26 lines
864 B
Python
26 lines
864 B
Python
import pandas as pd
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from sklearn.model_selection import train_test_split
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energy_data = pd.read_csv('Steel_industry_data.csv')
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train_data, test_data = train_test_split(energy_data, test_size=7008, random_state=1)
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test_data, dev_data = train_test_split(test_data, test_size=3504, random_state=1)
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# stats
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print(energy_data.describe(include='all'))
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print('Training set size:')
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print(train_data.shape)
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print('Testing set size:')
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print(test_data.shape)
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print('Dev set size:')
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print(dev_data.shape)
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#print(train_data.describe(include='all'))
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#print(test_data.describe(include='all'))
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#print(dev_data.describe(include='all'))
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test_data.to_csv("steel_industry_data_test.csv", encoding="utf-8", index=False)
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dev_data.to_csv("steel_industry_data_dev.csv", encoding="utf-8", index=False)
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train_data.to_csv("steel_industry_data_train.csv", encoding="utf-8", index=False)
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