{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "Zdars7QjaEji"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.datasets import fetch_california_housing"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "california_housing = fetch_california_housing()\n",
        "\n",
        "X = pd.DataFrame(california_housing.data, columns=california_housing.feature_names)\n",
        "y = pd.Series(california_housing.target)"
      ],
      "metadata": {
        "id": "AalFxTEWaFpG"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X = X[['MedInc', 'AveRooms']]"
      ],
      "metadata": {
        "id": "7mcPe1vhaH3a"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    X, y, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "RDQRmRDmaRA4"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = LinearRegression()\n",
        "\n",
        "model.fit(X_train, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 82
        },
        "id": "qQ_inSKgaMkv",
        "outputId": "2f03971c-4020-402b-8088-8625bbea954b"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "LinearRegression()"
            ],
            "text/html": [
              "<style>#sk-container-id-2 {\n",
              "  /* Definition of color scheme common for light and dark mode */\n",
              "  --sklearn-color-text: #000;\n",
              "  --sklearn-color-text-muted: #666;\n",
              "  --sklearn-color-line: gray;\n",
              "  /* Definition of color scheme for unfitted estimators */\n",
              "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
              "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
              "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
              "  --sklearn-color-unfitted-level-3: chocolate;\n",
              "  /* Definition of color scheme for fitted estimators */\n",
              "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
              "  --sklearn-color-fitted-level-1: #d4ebff;\n",
              "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
              "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
              "\n",
              "  /* Specific color for light theme */\n",
              "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
              "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
              "  --sklearn-color-icon: #696969;\n",
              "\n",
              "  @media (prefers-color-scheme: dark) {\n",
              "    /* Redefinition of color scheme for dark theme */\n",
              "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
              "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
              "    --sklearn-color-icon: #878787;\n",
              "  }\n",
              "}\n",
              "\n",
              "#sk-container-id-2 {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 pre {\n",
              "  padding: 0;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-hidden--visually {\n",
              "  border: 0;\n",
              "  clip: rect(1px 1px 1px 1px);\n",
              "  clip: rect(1px, 1px, 1px, 1px);\n",
              "  height: 1px;\n",
              "  margin: -1px;\n",
              "  overflow: hidden;\n",
              "  padding: 0;\n",
              "  position: absolute;\n",
              "  width: 1px;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-dashed-wrapped {\n",
              "  border: 1px dashed var(--sklearn-color-line);\n",
              "  margin: 0 0.4em 0.5em 0.4em;\n",
              "  box-sizing: border-box;\n",
              "  padding-bottom: 0.4em;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-container {\n",
              "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
              "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
              "     so we also need the `!important` here to be able to override the\n",
              "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
              "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
              "  display: inline-block !important;\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-text-repr-fallback {\n",
              "  display: none;\n",
              "}\n",
              "\n",
              "div.sk-parallel-item,\n",
              "div.sk-serial,\n",
              "div.sk-item {\n",
              "  /* draw centered vertical line to link estimators */\n",
              "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
              "  background-size: 2px 100%;\n",
              "  background-repeat: no-repeat;\n",
              "  background-position: center center;\n",
              "}\n",
              "\n",
              "/* Parallel-specific style estimator block */\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item::after {\n",
              "  content: \"\";\n",
              "  width: 100%;\n",
              "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
              "  flex-grow: 1;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel {\n",
              "  display: flex;\n",
              "  align-items: stretch;\n",
              "  justify-content: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  position: relative;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
              "  align-self: flex-end;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
              "  align-self: flex-start;\n",
              "  width: 50%;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
              "  width: 0;\n",
              "}\n",
              "\n",
              "/* Serial-specific style estimator block */\n",
              "\n",
              "#sk-container-id-2 div.sk-serial {\n",
              "  display: flex;\n",
              "  flex-direction: column;\n",
              "  align-items: center;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  padding-right: 1em;\n",
              "  padding-left: 1em;\n",
              "}\n",
              "\n",
              "\n",
              "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
              "clickable and can be expanded/collapsed.\n",
              "- Pipeline and ColumnTransformer use this feature and define the default style\n",
              "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
              "*/\n",
              "\n",
              "/* Pipeline and ColumnTransformer style (default) */\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable {\n",
              "  /* Default theme specific background. It is overwritten whether we have a\n",
              "  specific estimator or a Pipeline/ColumnTransformer */\n",
              "  background-color: var(--sklearn-color-background);\n",
              "}\n",
              "\n",
              "/* Toggleable label */\n",
              "#sk-container-id-2 label.sk-toggleable__label {\n",
              "  cursor: pointer;\n",
              "  display: flex;\n",
              "  width: 100%;\n",
              "  margin-bottom: 0;\n",
              "  padding: 0.5em;\n",
              "  box-sizing: border-box;\n",
              "  text-align: center;\n",
              "  align-items: start;\n",
              "  justify-content: space-between;\n",
              "  gap: 0.5em;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
              "  font-size: 0.6rem;\n",
              "  font-weight: lighter;\n",
              "  color: var(--sklearn-color-text-muted);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
              "  /* Arrow on the left of the label */\n",
              "  content: \"▸\";\n",
              "  float: left;\n",
              "  margin-right: 0.25em;\n",
              "  color: var(--sklearn-color-icon);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
              "  color: var(--sklearn-color-text);\n",
              "}\n",
              "\n",
              "/* Toggleable content - dropdown */\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content {\n",
              "  max-height: 0;\n",
              "  max-width: 0;\n",
              "  overflow: hidden;\n",
              "  text-align: left;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content pre {\n",
              "  margin: 0.2em;\n",
              "  border-radius: 0.25em;\n",
              "  color: var(--sklearn-color-text);\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
              "  /* Expand drop-down */\n",
              "  max-height: 200px;\n",
              "  max-width: 100%;\n",
              "  overflow: auto;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
              "  content: \"▾\";\n",
              "}\n",
              "\n",
              "/* Pipeline/ColumnTransformer-specific style */\n",
              "\n",
              "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator-specific style */\n",
              "\n",
              "/* Colorize estimator box */\n",
              "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
              "#sk-container-id-2 div.sk-label label {\n",
              "  /* The background is the default theme color */\n",
              "  color: var(--sklearn-color-text-on-default-background);\n",
              "}\n",
              "\n",
              "/* On hover, darken the color of the background */\n",
              "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "/* Label box, darken color on hover, fitted */\n",
              "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
              "  color: var(--sklearn-color-text);\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Estimator label */\n",
              "\n",
              "#sk-container-id-2 div.sk-label label {\n",
              "  font-family: monospace;\n",
              "  font-weight: bold;\n",
              "  display: inline-block;\n",
              "  line-height: 1.2em;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-label-container {\n",
              "  text-align: center;\n",
              "}\n",
              "\n",
              "/* Estimator-specific */\n",
              "#sk-container-id-2 div.sk-estimator {\n",
              "  font-family: monospace;\n",
              "  border: 1px dotted var(--sklearn-color-border-box);\n",
              "  border-radius: 0.25em;\n",
              "  box-sizing: border-box;\n",
              "  margin-bottom: 0.5em;\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-0);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-0);\n",
              "}\n",
              "\n",
              "/* on hover */\n",
              "#sk-container-id-2 div.sk-estimator:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-2);\n",
              "}\n",
              "\n",
              "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-2);\n",
              "}\n",
              "\n",
              "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
              "\n",
              "/* Common style for \"i\" and \"?\" */\n",
              "\n",
              ".sk-estimator-doc-link,\n",
              "a:link.sk-estimator-doc-link,\n",
              "a:visited.sk-estimator-doc-link {\n",
              "  float: right;\n",
              "  font-size: smaller;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1em;\n",
              "  height: 1em;\n",
              "  width: 1em;\n",
              "  text-decoration: none !important;\n",
              "  margin-left: 0.5em;\n",
              "  text-align: center;\n",
              "  /* unfitted */\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted,\n",
              "a:link.sk-estimator-doc-link.fitted,\n",
              "a:visited.sk-estimator-doc-link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
              ".sk-estimator-doc-link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover,\n",
              "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
              ".sk-estimator-doc-link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "/* Span, style for the box shown on hovering the info icon */\n",
              ".sk-estimator-doc-link span {\n",
              "  display: none;\n",
              "  z-index: 9999;\n",
              "  position: relative;\n",
              "  font-weight: normal;\n",
              "  right: .2ex;\n",
              "  padding: .5ex;\n",
              "  margin: .5ex;\n",
              "  width: min-content;\n",
              "  min-width: 20ex;\n",
              "  max-width: 50ex;\n",
              "  color: var(--sklearn-color-text);\n",
              "  box-shadow: 2pt 2pt 4pt #999;\n",
              "  /* unfitted */\n",
              "  background: var(--sklearn-color-unfitted-level-0);\n",
              "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link.fitted span {\n",
              "  /* fitted */\n",
              "  background: var(--sklearn-color-fitted-level-0);\n",
              "  border: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "\n",
              ".sk-estimator-doc-link:hover span {\n",
              "  display: block;\n",
              "}\n",
              "\n",
              "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link {\n",
              "  float: right;\n",
              "  font-size: 1rem;\n",
              "  line-height: 1em;\n",
              "  font-family: monospace;\n",
              "  background-color: var(--sklearn-color-background);\n",
              "  border-radius: 1rem;\n",
              "  height: 1rem;\n",
              "  width: 1rem;\n",
              "  text-decoration: none;\n",
              "  /* unfitted */\n",
              "  color: var(--sklearn-color-unfitted-level-1);\n",
              "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
              "  /* fitted */\n",
              "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
              "  color: var(--sklearn-color-fitted-level-1);\n",
              "}\n",
              "\n",
              "/* On hover */\n",
              "#sk-container-id-2 a.estimator_doc_link:hover {\n",
              "  /* unfitted */\n",
              "  background-color: var(--sklearn-color-unfitted-level-3);\n",
              "  color: var(--sklearn-color-background);\n",
              "  text-decoration: none;\n",
              "}\n",
              "\n",
              "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
              "  /* fitted */\n",
              "  background-color: var(--sklearn-color-fitted-level-3);\n",
              "}\n",
              "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>LinearRegression</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.6/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "intercept = model.intercept_\n",
        "coefficients = model.coef_\n",
        "\n",
        "print(\"Intercept:\", intercept)\n",
        "print(\"Coefficients:\", coefficients)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iVexU9fraY7K",
        "outputId": "951f3850-da09-414e-f114-52936b32c569"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Intercept: 0.5972677793933272\n",
            "Coefficients: [ 0.43626089 -0.04017161]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = model.predict(X_test)"
      ],
      "metadata": {
        "id": "3mt0rdX3a9-n"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(10, 7))\n",
        "ax = fig.add_subplot(111, projection='3d')\n",
        "\n",
        "ax.scatter(X_test['MedInc'], X_test['AveRooms'],\n",
        "           y_test, color='blue', label='Actual Data')\n",
        "\n",
        "x1_range = np.linspace(X_test['MedInc'].min(), X_test['MedInc'].max(), 100)\n",
        "x2_range = np.linspace(X_test['AveRooms'].min(), X_test['AveRooms'].max(), 100)\n",
        "x1, x2 = np.meshgrid(x1_range, x2_range)\n",
        "\n",
        "z = model.predict(np.c_[x1.ravel(), x2.ravel()]).reshape(x1.shape)\n",
        "\n",
        "ax.plot_surface(x1, x2, z, color='red', alpha=0.5, rstride=100, cstride=100)\n",
        "\n",
        "ax.set_xlabel('Median Income')\n",
        "ax.set_ylabel('Average Rooms')\n",
        "ax.set_zlabel('House Price')\n",
        "ax.set_title('Multiple Linear Regression Best Fit Line (3D)')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 636
        },
        "id": "C3pdMQeGaaXl",
        "outputId": "3417872d-cdd3-4451-f467-96f892382acf"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.12/dist-packages/sklearn/utils/validation.py:2739: UserWarning: X does not have valid feature names, but LinearRegression was fitted with feature names\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x700 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "GDC4Phmladgs"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}