ML0(LinearRegression).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = 2 * np.random.rand(100, 1)\n",
    "y = 4 + 3 * X + np.random.randn(100, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(X, y, \"b.\")\n",
    "plt.xlabel(\"$x_1$\", fontsize=18)\n",
    "plt.ylabel(\"$y$\", rotation=0, fontsize=18)\n",
    "plt.axis([0, 2, 0, 15])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3.84639979]), array([[3.30854901]]))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_reg = LinearRegression()\n",
    "lin_reg.fit(X, y)\n",
    "lin_reg.intercept_, lin_reg.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.700</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.880</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.098</td>\n",
       "      <td>25.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>0.9968</td>\n",
       "      <td>3.20</td>\n",
       "      <td>0.68</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.8</td>\n",
       "      <td>0.760</td>\n",
       "      <td>0.04</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.092</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.9970</td>\n",
       "      <td>3.26</td>\n",
       "      <td>0.65</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.2</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.56</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.075</td>\n",
       "      <td>17.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>0.9980</td>\n",
       "      <td>3.16</td>\n",
       "      <td>0.58</td>\n",
       "      <td>9.8</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.4</td>\n",
       "      <td>0.700</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.076</td>\n",
       "      <td>11.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.9978</td>\n",
       "      <td>3.51</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>4.7</td>\n",
       "      <td>0.600</td>\n",
       "      <td>0.17</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.058</td>\n",
       "      <td>17.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>0.9932</td>\n",
       "      <td>3.85</td>\n",
       "      <td>0.60</td>\n",
       "      <td>12.9</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>6.8</td>\n",
       "      <td>0.775</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.102</td>\n",
       "      <td>8.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.9965</td>\n",
       "      <td>3.45</td>\n",
       "      <td>0.56</td>\n",
       "      <td>10.7</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.500</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.070</td>\n",
       "      <td>3.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.9963</td>\n",
       "      <td>3.25</td>\n",
       "      <td>0.63</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>7.6</td>\n",
       "      <td>0.900</td>\n",
       "      <td>0.06</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.079</td>\n",
       "      <td>5.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.9967</td>\n",
       "      <td>3.39</td>\n",
       "      <td>0.56</td>\n",
       "      <td>9.8</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>8.1</td>\n",
       "      <td>0.545</td>\n",
       "      <td>0.18</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.080</td>\n",
       "      <td>13.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.9972</td>\n",
       "      <td>3.30</td>\n",
       "      <td>0.59</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    fixed acidity  volatile acidity  citric acid  residual sugar  chlorides  \\\n",
       "0             7.4             0.700         0.00             1.9      0.076   \n",
       "1             7.8             0.880         0.00             2.6      0.098   \n",
       "2             7.8             0.760         0.04             2.3      0.092   \n",
       "3            11.2             0.280         0.56             1.9      0.075   \n",
       "4             7.4             0.700         0.00             1.9      0.076   \n",
       "..            ...               ...          ...             ...        ...   \n",
       "95            4.7             0.600         0.17             2.3      0.058   \n",
       "96            6.8             0.775         0.00             3.0      0.102   \n",
       "97            7.0             0.500         0.25             2.0      0.070   \n",
       "98            7.6             0.900         0.06             2.5      0.079   \n",
       "99            8.1             0.545         0.18             1.9      0.080   \n",
       "\n",
       "    free sulfur dioxide  total sulfur dioxide  density    pH  sulphates  \\\n",
       "0                  11.0                  34.0   0.9978  3.51       0.56   \n",
       "1                  25.0                  67.0   0.9968  3.20       0.68   \n",
       "2                  15.0                  54.0   0.9970  3.26       0.65   \n",
       "3                  17.0                  60.0   0.9980  3.16       0.58   \n",
       "4                  11.0                  34.0   0.9978  3.51       0.56   \n",
       "..                  ...                   ...      ...   ...        ...   \n",
       "95                 17.0                 106.0   0.9932  3.85       0.60   \n",
       "96                  8.0                  23.0   0.9965  3.45       0.56   \n",
       "97                  3.0                  22.0   0.9963  3.25       0.63   \n",
       "98                  5.0                  10.0   0.9967  3.39       0.56   \n",
       "99                 13.0                  35.0   0.9972  3.30       0.59   \n",
       "\n",
       "    alcohol  quality  \n",
       "0       9.4        5  \n",
       "1       9.8        5  \n",
       "2       9.8        5  \n",
       "3       9.8        6  \n",
       "4       9.4        5  \n",
       "..      ...      ...  \n",
       "95     12.9        6  \n",
       "96     10.7        5  \n",
       "97      9.2        5  \n",
       "98      9.8        5  \n",
       "99      9.0        6  \n",
       "\n",
       "[100 rows x 12 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_data = pd.read_csv(r'https://raw.githubusercontent.com/data-max-hq/workshop-epoka/main/data/winequality-red.csv')\n",
    "wine_data.head(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "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>fixed acidity</th>\n",
       "      <th>volatile acidity</th>\n",
       "      <th>citric acid</th>\n",
       "      <th>residual sugar</th>\n",
       "      <th>chlorides</th>\n",
       "      <th>free sulfur dioxide</th>\n",
       "      <th>total sulfur dioxide</th>\n",
       "      <th>density</th>\n",
       "      <th>pH</th>\n",
       "      <th>sulphates</th>\n",
       "      <th>alcohol</th>\n",
       "      <th>quality</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "      <td>1599.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8.319637</td>\n",
       "      <td>0.527821</td>\n",
       "      <td>0.270976</td>\n",
       "      <td>2.538806</td>\n",
       "      <td>0.087467</td>\n",
       "      <td>15.874922</td>\n",
       "      <td>46.467792</td>\n",
       "      <td>0.996747</td>\n",
       "      <td>3.311113</td>\n",
       "      <td>0.658149</td>\n",
       "      <td>10.422983</td>\n",
       "      <td>5.636023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.741096</td>\n",
       "      <td>0.179060</td>\n",
       "      <td>0.194801</td>\n",
       "      <td>1.409928</td>\n",
       "      <td>0.047065</td>\n",
       "      <td>10.460157</td>\n",
       "      <td>32.895324</td>\n",
       "      <td>0.001887</td>\n",
       "      <td>0.154386</td>\n",
       "      <td>0.169507</td>\n",
       "      <td>1.065668</td>\n",
       "      <td>0.807569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.600000</td>\n",
       "      <td>0.120000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.012000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.990070</td>\n",
       "      <td>2.740000</td>\n",
       "      <td>0.330000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>7.100000</td>\n",
       "      <td>0.390000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>1.900000</td>\n",
       "      <td>0.070000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.995600</td>\n",
       "      <td>3.210000</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.260000</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>0.079000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>0.996750</td>\n",
       "      <td>3.310000</td>\n",
       "      <td>0.620000</td>\n",
       "      <td>10.200000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.200000</td>\n",
       "      <td>0.640000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>2.600000</td>\n",
       "      <td>0.090000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.997835</td>\n",
       "      <td>3.400000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>11.100000</td>\n",
       "      <td>6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>15.900000</td>\n",
       "      <td>1.580000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>15.500000</td>\n",
       "      <td>0.611000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>289.000000</td>\n",
       "      <td>1.003690</td>\n",
       "      <td>4.010000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>14.900000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       fixed acidity  volatile acidity  citric acid  residual sugar  \\\n",
       "count    1599.000000       1599.000000  1599.000000     1599.000000   \n",
       "mean        8.319637          0.527821     0.270976        2.538806   \n",
       "std         1.741096          0.179060     0.194801        1.409928   \n",
       "min         4.600000          0.120000     0.000000        0.900000   \n",
       "25%         7.100000          0.390000     0.090000        1.900000   \n",
       "50%         7.900000          0.520000     0.260000        2.200000   \n",
       "75%         9.200000          0.640000     0.420000        2.600000   \n",
       "max        15.900000          1.580000     1.000000       15.500000   \n",
       "\n",
       "         chlorides  free sulfur dioxide  total sulfur dioxide      density  \\\n",
       "count  1599.000000          1599.000000           1599.000000  1599.000000   \n",
       "mean      0.087467            15.874922             46.467792     0.996747   \n",
       "std       0.047065            10.460157             32.895324     0.001887   \n",
       "min       0.012000             1.000000              6.000000     0.990070   \n",
       "25%       0.070000             7.000000             22.000000     0.995600   \n",
       "50%       0.079000            14.000000             38.000000     0.996750   \n",
       "75%       0.090000            21.000000             62.000000     0.997835   \n",
       "max       0.611000            72.000000            289.000000     1.003690   \n",
       "\n",
       "                pH    sulphates      alcohol      quality  \n",
       "count  1599.000000  1599.000000  1599.000000  1599.000000  \n",
       "mean      3.311113     0.658149    10.422983     5.636023  \n",
       "std       0.154386     0.169507     1.065668     0.807569  \n",
       "min       2.740000     0.330000     8.400000     3.000000  \n",
       "25%       3.210000     0.550000     9.500000     5.000000  \n",
       "50%       3.310000     0.620000    10.200000     6.000000  \n",
       "75%       3.400000     0.730000    11.100000     6.000000  \n",
       "max       4.010000     2.000000    14.900000     8.000000  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wine_data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation = wine_data.corr()\n",
    "fig = plt.subplots(figsize=(10,10))\n",
    "sns.heatmap(correlation,vmax=1,square=True,annot=True,cmap='Blues')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = wine_data.drop('quality', axis=1)\n",
    "y = wine_data['quality']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=101, train_size=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor = LinearRegression()\n",
    "regressor.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5.6376633958174995,\n",
       " array([ 0.0290763 , -1.18318038, -0.27601214,  0.01242033, -1.81660638,\n",
       "         0.00251779, -0.00290222, -1.66215311, -0.42499618,  0.87459387,\n",
       "         0.3053825 ]))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor.intercept_ , regressor.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import mean_absolute_error, mean_squared_error\n",
    "y_pred = regressor.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5261410255981688\n",
      "0.725355792420636\n"
     ]
    }
   ],
   "source": [
    "mse = mean_squared_error(y_test, y_pred)\n",
    "rmse = np.sqrt(mse)\n",
    "print(mse)\n",
    "print(rmse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\marvi\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but LinearRegression was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([6.64994812])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data = np.array([7.8, 0.880, 0.03, 1.7, 0.094, 17.0, 57.0, 0.9, 3.74, 0.56, 15.4]).reshape(1, -1)\n",
    "regressor.predict(new_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open ('./model.pkl', 'wb') as file:\n",
    "    pickle.dump(regressor, file)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}