Escodrinyar: extending seaborn for complex data visualization#
Escodrinyar (Catalan word, derived from the Latin “scrutari”, meaning “to examine”, or “to search carefully”)
is a data visualization tool that extends the seaborn.objects
library by:
providing a new set of Marks and Stats
facilitating the creation of complex subfigures
TODO: add more information here
Example#
import escodrinyar as sc
import seaborn.objects as so
import seaborn as sns
penguins = sns.load_dataset("penguins")
# Define multiple plots
points = (
sc.Plot(data=penguins, x='bill_length_mm', y='bill_depth_mm', color='species')
.add(so.Dot(marker='.', alpha=0.1))
)
centroids = (
sc.Plot(data=penguins, x='bill_length_mm', y='bill_depth_mm', color='species')
.add(so.Dot(alpha=1e-8)) # keep axis limits
.add(so.Dot(), sc.Agg2d())
)
chull = (
sc.Plot(data=penguins, x='bill_length_mm', y='bill_depth_mm', color='species')
.add(sc.ConvexHull(edgewidth=1))
)
# Combine plots in a single figure
fig = (
points + (chull * points * centroids) |
(chull * points * centroids).facet('species')
).opts(figsize=(7, 7), height_ratios=[1.3, 1])
# Show figure
fig.show()