Reference lines

Explain the evidence · V27 · 8 MIN

Add a benchmark with a clear meaning.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

Reference lines put an interpretable benchmark beside observations. Their orientation determines which measurement they refer to.

Illustration · not the exercise output

A small example

A horizontal line at rating=4 compares every point’s rating with 4; a vertical line at minutes=30 compares durations.

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.axvline(df["hours"].median(), linestyle="--")
ax.axhline(df["score"].median(), linestyle="--")
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
plt.show()

What each part does

ax.axhline(y, ...): horizontal reference
ax.axvline(x, ...): vertical reference
linestyle="--": dashed line

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; add dashed reference lines at median hours and median score.
Chart: title "Study club"; x "hours"; y "score".
Use: axhline(), axvline().

Hint

Horizontal benchmarks use y units and vertical benchmarks use x units.

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.axvline(df["hours"].median(), linestyle="--")
ax.axhline(df["score"].median(), linestyle="--")
ax.set(title="Study club", xlabel="hours", ylabel="score")
fig.tight_layout()
plt.show()

Your task · Follow

Using df, scatter hours against score; add dashed reference lines at median hours and median score.
Chart: title "Study club"; x "hours"; y "score".
Use: axhline(), axvline().

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.