Learning the Pandas Library: Python Tools for Data Munging, Analysis, and Visualization (Treading on Python Book 3) by Matt Harrison

Author:Matt Harrison [Harrison, Matt]
Language: eng
Format: epub, pdf
Tags: Python Programming Language
Publisher: Matt Harrison
Published: 2016-06-06T21:00:00+00:00

Plot using secondary_y parameter to use different scales on the left and right axis for elevation and distance.

Another way to convey information is to plot with labels along the x axis instead of using a numerical index (which does not mean much to viewers of the graph). By default, pandas plots the index along the x axis. To graph against the name of the station, we need to pass in an explicit value for x, the ELEVATION column. The labels will need to tilted a bit so that they do not overlap. This rotation is done with fig.autofmt_xdate(). The bounding box also needs to be expanded a bit so the labels do not get clipped off at the edges. The bbox_inches='tight' parameter to fig.savefig will help with this:

>>> fig = plt.figure() >>> ax = fig.add_subplot(111) >>> df.plot(x='LOCATION', y=['ELEVATION', 'CUMUL'], ax=ax) >>> df.plot(x='LOCATION', y='MILES', secondary_y=True, ax=ax) >>> ax.set_ylabel('Elevation (feet)') >>> ax.right_ax.set_ylabel('Distance (miles)') >>> fig.autofmt_xdate() >>> fig.savefig('/tmp/df-ex4.png', bbox_inches='tight')

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