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- import pandas as pd
- import numpy as np
- from sklearn.model_selection import train_test_split
- from sklearn.metrics import mean_absolute_error
- data = pd.read_csv('/datasets/energy_consumption.csv', index_col=[0], parse_dates=[0])
- data.sort_index(inplace=True)
- data = data.resample('1D').sum()
- train, test = train_test_split(data, shuffle=False, test_size=0.2)
- print("Средний объём электропотребления в день:", test['PJME_MW'].mean())
- pred_median = np.ones(test.shape) * train['PJME_MW'].median()
- print("MAE:", mean_absolute_error(test, pred_median))
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