Adding data to an Axes object

Adding data to a figure is done by calling methods of the Axes object. In this exercise, we will use the plot method to add data about rainfall in two American cities: Seattle, WA and Austin, TX.

The data are stored in two pandas DataFrame objects that are already loaded into memory: seattle_weather stores information about the weather in Seattle, and austin_weather stores information about the weather in Austin. Each of the DataFrames has a "MONTH" column that stores the three-letter name of the months. Each also has a column named "MLY-PRCP-NORMAL" that stores the average rainfall in each month during a ten-year period.

In this exercise, you will create a visualization that will allow you to compare the rainfall in these two cities.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

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Exercise instructions

Import the matplotlib.pyplot submodule as plt.
Create a Figure and an Axes object by calling plt.subplots.
Add data from the seattle_weather DataFrame by calling the Axes plot method.
Add data from the austin_weather DataFrame in a similar manner and call plt.show to show the results.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the matplotlib.pyplot submodule and name it plt
____

# Create a Figure and an Axes with plt.subplots
fig, ax = ____

# Plot MLY-PRCP-NORMAL from seattle_weather against the MONTH
ax.____(seattle_weather["MONTH"], ____)

# Plot MLY-PRCP-NORMAL from austin_weather against MONTH
ax.____(____, ____)

# Call the show function
____

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