Add dimensions to scatter

Compare observations · V17 · 8 MIN

Use colour and shape without losing readability.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

Use a small number of visual mappings so a scatter plot stays readable. Mapping the same group to colour and shape gives two ways to recognize it.

Illustration · not the exercise output

A small example

Club A might be blue circles and club B orange crosses; the legend explains both cues.

Follow the code

Apply the idea to the supplied table. Read from top to bottom; the final line displays the result.

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(figsize=(6, 4))
sns.scatterplot(
    data=df, x="hours", y="score", hue="club", style="club", size="hours", ax=ax
)
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
plt.show()

What each part does

hue=: category colours
style=: category marker shapes
size=: numeric marker areas

Your inputs

The editable setup on the right creates df. Run executes the setup and your work from top to bottom.

Study club · 8 synthetic rows
student	club	hours	score	group
Ari	Art	1	52	A
Bo	Code	3	71	A
Cy	Art	2	65	B
Dee	Code	4	82	B
Eli	Art	5	89	A
Flo	Code	3	76	A
Gus	Art	6	93	B
Han	Code	2	61	B

Your task · Follow

Using df, call sns.scatterplot with x=hours, y=score, hue=club, style=club and size=hours.
Chart: title "Study club"; x "hours"; y "score".

Hint

Use the same category for hue and style so colour is not the only cue.

Reveal solution

One way to do it. Keep any supplied setup in the editor and use this in the Your work section.

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(figsize=(6, 4))
sns.scatterplot(
    data=df, x="hours", y="score", hue="club", style="club", size="hours", ax=ax
)
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
plt.show()

Your task · Follow

Using df, call sns.scatterplot with x=hours, y=score, hue=club, style=club and size=hours.
Chart: title "Study club"; x "hours"; y "score".

YOUR PYTHON

Tab: indent · Shift+Tab: outdent · Esc, then Tab: leave editor

# Supplied setup — editable
import pandas as pd

data = {
    "student": ["Ari", "Bo", "Cy", "Dee", "Eli", "Flo", "Gus", "Han"],
    "club": ["Art", "Code", "Art", "Code", "Art", "Code", "Art", "Code"],
    "hours": [1, 3, 2, 4, 5, 3, 6, 2],
    "score": [52, 71, 65, 82, 89, 76, 93, 61],
    "group": ["A", "A", "B", "B", "A", "A", "B", "B"],
}

df = pd.DataFrame(data)

# Your work
import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(figsize=(6, 4))
# Build the requested chart
____
# Add the labels from Your task
ax.set(____)
fig.tight_layout()
plt.show()

Each run executes all editor code in a fresh Python session. Display charts with plt.show().

Python starts when you open a lesson.

Output

Run your code to see what Python returns.