Point plots

Introduction to Data Visualization with Seaborn

Erin Case

Data Scientist

What are point plots?

Points show mean of quantitative variable
Vertical lines show 95% confidence intervals

Point plot of average bill of smokers vs. non-smokers

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

Line plot: average level of nitrogen dioxide over time Line plot of nitrogen dioxide over time

Point plot: average restaurant bill, smokers vs. non-smokers Point plot of average bill of smokers vs. non-smokers

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

Point plots vs. line plots

Both show:

Mean of quantitative variable
95% confidence intervals for the mean

Differences:

Line plot has quantitative variable (usually time) on x-axis
Point plot has categorical variable on x-axis

Point plots vs. bar plots

Both show:

Mean of quantitative variable
95% confidence intervals for the mean

Point plots vs. bar plots

Bar plot of masculinity with hue

Point plot of masculinity with hue

Creating a point plot

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="age", 
            y="masculinity_important", 
            data=masculinity_data,
            hue="feel_masculine",
            kind="point")

plt.show()

Point plot of masculinity with hue

Disconnecting the points

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="age", 
            y="masculinity_important", 
            data=masculinity_data,
            hue="feel_masculine",
            kind="point",
            join=False)

plt.show()

Point plot of masculinity with hue and points disconnected

Displaying the median

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="smoker", 
            y="total_bill", 
            data=tips, 
            kind="point")

plt.show()

Point plot of average total bill for smokers vs. non-smokers

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

Displaying the median

import matplotlib.pyplot as plt
import seaborn as sns
from numpy import median

sns.catplot(x="smoker", 
            y="total_bill", 
            data=tips, 
            kind="point", 
            estimator=median)

plt.show()

Point plot of median total bill for smokers vs. non-smokers

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

Customizing the confidence intervals

import matplotlib.pyplot as plt
import seaborn as sns

sns.catplot(x="smoker", 
            y="total_bill", 
            data=tips, 
            kind="point",
            capsize=0.2)

plt.show()

Point plot with caps on confidence intervals

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="smoker", 
            y="total_bill", 
            data=tips, 
            kind="point",
            ci=None)

plt.show()

Point plot with no confidence intervals

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

Let's practice!

Introduction to Data Visualization with Seaborn