Dogs (1992)\",\n          \"Fried Green Tomatoes (1991)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SecondMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 295,\n        \"samples\": [\n          \"Ed Wood (1994)\",\n          \"Fried Green Tomatoes (1991)\",\n          \"Batman Returns (1992)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ThirdMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 297,\n        \"samples\": [\n          \"My Best Friend's Wedding (1997)\",\n          \"Forrest Gump (1994)\",\n          \"Star Trek III: The Search for Spock (1984)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"FourthMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 309,\n        \"samples\": [\n          \"Monty Python's Life of Brian (1979)\",\n          \"River Wild, The (1994)\",\n          \"Beavis and Butt-head Do America (1996)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Save the rating data for later use into csv file\n",
        "ratings.to_csv('MovieRecommendations.csv')"
      ],
      "metadata": {
        "id": "ZV7sP1Cnz_qw"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Load the Recommendation Data**"
      ],
      "metadata": {
        "id": "kP_P63fH0jYz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#load recommendation data\n",
        "df=pd.read_csv('MovieRecommendations.csv')\n",
        "df.head()"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 365
        },
        "id": "x_Zg-FZM0a3q",
        "outputId": "42950925-1085-4928-ab04-e96abde40679"
      },
      "execution_count": 34,
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              "                       title    rating  numOfRatings FirstMovieRecommendation  \\\n",
              "0  'Til There Was You (1997)  2.333333             9         Edge, The (1997)   \n",
              "1               1-900 (1994)  2.600000             5   Full Monty, The (1997)   \n",
              "2      101 Dalmatians (1996)  2.908257           109    Murder at 1600 (1997)   \n",
              "3        12 Angry Men (1957)  4.344000           125       Ulee's Gold (1997)   \n",
              "4                 187 (1997)  3.024390            41          Maverick (1994)   \n",
              "\n",
              "                       SecondMovieRecommendation  \\\n",
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              "1                               Crow, The (1994)   \n",
              "2                  Miracle on 34th Street (1994)   \n",
              "3                             Rear Window (1954)   \n",
              "4                     Conan the Barbarian (1981)   \n",
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              "              ThirdMovieRecommendation       FourthMovieRecommendation  \n",
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              "1                Ice Storm, The (1997)              Hoop Dreams (1994)  \n",
              "2                   Being There (1979)  Remains of the Day, The (1993)  \n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>'Til There Was You (1997)</td>\n",
              "      <td>2.333333</td>\n",
              "      <td>9</td>\n",
              "      <td>Edge, The (1997)</td>\n",
              "      <td>William Shakespeare's Romeo and Juliet (1996)</td>\n",
              "      <td>Star Trek: The Wrath of Khan (1982)</td>\n",
              "      <td>Dumbo (1941)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1-900 (1994)</td>\n",
              "      <td>2.600000</td>\n",
              "      <td>5</td>\n",
              "      <td>Full Monty, The (1997)</td>\n",
              "      <td>Crow, The (1994)</td>\n",
              "      <td>Ice Storm, The (1997)</td>\n",
              "      <td>Hoop Dreams (1994)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>101 Dalmatians (1996)</td>\n",
              "      <td>2.908257</td>\n",
              "      <td>109</td>\n",
              "      <td>Murder at 1600 (1997)</td>\n",
              "      <td>Miracle on 34th Street (1994)</td>\n",
              "      <td>Being There (1979)</td>\n",
              "      <td>Remains of the Day, The (1993)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>12 Angry Men (1957)</td>\n",
              "      <td>4.344000</td>\n",
              "      <td>125</td>\n",
              "      <td>Ulee's Gold (1997)</td>\n",
              "      <td>Rear Window (1954)</td>\n",
              "      <td>Seven Years in Tibet (1997)</td>\n",
              "      <td>Clerks (1994)</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>187 (1997)</td>\n",
              "      <td>3.024390</td>\n",
              "      <td>41</td>\n",
              "      <td>Maverick (1994)</td>\n",
              "      <td>Conan the Barbarian (1981)</td>\n",
              "      <td>Magnificent Seven, The (1954)</td>\n",
              "      <td>Cool Hand Luke (1967)</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
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              "  }\n",
              "</style>\n",
              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 1664,\n  \"fields\": [\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1664,\n        \"samples\": [\n          \"Tainted (1998)\",\n          \"Big Bully (1996)\",\n          \"Boys, Les (1997)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"rating\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.7804112593703867,\n        \"min\": 1.0,\n        \"max\": 5.0,\n        \"num_unique_values\": 896,\n        \"samples\": [\n          3.143835616438356,\n          2.125,\n          4.23121387283237\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"numOfRatings\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 80,\n        \"min\": 1,\n        \"max\": 584,\n        \"num_unique_values\": 273,\n        \"samples\": [\n          32,\n          24,\n          86\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"FirstMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 296,\n        \"samples\": [\n          \"Mighty Aphrodite (1995)\",\n          \"Chinatown (1974)\",\n          \"On Golden Pond (1981)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"SecondMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 294,\n        \"samples\": [\n          \"Cinderella (1950)\",\n          \"Rainmaker, The (1997)\",\n          \"Michael (1996)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ThirdMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 296,\n        \"samples\": [\n          \"Postino, Il (1994)\",\n          \"Outbreak (1995)\",\n          \"Room with a View, A (1986)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"FourthMovieRecommendation\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 308,\n        \"samples\": [\n          \"Grease (1978)\",\n          \"Close Shave, A (1995)\",\n          \"Abyss, The (1989)\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for a in df['title']:\n",
        "  print(a)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AZ0h-gcN05mx",
        "outputId": "2100b410-f36a-4425-fdf3-a354cabd749a"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "'Til There Was You (1997)\n",
            "1-900 (1994)\n",
            "101 Dalmatians (1996)\n",
            "12 Angry Men (1957)\n",
            "187 (1997)\n",
            "2 Days in the Valley (1996)\n",
            "20,000 Leagues Under the Sea (1954)\n",
            "2001: A Space Odyssey (1968)\n",
            "3 Ninjas: High Noon At Mega Mountain (1998)\n",
            "39 Steps, The (1935)\n",
            "8 1/2 (1963)\n",
            "8 Heads in a Duffel Bag (1997)\n",
            "8 Seconds (1994)\n",
            "A Chef in Love (1996)\n",
            "Above the Rim (1994)\n",
            "Absolute Power (1997)\n",
            "Abyss, The (1989)\n",
            "Ace Ventura: Pet Detective (1994)\n",
            "Ace Ventura: When Nature Calls (1995)\n",
            "Across the Sea of Time (1995)\n",
            "Addams Family Values (1993)\n",
            "Addicted to Love (1997)\n",
            "Addiction, The (1995)\n",
            "Adventures of Pinocchio, The (1996)\n",
            "Adventures of Priscilla, Queen of the Desert, The (1994)\n",
            "Adventures of Robin Hood, The (1938)\n",
            "Affair to Remember, An (1957)\n",
            "African Queen, The (1951)\n",
            "Afterglow (1997)\n",
            "Age of Innocence, The (1993)\n",
            "Aiqing wansui (1994)\n",
            "Air Bud (1997)\n",
            "Air Force One (1997)\n",
            "Air Up There, The (1994)\n",
            "Airheads (1994)\n",
            "Akira (1988)\n",
            "Aladdin (1992)\n",
            "Aladdin and the King of Thieves (1996)\n",
            "Alaska (1996)\n",
            "Albino Alligator (1996)\n",
            "Alice in Wonderland (1951)\n",
            "Alien (1979)\n",
            "Alien 3 (1992)\n",
            "Alien: Resurrection (1997)\n",
            "Aliens (1986)\n",
            "All About Eve (1950)\n",
            "All Dogs Go to Heaven 2 (1996)\n",
            "All Over Me (1997)\n",
            "All Things Fair (1996)\n",
            "Alphaville (1965)\n",
            "Amadeus (1984)\n",
            "Amateur (1994)\n",
            "Amazing Panda Adventure, The (1995)\n",
            "American Buffalo (1996)\n",
            "American Dream (1990)\n",
            "American President, The (1995)\n",
            "American Strays (1996)\n",
            "American Werewolf in London, An (1981)\n",
            "American in Paris, An (1951)\n",
            "Amistad (1997)\n",
            "Amityville 1992: It's About Time (1992)\n",
            "Amityville 3-D (1983)\n",
            "Amityville Curse, The (1990)\n",
            "Amityville Horror, The (1979)\n",
            "Amityville II: The Possession (1982)\n",
            "Amityville: A New Generation (1993)\n",
            "Amityville: Dollhouse (1996)\n",
            "Amos & Andrew (1993)\n",
            "An Unforgettable Summer (1994)\n",
            "Anaconda (1997)\n",
            "Anastasia (1997)\n",
            "Andre (1994)\n",
            "Angel Baby (1995)\n",
            "Angel and the Badman (1947)\n",
            "Angel on My Shoulder (1946)\n",
            "Angela (1995)\n",
            "Angels and Insects (1995)\n",
            "Angels in the Outfield (1994)\n",
            "Angus (1995)\n",
            "Anna (1996)\n",
            "Anna Karenina (1997)\n",
            "Anne Frank Remembered (1995)\n",
            "Annie Hall (1977)\n",
            "Another Stakeout (1993)\n",
            "Antonia's Line (1995)\n",
            "Aparajito (1956)\n",
            "Apartment, The (1960)\n",
            "Apocalypse Now (1979)\n",
            "Apollo 13 (1995)\n",
            "Apostle, The (1997)\n",
            "Apple Dumpling Gang, The (1975)\n",
            "April Fool's Day (1986)\n",
            "Apt Pupil (1998)\n",
            "Aristocats, The (1970)\n",
            "Army of Darkness (1993)\n",
            "Around the World in 80 Days (1956)\n",
            "Arrival, The (1996)\n",
            "Arsenic and Old Lace (1944)\n",
            "As Good As It Gets (1997)\n",
            "Assassins (1995)\n",
            "Assignment, The (1997)\n",
            "Associate, The (1996)\n",
            "Audrey Rose (1977)\n",
            "August (1996)\n",
            "Austin Powers: International Man of Mystery (1997)\n",
            "Awfully Big Adventure, An (1995)\n",
            "Ayn Rand: A Sense of Life (1997)\n",
            "B*A*P*S (1997)\n",
            "B. Monkey (1998)\n",
            "Babe (1995)\n",
            "Baby-Sitters Club, The (1995)\n",
            "Babyfever (1994)\n",
            "Babysitter, The (1995)\n",
            "Back to the Future (1985)\n",
            "Backbeat (1993)\n",
            "Bad Boys (1995)\n",
            "Bad Company (1995)\n",
            "Bad Girls (1994)\n",
            "Bad Moon (1996)\n",
            "Bad Taste (1987)\n",
            "Ballad of Narayama, The (Narayama Bushiko) (1958)\n",
            "Balto (1995)\n",
            "Bananas (1971)\n",
            "Band Wagon, The (1953)\n",
            "Barb Wire (1996)\n",
            "Barbarella (1968)\n",
            "Barcelona (1994)\n",
            "Basic Instinct (1992)\n",
            "Basketball Diaries, The (1995)\n",
            "Basquiat (1996)\n",
            "Bastard Out of Carolina (1996)\n",
            "Batman & Robin (1997)\n",
            "Batman (1989)\n",
            "Batman Forever (1995)\n",
            "Batman Returns (1992)\n",
            "Baton Rouge (1988)\n",
            "Bean (1997)\n",
            "Beans of Egypt, Maine, The (1994)\n",
            "Beat the Devil (1954)\n",
            "Beautician and the Beast, The (1997)\n",
            "Beautiful Girls (1996)\n",
            "Beautiful Thing (1996)\n",
            "Beauty and the Beast (1991)\n",
            "Beavis and Butt-head Do America (1996)\n",
            "Bed of Roses (1996)\n",
            "Bedknobs and Broomsticks (1971)\n",
            "Before Sunrise (1995)\n",
            "Before and After (1996)\n",
            "Before the Rain (Pred dozhdot) (1994)\n",
            "Being Human (1993)\n",
            "Being There (1979)\n",
            "Believers, The (1987)\n",
            "Belle de jour (1967)\n",
            "Ben-Hur (1959)\n",
            "Benny & Joon (1993)\n",
            "Bent (1997)\n",
            "Best Men (1997)\n",
            "Best of the Best 3: No Turning Back (1995)\n",
            "Better Off Dead... (1985)\n",
            "Beverly Hillbillies, The (1993)\n",
            "Beverly Hills Cop III (1994)\n",
            "Beverly Hills Ninja (1997)\n",
            "Bewegte Mann, Der (1994)\n",
            "Beyond Bedlam (1993)\n",
            "Beyond Rangoon (1995)\n",
            "Bhaji on the Beach (1993)\n",
            "Big Bang Theory, The (1994)\n",
            "Big Blue, The (Grand bleu, Le) (1988)\n",
            "Big Bully (1996)\n",
            "Big Green, The (1995)\n",
            "Big Lebowski, The (1998)\n",
            "Big Night (1996)\n",
            "Big One, The (1997)\n",
            "Big Sleep, The (1946)\n",
            "Big Squeeze, The (1996)\n",
            "Billy Madison (1995)\n",
            "Bio-Dome (1996)\n",
            "Bird of Prey (1996)\n",
            "Birdcage, The (1996)\n",
            "Birds, The (1963)\n",
            "Bitter Moon (1992)\n",
            "Bitter Sugar (Azucar Amargo) (1996)\n",
            "Black Beauty (1994)\n",
            "Black Sheep (1996)\n",
            "Blade Runner (1982)\n",
            "Blink (1994)\n",
            "Bliss (1997)\n",
            "Blob, The (1958)\n",
            "Blood & Wine (1997)\n",
            "Blood Beach (1981)\n",
            "Blood For Dracula (Andy Warhol's Dracula) (1974)\n",
            "Bloodsport 2 (1995)\n",
            "Bloody Child, The (1996)\n",
            "Blown Away (1994)\n",
            "Blue Angel, The (Blaue Engel, Der) (1930)\n",
            "Blue Chips (1994)\n",
            "Blue Sky (1994)\n",
            "Blue in the Face (1995)\n",
            "Blues Brothers 2000 (1998)\n",
            "Blues Brothers, The (1980)\n",
            "Bob Roberts (1992)\n",
            "Body Parts (1991)\n",
            "Body Snatcher, The (1945)\n",
            "Body Snatchers (1993)\n",
            "Bogus (1996)\n",
            "Bonheur, Le (1965)\n",
            "Bonnie and Clyde (1967)\n",
            "Boogie Nights (1997)\n",
            "Boomerang (1992)\n",
            "Boot, Das (1981)\n",
            "Booty Call (1997)\n",
            "Bottle Rocket (1996)\n",
            "Bound (1996)\n",
            "Boxing Helena (1993)\n",
            "Boy's Life 2 (1997)\n",
            "Boys (1996)\n",
            "Boys Life (1995)\n",
            "Boys in Venice (1996)\n",
            "Boys of St. Vincent, The (1993)\n",
            "Boys on the Side (1995)\n",
            "Boys, Les (1997)\n",
            "Brady Bunch Movie, The (1995)\n",
            "Braindead (1992)\n",
            "Bram Stoker's Dracula (1992)\n",
            "Brassed Off (1996)\n",
            "Braveheart (1995)\n",
            "Brazil (1985)\n",
            "Bread and Chocolate (Pane e cioccolata) (1973)\n",
            "Breakdown (1997)\n",
            "Breakfast at Tiffany's (1961)\n",
            "Breaking the Waves (1996)\n",
            "Bride of Frankenstein (1935)\n",
            "Bridge on the River Kwai, The (1957)\n",
            "Bridges of Madison County, The (1995)\n",
            "Bringing Up Baby (1938)\n",
            "Broken Arrow (1996)\n",
            "Broken English (1996)\n",
            "Bronx Tale, A (1993)\n",
            "Brother Minister: The Assassination of Malcolm X (1994)\n",
            "Brother's Kiss, A (1997)\n",
            "Brothers McMullen, The (1995)\n",
            "Brothers in Trouble (1995)\n",
            "Browning Version, The (1994)\n",
            "Buddy (1997)\n",
            "Bulletproof (1996)\n",
            "Bullets Over Broadway (1994)\n",
            "Burnt By the Sun (1994)\n",
            "Burnt Offerings (1976)\n",
            "Bushwhacked (1995)\n",
            "Butch Cassidy and the Sundance Kid (1969)\n",
            "Butcher Boy, The (1998)\n",
            "Butterfly Kiss (1995)\n",
            "Bye Bye, Love (1995)\n",
            "C'est arrivé près de chez vous (1992)\n",
            "Cabin Boy (1994)\n",
            "Cable Guy, The (1996)\n",
            "Calendar Girl (1993)\n",
            "Canadian Bacon (1994)\n",
            "Candidate, The (1972)\n",
            "Candyman (1992)\n",
            "Candyman: Farewell to the Flesh (1995)\n",
            "Cape Fear (1962)\n",
            "Cape Fear (1991)\n",
            "Captives (1994)\n",
            "Career Girls (1997)\n",
            "Careful (1992)\n",
            "Carlito's Way (1993)\n",
            "Carmen Miranda: Bananas Is My Business (1994)\n",
            "Caro Diario (Dear Diary) (1994)\n",
            "Carpool (1996)\n",
            "Carrie (1976)\n",
            "Carried Away (1996)\n",
            "Carrington (1995)\n",
            "Casablanca (1942)\n",
            "Casino (1995)\n",
            "Casper (1995)\n",
            "Castle Freak (1995)\n",
            "Cat People (1982)\n",
            "Cat on a Hot Tin Roof (1958)\n",
            "Cats Don't Dance (1997)\n",
            "Catwalk (1995)\n",
            "Caught (1996)\n",
            "Celestial Clockwork (1994)\n",
            "Celluloid Closet, The (1995)\n",
            "Celtic Pride (1996)\n",
            "Cement Garden, The (1993)\n",
            "Cemetery Man (Dellamorte Dellamore) (1994)\n",
            "Century (1993)\n",
            "Chain Reaction (1996)\n",
            "Chairman of the Board (1998)\n",
            "Chamber, The (1996)\n",
            "Charade (1963)\n",
            "Chasers (1994)\n",
            "Chasing Amy (1997)\n",
            "Children of the Corn: The Gathering (1996)\n",
            "Children of the Revolution (1996)\n",
            "Chinatown (1974)\n",
            "Christmas Carol, A (1938)\n",
            "Chungking Express (1994)\n",
            "Ciao, Professore! (1993)\n",
            "Cinderella (1950)\n",
            "Cinema Paradiso (1988)\n",
            "Circle of Friends (1995)\n",
            "Citizen Kane (1941)\n",
            "Citizen Ruth (1996)\n",
            "City Hall (1996)\n",
            "City Slickers II: The Legend of Curly's Gold (1994)\n",
            "City of Angels (1998)\n",
            "City of Industry (1997)\n",
            "City of Lost Children, The (1995)\n",
            "Clean Slate (1994)\n",
            "Clean Slate (Coup de Torchon) (1981)\n",
            "Clear and Present Danger (1994)\n",
            "Clerks (1994)\n",
            "Client, The (1994)\n",
            "Cliffhanger (1993)\n",
            "Clockers (1995)\n",
            "Clockwork Orange, A (1971)\n",
            "Close Shave, A (1995)\n",
            "Clueless (1995)\n",
            "Cobb (1994)\n",
            "Cold Comfort Farm (1995)\n",
            "Coldblooded (1995)\n",
            "Collectionneuse, La (1967)\n",
            "Colonel Chabert, Le (1994)\n",
            "Color of Night (1994)\n",
            "Commandments (1997)\n",
            "Con Air (1997)\n",
            "Conan the Barbarian (1981)\n",
            "Condition Red (1995)\n",
            "Coneheads (1993)\n",
            "Congo (1995)\n",
            "Conspiracy Theory (1997)\n",
            "Contact (1997)\n",
            "Contempt (Mépris, Le) (1963)\n",
            "Convent, The (Convento, O) (1995)\n",
            "Cook the Thief His Wife & Her Lover, The (1989)\n",
            "Cool Hand Luke (1967)\n",
            "Cool Runnings (1993)\n",
            "Cop Land (1997)\n",
            "Cops and Robbersons (1994)\n",
            "Copycat (1995)\n",
            "Corrina, Corrina (1994)\n",
            "Cosi (1996)\n",
            "Country Life (1994)\n",
            "Courage Under Fire (1996)\n",
            "Cowboy Way, The (1994)\n",
            "Craft, The (1996)\n",
            "Crash (1996)\n",
            "Crimson Tide (1995)\n",
            "Critical Care (1997)\n",
            "Cronos (1992)\n",
            "Crooklyn (1994)\n",
            "Crossfire (1947)\n",
            "Crossing Guard, The (1995)\n",
            "Crow, The (1994)\n",
            "Crow: City of Angels, The (1996)\n",
            "Crows and Sparrows (1949)\n",
            "Crucible, The (1996)\n",
            "Crude Oasis, The (1995)\n",
            "Crumb (1994)\n",
            "Cry, the Beloved Country (1995)\n",
            "Crying Game, The (1992)\n",
            "Curdled (1996)\n",
            "Cure, The (1995)\n",
            "Cutthroat Island (1995)\n",
            "Cyclo (1995)\n",
            "Cyrano de Bergerac (1990)\n",
            "Cérémonie, La (1995)\n",
            "D3: The Mighty Ducks (1996)\n",
            "Dadetown (1995)\n",
            "Daens (1992)\n",
            "Damsel in Distress, A (1937)\n",
            "Dances with Wolves (1990)\n",
            "Dangerous Beauty (1998)\n",
            "Dangerous Ground (1997)\n",
            "Dangerous Minds (1995)\n",
            "Daniel Defoe's Robinson Crusoe (1996)\n",
            "Dante's Peak (1997)\n",
            "Dark City (1998)\n",
            "Dave (1993)\n",
            "Davy Crockett, King of the Wild Frontier (1955)\n",
            "Day the Earth Stood Still, The (1951)\n",
            "Day the Sun Turned Cold, The (Tianguo niezi) (1994)\n",
            "Daylight (1996)\n",
            "Days of Thunder (1990)\n",
            "Daytrippers, The (1996)\n",
            "Dazed and Confused (1993)\n",
            "Dead Man (1995)\n",
            "Dead Man Walking (1995)\n",
            "Dead Poets Society (1989)\n",
            "Dead Presidents (1995)\n",
            "Dear God (1996)\n",
            "Death and the Maiden (1994)\n",
            "Death in Brunswick (1991)\n",
            "Death in the Garden (Mort en ce jardin, La) (1956)\n",
            "Deceiver (1997)\n",
            "Deconstructing Harry (1997)\n",
            "Deep Rising (1998)\n",
            "Deer Hunter, The (1978)\n",
            "Delicatessen (1991)\n",
            "Delta of Venus (1994)\n",
            "Demolition Man (1993)\n",
            "Denise Calls Up (1995)\n",
            "Desert Winds (1995)\n",
            "Designated Mourner, The (1997)\n",
            "Desperado (1995)\n",
            "Desperate Measures (1998)\n",
            "Destiny Turns on the Radio (1995)\n",
            "Devil in a Blue Dress (1995)\n",
            "Devil's Advocate, The (1997)\n",
            "Devil's Own, The (1997)\n",
            "Diabolique (1996)\n",
            "Dial M for Murder (1954)\n",
            "Die Hard (1988)\n",
            "Die Hard 2 (1990)\n",
            "Die Hard: With a Vengeance (1995)\n",
            "Die xue shuang xiong (Killer, The) (1989)\n",
            "Dingo (1992)\n",
            "Dirty Dancing (1987)\n",
            "Disclosure (1994)\n",
            "Diva (1981)\n",
            "Dolores Claiborne (1994)\n",
            "Don Juan DeMarco (1995)\n",
            "Don't Be a Menace to South Central While Drinking Your Juice in the Hood (1996)\n",
            "Donnie Brasco (1997)\n",
            "Doom Generation, The (1995)\n",
            "Doors, The (1991)\n",
            "Double Happiness (1994)\n",
            "Double Team (1997)\n",
            "Double vie de Véronique, La (Double Life of Veronique, The) (1991)\n",
            "Down Periscope (1996)\n",
            "Down by Law (1986)\n",
            "Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb (1963)\n",
            "Dracula: Dead and Loving It (1995)\n",
            "Dragonheart (1996)\n",
            "Dream Man (1995)\n",
            "Dream With the Fishes (1997)\n",
            "Drop Dead Fred (1991)\n",
            "Drop Zone (1994)\n",
            "Drunks (1995)\n",
            "Duck Soup (1933)\n",
            "Dumb & Dumber (1994)\n",
            "Dumbo (1941)\n",
            "Dunston Checks In (1996)\n",
            "Duoluo tianshi (1995)\n",
            "E.T. the Extra-Terrestrial (1982)\n",
            "East of Eden (1955)\n",
            "Eat Drink Man Woman (1994)\n",
            "Ed (1996)\n",
            "Ed Wood (1994)\n",
            "Ed's Next Move (1996)\n",
            "Eddie (1996)\n",
            "Edge, The (1997)\n",
            "Eighth Day, The (1996)\n",
            "Emma (1996)\n",
            "Empire Strikes Back, The (1980)\n",
            "Enchanted April (1991)\n",
            "Endless Summer 2, The (1994)\n",
            "Enfer, L' (1994)\n",
            "English Patient, The (1996)\n",
            "Englishman Who Went Up a Hill, But Came Down a Mountain, The (1995)\n",
            "Entertaining Angels: The Dorothy Day Story (1996)\n",
            "Eraser (1996)\n",
            "Escape from L.A. (1996)\n",
            "Escape from New York (1981)\n",
            "Escape to Witch Mountain (1975)\n",
            "Etz Hadomim Tafus (Under the Domin Tree) (1994)\n",
            "Eve's Bayou (1997)\n",
            "Even Cowgirls Get the Blues (1993)\n",
            "Evening Star, The (1996)\n",
            "Event Horizon (1997)\n",
            "Everest (1998)\n",
            "Every Other Weekend (1990)\n",
            "Everyone Says I Love You (1996)\n",
            "Evil Dead II (1987)\n",
            "Evita (1996)\n",
            "Excess Baggage (1997)\n",
            "Executive Decision (1996)\n",
            "Exit to Eden (1994)\n",
            "Exotica (1994)\n",
            "Extreme Measures (1996)\n",
            "Eye for an Eye (1996)\n",
            "Eye of Vichy, The (Oeil de Vichy, L') (1993)\n",
            "Face/Off (1997)\n",
            "Faces (1968)\n",
            "Fair Game (1995)\n",
            "FairyTale: A True Story (1997)\n",
            "Faithful (1996)\n",
            "Fall (1997)\n",
            "Fallen (1998)\n",
            "Falling in Love Again (1980)\n",
            "Family Thing, A (1996)\n",
            "Fan, The (1996)\n",
            "Fantasia (1940)\n",
            "Far From Home: The Adventures of Yellow Dog (1995)\n",
            "Farewell My Concubine (1993)\n",
            "Farewell to Arms, A (1932)\n",
            "Fargo (1996)\n",
            "Farinelli: il castrato (1994)\n",
            "Farmer & Chase (1995)\n",
            "Fast, Cheap & Out of Control (1997)\n",
            "Faster Pussycat! Kill! Kill! (1965)\n",
            "Fatal Instinct (1993)\n",
            "Father of the Bride (1950)\n",
            "Father of the Bride Part II (1995)\n",
            "Fathers' Day (1997)\n",
            "Faust (1994)\n",
            "Fausto (1993)\n",
            "Favor, The (1994)\n",
            "Fear (1996)\n",
            "Fear of a Black Hat (1993)\n",
            "Fear, The (1995)\n",
            "Fearless (1993)\n",
            "Feast of July (1995)\n",
            "Feeling Minnesota (1996)\n",
            "Female Perversions (1996)\n",
            "Field of Dreams (1989)\n",
            "Fierce Creatures (1997)\n",
            "Fifth Element, The (1997)\n",
            "Fille seule, La (A Single Girl) (1995)\n",
            "Fire Down Below (1997)\n",
            "Fire on the Mountain (1996)\n",
            "Firestorm (1998)\n",
            "Firm, The (1993)\n",
            "First Kid (1996)\n",
            "First Knight (1995)\n",
            "First Wives Club, The (1996)\n",
            "Fish Called Wanda, A (1988)\n",
            "Fled (1996)\n",
            "Flesh and Bone (1993)\n",
            "Flintstones, The (1994)\n",
            "Flipper (1996)\n",
            "Flirt (1995)\n",
            "Flirting With Disaster (1996)\n",
            "Flower of My Secret, The (Flor de mi secreto, La) (1995)\n",
            "Flubber (1997)\n",
            "Fluke (1995)\n",
            "Fly Away Home (1996)\n",
            "Fog, The (1980)\n",
            "Fools Rush In (1997)\n",
            "For Ever Mozart (1996)\n",
            "For Love or Money (1993)\n",
            "For Richer or Poorer (1997)\n",
            "For Whom the Bell Tolls (1943)\n",
            "For the Moment (1994)\n",
            "Forbidden Christ, The (Cristo proibito, Il) (1950)\n",
            "Forbidden Planet (1956)\n",
            "Foreign Correspondent (1940)\n",
            "Foreign Student (1994)\n",
            "Forget Paris (1995)\n",
            "Forrest Gump (1994)\n",
            "Four Days in September (1997)\n",
            "Four Rooms (1995)\n",
            "Four Weddings and a Funeral (1994)\n",
            "Fox and the Hound, The (1981)\n",
            "Foxfire (1996)\n",
            "Frankie Starlight (1995)\n",
            "Free Willy (1993)\n",
            "Free Willy 2: The Adventure Home (1995)\n",
            "Free Willy 3: The Rescue (1997)\n",
            "Freeway (1996)\n",
            "French Kiss (1995)\n",
            "French Twist (Gazon maudit) (1995)\n",
            "Fresh (1994)\n",
            "Friday (1995)\n",
            "Fried Green Tomatoes (1991)\n",
            "Frighteners, The (1996)\n",
            "Frisk (1995)\n",
            "From Dusk Till Dawn (1996)\n",
            "Fugitive, The (1993)\n",
            "Full Metal Jacket (1987)\n",
            "Full Monty, The (1997)\n",
            "Full Speed (1996)\n",
            "Funeral, The (1996)\n",
            "Funny Face (1957)\n",
            "Further Gesture, A (1996)\n",
            "G.I. Jane (1997)\n",
            "Gabbeh (1996)\n",
            "Game, The (1997)\n",
            "Gandhi (1982)\n",
            "Gang Related (1997)\n",
            "Garden of Finzi-Contini, The (Giardino dei Finzi-Contini, Il) (1970)\n",
            "Gaslight (1944)\n",
            "Gate of Heavenly Peace, The (1995)\n",
            "Gattaca (1997)\n",
            "Gay Divorcee, The (1934)\n",
            "George of the Jungle (1997)\n",
            "Georgia (1995)\n",
            "Germinal (1993)\n",
            "Geronimo: An American Legend (1993)\n",
            "Get Shorty (1995)\n",
            "Get on the Bus (1996)\n",
            "Getaway, The (1994)\n",
            "Getting Away With Murder (1996)\n",
            "Getting Even with Dad (1994)\n",
            "Ghost (1990)\n",
            "Ghost and Mrs. Muir, The (1947)\n",
            "Ghost and the Darkness, The (1996)\n",
            "Ghost in the Shell (Kokaku kidotai) (1995)\n",
            "Ghosts of Mississippi (1996)\n",
            "Giant (1956)\n",
            "Gigi (1958)\n",
            "Gilligan's Island: The Movie (1998)\n",
            "Girl 6 (1996)\n",
            "Girl in the Cadillac (1995)\n",
            "Girls Town (1996)\n",
            "Glass Shield, The (1994)\n",
            "Glengarry Glen Ross (1992)\n",
            "Glimmer Man, The (1996)\n",
            "Glory (1989)\n",
            "Go Fish (1994)\n",
            "Godfather, The (1972)\n",
            "Godfather: Part II, The (1974)\n",
            "Gold Diggers: The Secret of Bear Mountain (1995)\n",
            "Golden Earrings (1947)\n",
            "GoldenEye (1995)\n",
            "Gone Fishin' (1997)\n",
            "Gone with the Wind (1939)\n",
            "Good Man in Africa, A (1994)\n",
            "Good Morning (1971)\n",
            "Good Will Hunting (1997)\n",
            "Good, The Bad and The Ugly, The (1966)\n",
            "GoodFellas (1990)\n",
            "Goofy Movie, A (1995)\n",
            "Gordy (1995)\n",
            "Grace of My Heart (1996)\n",
            "Graduate, The (1967)\n",
            "Grand Day Out, A (1992)\n",
            "Grass Harp, The (1995)\n",
            "Grateful Dead (1995)\n",
            "Grease (1978)\n",
            "Grease 2 (1982)\n",
            "Great Day in Harlem, A (1994)\n",
            "Great Dictator, The (1940)\n",
            "Great Escape, The (1963)\n",
            "Great Expectations (1998)\n",
            "Great Race, The (1965)\n",
            "Great White Hype, The (1996)\n",
            "Gridlock'd (1997)\n",
            "Grifters, The (1990)\n",
            "Grosse Fatigue (1994)\n",
            "Grosse Pointe Blank (1997)\n",
            "Groundhog Day (1993)\n",
            "Grumpier Old Men (1995)\n",
            "Guantanamera (1994)\n",
            "Guilty as Sin (1993)\n",
            "Gumby: The Movie (1995)\n",
            "Hackers (1995)\n",
            "Half Baked (1998)\n",
            "Halloween: The Curse of Michael Myers (1995)\n",
            "Hamlet (1996)\n",
            "Hana-bi (1997)\n",
            "Happy Gilmore (1996)\n",
            "Hard Eight (1996)\n",
            "Hard Rain (1998)\n",
            "Hard Target (1993)\n",
            "Harlem (1993)\n",
            "Harold and Maude (1971)\n",
            "Harriet the Spy (1996)\n",
            "Hate (Haine, La) (1995)\n",
            "Haunted World of Edward D. Wood Jr., The (1995)\n",
            "He Walked by Night (1948)\n",
            "Head Above Water (1996)\n",
            "Hear My Song (1991)\n",
            "Hearts and Minds (1996)\n",
            "Heat (1995)\n",
            "Heathers (1989)\n",
            "Heaven & Earth (1993)\n",
            "Heaven's Prisoners (1996)\n",
            "Heavenly Creatures (1994)\n",
            "Heavy (1995)\n",
            "Heavy Metal (1981)\n",
            "Heavyweights (1994)\n",
            "Hedd Wyn (1992)\n",
            "Heidi Fleiss: Hollywood Madam (1995) \n",
            "Hellraiser: Bloodline (1996)\n",
            "Henry V (1989)\n",
            "Herbie Rides Again (1974)\n",
            "Hercules (1997)\n",
            "Here Comes Cookie (1935)\n",
            "Hideaway (1995)\n",
            "High Noon (1952)\n",
            "High School High (1996)\n",
            "Higher Learning (1995)\n",
            "Highlander (1986)\n",
            "Highlander III: The Sorcerer (1994)\n",
            "His Girl Friday (1940)\n",
            "Hollow Reed (1996)\n",
            "Homage (1995)\n",
            "Home Alone (1990)\n",
            "Home Alone 3 (1997)\n",
            "Home for the Holidays (1995)\n",
            "Homeward Bound II: Lost in San Francisco (1996)\n",
            "Homeward Bound: The Incredible Journey (1993)\n",
            "Hoodlum (1997)\n",
            "Hoop Dreams (1994)\n",
            "Horse Whisperer, The (1998)\n",
            "Horseman on the Roof, The (Hussard sur le toit, Le) (1995)\n",
            "Hostile Intentions (1994)\n",
            "Hot Shots! Part Deux (1993)\n",
            "Hotel de Love (1996)\n",
            "Hour of the Pig, The (1993)\n",
            "House Arrest (1996)\n",
            "House Party 3 (1994)\n",
            "House of Yes, The (1997)\n",
            "House of the Spirits, The (1993)\n",
            "Houseguest (1994)\n",
            "How to Be a Player (1997)\n",
            "How to Make an American Quilt (1995)\n",
            "Howling, The (1981)\n",
            "Hudsucker Proxy, The (1994)\n",
            "Hugo Pool (1997)\n",
            "Hunchback of Notre Dame, The (1996)\n",
            "Hungarian Fairy Tale, A (1987)\n",
            "Hunt for Red October, The (1990)\n",
            "Hunted, The (1995)\n",
            "Hurricane Streets (1998)\n",
            "Hush (1998)\n",
            "I Can't Sleep (J'ai pas sommeil) (1994)\n",
            "I Don't Want to Talk About It (De eso no se habla) (1993)\n",
            "I Know What You Did Last Summer (1997)\n",
            "I Like It Like That (1994)\n",
            "I Love Trouble (1994)\n",
            "I Shot Andy Warhol (1996)\n",
            "I'll Do Anything (1994)\n",
            "I'm Not Rappaport (1996)\n",
            "I, Worst of All (Yo, la peor de todas) (1990)\n",
            "I.Q. (1994)\n",
            "Ice Storm, The (1997)\n",
            "If Lucy Fell (1996)\n",
            "Ill Gotten Gains (1997)\n",
            "Immortal Beloved (1994)\n",
            "In & Out (1997)\n",
            "In Love and War (1996)\n",
            "In the Army Now (1994)\n",
            "In the Bleak Midwinter (1995)\n",
            "In the Company of Men (1997)\n",
            "In the Line of Duty 2 (1987)\n",
            "In the Line of Fire (1993)\n",
            "In the Mouth of Madness (1995)\n",
            "In the Name of the Father (1993)\n",
            "In the Realm of the Senses (Ai no corrida) (1976)\n",
            "Incognito (1997)\n",
            "Independence Day (ID4) (1996)\n",
            "Indian Summer (1996)\n",
            "Indian in the Cupboard, The (1995)\n",
            "Indiana Jones and the Last Crusade (1989)\n",
            "Infinity (1996)\n",
            "Inkwell, The (1994)\n",
            "Innocent Sleep, The (1995)\n",
            "Innocents, The (1961)\n",
            "Inspector General, The (1949)\n",
            "Interview with the Vampire (1994)\n",
            "Intimate Relations (1996)\n",
            "Inventing the Abbotts (1997)\n",
            "Invitation, The (Zaproszenie) (1986)\n",
            "Island of Dr. Moreau, The (1996)\n",
            "It Could Happen to You (1994)\n",
            "It Happened One Night (1934)\n",
            "It Takes Two (1995)\n",
            "It's My Party (1995)\n",
            "It's a Wonderful Life (1946)\n",
            "JLG/JLG - autoportrait de décembre (1994)\n",
            "Jack (1996)\n",
            "Jack and Sarah (1995)\n",
            "Jackal, The (1997)\n",
            "Jackie Brown (1997)\n",
            "Jackie Chan's First Strike (1996)\n",
            "Jade (1995)\n",
            "James and the Giant Peach (1996)\n",
            "Jane Eyre (1996)\n",
            "Jason's Lyric (1994)\n",
            "Jaws (1975)\n",
            "Jaws 2 (1978)\n",
            "Jaws 3-D (1983)\n",
            "Jean de Florette (1986)\n",
            "Jefferson in Paris (1995)\n",
            "Jeffrey (1995)\n",
            "Jerky Boys, The (1994)\n",
            "Jerry Maguire (1996)\n",
            "Jimmy Hollywood (1994)\n",
            "Jingle All the Way (1996)\n",
            "Joe's Apartment (1996)\n",
            "Johnny 100 Pesos (1993)\n",
            "Johnny Mnemonic (1995)\n",
            "Johns (1996)\n",
            "Journey of August King, The (1995)\n",
            "Joy Luck Club, The (1993)\n",
            "Jude (1996)\n",
            "Judge Dredd (1995)\n",
            "Judgment Night (1993)\n",
            "Jumanji (1995)\n",
            "Jungle Book, The (1994)\n",
            "Jungle2Jungle (1997)\n",
            "Junior (1994)\n",
            "Jupiter's Wife (1994)\n",
            "Jurassic Park (1993)\n",
            "Juror, The (1996)\n",
            "Jury Duty (1995)\n",
            "Just Cause (1995)\n",
            "Kalifornia (1993)\n",
            "Kama Sutra: A Tale of Love (1996)\n",
            "Kansas City (1996)\n",
            "Kaspar Hauser (1993)\n",
            "Kazaam (1996)\n",
            "Keys to Tulsa (1997)\n",
            "Kicked in the Head (1997)\n",
            "Kicking and Screaming (1995)\n",
            "Kid in King Arthur's Court, A (1995)\n",
            "Kids (1995)\n",
            "Kids in the Hall: Brain Candy (1996)\n",
            "Kika (1993)\n",
            "Killer (Bulletproof Heart) (1994)\n",
            "Killer: A Journal of Murder (1995)\n",
            "Killing Fields, The (1984)\n",
            "Killing Zoe (1994)\n",
            "Kim (1950)\n",
            "King of New York (1990)\n",
            "King of the Hill (1993)\n",
            "Kingpin (1996)\n",
            "Kiss Me, Guido (1997)\n",
            "Kiss of Death (1995)\n",
            "Kiss the Girls (1997)\n",
            "Kissed (1996)\n",
            "Kolya (1996)\n",
            "Koyaanisqatsi (1983)\n",
            "Kull the Conqueror (1997)\n",
            "Kundun (1997)\n",
            "L.A. Confidential (1997)\n",
            "Lady of Burlesque (1943)\n",
            "Ladybird Ladybird (1994)\n",
            "Lamerica (1994)\n",
            "Land Before Time III: The Time of the Great Giving (1995) (V)\n",
            "Land and Freedom (Tierra y libertad) (1995)\n",
            "Larger Than Life (1996)\n",
            "Lashou shentan (1992)\n",
            "Lassie (1994)\n",
            "Last Action Hero (1993)\n",
            "Last Dance (1996)\n",
            "Last Klezmer: Leopold Kozlowski, His Life and Music, The (1995)\n",
            "Last Man Standing (1996)\n",
            "Last Summer in the Hamptons (1995)\n",
            "Last Supper, The (1995)\n",
            "Last Time I Committed Suicide, The (1997)\n",
            "Last Time I Saw Paris, The (1954)\n",
            "Last of the Mohicans, The (1992)\n",
            "Late Bloomers (1996)\n",
            "Laura (1944)\n",
            "Lawnmower Man 2: Beyond Cyberspace (1996)\n",
            "Lawnmower Man, The (1992)\n",
            "Lawrence of Arabia (1962)\n",
            "Lay of the Land, The (1997)\n",
            "Leading Man, The (1996)\n",
            "Leave It to Beaver (1997)\n",
            "Leaving Las Vegas (1995)\n",
            "Legal Deceit (1997)\n",
            "Legends of the Fall (1994)\n",
            "Leopard Son, The (1996)\n",
            "Letter From Death Row, A (1998)\n",
            "Liar Liar (1997)\n",
            "Liebelei (1933)\n",
            "Life Less Ordinary, A (1997)\n",
            "Life with Mikey (1993)\n",
            "Lightning Jack (1994)\n",
            "Like Water For Chocolate (Como agua para chocolate) (1992)\n",
            "Line King: Al Hirschfeld, The (1996)\n",
            "Lion King, The (1994)\n",
            "Little Big League (1994)\n",
            "Little Buddha (1993)\n",
            "Little City (1998)\n",
            "Little Lord Fauntleroy (1936)\n",
            "Little Odessa (1994)\n",
            "Little Princess, A (1995)\n",
            "Little Princess, The (1939)\n",
            "Little Rascals, The (1994)\n",
            "Little Women (1994)\n",
            "Live Nude Girls (1995)\n",
            "Living in Oblivion (1995)\n",
            "Loaded (1994)\n",
            "Local Hero (1983)\n",
            "Loch Ness (1995)\n",
            "Locusts, The (1997)\n",
            "Lone Star (1996)\n",
            "Long Kiss Goodnight, The (1996)\n",
            "Looking for Richard (1996)\n",
            "Lord of Illusions (1995)\n",
            "Losing Chase (1996)\n",
            "Losing Isaiah (1995)\n",
            "Lost Highway (1997)\n",
            "Lost Horizon (1937)\n",
            "Lost World: Jurassic Park, The (1997)\n",
            "Lost in Space (1998)\n",
            "Lotto Land (1995)\n",
            "Love & Human Remains (1993)\n",
            "Love Affair (1994)\n",
            "Love Bug, The (1969)\n",
            "Love Is All There Is (1996)\n",
            "Love Jones (1997)\n",
            "Love Serenade (1996)\n",
            "Love and Death on Long Island (1997)\n",
            "Love and Other Catastrophes (1996)\n",
            "Love and a .45 (1994)\n",
            "Love in the Afternoon (1957)\n",
            "Love! Valour! Compassion! (1997)\n",
            "Lover's Knot (1996)\n",
            "Low Down Dirty Shame, A (1994)\n",
            "Low Life, The (1994)\n",
            "M (1931)\n",
            "M*A*S*H (1970)\n",
            "M. Butterfly (1993)\n",
            "MURDER and murder (1996)\n",
            "Ma vie en rose (My Life in Pink) (1997)\n",
            "Machine, The (1994)\n",
            "Mad City (1997)\n",
            "Mad Dog Time (1996)\n",
            "Mad Love (1995)\n",
            "Madame Butterfly (1995)\n",
            "Made in America (1993)\n",
            "Madness of King George, The (1994)\n",
            "Madonna: Truth or Dare (1991)\n",
            "Magic Hour, The (1998)\n",
            "Magnificent Seven, The (1954)\n",
            "Major Payne (1994)\n",
            "Malice (1993)\n",
            "Mallrats (1995)\n",
            "Maltese Falcon, The (1941)\n",
            "Mamma Roma (1962)\n",
            "Man Who Knew Too Little, The (1997)\n",
            "Man Who Would Be King, The (1975)\n",
            "Man Without a Face, The (1993)\n",
            "Man from Down Under, The (1943)\n",
            "Man in the Iron Mask, The (1998)\n",
            "Man of No Importance, A (1994)\n",
            "Man of the House (1995)\n",
            "Man of the Year (1995)\n",
            "Manchurian Candidate, The (1962)\n",
            "Manhattan (1979)\n",
            "Manhattan Murder Mystery (1993)\n",
            "Manny & Lo (1996)\n",
            "Manon of the Spring (Manon des sources) (1986)\n",
            "Margaret's Museum (1995)\n",
            "Mark of Zorro, The (1940)\n",
            "Marked for Death (1990)\n",
            "Marlene Dietrich: Shadow and Light (1996) \n",
            "Mars Attacks! (1996)\n",
            "Marvin's Room (1996)\n",
            "Mary Poppins (1964)\n",
            "Mary Reilly (1996)\n",
            "Mary Shelley's Frankenstein (1994)\n",
            "Mask, The (1994)\n",
            "Mat' i syn (1997)\n",
            "MatchMaker, The (1997)\n",
            "Matilda (1996)\n",
            "Maverick (1994)\n",
            "Maximum Risk (1996)\n",
            "Maya Lin: A Strong Clear Vision (1994)\n",
            "Maybe, Maybe Not (Bewegte Mann, Der) (1994)\n",
            "McHale's Navy (1997)\n",
            "Mediterraneo (1991)\n",
            "Meet John Doe (1941)\n",
            "Meet Me in St. Louis (1944)\n",
            "Meet Wally Sparks (1997)\n",
            "Men With Guns (1997)\n",
            "Men in Black (1997)\n",
            "Men of Means (1998)\n",
            "Menace II Society (1993)\n",
            "Mercury Rising (1998)\n",
            "Metisse (Café au Lait) (1993)\n",
            "Metro (1997)\n",
            "Miami Rhapsody (1995)\n",
            "Michael (1996)\n",
            "Michael Collins (1996)\n",
            "Microcosmos: Le peuple de l'herbe (1996)\n",
            "Midnight Dancers (Sibak) (1994)\n",
            "Midnight in the Garden of Good and Evil (1997)\n",
            "Mighty Aphrodite (1995)\n",
            "Mighty Morphin Power Rangers: The Movie (1995)\n",
            "Mighty, The (1998)\n",
            "Milk Money (1994)\n",
            "Mille bolle blu (1993)\n",
            "Miller's Crossing (1990)\n",
            "Mimic (1997)\n",
            "Mina Tannenbaum (1994)\n",
            "Miracle on 34th Street (1994)\n",
            "Mirage (1995)\n",
            "Mirror Has Two Faces, The (1996)\n",
            "Mission: Impossible (1996)\n",
            "Misérables, Les (1995)\n",
            "Mixed Nuts (1994)\n",
            "Modern Affair, A (1995)\n",
            "Moll Flanders (1996)\n",
            "Mondo (1996)\n",
            "Money Talks (1997)\n",
            "Money Train (1995)\n",
            "Month by the Lake, A (1995)\n",
            "Monty Python and the Holy Grail (1974)\n",
            "Monty Python's Life of Brian (1979)\n",
            "Moonlight and Valentino (1995)\n",
            "Mortal Kombat (1995)\n",
            "Mortal Kombat: Annihilation (1997)\n",
            "Mostro, Il (1994)\n",
            "Mother (1996)\n",
            "Mother Night (1996)\n",
            "Mouse Hunt (1997)\n",
            "Mr. Holland's Opus (1995)\n",
            "Mr. Jones (1993)\n",
            "Mr. Magoo (1997)\n",
            "Mr. Smith Goes to Washington (1939)\n",
            "Mr. Wonderful (1993)\n",
            "Mr. Wrong (1996)\n",
            "Mrs. Brown (Her Majesty, Mrs. Brown) (1997)\n",
            "Mrs. Dalloway (1997)\n",
            "Mrs. Doubtfire (1993)\n",
            "Mrs. Parker and the Vicious Circle (1994)\n",
            "Mrs. Winterbourne (1996)\n",
            "Much Ado About Nothing (1993)\n",
            "Mulholland Falls (1996)\n",
            "Multiplicity (1996)\n",
            "Muppet Treasure Island (1996)\n",
            "Murder at 1600 (1997)\n",
            "Murder in the First (1995)\n",
            "Murder, My Sweet (1944)\n",
            "Muriel's Wedding (1994)\n",
            "Mute Witness (1994)\n",
            "My Best Friend's Wedding (1997)\n",
            "My Crazy Life (Mi vida loca) (1993)\n",
            "My Fair Lady (1964)\n",
            "My Family (1995)\n",
            "My Favorite Season (1993)\n",
            "My Favorite Year (1982)\n",
            "My Fellow Americans (1996)\n",
            "My Left Foot (1989)\n",
            "My Life and Times With Antonin Artaud (En compagnie d'Antonin Artaud) (1993)\n",
            "My Life as a Dog (Mitt liv som hund) (1985)\n",
            "My Man Godfrey (1936)\n",
            "My Own Private Idaho (1991)\n",
            "Mystery Science Theater 3000: The Movie (1996)\n",
            "Nadja (1994)\n",
            "Naked (1993)\n",
            "Naked Gun 33 1/3: The Final Insult (1994)\n",
            "Naked in New York (1994)\n",
            "National Lampoon's Senior Trip (1995)\n",
            "Natural Born Killers (1994)\n",
            "Nell (1994)\n",
            "Nelly & Monsieur Arnaud (1995)\n",
            "Nemesis 2: Nebula (1995)\n",
            "Neon Bible, The (1995)\n",
            "Net, The (1995)\n",
            "NeverEnding Story III, The (1994)\n",
            "New Age, The (1994)\n",
            "New Jersey Drive (1995)\n",
            "New York Cop (1996)\n",
            "Newton Boys, The (1998)\n",
            "Next Karate Kid, The (1994)\n",
            "Next Step, The (1995)\n",
            "Niagara, Niagara (1997)\n",
            "Nick of Time (1995)\n",
            "Nico Icon (1995)\n",
            "Night Falls on Manhattan (1997)\n",
            "Night Flier (1997)\n",
            "Night of the Living Dead (1968)\n",
            "Night on Earth (1991)\n",
            "Nightmare Before Christmas, The (1993)\n",
            "Nightmare on Elm Street, A (1984)\n",
            "Nightwatch (1997)\n",
            "Nikita (La Femme Nikita) (1990)\n",
            "Nil By Mouth (1997)\n",
            "Nina Takes a Lover (1994)\n",
            "Nine Months (1995)\n",
            "Ninotchka (1939)\n",
            "Nixon (1995)\n",
            "No Escape (1994)\n",
            "Nobody Loves Me (Keiner liebt mich) (1994)\n",
            "Nobody's Fool (1994)\n",
            "Normal Life (1996)\n",
            "North (1994)\n",
            "North by Northwest (1959)\n",
            "Nosferatu (Nosferatu, eine Symphonie des Grauens) (1922)\n",
            "Nosferatu a Venezia (1986)\n",
            "Nothing Personal (1995)\n",
            "Nothing to Lose (1994)\n",
            "Notorious (1946)\n",
            "Now and Then (1995)\n",
            "Nowhere (1997)\n",
            "Nutty Professor, The (1996)\n",
            "Nénette et Boni (1996)\n",
            "Object of My Affection, The (1998)\n",
            "Of Human Bondage (1934)\n",
            "Of Love and Shadows (1994)\n",
            "Office Killer (1997)\n",
            "Old Lady Who Walked in the Sea, The (Vieille qui marchait dans la mer, La) (1991)\n",
            "Old Man and the Sea, The (1958)\n",
            "Old Yeller (1957)\n",
            "Oliver & Company (1988)\n",
            "Omen, The (1976)\n",
            "On Golden Pond (1981)\n",
            "Once Upon a Time in America (1984)\n",
            "Once Upon a Time in the West (1969)\n",
            "Once Upon a Time... When We Were Colored (1995)\n",
            "Once Were Warriors (1994)\n",
            "One Fine Day (1996)\n",
            "One Flew Over the Cuckoo's Nest (1975)\n",
            "One Night Stand (1997)\n",
            "Only You (1994)\n",
            "Open Season (1996)\n",
            "Operation Dumbo Drop (1995)\n",
            "Original Gangstas (1996)\n",
            "Orlando (1993)\n",
            "Oscar & Lucinda (1997)\n",
            "Othello (1995)\n",
            "Other Voices, Other Rooms (1997)\n",
            "Out to Sea (1997)\n",
            "Outbreak (1995)\n",
            "Outlaw, The (1943)\n",
            "Pagemaster, The (1994)\n",
            "Pallbearer, The (1996)\n",
            "Palmetto (1998)\n",
            "Palookaville (1996)\n",
            "Panther (1995)\n",
            "Paper, The (1994)\n",
            "Paradise Lost: The Child Murders at Robin Hood Hills (1996)\n",
            "Paradise Road (1997)\n",
            "Parent Trap, The (1961)\n",
            "Paris Is Burning (1990)\n",
            "Paris Was a Woman (1995)\n",
            "Paris, France (1993)\n",
            "Paris, Texas (1984)\n",
            "Party Girl (1995)\n",
            "Passion Fish (1992)\n",
            "Pather Panchali (1955)\n",
            "Paths of Glory (1957)\n",
            "Patton (1970)\n",
            "Peacemaker, The (1997)\n",
            "Penny Serenade (1941)\n",
            "People vs. Larry Flynt, The (1996)\n",
            "Perez Family, The (1995)\n",
            "Perfect Candidate, A (1996)\n",
            "Perfect World, A (1993)\n",
            "Persuasion (1995)\n",
            "Pest, The (1997)\n",
            "Pete's Dragon (1977)\n",
            "Phantom, The (1996)\n",
            "Phantoms (1998)\n",
            "Pharaoh's Army (1995)\n",
            "Phat Beach (1996)\n",
            "Phenomenon (1996)\n",
            "Philadelphia (1993)\n",
            "Philadelphia Story, The (1940)\n",
            "Piano, The (1993)\n",
            "Picnic (1955)\n",
            "Picture Bride (1995)\n",
            "Picture Perfect (1997)\n",
            "Pie in the Sky (1995)\n",
            "Pillow Book, The (1995)\n",
            "Pink Floyd - The Wall (1982)\n",
            "Pinocchio (1940)\n",
            "Platoon (1986)\n",
            "Playing God (1997)\n",
            "Pocahontas (1995)\n",
            "Poetic Justice (1993)\n",
            "Poison Ivy II (1995)\n",
            "Police Story 4: Project S (Chao ji ji hua) (1993)\n",
            "Pollyanna (1960)\n",
            "Pompatus of Love, The (1996)\n",
            "Ponette (1996)\n",
            "Portrait of a Lady, The (1996)\n",
            "Postino, Il (1994)\n",
            "Postman, The (1997)\n",
            "Powder (1995)\n",
            "Power 98 (1995)\n",
            "Preacher's Wife, The (1996)\n",
            "Prefontaine (1997)\n",
            "Pretty Woman (1990)\n",
            "Price Above Rubies, A (1998)\n",
            "Priest (1994)\n",
            "Primal Fear (1996)\n",
            "Primary Colors (1998)\n",
            "Princess Bride, The (1987)\n",
            "Princess Caraboo (1994)\n",
            "Prisoner of the Mountains (Kavkazsky Plennik) (1996)\n",
            "Private Benjamin (1980)\n",
            "Private Parts (1997)\n",
            "Professional, The (1994)\n",
            "Program, The (1993)\n",
            "Promesse, La (1996)\n",
            "Promise, The (Versprechen, Das) (1994)\n",
            "Prophecy II, The (1998)\n",
            "Prophecy, The (1995)\n",
            "Psycho (1960)\n",
            "Pulp Fiction (1994)\n",
            "Pump Up the Volume (1990)\n",
            "Purple Noon (1960)\n",
            "Pushing Hands (1992)\n",
            "Pyromaniac's Love Story, A (1995)\n",
            "Quartier Mozart (1992)\n",
            "Queen Margot (Reine Margot, La) (1994)\n",
            "Quest, The (1996)\n",
            "Quick and the Dead, The (1995)\n",
            "Quiet Man, The (1952)\n",
            "Quiet Room, The (1996)\n",
            "Quiz Show (1994)\n",
            "Race the Sun (1996)\n",
            "Radioland Murders (1994)\n",
            "Raging Bull (1980)\n",
            "Raiders of the Lost Ark (1981)\n",
            "Rainmaker, The (1997)\n",
            "Raise the Red Lantern (1991)\n",
            "Raising Arizona (1987)\n",
            "Ran (1985)\n",
            "Ransom (1996)\n",
            "Raw Deal (1948)\n",
            "Ready to Wear (Pret-A-Porter) (1994)\n",
            "Real Genius (1985)\n",
            "Reality Bites (1994)\n",
            "Rear Window (1954)\n",
            "Rebecca (1940)\n",
            "Rebel Without a Cause (1955)\n",
            "Reckless (1995)\n",
            "Red Corner (1997)\n",
            "Red Firecracker, Green Firecracker (1994)\n",
            "Red Rock West (1992)\n",
            "Ref, The (1994)\n",
            "Relative Fear (1994)\n",
            "Relic, The (1997)\n",
            "Reluctant Debutante, The (1958)\n",
            "Remains of the Day, The (1993)\n",
            "Renaissance Man (1994)\n",
            "Rendezvous in Paris (Rendez-vous de Paris, Les) (1995)\n",
            "Rent-a-Kid (1995)\n",
            "Replacement Killers, The (1998)\n",
            "Reservoir Dogs (1992)\n",
            "Restoration (1995)\n",
            "Return of Martin Guerre, The (Retour de Martin Guerre, Le) (1982)\n",
            "Return of the Jedi (1983)\n",
            "Return of the Pink Panther, The (1974)\n",
            "Rhyme & Reason (1997)\n",
            "Rich Man's Wife, The (1996)\n",
            "Richard III (1995)\n",
            "Richie Rich (1994)\n",
            "Ridicule (1996)\n",
            "Right Stuff, The (1983)\n",
            "Ripe (1996)\n",
            "Rising Sun (1993)\n",
            "River Wild, The (1994)\n",
            "Road to Wellville, The (1994)\n",
            "Rob Roy (1995)\n",
            "Robert A. Heinlein's The Puppet Masters (1994)\n",
            "Robin Hood: Men in Tights (1993)\n",
            "Robin Hood: Prince of Thieves (1991)\n",
            "Robocop 3 (1993)\n",
            "Rock, The (1996)\n",
            "Rocket Man (1997)\n",
            "Roman Holiday (1953)\n",
            "Romeo Is Bleeding (1993)\n",
            "Romper Stomper (1992)\n",
            "Romy and Michele's High School Reunion (1997)\n",
            "Room with a View, A (1986)\n",
            "Roommates (1995)\n",
            "Roseanna's Grave (For Roseanna) (1997)\n",
            "Rosencrantz and Guildenstern Are Dead (1990)\n",
            "Rosewood (1997)\n",
            "Rough Magic (1995)\n",
            "Ruby in Paradise (1993)\n",
            "Rudy (1993)\n",
            "Ruling Class, The (1972)\n",
            "Rumble in the Bronx (1995)\n",
            "Run of the Country, The (1995)\n",
            "S.F.W. (1994)\n",
            "Sabrina (1954)\n",
            "Sabrina (1995)\n",
            "Safe (1995)\n",
            "Safe Passage (1994)\n",
            "Saint of Fort Washington, The (1993)\n",
            "Saint, The (1997)\n",
            "Salut cousin! (1996)\n",
            "Santa Clause, The (1994)\n",
            "Santa with Muscles (1996)\n",
            "Savage Nights (Nuits fauves, Les) (1992)\n",
            "Scarlet Letter, The (1926)\n",
            "Scarlet Letter, The (1995)\n",
            "Schindler's List (1993)\n",
            "Schizopolis (1996)\n",
            "Scout, The (1994)\n",
            "Scream (1996)\n",
            "Scream 2 (1997)\n",
            "Scream of Stone (Schrei aus Stein) (1991)\n",
            "Screamers (1995)\n",
            "Search for One-eye Jimmy, The (1996)\n",
            "Searching for Bobby Fischer (1993)\n",
            "Second Jungle Book: Mowgli & Baloo, The (1997)\n",
            "Secret Adventures of Tom Thumb, The (1993)\n",
            "Secret Agent, The (1996)\n",
            "Secret Garden, The (1993)\n",
            "Secret of Roan Inish, The (1994)\n",
            "Secrets & Lies (1996)\n",
            "Selena (1997)\n",
            "Sense and Sensibility (1995)\n",
            "Senseless (1998)\n",
            "Serial Mom (1994)\n",
            "Set It Off (1996)\n",
            "Seven (Se7en) (1995)\n",
            "Seven Years in Tibet (1997)\n",
            "Seventh Seal, The (Sjunde inseglet, Det) (1957)\n",
            "Sex, Lies, and Videotape (1989)\n",
            "Sexual Life of the Belgians, The (1994)\n",
            "Sgt. Bilko (1996)\n",
            "Shadow Conspiracy (1997)\n",
            "Shadow of Angels (Schatten der Engel) (1976)\n",
            "Shadow, The (1994)\n",
            "Shadowlands (1993)\n",
            "Shadows (Cienie) (1988)\n",
            "Shaggy Dog, The (1959)\n",
            "Shall We Dance? (1937)\n",
            "Shall We Dance? (1996)\n",
            "Shallow Grave (1994)\n",
            "Shanghai Triad (Yao a yao yao dao waipo qiao) (1995)\n",
            "Shawshank Redemption, The (1994)\n",
            "She's So Lovely (1997)\n",
            "She's the One (1996)\n",
            "Shiloh (1997)\n",
            "Shine (1996)\n",
            "Shining, The (1980)\n",
            "Shooter, The (1995)\n",
            "Shooting Fish (1997)\n",
            "Shopping (1994)\n",
            "Short Cuts (1993)\n",
            "Show, The (1995)\n",
            "Showgirls (1995)\n",
            "Silence of the Lambs, The (1991)\n",
            "Silence of the Palace, The (Saimt el Qusur) (1994)\n",
            "Simple Twist of Fate, A (1994)\n",
            "Simple Wish, A (1997)\n",
            "Singin' in the Rain (1952)\n",
            "Sirens (1994)\n",
            "Six Degrees of Separation (1993)\n",
            "Sixth Man, The (1997)\n",
            "Sleeper (1973)\n",
            "Sleepers (1996)\n",
            "Sleepless in Seattle (1993)\n",
            "Sleepover (1995)\n",
            "Sliding Doors (1998)\n",
            "Sling Blade (1996)\n",
            "Slingshot, The (1993)\n",
            "Sliver (1993)\n",
            "Small Faces (1995)\n",
            "Smile Like Yours, A (1997)\n",
            "Smilla's Sense of Snow (1997)\n",
            "Smoke (1995)\n",
            "Sneakers (1992)\n",
            "Snow White and the Seven Dwarfs (1937)\n",
            "So Dear to My Heart (1949)\n",
            "So I Married an Axe Murderer (1993)\n",
            "Solo (1996)\n",
            "Some Folks Call It a Sling Blade (1993)\n",
            "Some Kind of Wonderful (1987)\n",
            "Some Like It Hot (1959)\n",
            "Some Mother's Son (1996)\n",
            "Somebody to Love (1994)\n",
            "Someone Else's America (1995)\n",
            "Something to Talk About (1995)\n",
            "Somewhere in Time (1980)\n",
            "Son in Law (1993)\n",
            "Sophie's Choice (1982)\n",
            "Soul Food (1997)\n",
            "Sound of Music, The (1965)\n",
            "Space Jam (1996)\n",
            "Spanish Prisoner, The (1997)\n",
            "Spanking the Monkey (1994)\n",
            "Spawn (1997)\n",
            "Specialist, The (1994)\n",
            "Species (1995)\n",
            "Speechless (1994)\n",
            "Speed (1994)\n",
            "Speed 2: Cruise Control (1997)\n",
            "Spellbound (1945)\n",
            "Sphere (1998)\n",
            "Spice World (1997)\n",
            "Spirits of the Dead (Tre passi nel delirio) (1968)\n",
            "Spitfire Grill, The (1996)\n",
            "Sprung (1997)\n",
            "Spy Hard (1996)\n",
            "Squeeze (1996)\n",
            "Stag (1997)\n",
            "Stalingrad (1993)\n",
            "Stalker (1979)\n",
            "Stand by Me (1986)\n",
            "Star Kid (1997)\n",
            "Star Maker, The (Uomo delle stelle, L') (1995)\n",
            "Star Maps (1997)\n",
            "Star Trek III: The Search for Spock (1984)\n",
            "Star Trek IV: The Voyage Home (1986)\n",
            "Star Trek V: The Final Frontier (1989)\n",
            "Star Trek VI: The Undiscovered Country (1991)\n",
            "Star Trek: First Contact (1996)\n",
            "Star Trek: Generations (1994)\n",
            "Star Trek: The Motion Picture (1979)\n",
            "Star Trek: The Wrath of Khan (1982)\n",
            "Star Wars (1977)\n",
            "Stargate (1994)\n",
            "Stars Fell on Henrietta, The (1995)\n",
            "Starship Troopers (1997)\n",
            "Steal Big, Steal Little (1995)\n",
            "Stealing Beauty (1996)\n",
            "Steel (1997)\n",
            "Stefano Quantestorie (1993)\n",
            "Stephen King's The Langoliers (1995)\n",
            "Sting, The (1973)\n",
            "Stonewall (1995)\n",
            "Story of Xinghua, The (1993)\n",
            "Strange Days (1995)\n",
            "Stranger in the House (1997)\n",
            "Stranger, The (1994)\n",
            "Strawberry and Chocolate (Fresa y chocolate) (1993)\n",
            "Street Fighter (1994)\n",
            "Streetcar Named Desire, A (1951)\n",
            "Strictly Ballroom (1992)\n",
            "Striking Distance (1993)\n",
            "Stripes (1981)\n",
            "Striptease (1996)\n",
            "Stuart Saves His Family (1995)\n",
            "Stupids, The (1996)\n",
            "SubUrbia (1997)\n",
            "Substance of Fire, The (1996)\n",
            "Substitute, The (1996)\n",
            "Sudden Death (1995)\n",
            "Sudden Manhattan (1996)\n",
            "Sum of Us, The (1994)\n",
            "Sunchaser, The (1996)\n",
            "Sunset Blvd. (1950)\n",
            "Sunset Park (1996)\n",
            "Super Mario Bros. (1993)\n",
            "Supercop (1992)\n",
            "Surviving Picasso (1996)\n",
            "Surviving the Game (1994)\n",
            "Suture (1993)\n",
            "Swan Princess, The (1994)\n",
            "Sweet Hereafter, The (1997)\n",
            "Sweet Nothing (1995)\n",
            "Swept from the Sea (1997)\n",
            "Swimming with Sharks (1995)\n",
            "Swingers (1996)\n",
            "Swiss Family Robinson (1960)\n",
            "Switchback (1997)\n",
            "Switchblade Sisters (1975)\n",
            "Sword in the Stone, The (1963)\n",
            "Symphonie pastorale, La (1946)\n",
            "T-Men (1947)\n",
            "Tainted (1998)\n",
            "Tales From the Crypt Presents: Demon Knight (1995)\n",
            "Tales from the Crypt Presents: Bordello of Blood (1996)\n",
            "Tales from the Hood (1995)\n",
            "Talking About Sex (1994)\n",
            "Tango Lesson, The (1997)\n",
            "Tank Girl (1995)\n",
            "Target (1995)\n",
            "Taxi Driver (1976)\n",
            "Telling Lies in America (1997)\n",
            "Temptress Moon (Feng Yue) (1996)\n",
            "Terminal Velocity (1994)\n",
            "Terminator 2: Judgment Day (1991)\n",
            "Terminator, The (1984)\n",
            "Terror in a Texas Town (1958)\n",
            "Tetsuo II: Body Hammer (1992)\n",
            "That Darn Cat! (1965)\n",
            "That Darn Cat! (1997)\n",
            "That Old Feeling (1997)\n",
            "That Thing You Do! (1996)\n",
            "The Courtyard (1995)\n",
            "The Deadly Cure (1996)\n",
            "The Innocent (1994)\n",
            "Theodore Rex (1995)\n",
            "They Made Me a Criminal (1939)\n",
            "Thieves (Voleurs, Les) (1996)\n",
            "Thin Blue Line, The (1988)\n",
            "Thin Line Between Love and Hate, A (1996)\n",
            "Thin Man, The (1934)\n",
            "Things to Do in Denver when You're Dead (1995)\n",
            "Thinner (1996)\n",
            "Third Man, The (1949)\n",
            "Thirty-Two Short Films About Glenn Gould (1993)\n",
            "This Is Spinal Tap (1984)\n",
            "Thousand Acres, A (1997)\n",
            "Three Caballeros, The (1945)\n",
            "Three Colors: Blue (1993)\n",
            "Three Colors: Red (1994)\n",
            "Three Colors: White (1994)\n",
            "Three Lives and Only One Death (1996)\n",
            "Three Musketeers, The (1993)\n",
            "Three Wishes (1995)\n",
            "Threesome (1994)\n",
            "Tie Me Up! Tie Me Down! (1990)\n",
            "Tie That Binds, The (1995)\n",
            "Tigrero: A Film That Was Never Made (1994)\n",
            "Time Tracers (1995)\n",
            "Time to Kill, A (1996)\n",
            "Timecop (1994)\n",
            "Tin Cup (1996)\n",
            "Tin Drum, The (Blechtrommel, Die) (1979)\n",
            "Tin Men (1987)\n",
            "Titanic (1997)\n",
            "To Be or Not to Be (1942)\n",
            "To Catch a Thief (1955)\n",
            "To Cross the Rubicon (1991)\n",
            "To Die For (1995)\n",
            "To Gillian on Her 37th Birthday (1996)\n",
            "To Have, or Not (1995)\n",
            "To Kill a Mockingbird (1962)\n",
            "To Live (Huozhe) (1994)\n",
            "To Wong Foo, Thanks for Everything! Julie Newmar (1995)\n",
            "Tokyo Fist (1995)\n",
            "Tom & Viv (1994)\n",
            "Tom and Huck (1995)\n",
            "Tombstone (1993)\n",
            "Tommy Boy (1995)\n",
            "Tomorrow Never Dies (1997)\n",
            "Top Gun (1986)\n",
            "Top Hat (1935)\n",
            "Total Eclipse (1995)\n",
            "Touch (1997)\n",
            "Touch of Evil (1958)\n",
            "Tough and Deadly (1995)\n",
            "Touki Bouki (Journey of the Hyena) (1973)\n",
            "Toy Story (1995)\n",
            "Trainspotting (1996)\n",
            "Transformers: The Movie, The (1986)\n",
            "Traveller (1997)\n",
            "Treasure of the Sierra Madre, The (1948)\n",
            "Trees Lounge (1996)\n",
            "Trial and Error (1997)\n",
            "Trial by Jury (1994)\n",
            "Trigger Effect, The (1996)\n",
            "True Crime (1995)\n",
            "True Lies (1994)\n",
            "True Romance (1993)\n",
            "Truman Show, The (1998)\n",
            "Trust (1990)\n",
            "Truth About Cats & Dogs, The (1996)\n",
            "Truth or Consequences, N.M. (1997)\n",
            "Turbo: A Power Rangers Movie (1997)\n",
            "Turbulence (1997)\n",
            "Turning, The (1992)\n",
            "Twelfth Night (1996)\n",
            "Twelve Monkeys (1995)\n",
            "Twilight (1998)\n",
            "Twin Town (1997)\n",
            "Twisted (1996)\n",
            "Twister (1996)\n",
            "Two Bits (1995)\n",
            "Two Deaths (1995)\n",
            "Two Friends (1986) \n",
            "Two Much (1996)\n",
            "Two if by Sea (1996)\n",
            "Two or Three Things I Know About Her (1966)\n",
            "U Turn (1997)\n",
            "U.S. Marshalls (1998)\n",
            "Ulee's Gold (1997)\n",
            "Umbrellas of Cherbourg, The (Parapluies de Cherbourg, Les) (1964)\n",
            "Unbearable Lightness of Being, The (1988)\n",
            "Under Siege (1992)\n",
            "Under Siege 2: Dark Territory (1995)\n",
            "Underground (1995)\n",
            "Underneath, The (1995)\n",
            "Underworld (1997)\n",
            "Unforgettable (1996)\n",
            "Unforgiven (1992)\n",
            "Unhook the Stars (1996)\n",
            "Unstrung Heroes (1995)\n",
            "Until the End of the World (Bis ans Ende der Welt) (1991)\n",
            "Unzipped (1995)\n",
            "Up Close and Personal (1996)\n",
            "Up in Smoke (1978)\n",
            "Usual Suspects, The (1995)\n",
            "Vampire in Brooklyn (1995)\n",
            "Van, The (1996)\n",
            "Vanya on 42nd Street (1994)\n",
            "Vegas Vacation (1997)\n",
            "Venice/Venice (1992)\n",
            "Vermin (1998)\n",
            "Vermont Is For Lovers (1992)\n",
            "Vertigo (1958)\n",
            "Very Brady Sequel, A (1996)\n",
            "Very Natural Thing, A (1974)\n",
            "Victor/Victoria (1982)\n",
            "Vie est belle, La (Life is Rosey) (1987)\n",
            "Village of the Damned (1995)\n",
            "Virtuosity (1995)\n",
            "Visitors, The (Visiteurs, Les) (1993)\n",
            "Volcano (1997)\n",
            "Wag the Dog (1997)\n",
            "Waiting for Guffman (1996)\n",
            "Waiting to Exhale (1995)\n",
            "Walk in the Clouds, A (1995)\n",
            "Walk in the Sun, A (1945)\n",
            "Walkabout (1971)\n",
            "Walking Dead, The (1995)\n",
            "Walking and Talking (1996)\n",
            "Wallace & Gromit: The Best of Aardman Animation (1996)\n",
            "War Room, The (1993)\n",
            "War at Home, The (1996)\n",
            "War, The (1994)\n",
            "Warriors of Virtue (1997)\n",
            "Washington Square (1997)\n",
            "Waterworld (1995)\n",
            "Wedding Bell Blues (1996)\n",
            "Wedding Gift, The (1994)\n",
            "Wedding Singer, The (1998)\n",
            "Weekend at Bernie's (1989)\n",
            "Welcome To Sarajevo (1997)\n",
            "Welcome to the Dollhouse (1995)\n",
            "Wend Kuuni (God's Gift) (1982)\n",
            "Wes Craven's New Nightmare (1994)\n",
            "What Happened Was... (1994)\n",
            "What's Eating Gilbert Grape (1993)\n",
            "What's Love Got to Do with It (1993)\n",
            "When Harry Met Sally... (1989)\n",
            "When Night Is Falling (1995)\n",
            "When We Were Kings (1996)\n",
            "When a Man Loves a Woman (1994)\n",
            "When the Cats Away (Chacun cherche son chat) (1996)\n",
            "While You Were Sleeping (1995)\n",
            "White Balloon, The (1995)\n",
            "White Man's Burden (1995)\n",
            "White Squall (1996)\n",
            "Whole Wide World, The (1996)\n",
            "Widows' Peak (1994)\n",
            "Wife, The (1995)\n",
            "Wild America (1997)\n",
            "Wild Bill (1995)\n",
            "Wild Bunch, The (1969)\n",
            "Wild Reeds (1994)\n",
            "Wild Things (1998)\n",
            "William Shakespeare's Romeo and Juliet (1996)\n",
            "Willy Wonka and the Chocolate Factory (1971)\n",
            "Window to Paris (1994)\n",
            "Wings of Courage (1995)\n",
            "Wings of Desire (1987)\n",
            "Wings of the Dove, The (1997)\n",
            "Winnie the Pooh and the Blustery Day (1968)\n",
            "Winter Guest, The (1997)\n",
            "Wishmaster (1997)\n",
            "With Honors (1994)\n",
            "Withnail and I (1987)\n",
            "Witness (1985)\n",
            "Wizard of Oz, The (1939)\n",
            "Wolf (1994)\n",
            "Woman in Question, The (1950)\n",
            "Women, The (1939)\n",
            "Wonderful, Horrible Life of Leni Riefenstahl, The (1993)\n",
            "Wonderland (1997)\n",
            "Wooden Man's Bride, The (Wu Kui) (1994)\n",
            "World of Apu, The (Apur Sansar) (1959)\n",
            "Wrong Trousers, The (1993)\n",
            "Wyatt Earp (1994)\n",
            "Yankee Zulu (1994)\n",
            "Year of the Horse (1997)\n",
            "You So Crazy (1994)\n",
            "Young Frankenstein (1974)\n",
            "Young Guns (1988)\n",
            "Young Guns II (1990)\n",
            "Young Poisoner's Handbook, The (1995)\n",
            "Zeus and Roxanne (1997)\n",
            "unknown\n",
            "Á köldum klaka (Cold Fever) (1994)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from re import search\n",
        "from IPython.display import display\n",
        "import ipywidgets as widgets\n",
        "from ipywidgets import interact, interact_manual\n",
        "input_movieName=widgets.Text()\n",
        "\n",
        "#ready function for movie recommendation\n",
        "def getRecommendation(movieName):\n",
        "  searchMovie=input_movieName.value\n",
        "  list_result=df[df['title'].str.contains(searchMovie)]\n",
        "  m1=list_result['FirstMovieRecommendation'].values[0]\n",
        "  m2=list_result['SecondMovieRecommendation'].values[0]\n",
        "  m3=list_result['ThirdMovieRecommendation'].values[0]\n",
        "  m4=list_result['FourthMovieRecommendation'].values[0]\n",
        "  FinalRecomm=\"1:\"+m1+\"\\n\"+m2+\"\\n\"+m3+\"\\n\"+m4\n",
        "  print(\"Recommended Movie Names- \",searchMovie)\n",
        "  print(FinalRecomm)\n"
      ],
      "metadata": {
        "id": "UC98kBbI1ZlX"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#pass movie name to getRecommendation Function\n",
        "interact(getRecommendation,movieName=input_movieName)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 224,
          "referenced_widgets": [
            "2fbe1bf21ebc4aaba3c0157e4550ac8e",
            "724f8e1869b44dfda27b462f5f8b0135",
            "777309feb2254ba5878e44c68471c5d4",
            "9c8c704a2bea4bbda3e866ccb5811c86",
            "e722792e49d7445a8f20942867b3d1a4",
            "c3a706bba69c40d4806972e7cd6ac2bb",
            "c724c31eb45c496abcc5cf5660ee3e02"
          ]
        },
        "id": "W77EHRQ64UDe",
        "outputId": "019158ae-f8a3-4279-9956-48900cfb9c92"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "interactive(children=(Text(value='', description='movieName'), Output()), _dom_classes=('widget-interact',))"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2fbe1bf21ebc4aaba3c0157e4550ac8e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function __main__.getRecommendation(movieName)>"
            ],
            "text/html": [
              "<div style=\"max-width:800px; border: 1px solid var(--colab-border-color);\"><style>\n",
              "      pre.function-repr-contents {\n",
              "        overflow-x: auto;\n",
              "        padding: 8px 12px;\n",
              "        max-height: 500px;\n",
              "      }\n",
              "\n",
              "      pre.function-repr-contents.function-repr-contents-collapsed {\n",
              "        cursor: pointer;\n",
              "        max-height: 100px;\n",
              "      }\n",
              "    </style>\n",
              "    <pre style=\"white-space: initial; background:\n",
              "         var(--colab-secondary-surface-color); padding: 8px 12px;\n",
              "         border-bottom: 1px solid var(--colab-border-color);\"><b>getRecommendation</b><br/>def getRecommendation(movieName)</pre><pre class=\"function-repr-contents function-repr-contents-collapsed\" style=\"\"><a class=\"filepath\" style=\"display:none\" href=\"#\">/content/&lt;ipython-input-44-89eea14f0668&gt;</a>&lt;no docstring&gt;</pre></div>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    }
  ]
}