Catplot - Seaborn — ContextQMD

python

import seaborn as sns
sns.set_theme(style="whitegrid")

python

df = sns.load_dataset("titanic")
sns.catplot(data=df, x="age", y="class")

Use kind to select a different representation:

python

sns.catplot(data=df, x="age", y="class", kind="box")

One advantage is that the legend will be automatically placed outside the plot:

python

sns.catplot(data=df, x="age", y="class", hue="sex", kind="boxen")

Additional keyword arguments get passed through to the underlying seaborn function:

python

sns.catplot(
    data=df, x="age", y="class", hue="sex",
    kind="violin", bw_adjust=.5, cut=0, split=True,
)

Assigning a variable to col or row will automatically create subplots. Control figure size with the height and aspect parameters:

python

sns.catplot(
    data=df, x="class", y="survived", col="sex",
    kind="bar", height=4, aspect=.6,
)

For single-subplot figures, it is easy to layer different representations:

python

sns.catplot(data=df, x="age", y="class", kind="violin", color=".9", inner=None)
sns.swarmplot(data=df, x="age", y="class", size=3)

python

g = sns.catplot(
    data=df, x="who", y="survived", col="class",
    kind="bar", height=4, aspect=.6,
)
g.set_axis_labels("", "Survival Rate")
g.set_xticklabels(["Men", "Women", "Children"])
g.set_titles("{col_name} {col_var}")
g.set(ylim=(0, 1))
g.despine(left=True)