mqr.plot.anova.

main_effects

mqr.plot.anova.main_effects(data, response, factors, *, axs, line_kws=None, mean_kws=None)

Plot the main effects from experimental data.

Parameters:

datapandas.DataFrame

responsestr

factorslist[str]

axsarray_like[matplotlib.axes.Axes]

Axes for the plot. Must have the same number of elements as factors. Will be flattened before use.

line_kwsdict, optional

Keyword args for the effect lines. Passed to matplotlib.pyplot.plot.

mean_kwsdict, optional

Keyword args for the overall average line. Passed to matplotlib.pyplot.axhline.

Examples

This example loads sample data and shows a main effects plot for the two factors.

data = pd.read_csv(mqr.sample_data('anova-glue.csv'), index_col='Run')

fig, axs = plt.subplots(1, 2, figsize=(5, 2), layout='constrained')
mqr.plot.tools.sharey(fig, axs)
mqr.plot.anova.main_effects(
    data,
    response='adhesion_force',
    factors=['primer', 'glue'],
    axs=axs)

(Source code, png, pdf)