37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
import pandas as pd
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from sklearn import preprocessing
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from sklearn.model_selection import train_test_split
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df = pd.read_csv('smart_grid_stability_augmented.csv')
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scaler = preprocessing.StandardScaler().fit(df.iloc[:, 0:-1])
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df_norm_array = scaler.transform(df.iloc[:, 0:-1])
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df_norm = pd.DataFrame(data=df_norm_array,
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columns=df.columns[:-1])
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df_norm['stabf'] = df['stabf']
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df_norm_data = df_norm.copy()
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df_norm_data = df_norm_data.drop('stab', axis=1)
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df_norm_labels = df_norm_data.pop('stabf')
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X_train, X_testAndValid, Y_train, Y_testAndValid = train_test_split(
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df_norm_data,
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df_norm_labels,
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test_size=0.2,
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random_state=42)
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X_test, X_valid, Y_test, Y_valid = train_test_split(
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X_testAndValid,
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Y_testAndValid,
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test_size=0.5,
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random_state=42)
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train = pd.concat([X_train, Y_train], axis=1)
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test = pd.concat([X_test, Y_test], axis=1)
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valid = pd.concat([X_valid, Y_valid], axis=1)
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train.to_csv('train.cs', index_col = False)
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test.to_csv('test.csv', index_col = False)
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valid.to_csv('valid.csv', index_col = False)
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