Small multiples with shared y axis

When creating small multiples, it is often preferable to make sure that the different plots are displayed with the same scale used on the y-axis. This can be configured by setting the sharey key-word to True.

In this exercise, you will create a Figure with two Axes objects that share their y-axis. As before, the data is provided in seattle_weather and austin_weather DataFrames.

This exercise is part of the course

Introduction to Data Visualization with Matplotlib

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Exercise instructions

Create a Figure with an array of two Axes objects that share their y-axis range.
Plot Seattle's "MLY-PRCP-NORMAL" in a solid blue line in the top Axes.
Add Seattle's "MLY-PRCP-25PCTL" and "MLY-PRCP-75PCTL" in dashed blue lines to the top Axes.
Plot Austin's "MLY-PRCP-NORMAL" in a solid red line in the bottom Axes and the "MLY-PRCP-25PCTL" and "MLY-PRCP-75PCTL" in dashed red lines.

Hands-on interactive exercise

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

# Create a figure and an array of axes: 2 rows, 1 column with shared y axis
fig, ax = plt.subplots(2, 1, sharey=True)

# Plot Seattle precipitation data in the top axes
____.plot(____, ____, color = ____)
____.plot(____, ____, color = ____, linestyle = ____)
____.plot(____, ____, color = ____, linestyle = ____)

# Plot Austin precipitation data in the bottom axes
____.plot(____, ____, color = ____)
____.plot(____, ____, color = ____, linestyle = ____)
____.plot(____, ____, color = ____, linestyle = ____)

plt.show()

Edit and Run Code