application_vnd.jupyter.stderr_output_1.png image_output_1.png
import matplotlib.pyplot as plt

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

train = pd.read_csv('/kaggle/input/data-without-drift/train_clean.csv')
test = pd.read_csv('/kaggle/input/data-without-drift/test_clean.csv')

batch_indices = [slice(500000 * i, 500000 * (i + 1)) for i in range(10)]

fig, axes = plt.subplots(2, 5, sharex=False, sharey=True, figsize=(25, 10))
for i, ax in enumerate(axes.ravel()):
    train.iloc[batch_indices[i]].plot(kind='line', x='time', y=['signal'], ax=ax, linewidth=0.1)
    ax.set_title('Batch_' + str(i))
ax.set_ylim(-5, 14)
ax.legend()
fig.suptitle('Training Data', y=1.05)
plt.tight_layout()