Save a figure

Make a useful report · V34 · 8 MIN

Export the specific Figure you have finished.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferCombine earlier skills

Understand the idea

savefig exports a specific Figure to a file. Finish the labels and layout before saving, then display it.

Illustration · not the exercise output

A small example

A 6 × 4 inch Figure at 150 dpi is about 900 × 600 pixels before tight cropping changes the edges.

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", ax=ax)
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
fig.savefig("chart.png", dpi=150, bbox_inches="tight")
plt.show()

What each part does

fig.savefig("chart.png", dpi=150, bbox_inches="tight"): export this Figure
.png: raster image format
dpi=150: pixels per inch

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, scatter hours against score, finish its title and labels, then save chart.png at 150 dpi with a tight bounding box before displaying.
Use title "Study club", x label "hours", y label "score".
Display the chart with plt.show().
Use: savefig().

Hint

Save the explicit finished Figure before display, with the requested resolution.

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", ax=ax)
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
fig.savefig("chart.png", dpi=150, bbox_inches="tight")
plt.show()

Your task · Follow

Using df, scatter hours against score, finish its title and labels, then save chart.png at 150 dpi with a tight bounding box before displaying.
Use title "Study club", x label "hours", y label "score".
Display the chart with plt.show().
Use: savefig().

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()
# Save chart.png before display
____
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.