Raw points

Compare observations · V13 · 8 MIN

Show the observations behind a group summary.

Exercises within this concept

FollowFollow the techniqueCurrent exercise
ChangeAdapt a requirement
TransferChoose and combine

Understand the idea

A strip plot draws every observation at its category. Jitter separates overlapping points along the category direction.

Illustration · not the exercise output

A small example

Two observations both measuring 4 keep that measured height; jitter moves them slightly left or right.

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.stripplot(data=df, x="flavour", y="price", jitter=0.15, ax=ax)
ax.set(title="Candy shop", xlabel="flavour", ylabel="price")
fig.tight_layout()
plt.show()

What each part does

sns.stripplot: one marker per observation
jitter=0.15: small horizontal displacement

Your inputs

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

Candy shop · 6 synthetic rows
candy	flavour	price	rating	shelf
Gummy Bear	fruity	1.2	4.1	A
Choco Pop	chocolate	2.1	4.6	B
Mint Bite	mint	1.5	3.8	A
Berry Loop	fruity	2.8	4.4	B
Cocoa Cube	chocolate	3.4	4.9	A
Lemon Drop	fruity	1.8	4	B

Your task · Follow

Using df, call sns.stripplot with flavour on x and price on y, using jitter=0.15.
Chart: title "Candy shop"; x "flavour"; y "price".

Hint

Jitter changes sideways placement, not the measured value.

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.stripplot(data=df, x="flavour", y="price", jitter=0.15, ax=ax)
ax.set(title="Candy shop", xlabel="flavour", ylabel="price")
fig.tight_layout()
plt.show()

Your task · Follow

Using df, call sns.stripplot with flavour on x and price on y, using jitter=0.15.
Chart: title "Candy shop"; x "flavour"; y "price".

YOUR PYTHON

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

# Supplied setup — editable
import pandas as pd

data = {
    "candy": [
        "Gummy Bear",
        "Choco Pop",
        "Mint Bite",
        "Berry Loop",
        "Cocoa Cube",
        "Lemon Drop",
    ],
    "flavour": ["fruity", "chocolate", "mint", "fruity", "chocolate", "fruity"],
    "price": [1.2, 2.1, 1.5, 2.8, 3.4, 1.8],
    "rating": [4.1, 4.6, 3.8, 4.4, 4.9, 4],
    "shelf": ["A", "B", "A", "B", "A", "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.