grplot¶
Publication-ready statistical plots: one function, zero boilerplate.
from grplot import plot2d
import grplot_seaborn as gs
gs.set_theme(context='notebook', style='darkgrid', palette='deep')
tips = gs.load_dataset('tips')
ax = plot2d(plot={'[1,1]': 'histplot', '[1,2]': 'ecdfplot',
'[2,1]': 'treemapsplot', '[2,2]': 'pieplot',
'[3,1]': 'paretoplot', '[3,2]': 'boxplot+stripplot'},
Nx=2, Ny=3, df=tips, filter=(tips['total_bill'] > 10),
kde=True) # see Dashboard-Like for the full, annotated call
A histogram with KDE and summary statistics, an ECDF, a treemap, a pie
chart, a Pareto chart, and an annotated box + strip plot: six different
chart families, fully annotated, produced by one plot2d call. See
grplot vs. Matplotlib/Seaborn for the equivalent Matplotlib/Seaborn code side by side,
Dashboard-Like for this example’s full write-up, and
Plot Types for a worked example of every individual chart type.
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