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How to plot a time series array, with confidence intervals displayed in Python? (Matplotlib)
To plot a time series array, with confidence intervals displayed in Python, we can take the following steps −
- Set the figure size and adjust the padding between and around the subplots.
- Get the time series array.
- Initialize a variable, n_steps, to get the mean and standard deviation.
- Get the under and above lines for confidence intervals.
- Plot the mean line using plot() method.
- Use fill_between() method to get the confidence interval.
- To display the figure, use show() method.
Example
import numpy as np import pandas as pd import matplotlib.pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True time_series_array = np.sin(np.linspace (-np.pi, np.pi, 400)) + np.random.rand((400)) n_steps = 15 time_series_df = pd.DataFrame(time_series_array) line = time_series_df.rolling(n_steps).mean() line_deviation = 2 * time_series_df.rolling(n_steps).std() under_line = (line - line_deviation)[0] over_line = (line + line_deviation)[0] plt.plot(line, linewidth=2) plt.fill_between(line_deviation.index, under_line, over_line, color='red', alpha=.3) plt.show()
Output
Updated on: 17-Jun-2021
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