image_output_1.png
import matplotlib.pyplot as plt

import numpy as np # linear algebra

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

demo_data = pd.read_csv('/kaggle/input/pac-regression-4/PAC1954_Demo_default_data.csv')
num_samples = demo_data.shape[0]
split = round(num_samples * 0.7)
train_demo_data_x = np.array(demo_data[' Vsense_Ch1'].iloc[0:split]).reshape(-1, 1)
test_demo_data_x = np.array(demo_data[' Vsense_Ch1'].iloc[split + 1:num_samples]).reshape(-1, 1)
train_demo_data_y = np.array(demo_data['Count'].iloc[0:split]).reshape(-1, 1)
test_demo_data_y = np.array(demo_data['Count'].iloc[split + 1:num_samples]).reshape(-1, 1)

fig, ax = plt.subplots(figsize=(10, 10))
ax.plot(train_demo_data_y[0:80], train_demo_data_x[0:80], 'bo', label='Initial Vsense Data')
plt.xlabel('Window Position')
plt.ylabel('Vsense')
plt.title('Input Data')
plt.legend(loc='center right')
plt.show()