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How to visualize 95% confidence interval in Matplotlib?
To visualize 95% confidence interval in Matplotlib, we can take the following steps −
Set the figure size and adjust the padding between and around the subplots.
Create x and y data sets.
Get the confidence interval dataset.
Plot the x and y data points using plot() method.
Fill the area within the confidence interval range.
To display the figure, use show() method.
Example
from matplotlib import pyplot as plt import numpy as np plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True x = np.arange(0, 10, 0.05) y = np.sin(x) # Define the confidence interval ci = 0.1 * np.std(y) / np.mean(y) plt.plot(x, y, color='black', lw=7) plt.fill_between(x, (y-ci), (y+ci), color='blue', alpha=0.5) plt.show()
Output
Updated on: 10-Aug-2021
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