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Title: Creating Rolling Averages with Matplotlib Subplots in Python
Introduction:
Matplotlib is a powerful data visualization library in Python that allows users to create a wide range of plots and charts. In this tutorial, we'll explore how to create a subplot with multiple plots, including a rolling average plot. Specifically, we'll address the common issue where the rolling averages don't show up over an existing subplot.
Requirements:
Make sure you have the following libraries installed:
Code Example:
Explanation:
Import Libraries: Import the necessary libraries, including Matplotlib and Pandas.
Create Sample Data: Generate a sample DataFrame with date-indexed data.
Calculate Rolling Average: Define a function (calculate_rolling_average) to calculate the rolling average using the rolling method from Pandas.
Create Subplots: Use subplots to create a figure with two subplots vertically aligned. The sharex=True ensures that both subplots share the same x-axis.
Plot Original Data: Plot the original data in the first subplot.
Plot Rolling Average: Calculate the rolling average and plot it in the second subplot.
Show the Plot: Display the final plot using plt.show().
Conclusion:
This tutorial demonstrates how to create subplots in Matplotlib, addressing the common issue of rolling averages not showing over an existing subplot. By following these steps, you can effectively visualize original data alongside its rolling averages in a clear and informative manner.
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