Seaborn bar plots

Working with Categorical Data in Python

Kasey Jones

Research Data Scientist

Traditional bar chart

# Code provided for clarity
reviews["Traveler type"].value_counts().plot.bar()

A bar chart counting the number of reviews by different traveler types.

The syntax

sns.set(font_scale=1.3)
sns.set_style("darkgrid")

sns.catplot(x="Traveler type", y="Score", data=reviews, kind="bar")

A seaborn categorical bar plot for hotel reviews given the reviewers traveler type.

Ordering your categories

reviews["Traveler type"] = reviews["Traveler type"].astype("category")
reviews["Traveler type"].cat.categories

Index(['Business', 'Couples', 'Families', 'Friends', 'Solo'], dtype='object')

Updated visualization

sns.catplot(x="Traveler type", y="Score", data=reviews, kind="bar")

Note: catplot() has an order parameter

The hue parameter

hue:
- name of a variable in data
- used to split the data by a second category
- also used to color the graphic

sns.set(font_scale=1.2)
sns.set_style("darkgrid")
sns.catplot(x="Traveler type", y="Score", data=reviews, kind="bar",
            hue="Tennis court")  # <--- new parameter

Bar plot across two variables

Bar plot practice

Working with Categorical Data in Python