steam-score-prediction-with-randomforestregressor.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/yahyasoker/steam-score-prediction-with-randomforestregressor?scriptVersionId=130720801\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"markdown","id":"90f81ef8","metadata":{"papermill":{"duration":0.0093,"end_time":"2023-05-23T17:18:24.620032","exception":false,"start_time":"2023-05-23T17:18:24.610732","status":"completed"},"tags":[]},"source":["# [1.Preparing Data](#1)\n","### [2.Training Data](#2)\n","### [3.Predicting](#3)"]},{"cell_type":"code","execution_count":1,"id":"2065a3df","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","execution":{"iopub.execute_input":"2023-05-23T17:18:24.638928Z","iopub.status.busy":"2023-05-23T17:18:24.638427Z","iopub.status.idle":"2023-05-23T17:18:26.793682Z","shell.execute_reply":"2023-05-23T17:18:26.792433Z"},"papermill":{"duration":2.168443,"end_time":"2023-05-23T17:18:26.796931","exception":false,"start_time":"2023-05-23T17:18:24.628488","status":"completed"},"tags":[]},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.model_selection import train_test_split\n","from sklearn.ensemble import RandomForestRegressor\n","from sklearn import metrics\n","from sklearn.metrics import r2_score"]},{"cell_type":"markdown","id":"a0173dc7","metadata":{"papermill":{"duration":0.007351,"end_time":"2023-05-23T17:18:26.812089","exception":false,"start_time":"2023-05-23T17:18:26.804738","status":"completed"},"tags":[]},"source":["<a id='1'></a>\n","### 1.Perparing Data"]},{"cell_type":"code","execution_count":2,"id":"da03d7f6","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:26.82955Z","iopub.status.busy":"2023-05-23T17:18:26.829121Z","iopub.status.idle":"2023-05-23T17:18:27.217798Z","shell.execute_reply":"2023-05-23T17:18:27.216367Z"},"papermill":{"duration":0.401609,"end_time":"2023-05-23T17:18:27.221391","exception":false,"start_time":"2023-05-23T17:18:26.819782","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["Unnamed: 0          0\n","game                0\n","link                0\n","release             0\n","peak_players        0\n","positive_reviews    0\n","negative_reviews    0\n","total_reviews       0\n","rating              0\n","dtype: int64"]},"execution_count":2,"metadata":{},"output_type":"execute_result"}],"source":["df = pd.read_csv(\"/kaggle/input/steam-releases/games-release-ALL.csv\")\n","df.isnull().sum()"]},{"cell_type":"code","execution_count":3,"id":"16f45177","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.240039Z","iopub.status.busy":"2023-05-23T17:18:27.239573Z","iopub.status.idle":"2023-05-23T17:18:27.24995Z","shell.execute_reply":"2023-05-23T17:18:27.248603Z"},"papermill":{"duration":0.022982,"end_time":"2023-05-23T17:18:27.252694","exception":false,"start_time":"2023-05-23T17:18:27.229712","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["(66427, 9)"]},"execution_count":3,"metadata":{},"output_type":"execute_result"}],"source":["df.shape"]},{"cell_type":"code","execution_count":4,"id":"32c1f978","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.271957Z","iopub.status.busy":"2023-05-23T17:18:27.270607Z","iopub.status.idle":"2023-05-23T17:18:27.379136Z","shell.execute_reply":"2023-05-23T17:18:27.378037Z"},"papermill":{"duration":0.121125,"end_time":"2023-05-23T17:18:27.382133","exception":false,"start_time":"2023-05-23T17:18:27.261008","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 66427 entries, 0 to 66426\n","Data columns (total 9 columns):\n"," #   Column            Non-Null Count  Dtype \n","---  ------            --------------  ----- \n"," 0   Unnamed: 0        66427 non-null  int64 \n"," 1   game              66427 non-null  object\n"," 2   link              66427 non-null  object\n"," 3   release           66427 non-null  object\n"," 4   peak_players      66427 non-null  object\n"," 5   positive_reviews  66427 non-null  object\n"," 6   negative_reviews  66427 non-null  object\n"," 7   total_reviews     66427 non-null  object\n"," 8   rating            66427 non-null  object\n","dtypes: int64(1), object(8)\n","memory usage: 4.6+ MB\n"]}],"source":["df.info()"]},{"cell_type":"code","execution_count":5,"id":"8c7f5f60","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.401588Z","iopub.status.busy":"2023-05-23T17:18:27.401152Z","iopub.status.idle":"2023-05-23T17:18:27.436885Z","shell.execute_reply":"2023-05-23T17:18:27.435569Z"},"papermill":{"duration":0.049525,"end_time":"2023-05-23T17:18:27.440247","exception":false,"start_time":"2023-05-23T17:18:27.390722","status":"completed"},"tags":[]},"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>Unnamed: 0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>66427.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>33213.000000</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>19175.967503</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>16606.500000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>33213.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>49819.500000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>66426.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["         Unnamed: 0\n","count  66427.000000\n","mean   33213.000000\n","std    19175.967503\n","min        0.000000\n","25%    16606.500000\n","50%    33213.000000\n","75%    49819.500000\n","max    66426.000000"]},"execution_count":5,"metadata":{},"output_type":"execute_result"}],"source":["df.describe()"]},{"cell_type":"code","execution_count":6,"id":"aed609bf","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.459322Z","iopub.status.busy":"2023-05-23T17:18:27.458868Z","iopub.status.idle":"2023-05-23T17:18:27.479269Z","shell.execute_reply":"2023-05-23T17:18:27.477924Z"},"papermill":{"duration":0.033091,"end_time":"2023-05-23T17:18:27.482049","exception":false,"start_time":"2023-05-23T17:18:27.448958","status":"completed"},"tags":[]},"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>Unnamed: 0</th>\n","      <th>game</th>\n","      <th>link</th>\n","      <th>release</th>\n","      <th>peak_players</th>\n","      <th>positive_reviews</th>\n","      <th>negative_reviews</th>\n","      <th>total_reviews</th>\n","      <th>rating</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>Pizza Tower</td>\n","      <td>/app/2231450/</td>\n","      <td>Jan 26 2023</td>\n","      <td>4,529</td>\n","      <td>19,807</td>\n","      <td>227</td>\n","      <td>227</td>\n","      <td>96.39%</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>Resident Evil 4</td>\n","      <td>/app/2050650/</td>\n","      <td>Mar 24 2023</td>\n","      <td>168,191</td>\n","      <td>61,752</td>\n","      <td>1,616</td>\n","      <td>1,616</td>\n","      <td>95.75%</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>The Murder of Sonic the Hedgehog</td>\n","      <td>/app/2324650/</td>\n","      <td>Mar 31 2023</td>\n","      <td>15,543</td>\n","      <td>12,643</td>\n","      <td>213</td>\n","      <td>213</td>\n","      <td>95.54%</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>Pineapple on pizza</td>\n","      <td>/app/2263010/</td>\n","      <td>Mar 28 2023</td>\n","      <td>1,415</td>\n","      <td>11,717</td>\n","      <td>209</td>\n","      <td>209</td>\n","      <td>95.39%</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>4</td>\n","      <td>Hi-Fi RUSH</td>\n","      <td>/app/1817230/</td>\n","      <td>Jan 25 2023</td>\n","      <td>6,132</td>\n","      <td>14,152</td>\n","      <td>324</td>\n","      <td>324</td>\n","      <td>95.09%</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   Unnamed: 0                              game           link      release  \\\n","0           0                       Pizza Tower  /app/2231450/  Jan 26 2023   \n","1           1                   Resident Evil 4  /app/2050650/  Mar 24 2023   \n","2           2  The Murder of Sonic the Hedgehog  /app/2324650/  Mar 31 2023   \n","3           3                Pineapple on pizza  /app/2263010/  Mar 28 2023   \n","4           4                        Hi-Fi RUSH  /app/1817230/  Jan 25 2023   \n","\n","  peak_players positive_reviews negative_reviews total_reviews  rating  \n","0        4,529           19,807              227           227  96.39%  \n","1      168,191           61,752            1,616         1,616  95.75%  \n","2       15,543           12,643              213           213  95.54%  \n","3        1,415           11,717              209           209  95.39%  \n","4        6,132           14,152              324           324  95.09%  "]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["df.head()"]},{"cell_type":"code","execution_count":7,"id":"53cd4fe5","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.501894Z","iopub.status.busy":"2023-05-23T17:18:27.501379Z","iopub.status.idle":"2023-05-23T17:18:27.507287Z","shell.execute_reply":"2023-05-23T17:18:27.505889Z"},"papermill":{"duration":0.019332,"end_time":"2023-05-23T17:18:27.510293","exception":false,"start_time":"2023-05-23T17:18:27.490961","status":"completed"},"tags":[]},"outputs":[],"source":["# reducing data for faster run\n","df_new = df[:1000]"]},{"cell_type":"code","execution_count":8,"id":"6d7aef8f","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.529992Z","iopub.status.busy":"2023-05-23T17:18:27.529525Z","iopub.status.idle":"2023-05-23T17:18:27.540829Z","shell.execute_reply":"2023-05-23T17:18:27.539723Z"},"papermill":{"duration":0.024641,"end_time":"2023-05-23T17:18:27.543648","exception":false,"start_time":"2023-05-23T17:18:27.519007","status":"completed"},"tags":[]},"outputs":[],"source":["# droping unnecesary data\n","df_new = df_new.drop('game', axis=1)\n","df_new = df_new.drop('Unnamed: 0', axis=1)\n","df_new = df_new.drop('link', axis=1)\n","df_new = df_new.drop('release', axis=1)"]},{"cell_type":"code","execution_count":9,"id":"fda9b897","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.564182Z","iopub.status.busy":"2023-05-23T17:18:27.562894Z","iopub.status.idle":"2023-05-23T17:18:27.57976Z","shell.execute_reply":"2023-05-23T17:18:27.578695Z"},"papermill":{"duration":0.030366,"end_time":"2023-05-23T17:18:27.582755","exception":false,"start_time":"2023-05-23T17:18:27.552389","status":"completed"},"tags":[]},"outputs":[],"source":["#Changing string to int\n","df_new['positive_reviews'] = df_new['positive_reviews'].str.replace(',', '').astype(float)\n","df_new['negative_reviews'] = df_new['negative_reviews'].str.replace(',', '').astype(float)\n","df_new['peak_players'] = df_new['peak_players'].str.replace(',', '').astype(float)\n","df_new['rating'] = df_new['rating'].str.replace('%', '').astype(float)"]},{"cell_type":"code","execution_count":10,"id":"1e572d14","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.603803Z","iopub.status.busy":"2023-05-23T17:18:27.60294Z","iopub.status.idle":"2023-05-23T17:18:27.610886Z","shell.execute_reply":"2023-05-23T17:18:27.609564Z"},"papermill":{"duration":0.022098,"end_time":"2023-05-23T17:18:27.613524","exception":false,"start_time":"2023-05-23T17:18:27.591426","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["(1000, 5)"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["df_new.shape"]},{"cell_type":"code","execution_count":11,"id":"5a26dec6","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.633667Z","iopub.status.busy":"2023-05-23T17:18:27.632763Z","iopub.status.idle":"2023-05-23T17:18:27.640224Z","shell.execute_reply":"2023-05-23T17:18:27.638824Z"},"papermill":{"duration":0.02098,"end_time":"2023-05-23T17:18:27.643273","exception":false,"start_time":"2023-05-23T17:18:27.622293","status":"completed"},"tags":[]},"outputs":[],"source":["# fixing total_reviews column\n","df_new['total_reviews'] = df_new['positive_reviews'] + df_new['negative_reviews']"]},{"cell_type":"code","execution_count":12,"id":"1007adc6","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.663566Z","iopub.status.busy":"2023-05-23T17:18:27.663091Z","iopub.status.idle":"2023-05-23T17:18:27.680704Z","shell.execute_reply":"2023-05-23T17:18:27.67927Z"},"papermill":{"duration":0.031495,"end_time":"2023-05-23T17:18:27.683637","exception":false,"start_time":"2023-05-23T17:18:27.652142","status":"completed"},"tags":[]},"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>peak_players</th>\n","      <th>positive_reviews</th>\n","      <th>negative_reviews</th>\n","      <th>total_reviews</th>\n","      <th>rating</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>4529.0</td>\n","      <td>19807.0</td>\n","      <td>227.0</td>\n","      <td>20034.0</td>\n","      <td>96.39</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>168191.0</td>\n","      <td>61752.0</td>\n","      <td>1616.0</td>\n","      <td>63368.0</td>\n","      <td>95.75</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>15543.0</td>\n","      <td>12643.0</td>\n","      <td>213.0</td>\n","      <td>12856.0</td>\n","      <td>95.54</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1415.0</td>\n","      <td>11717.0</td>\n","      <td>209.0</td>\n","      <td>11926.0</td>\n","      <td>95.39</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>6132.0</td>\n","      <td>14152.0</td>\n","      <td>324.0</td>\n","      <td>14476.0</td>\n","      <td>95.09</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   peak_players  positive_reviews  negative_reviews  total_reviews  rating\n","0        4529.0           19807.0             227.0        20034.0   96.39\n","1      168191.0           61752.0            1616.0        63368.0   95.75\n","2       15543.0           12643.0             213.0        12856.0   95.54\n","3        1415.0           11717.0             209.0        11926.0   95.39\n","4        6132.0           14152.0             324.0        14476.0   95.09"]},"execution_count":12,"metadata":{},"output_type":"execute_result"}],"source":["df_new.head()"]},{"cell_type":"code","execution_count":13,"id":"04e72850","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:27.705671Z","iopub.status.busy":"2023-05-23T17:18:27.705159Z","iopub.status.idle":"2023-05-23T17:18:28.238928Z","shell.execute_reply":"2023-05-23T17:18:28.237653Z"},"papermill":{"duration":0.548362,"end_time":"2023-05-23T17:18:28.241874","exception":false,"start_time":"2023-05-23T17:18:27.693512","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["<AxesSubplot:>"]},"execution_count":13,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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\n","text/plain":["<Figure size 800x800 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["corr = df_new.corr()\n","plt.figure(figsize=(8,8))\n","sns.heatmap(corr, cmap=\"Greens\",annot=True)"]},{"cell_type":"code","execution_count":14,"id":"c3108d68","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:28.26524Z","iopub.status.busy":"2023-05-23T17:18:28.263648Z","iopub.status.idle":"2023-05-23T17:18:28.271574Z","shell.execute_reply":"2023-05-23T17:18:28.270432Z"},"papermill":{"duration":0.022421,"end_time":"2023-05-23T17:18:28.27443","exception":false,"start_time":"2023-05-23T17:18:28.252009","status":"completed"},"tags":[]},"outputs":[],"source":["x = df_new.drop(['rating'],axis=1)\n","y = df_new['rating']"]},{"cell_type":"markdown","id":"044d6b1f","metadata":{"papermill":{"duration":0.009761,"end_time":"2023-05-23T17:18:28.294718","exception":false,"start_time":"2023-05-23T17:18:28.284957","status":"completed"},"tags":[]},"source":["<a id='2'></a>\n","### 2.Training Data"]},{"cell_type":"code","execution_count":15,"id":"0e79befc","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:28.317171Z","iopub.status.busy":"2023-05-23T17:18:28.316668Z","iopub.status.idle":"2023-05-23T17:18:28.32508Z","shell.execute_reply":"2023-05-23T17:18:28.32388Z"},"papermill":{"duration":0.02304,"end_time":"2023-05-23T17:18:28.327826","exception":false,"start_time":"2023-05-23T17:18:28.304786","status":"completed"},"tags":[]},"outputs":[],"source":["# Train test split\n","x_train,x_test,y_train,y_test = train_test_split(x,y,train_size=0.2,random_state=42)"]},{"cell_type":"code","execution_count":16,"id":"6215d93b","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:28.349944Z","iopub.status.busy":"2023-05-23T17:18:28.349459Z","iopub.status.idle":"2023-05-23T17:18:28.57044Z","shell.execute_reply":"2023-05-23T17:18:28.568942Z"},"papermill":{"duration":0.236031,"end_time":"2023-05-23T17:18:28.573987","exception":false,"start_time":"2023-05-23T17:18:28.337956","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["RandomForestRegressor(random_state=42)"]},"execution_count":16,"metadata":{},"output_type":"execute_result"}],"source":["# Train a RandomForestRegressor model on the training data\n","model = RandomForestRegressor(n_estimators=100, random_state=42)\n","model.fit(x_train, y_train)"]},{"cell_type":"markdown","id":"a84125ca","metadata":{"papermill":{"duration":0.010417,"end_time":"2023-05-23T17:18:28.595292","exception":false,"start_time":"2023-05-23T17:18:28.584875","status":"completed"},"tags":[]},"source":["<a id='3'></a>\n","### 3.Predicting"]},{"cell_type":"code","execution_count":17,"id":"c62ba6b1","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:28.618901Z","iopub.status.busy":"2023-05-23T17:18:28.618428Z","iopub.status.idle":"2023-05-23T17:18:28.642645Z","shell.execute_reply":"2023-05-23T17:18:28.641036Z"},"papermill":{"duration":0.039284,"end_time":"2023-05-23T17:18:28.64567","exception":false,"start_time":"2023-05-23T17:18:28.606386","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["R squared value: 0.9695749428026805\n"]}],"source":["# Make predictions on the train data\n","training_data_pred = model.predict(x_train)\n","r2_train = metrics.r2_score(y_train, training_data_pred)\n","print(f\"R squared value: {r2_train}\")"]},{"cell_type":"code","execution_count":18,"id":"83fec50e","metadata":{"execution":{"iopub.execute_input":"2023-05-23T17:18:28.669135Z","iopub.status.busy":"2023-05-23T17:18:28.668199Z","iopub.status.idle":"2023-05-23T17:18:28.701615Z","shell.execute_reply":"2023-05-23T17:18:28.699908Z"},"papermill":{"duration":0.04861,"end_time":"2023-05-23T17:18:28.70476","exception":false,"start_time":"2023-05-23T17:18:28.65615","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["R squared value: 0.799296380824628\n"]}],"source":["# Make predictions on the test data\n","test_data_pred = model.predict(x_test)\n","r2_test = metrics.r2_score(y_test, test_data_pred)\n","print(f\"R squared value: {r2_test}\")"]}],"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":"3.7.12"},"papermill":{"default_parameters":{},"duration":19.327271,"end_time":"2023-05-23T17:18:29.539976","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2023-05-23T17:18:10.212705","version":"2.4.0"}},"nbformat":4,"nbformat_minor":5}