sem07_regression/sem07_group08.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "b903f566",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "b098b8cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 80)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>...</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "Id                                                                    \n",
       "1           60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "2           20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "3           60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "4           70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "5           60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "   LandContour Utilities LotConfig  ... PoolArea PoolQC Fence MiscFeature  \\\n",
       "Id                                  ...                                     \n",
       "1          Lvl    AllPub    Inside  ...        0    NaN   NaN         NaN   \n",
       "2          Lvl    AllPub       FR2  ...        0    NaN   NaN         NaN   \n",
       "3          Lvl    AllPub    Inside  ...        0    NaN   NaN         NaN   \n",
       "4          Lvl    AllPub    Corner  ...        0    NaN   NaN         NaN   \n",
       "5          Lvl    AllPub       FR2  ...        0    NaN   NaN         NaN   \n",
       "\n",
       "   MiscVal MoSold  YrSold  SaleType  SaleCondition  SalePrice  \n",
       "Id                                                             \n",
       "1        0      2    2008        WD         Normal     208500  \n",
       "2        0      5    2007        WD         Normal     181500  \n",
       "3        0      9    2008        WD         Normal     223500  \n",
       "4        0      2    2006        WD        Abnorml     140000  \n",
       "5        0     12    2008        WD         Normal     250000  \n",
       "\n",
       "[5 rows x 80 columns]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('train.csv', index_col=0)\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "f8561d7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "df_train, df_test = train_test_split(df, test_size=0.2)\n",
    "\n",
    "y_train = df_train['SalePrice'].values\n",
    "y_test = df_test['SalePrice'].values\n",
    "\n",
    "X_train = df_train.drop('SalePrice', axis=1)\n",
    "X_test = df_test.drop('SalePrice', axis=1)\n",
    "\n",
    "cat_features = X_train.dtypes[X_train.dtypes == 'object'].index.values\n",
    "num_features = X_train.dtypes[X_train.dtypes != 'object'].index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "e2060bfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MSSubClass       0\n",
       "LotFrontage    200\n",
       "LotArea          0\n",
       "OverallQual      0\n",
       "OverallCond      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train[num_features].isnull().sum()[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "f746a53d",
   "metadata": {},
   "outputs": [],
   "source": [
    "med = X_train[num_features].median()\n",
    "X_train = X_train.fillna(med)\n",
    "X_test = X_test.fillna(med)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4e3efd52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.30670400859565966"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_percentage_error\n",
    "\n",
    "# наивный прогноз\n",
    "y_naive_pred = np.median(y_train) * np.ones_like(y_test)\n",
    "mean_absolute_percentage_error(y_test, y_naive_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "d3bcd327",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15675769254871963"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "\n",
    "model_knn = KNeighborsRegressor(n_neighbors=10, p=2, weights='distance')\n",
    "model_knn.fit(X_train[num_features], y_train)\n",
    "y_pred = model_knn.predict(X_test[num_features])\n",
    "\n",
    "mean_absolute_percentage_error(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d0c88af3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11863087732916804"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "model_reg = LinearRegression()\n",
    "model_reg.fit(X_train[num_features], y_train)\n",
    "y_pred = model_reg.predict(X_test[num_features])\n",
    "\n",
    "mean_absolute_percentage_error(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "02c2dc26",
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_weights(features, weights, scales):\n",
    "    fig, axs = plt.subplots(figsize=(14, 10), ncols=2)\n",
    "    sorted_weights = sorted(zip(weights, features, scales), reverse=True)\n",
    "    weights = [x[0] for x in sorted_weights]\n",
    "    features = [x[1] for x in sorted_weights]\n",
    "    scales = [x[2] for x in sorted_weights]\n",
    "    sns.barplot(y=features, x=weights, ax=axs[0])\n",
    "    axs[0].set_xlabel(\"Weight\")\n",
    "    sns.barplot(y=features, x=scales, ax=axs[1])\n",
    "    axs[1].set_xlabel(\"Scale\")\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d5aad1cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1400x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_weights(num_features, model_reg.coef_, X_train[num_features].std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "e82176fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "scaler = StandardScaler()\n",
    "\n",
    "X_train_scale = scaler.fit_transform(X_train[num_features])\n",
    "X_test_scale = scaler.transform(X_test[num_features])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "82ad52a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1132236546369891"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_knn = KNeighborsRegressor(n_neighbors=10, p=2, weights='distance')\n",
    "model_knn.fit(X_train_scale, y_train)\n",
    "y_pred = model_knn.predict(X_test_scale)\n",
    "\n",
    "mean_absolute_percentage_error(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "670dbe3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.11865773512470577"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_reg = LinearRegression()\n",
    "model_reg.fit(X_train_scale, y_train)\n",
    "y_pred = model_reg.predict(X_test_scale)\n",
    "\n",
    "mean_absolute_percentage_error(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "69fa32c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1400x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scales = pd.Series(data=X_train_scale.std(axis=0), index=num_features)\n",
    "show_weights(num_features, model_reg.coef_, scales)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "831269d2",
   "metadata": {},
   "source": [
    "------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "fa20f8ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.preprocessing import OneHotEncoder, StandardScaler, PolynomialFeatures\n",
    "from sklearn.linear_model import Ridge, Lasso\n",
    "\n",
    "def get_quality(model, X_train=X_train, X_test=X_test,\n",
    "               y_train=y_train, y_test=y_test):\n",
    "    y_pred = model.predict(X_test)\n",
    "    y_pred_tr = model.predict(X_train)\n",
    "    print('train mape:', mean_absolute_percentage_error(y_train, y_pred_tr))\n",
    "    print('test mape:', mean_absolute_percentage_error(y_test, y_pred))\n",
    "\n",
    "\n",
    "column_transformer = ColumnTransformer([\n",
    "    ('scaler', StandardScaler(), num_features),\n",
    "    ('poly', PolynomialFeatures(degree=2, include_bias=False), num_features),\n",
    "    ('ohe', OneHotEncoder(handle_unknown=\"ignore\", drop='first', \n",
    "                          min_frequency=0.001), cat_features)\n",
    "])\n",
    "\n",
    "pipeline_knn = Pipeline([\n",
    "    ('transform', column_transformer),\n",
    "    ('knn', KNeighborsRegressor())\n",
    "])\n",
    "\n",
    "pipeline_rige =  Pipeline([\n",
    "    ('transform', column_transformer),\n",
    "    ('ridge', Ridge())\n",
    "])\n",
    "\n",
    "pipeline_lasso =  Pipeline([\n",
    "    ('transform', column_transformer),\n",
    "    ('lasso', Lasso())\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "480a228e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "alphas = np.logspace(-2, 3, 20)\n",
    "\n",
    "searcher = GridSearchCV(\n",
    "    pipeline_rige, [{\"ridge__alpha\": alphas}],\n",
    "    scoring=\"neg_mean_absolute_error\", cv=5\n",
    ")\n",
    "\n",
    "searcher.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "9b635421",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.3357214690901213"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "searcher.best_params_[\"ridge__alpha\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "2d26ca4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(5,4))\n",
    "plt.plot(alphas, -searcher.cv_results_[\"mean_test_score\"])\n",
    "plt.xscale(\"log\")\n",
    "plt.xlabel(\"alpha\")\n",
    "plt.ylabel(\"CV score\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60844ed1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7ad102f2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "47b89d7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "72893.5647805425"
      ]
     },
     "execution_count": 127,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.abs(pipeline_rige['ridge'].coef_).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "93f4454c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train mape: 0.06701977659644026\n",
      "test mape: 0.2440571448088601\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/lib/python3.10/site-packages/sklearn/linear_model/_ridge.py:216: LinAlgWarning: Ill-conditioned matrix (rcond=4.88908e-20): result may not be accurate.\n",
      "  return linalg.solve(A, Xy, assume_a=\"pos\", overwrite_a=True).T\n",
      "/opt/homebrew/lib/python3.10/site-packages/sklearn/preprocessing/_encoders.py:202: UserWarning: Found unknown categories in columns [10, 14, 26] during transform. These unknown categories will be encoded as all zeros\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "pipeline_rige.fit(X_train, y_train)\n",
    "get_quality(pipeline_rige)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c7b7da20",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eef84f1d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "384f003d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "c77357b6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train mape: 0.009794916219460211\n",
      "test mape: 0.20304153556895346\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.784e+09, tolerance: 7.414e+08\n",
      "  model = cd_fast.enet_coordinate_descent(\n",
      "/opt/homebrew/lib/python3.10/site-packages/sklearn/preprocessing/_encoders.py:202: UserWarning: Found unknown categories in columns [10, 14, 26] during transform. These unknown categories will be encoded as all zeros\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "pipeline_lasso.fit(X_train, y_train)\n",
    "get_quality(pipeline_lasso)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "aa00c577",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9a6f4ef0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fdc3e23b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be2b349b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7bb2061a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a10b042b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}