1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
|
"""
Conditional means with observations
===================================
"""
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style="whitegrid")
iris = sns.load_dataset("iris")
# "Melt" the dataset to "long-form" or "tidy" representation
iris = pd.melt(iris, "species", var_name="measurement")
# Initialize the figure
f, ax = plt.subplots()
sns.despine(bottom=True, left=True)
# Show each observation with a scatterplot
sns.stripplot(
data=iris, x="value", y="measurement", hue="species",
dodge=True, alpha=.25, zorder=1, legend=False
)
# Show the conditional means, aligning each pointplot in the
# center of the strips by adjusting the width allotted to each
# category (.8 by default) by the number of hue levels
sns.pointplot(
data=iris, x="value", y="measurement", hue="species",
join=False, dodge=.8 - .8 / 3, palette="dark",
markers="d", scale=.75, errorbar=None
)
# Improve the legend
sns.move_legend(
ax, loc="lower right", ncol=3, frameon=True, columnspacing=1, handletextpad=0
)
|
