33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
import os
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from sklearn.model_selection import train_test_split
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import pandas as pd
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pd.set_option('display.max_columns', 100)
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DATA_DIRECTORY = './ium_z486867/'
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CSV_NAME = DATA_DIRECTORY + 'openpowerlifting.csv'
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def process_data(csv_name):
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CUTOFF = int(os.environ['CUTOFF'])
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powerlifting_data = pd.read_csv(csv_name,
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engine='python',
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encoding='ISO-8859-1',
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sep=',')
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powerlifting_data.dropna()
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powerlifting_data.drop(columns=["Squat4Kg", "Bench4Kg", "Deadlift4Kg"], inplace=True)
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powerlifting_data.sample(CUTOFF)
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X, Y = powerlifting_data, powerlifting_data
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X_train, X_temp, Y_train, Y_temp = train_test_split(X, Y, test_size=0.3, random_state=1)
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X_dev, X_test, Y_dev, Y_test = train_test_split(X_temp, Y_temp, test_size=0.3, random_state=1)
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X_train.to_csv('X_train.csv', index=False)
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X_dev.to_csv('X_dev.csv', index=False)
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X_test.to_csv('X_test.csv', index=False)
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process_data(CSV_NAME) |