Copy_of_main.ipynb

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      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/QianZhu/bigdata--kafkastream/blob/master/Copy_of_main.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nDs-Mp5MJikn"
      },
      "source": [
        "# Building a Simple Movie Recommender with LanceDB Cloud"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eJWtFbhzJ9_b"
      },
      "source": [
        "## Credentials\n",
        "\n",
        "Copy and paste the project name and the api key from your project page.\n",
        "These will be used later to [connect to LanceDB Cloud](#scroll-to=5q8m6GMD7sGu)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "v1tlHcnMmJEh"
      },
      "outputs": [],
      "source": [
        "project_slug = \"test\" # @param {type:\"string\"}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iCMDeJ8jma1z"
      },
      "outputs": [],
      "source": [
        "api_key = \"sk_4QE4HYWUBMXYDFWFSP3VRZZZPRJQRIUSTQALMV2ZLMWSHURVDVAQ====\" # @param {type:\"string\"}!"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can also set the LANCEDB_API_KEY as an environment variable"
      ],
      "metadata": {
        "id": "a27ICh-1rONc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!export LANCEDB_API_KEY=\"sk_...\""
      ],
      "metadata": {
        "id": "iYCNW6rHriOS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import getpass\n",
        "os.environ[\"LANCEDB_API_KEY\"] = getpass.getpass(\"Enter Your LANCEDB API Key:\")"
      ],
      "metadata": {
        "id": "KS93TA5UsPit"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DAyxhybfKTQu"
      },
      "source": [
        "## Download the raw data\n",
        "Download and unzip the dataset from [MovieLens](https://grouplens.org/datasets/movielens/latest/). The example uses the 100k small dataset."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3jXSVspr7sGe",
        "vscode": {
          "languageId": "shellscript"
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        },
        "outputId": "f6198e67-0504-4a69-bf90-87817108ab17"
      },
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n",
            "                                 Dload  Upload   Total   Spent    Left  Speed\n",
            "100  955k  100  955k    0     0   426k      0  0:00:02  0:00:02 --:--:--  426k\n",
            "Archive:  ml-latest-small.zip\n",
            "replace ml-latest-small/links.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: "
          ]
        }
      ],
      "source": [
        "!curl https://files.grouplens.org/datasets/movielens/ml-latest-small.zip -o ml-latest-small.zip\n",
        "!unzip ml-latest-small.zip"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TgqEEYd38kED"
      },
      "source": [
        "## Let's start by installing and importing the libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2jXSVspr7sGe"
      },
      "outputs": [],
      "source": [
        "!pip install lancedb pandas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yLD8vsMB7sGh"
      },
      "outputs": [],
      "source": [
        "import lancedb\n",
        "import numpy as np\n",
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xSqPUBYw8s30"
      },
      "source": [
        "## Load and unpack the dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "apWYq2AZ7sGi"
      },
      "source": [
        "After unzipping the dataset from MovieLens, we'll load the user ratings into a dataframe `ratings`. Since we don't need timestamp, we can drop that column. We also have to prepare the columns in proper formats."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
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          "data": {
            "text/plain": [
              "        user id  movie id  rating\n",
              "1             1         1     4.0\n",
              "2             1         3     4.0\n",
              "3             1         6     4.0\n",
              "4             1        47     5.0\n",
              "5             1        50     5.0\n",
              "...         ...       ...     ...\n",
              "100832      610    166534     4.0\n",
              "100833      610    168248     5.0\n",
              "100834      610    168250     5.0\n",
              "100835      610    168252     5.0\n",
              "100836      610    170875     3.0\n",
              "\n",
              "[100836 rows x 3 columns]"
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          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "ratings = pd.read_csv('./ml-latest-small/ratings.csv', header=None, names=[\"user id\", \"movie id\", \"rating\", \"timestamp\"])\n",
        "ratings = ratings.drop(columns=['timestamp'])\n",
        "ratings = ratings.drop(0)\n",
        "ratings[\"rating\"] = ratings[\"rating\"].values.astype(np.float32)\n",
        "ratings[\"user id\"] = ratings[\"user id\"].values.astype(np.int32)\n",
        "ratings[\"movie id\"] = ratings[\"movie id\"].values.astype(np.int32)\n",
        "ratings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "btYN_c0q7sGl"
      },
      "source": [
        "We can now create a matrix of user ratings, where each row represents a user and each column represents a movie."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Kmuv9gxf7sGm",
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          "data": {
            "text/plain": [
              "movie id  1       2       3       4       5       6       7       8       \\\n",
              "user id                                                                    \n",
              "1            4.0     0.0     4.0     0.0     0.0     4.0     0.0     0.0   \n",
              "2            0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "3            0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "4            0.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "5            4.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "...          ...     ...     ...     ...     ...     ...     ...     ...   \n",
              "606          2.5     0.0     0.0     0.0     0.0     0.0     2.5     0.0   \n",
              "607          4.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "608          2.5     2.0     2.0     0.0     0.0     0.0     0.0     0.0   \n",
              "609          3.0     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "610          5.0     0.0     0.0     0.0     0.0     5.0     0.0     0.0   \n",
              "\n",
              "movie id  9       10      ...  193565  193567  193571  193573  193579  193581  \\\n",
              "user id                   ...                                                   \n",
              "1            0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "2            0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "3            0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "4            0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "5            0.0     0.0  ...     0.0     0.0     0.0     0.0     0.0     0.0   \n",
              "...          ...     ...  ...     ...     ...     ...     ...     ...     ...   \n",
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              "    async function quickchart(key) {\n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "reviewmatrix = ratings.pivot(index=\"user id\", columns=\"movie id\", values=\"rating\").fillna(0)\n",
        "reviewmatrix"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0a3qCjRN7sGn"
      },
      "source": [
        "Now, we apply the **SVD**. `vh` represents the orthogonal matrix that describes the relationship between columns of the original matrix. Because the\n",
        "\n",
        "---\n",
        "\n",
        "columns of `vh` correspond to the movies, we can flip it to get the movie embeddings on the rows."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "mGWO8R0i7sGp",
        "outputId": "1720258d-4e49-4490-ab6c-e32a59c1fa23",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-7.0449896e-02, -3.8539346e-02, -1.5912922e-02, ...,\n",
              "        -6.4683605e-05, -6.4683605e-05, -2.7172931e-04],\n",
              "       [ 2.7591195e-02,  2.0666271e-03,  2.4714615e-02, ...,\n",
              "        -5.9758622e-04, -5.9758622e-04, -1.2723620e-03],\n",
              "       [-7.8443885e-02, -5.6844711e-02, -1.8005114e-02, ...,\n",
              "         8.7109387e-05,  8.7109387e-05, -1.2283334e-04],\n",
              "       ...,\n",
              "       [ 2.0168955e-02,  1.3377998e-02, -1.9083519e-02, ...,\n",
              "        -1.9121233e-03, -1.9121233e-03, -2.1089672e-03],\n",
              "       [ 3.5461895e-02, -1.0232525e-01, -1.1956284e-02, ...,\n",
              "         9.4549108e-04,  9.4549108e-04,  2.5773358e-03],\n",
              "       [ 6.7939058e-02,  1.2740049e-02, -2.3002084e-02, ...,\n",
              "        -9.3789837e-05, -9.3789837e-05, -1.9718462e-03]], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "matrix = reviewmatrix.values\n",
        "u, s, vh = np.linalg.svd(matrix, full_matrices=False)\n",
        "vh"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a7FYDE5P7sGs",
        "outputId": "9cb4a012-72f6-4a7f-e1a4-69869a92bd38",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           0         1         2         3         4         5         6    \\\n",
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              "...        ...       ...       ...       ...       ...       ...       ...   \n",
              "9719 -0.000074 -0.000683  0.000100 -0.000056 -0.000161 -0.001114 -0.001347   \n",
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              "9722 -0.000065 -0.000598  0.000087 -0.000049 -0.000141 -0.000975 -0.001179   \n",
              "9723 -0.000272 -0.001272 -0.000123 -0.000895  0.000726 -0.000508  0.000391   \n",
              "\n",
              "           7         8         9    ...       600       601       602  \\\n",
              "0     0.017924 -0.009497  0.012267  ...  0.020612 -0.019381 -0.057998   \n",
              "1     0.031154  0.027948  0.002091  ... -0.088892 -0.096330  0.050715   \n",
              "2     0.004421 -0.026932  0.016773  ... -0.028688  0.002024  0.012164   \n",
              "3     0.004299 -0.000654  0.000138  ...  0.031561  0.031872  0.077064   \n",
              "4     0.010664 -0.010917  0.010871  ... -0.019130  0.018233  0.093399   \n",
              "...        ...       ...       ...  ...       ...       ...       ...   \n",
              "9719 -0.000580 -0.000080 -0.000409  ... -0.001130  0.001340  0.000037   \n",
              "9720 -0.000507 -0.000070 -0.000357  ... -0.000989  0.001173  0.000032   \n",
              "9721 -0.000507 -0.000070 -0.000357  ... -0.000989  0.001173  0.000032   \n",
              "9722 -0.000507 -0.000070 -0.000357  ... -0.000989  0.001173  0.000032   \n",
              "9723 -0.000391 -0.000643  0.001185  ... -0.000378  0.005020  0.001524   \n",
              "\n",
              "           603       604       605       606       607       608       609  \n",
              "0    -0.027171 -0.006926  0.059270  0.110072  0.020169  0.035462  0.067939  \n",
              "1     0.057505 -0.067907  0.080617 -0.105529  0.013378 -0.102325  0.012740  \n",
              "2     0.040334 -0.016997  0.041067 -0.002768 -0.019084 -0.011956 -0.023002  \n",
              "3     0.009637  0.001437 -0.003798 -0.015851 -0.007668 -0.007170  0.049587  \n",
              "4     0.039459 -0.025126  0.031353  0.004618 -0.055738  0.016194 -0.009322  \n",
              "...        ...       ...       ...       ...       ...       ...       ...  \n",
              "9719  0.000423  0.001391  0.000826 -0.001491 -0.002185  0.001081 -0.000107  \n",
              "9720  0.000370  0.001217  0.000722 -0.001305 -0.001912  0.000945 -0.000094  \n",
              "9721  0.000370  0.001217  0.000722 -0.001305 -0.001912  0.000945 -0.000094  \n",
              "9722  0.000370  0.001217  0.000722 -0.001305 -0.001912  0.000945 -0.000094  \n",
              "9723  0.002238 -0.000477 -0.002297  0.001557 -0.002109  0.002577 -0.001972  \n",
              "\n",
              "[9724 rows x 610 columns]"
            ],
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              "      <td>-0.096330</td>\n",
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              "      <td>0.037453</td>\n",
              "      <td>-0.000156</td>\n",
              "      <td>-0.005317</td>\n",
              "      <td>0.010490</td>\n",
              "      <td>0.004421</td>\n",
              "      <td>-0.026932</td>\n",
              "      <td>0.016773</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.028688</td>\n",
              "      <td>0.002024</td>\n",
              "      <td>0.012164</td>\n",
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              "      <td>-0.011956</td>\n",
              "      <td>-0.023002</td>\n",
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              "      <td>-0.007170</td>\n",
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              "      <td>0.039459</td>\n",
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              "      <td>...</td>\n",
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              "      <td>0.001173</td>\n",
              "      <td>0.000032</td>\n",
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              "      <td>0.001217</td>\n",
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              "      <td>-0.000357</td>\n",
              "      <td>...</td>\n",
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              "      <td>0.001173</td>\n",
              "      <td>0.000032</td>\n",
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              "      <td>-0.000391</td>\n",
              "      <td>-0.000643</td>\n",
              "      <td>0.001185</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.000378</td>\n",
              "      <td>0.005020</td>\n",
              "      <td>0.001524</td>\n",
              "      <td>0.002238</td>\n",
              "      <td>-0.000477</td>\n",
              "      <td>-0.002297</td>\n",
              "      <td>0.001557</td>\n",
              "      <td>-0.002109</td>\n",
              "      <td>0.002577</td>\n",
              "      <td>-0.001972</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9724 rows × 610 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-89275df8-7ee4-417b-aef3-f803e24eb17d')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\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-89275df8-7ee4-417b-aef3-f803e24eb17d 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-89275df8-7ee4-417b-aef3-f803e24eb17d');\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-0d4aa3a6-c346-4f5c-b51d-a715a6efc08f\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0d4aa3a6-c346-4f5c-b51d-a715a6efc08f')\"\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",
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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",
              "      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-0d4aa3a6-c346-4f5c-b51d-a715a6efc08f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ],
      "source": [
        "vectors = np.rot90(np.fliplr(vh))\n",
        "pd.DataFrame(vectors)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "76aNsoY_7sGt"
      },
      "source": [
        "Now, let's take the movies dataset to gather the **metadata** for each movie. We'll create an array `data` that contains all this information."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9qbdp3mq7sGu",
        "outputId": "55dbb42e-35ed-42e9-c1ac-ae82da2e925b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      movie id                                      title  \\\n",
              "0            1                           Toy Story (1995)   \n",
              "1            2                             Jumanji (1995)   \n",
              "2            3                    Grumpier Old Men (1995)   \n",
              "3            4                   Waiting to Exhale (1995)   \n",
              "4            5         Father of the Bride Part II (1995)   \n",
              "...        ...                                        ...   \n",
              "9737    193581  Black Butler: Book of the Atlantic (2017)   \n",
              "9738    193583               No Game No Life: Zero (2017)   \n",
              "9739    193585                               Flint (2017)   \n",
              "9740    193587        Bungo Stray Dogs: Dead Apple (2018)   \n",
              "9741    193609        Andrew Dice Clay: Dice Rules (1991)   \n",
              "\n",
              "                                           genres  \n",
              "0     Adventure|Animation|Children|Comedy|Fantasy  \n",
              "1                      Adventure|Children|Fantasy  \n",
              "2                                  Comedy|Romance  \n",
              "3                            Comedy|Drama|Romance  \n",
              "4                                          Comedy  \n",
              "...                                           ...  \n",
              "9737              Action|Animation|Comedy|Fantasy  \n",
              "9738                     Animation|Comedy|Fantasy  \n",
              "9739                                        Drama  \n",
              "9740                             Action|Animation  \n",
              "9741                                       Comedy  \n",
              "\n",
              "[9724 rows x 3 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-675c8d6d-647a-4ae6-bffc-2d324fdb6bd5\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>movie id</th>\n",
              "      <th>title</th>\n",
              "      <th>genres</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
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              "      <td>Jumanji (1995)</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Grumpier Old Men (1995)</td>\n",
              "      <td>Comedy|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Waiting to Exhale (1995)</td>\n",
              "      <td>Comedy|Drama|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Father of the Bride Part II (1995)</td>\n",
              "      <td>Comedy</td>\n",
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              "      <th>9737</th>\n",
              "      <td>193581</td>\n",
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              "      <td>Action|Animation|Comedy|Fantasy</td>\n",
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              "    <tr>\n",
              "      <th>9738</th>\n",
              "      <td>193583</td>\n",
              "      <td>No Game No Life: Zero (2017)</td>\n",
              "      <td>Animation|Comedy|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9739</th>\n",
              "      <td>193585</td>\n",
              "      <td>Flint (2017)</td>\n",
              "      <td>Drama</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9740</th>\n",
              "      <td>193587</td>\n",
              "      <td>Bungo Stray Dogs: Dead Apple (2018)</td>\n",
              "      <td>Action|Animation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9741</th>\n",
              "      <td>193609</td>\n",
              "      <td>Andrew Dice Clay: Dice Rules (1991)</td>\n",
              "      <td>Comedy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9724 rows × 3 columns</p>\n",
              "</div>\n",
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              "  </svg>\n",
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              "\n",
              "  <style>\n",
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              "      display:flex;\n",
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              "      background-color: #E8F0FE;\n",
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              "      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",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-675c8d6d-647a-4ae6-bffc-2d324fdb6bd5 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-675c8d6d-647a-4ae6-bffc-2d324fdb6bd5');\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",
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              "\n",
              "\n",
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              "            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",
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              "  }\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",
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              "    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-38e5fcd2-b300-49be-9162-072c08604dda button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "movies = pd.read_csv('./ml-latest-small/movies.csv', header=0, names=[\"movie id\", \"title\", \"genres\"])\n",
        "movies = movies[movies['movie id'].isin(reviewmatrix.columns)]\n",
        "movies"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LRu_3sM39D0Q"
      },
      "source": [
        "## Let's see some data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "duhgOmTq7sGu",
        "outputId": "8fba508c-ded5-4650-996a-142f18e9ed59",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          id                                      title  \\\n",
              "0          1                           Toy Story (1995)   \n",
              "1          2                             Jumanji (1995)   \n",
              "2          3                    Grumpier Old Men (1995)   \n",
              "3          4                   Waiting to Exhale (1995)   \n",
              "4          5         Father of the Bride Part II (1995)   \n",
              "...      ...                                        ...   \n",
              "9719  193581  Black Butler: Book of the Atlantic (2017)   \n",
              "9720  193583               No Game No Life: Zero (2017)   \n",
              "9721  193585                               Flint (2017)   \n",
              "9722  193587        Bungo Stray Dogs: Dead Apple (2018)   \n",
              "9723  193609        Andrew Dice Clay: Dice Rules (1991)   \n",
              "\n",
              "                                                 vector  \\\n",
              "0     [-0.070449896, 0.027591195, -0.078443885, -0.0...   \n",
              "1     [-0.038539346, 0.0020666271, -0.05684471, 0.05...   \n",
              "2     [-0.015912922, 0.024714615, -0.018005114, 0.03...   \n",
              "3     [-0.00087145035, 0.0035811856, -0.0049938704, ...   \n",
              "4     [-0.011360065, 0.011561904, -0.024578463, 0.02...   \n",
              "...                                                 ...   \n",
              "9719  [-7.392412e-05, -0.0006829557, 9.955359e-05, -...   \n",
              "9720  [-6.4683605e-05, -0.0005975862, 8.710939e-05, ...   \n",
              "9721  [-6.4683605e-05, -0.0005975862, 8.710939e-05, ...   \n",
              "9722  [-6.4683605e-05, -0.0005975862, 8.710939e-05, ...   \n",
              "9723  [-0.0002717293, -0.001272362, -0.00012283334, ...   \n",
              "\n",
              "                                            genre  \n",
              "0     Adventure|Animation|Children|Comedy|Fantasy  \n",
              "1                      Adventure|Children|Fantasy  \n",
              "2                                  Comedy|Romance  \n",
              "3                            Comedy|Drama|Romance  \n",
              "4                                          Comedy  \n",
              "...                                           ...  \n",
              "9719              Action|Animation|Comedy|Fantasy  \n",
              "9720                     Animation|Comedy|Fantasy  \n",
              "9721                                        Drama  \n",
              "9722                             Action|Animation  \n",
              "9723                                       Comedy  \n",
              "\n",
              "[9724 rows x 4 columns]"
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
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              "    .dataframe tbody tr th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>title</th>\n",
              "      <th>vector</th>\n",
              "      <th>genre</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Toy Story (1995)</td>\n",
              "      <td>[-0.070449896, 0.027591195, -0.078443885, -0.0...</td>\n",
              "      <td>Adventure|Animation|Children|Comedy|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Jumanji (1995)</td>\n",
              "      <td>[-0.038539346, 0.0020666271, -0.05684471, 0.05...</td>\n",
              "      <td>Adventure|Children|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>Grumpier Old Men (1995)</td>\n",
              "      <td>[-0.015912922, 0.024714615, -0.018005114, 0.03...</td>\n",
              "      <td>Comedy|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Waiting to Exhale (1995)</td>\n",
              "      <td>[-0.00087145035, 0.0035811856, -0.0049938704, ...</td>\n",
              "      <td>Comedy|Drama|Romance</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Father of the Bride Part II (1995)</td>\n",
              "      <td>[-0.011360065, 0.011561904, -0.024578463, 0.02...</td>\n",
              "      <td>Comedy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9719</th>\n",
              "      <td>193581</td>\n",
              "      <td>Black Butler: Book of the Atlantic (2017)</td>\n",
              "      <td>[-7.392412e-05, -0.0006829557, 9.955359e-05, -...</td>\n",
              "      <td>Action|Animation|Comedy|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9720</th>\n",
              "      <td>193583</td>\n",
              "      <td>No Game No Life: Zero (2017)</td>\n",
              "      <td>[-6.4683605e-05, -0.0005975862, 8.710939e-05, ...</td>\n",
              "      <td>Animation|Comedy|Fantasy</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9721</th>\n",
              "      <td>193585</td>\n",
              "      <td>Flint (2017)</td>\n",
              "      <td>[-6.4683605e-05, -0.0005975862, 8.710939e-05, ...</td>\n",
              "      <td>Drama</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9722</th>\n",
              "      <td>193587</td>\n",
              "      <td>Bungo Stray Dogs: Dead Apple (2018)</td>\n",
              "      <td>[-6.4683605e-05, -0.0005975862, 8.710939e-05, ...</td>\n",
              "      <td>Action|Animation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9723</th>\n",
              "      <td>193609</td>\n",
              "      <td>Andrew Dice Clay: Dice Rules (1991)</td>\n",
              "      <td>[-0.0002717293, -0.001272362, -0.00012283334, ...</td>\n",
              "      <td>Comedy</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9724 rows × 4 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\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",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      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-8f8c6d0a-2c9e-4c10-848c-804232d3715b 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-8f8c6d0a-2c9e-4c10-848c-804232d3715b');\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-b1b348f5-2622-42cf-8886-1810a22c466e\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-b1b348f5-2622-42cf-8886-1810a22c466e')\"\n",
              "            title=\"Suggest charts\"\n",
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              "\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",
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              "    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",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "  }\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",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
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              "      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-b1b348f5-2622-42cf-8886-1810a22c466e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "data = []\n",
        "for i in range(len(movies)):\n",
        "    data.append({\"id\": movies.iloc[i][\"movie id\"], \"title\": movies.iloc[i]['title'], \"vector\": vectors[i], \"genre\": movies.iloc[i]['genres']})\n",
        "pd.DataFrame(data)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5q8m6GMD7sGu"
      },
      "source": [
        "## Connect to LanceDB Cloud\n",
        "We can now connect to LanceDB Cloud, with the API key that is accquired from the dashboard. We'll also create a new table `movie_set` with the data we just created."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "bboag_S67sGv",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "605c4cb4-5b0b-4306-f823-d79a0884c815"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n"
          ]
        }
      ],
      "source": [
        "# you can simply replace the following line from the code copied from the dashboard\n",
        "# or substitute  with your project/api key\n",
        "uri = \"db://\" + project_slug\n",
        "db = lancedb.connect(uri, api_key=api_key, region=\"us-east-1-dev\")\n",
        "try:\n",
        "    table = db.create_table(\"movie_set\", data=data)\n",
        "except:\n",
        "    table = db.open_table(\"movie_set\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KoiIKjZx7sGv"
      },
      "source": [
        "## Get the Recommendations\n",
        "Finally, we can create a function that takes a movie title and returns the top 5 similar movies. By searching in our vector store for the embeddings of the movie, we can return a dataframe of the most similar movies. We can also add some flair reading and displaying the links of each movie."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8SVEEluC7sGv"
      },
      "outputs": [],
      "source": [
        "def get_recommendations(title):\n",
        "    pd_data = pd.DataFrame(data)\n",
        "    result = table.search(pd_data[pd_data['title'] == title][\"vector\"].values[0]).limit(5).to_pandas()\n",
        "\n",
        "    links = pd.read_csv('./ml-latest-small/links.csv', header=0, names=[\"movie id\", \"imdb id\", \"tmdb id\"], converters={'imdb id': str})\n",
        "\n",
        "    ret = result['title'].values.tolist()\n",
        "    for i in range(len(ret)):\n",
        "        link = links[links['movie id'] == result['id'].values[i]][\"imdb id\"].values[0]\n",
        "        link = \"https://www.imdb.com/title/tt\" + link\n",
        "        ret[i] = [ret[i], link]\n",
        "    return ret"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2mgrcOva7sGv"
      },
      "source": [
        "## Let's test it out!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KUVSrkew7sGw",
        "outputId": "99fa1814-e3d3-4f9d-8d36-451e905a7427"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Moana (2016)', 'https://www.imdb.com/title/tt3521164'],\n",
              " ['The Boss Baby (2017)', 'https://www.imdb.com/title/tt3874544'],\n",
              " ['The Book of Life (2014)', 'https://www.imdb.com/title/tt2262227'],\n",
              " ['Kubo and the Two Strings (2016)', 'https://www.imdb.com/title/tt4302938'],\n",
              " ['Bad Moms (2016)', 'https://www.imdb.com/title/tt4651520']]"
            ]
          },
          "execution_count": 12,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "get_recommendations(\"Moana (2016)\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ws889F097sGw",
        "outputId": "b0ffe57e-67c7-4ba2-d715-92390c42562a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Rogue One: A Star Wars Story (2016)',\n",
              "  'https://www.imdb.com/title/tt3748528'],\n",
              " ['Wonder Woman (2017)', 'https://www.imdb.com/title/tt0451279'],\n",
              " ['Miss Sloane (2016)', 'https://www.imdb.com/title/tt4540710'],\n",
              " ['Passengers (2016)', 'https://www.imdb.com/title/tt1355644'],\n",
              " ['Man of Steel (2013)', 'https://www.imdb.com/title/tt0770828']]"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "get_recommendations(\"Rogue One: A Star Wars Story (2016)\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zsXoZEBL7sGw"
      },
      "source": [
        "## Tada!! your first movie recommendation system is live\n",
        "\n",
        "Of course, this won't be completely accurate. There are other ways improve the accuracy, such as `reducing the dimensions` of the original data, or filtering out users/movies with few ratings. But this is a good start to building a movie recommender system."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3iTqwDNQ9WtD"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
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    "kernelspec": {
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      "language": "python",
      "name": "python3"
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