Count plots and bar plots

Introduction to Data Visualization with Seaborn

Erin Case

Data Scientist

Categorical plots

Examples: count plots, bar plots
Involve a categorical variable
Comparisons between groups

Count plot of masculinity responses

catplot()

Used to create categorical plots
Same advantages of relplot()
Easily create subplots with col= and row=

countplot() vs. catplot()

import matplotlib.pyplot as plt
import seaborn as sns

sns.countplot(x="how_masculine",
              data=masculinity_data)

plt.show()

Count plot of masculinity responses

countplot() vs. catplot()

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="how_masculine",
            data=masculinity_data,
            kind="count")

plt.show()

Count plot of masculinity responses

Changing the order

import matplotlib.pyplot as plt
import seaborn as sns

category_order = ["No answer", 
                  "Not at all",
                  "Not very", 
                  "Somewhat", 
                  "Very"]

sns.catplot(x="how_masculine",
            data=masculinity_data,
            kind="count",
            order=category_order)

plt.show()

Reordered count plot of masculinity responses

Bar plots

Displays mean of quantitative variable per category

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="day",
            y="total_bill",
            data=tips,
            kind="bar")

plt.show()

Bar plot of average bill per day

¹ Waskom, M. L. (2021). seaborn: statistical data visualization. https://seaborn.pydata.org/

Confidence intervals

Lines show 95% confidence intervals for the mean
Shows uncertainty about our estimate
Assumes our data is a random sample

Bar plot of average bill per day

¹ Waskom, M. L. (2021). seaborn: statistical data visualization. https://seaborn.pydata.org/

Turning off confidence intervals

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="day",
            y="total_bill",
            data=tips,
            kind="bar",
            ci=None)

plt.show()

Bar plot with no confidence intervals

¹ Waskom, M. L. (2021). seaborn: statistical data visualization. https://seaborn.pydata.org/

Changing the orientation

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="total_bill",
            y="day",
            data=tips,
            kind="bar")

plt.show()

Horizontal bar plot

¹ Waskom, M. L. (2021). seaborn: statistical data visualization. https://seaborn.pydata.org/

Let's practice!

Introduction to Data Visualization with Seaborn