Customizing scatter plots

Introduction to Data Visualization with Seaborn

Erin Case

Data Scientist

Scatter plot overview

Show relationship between two quantitative variables

We've seen:

Subplots (col and row)
Subgroups with color (hue)

New Customizations:

Subgroups with point size and style
Changing point transparency

Use with both scatterplot() and relplot()

Subgroups with point size

import seaborn as sns
import matplotlib.pyplot as plt

sns.relplot(x="total_bill", 
            y="tip", 
            data=tips, 
            kind="scatter", 
            size="size")

plt.show()

Scatter plot with varying point size

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

Point size and hue

import seaborn as sns
import matplotlib.pyplot as plt

sns.relplot(x="total_bill", 
            y="tip", 
            data=tips, 
            kind="scatter", 
            size="size",
            hue="size")

plt.show()

Scatter plot with varying point size and color

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

Subgroups with point style

import seaborn as sns
import matplotlib.pyplot as plt

sns.relplot(x="total_bill", 
            y="tip", 
            data=tips, 
            kind="scatter", 
            hue="smoker", 
            style="smoker")

plt.show()

Scatter plot with varying color and style

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

Changing point transparency

import seaborn as sns
import matplotlib.pyplot as plt

# Set alpha to be between 0 and 1
sns.relplot(x="total_bill", 
            y="tip", 
            data=tips, 
            kind="scatter", 
            alpha=0.4)

plt.show()

Scatter plot with more transparent points

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

Let's practice!

Introduction to Data Visualization with Seaborn