Plotting schemes¶

This is a brief discussion on various plotting schemes and tips that would be helpful in consideration, while customizing plots and plotting in different environments.

Plot features¶

For most of the plotting purposes, we can stick to benchit’s plot method - benchit.BenchmarkObj.plot. This method enables kwargs to pandas.DataFrame.plot Also, pandas.DataFrame.plot has its own kwargs that traces back to matplotlib.pyplot.plot. In essence, within benchit’s plot we can explore all plot arguments available to pandas and matplotlib plot versions. This should be sufficient for most plotting requirements.

To go the full hog, we can employ two more methods, which could be used individually or in combination.

Method #1 : Modify matplotlib rc settings¶

All of the matplotlib plot settings are stored in a dictionary-like variable called matplotlib.rcParams, which is global to the matplotlib package. More info on this is available at - Customizing Matplotlib with style sheets and rcParams. We can modify these to suit our plotting requirements. This setup is to be done before plotting.

Method #2 : Use axes methods¶

benchit’s plot method returns an object of class matplotlib.axes.Axes. This has methods to change certain plot parameters. These could be located at matplotlib.axes.Axes. Most of those would be named as Axes.set_[property]. This is an after-plot adjustment and only applicable on interactive matplotlib backends.

Notebook plots¶

Plotting in IPython notebooks or Jupyter notebooks is supported for different matplotlib backends. Simply tell benchit to set the environment accordingly before plotting, with :

benchit.setparams(environ='notebook')

Note that this could also be used for non-interactive backends for better visualization. Matplotlib backends lists these backends and provides some general information on backends.

Sample notebook run.

Plot tips¶

When plotting with benchit.BenchmarkObj.plot, following tips could come in handy :

If xticks seem congested, we can pass over the setting up for them to pandas version with set_xticks_from_index set as False. Another way would be to rotate xticks using its rot argument.