Annotate pointplot

Question

How can I annotate a seaborn pointplot with the values of col1 "A" "B" or "C" as a text, next to the points where they are drawn.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

# Data
a = list("ABC") * 4
c = list("DE") * 6
score = np.random.randint(-5, 5, 12)
df = pd.DataFrame({"col1": a, "col2": c, "score": score})
print(df)

   col1 col2  value
0     A    D      3
1     B    E      1
2     C    D     -3
3     A    E     -5
4     B    D     -4
5     C    E     -5
6     A    D      2
7     B    E     -4
8     C    D      4
9     A    E      1
10    B    D      3
11    C    E     -2

sns.pointplot(data=df, x="col2", y="value", hue='col1');

Desired outcome is with the labels A, B and C:

pointplot return a matplotlib Axes. You can use its annotate or text methods — Paul H
– Paul H, Commented Oct 22, 2020 at 15:52

JohanC · Accepted Answer · 2020-10-23 07:02:35Z

plt.text(x, y, 'a text') places a text in a plot. The main problem is to find the exact positions and colors. To get a consistent order, it helps to explicitly make the columns categorical. The categorical numbering (0, 1, 2, ...) is the same as matplotlib uses internally for its categorical axes.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

a = list("ABC") * 4
c = list("DE") * 6
score = np.random.randint(-5, 5, 12)
df = pd.DataFrame({"col1": a, "col2": c, "score": score})
df['col1'] = pd.Categorical(df['col1'])
df['col2'] = pd.Categorical(df['col2'])

palette = sns.color_palette("tab10")
ax = sns.pointplot(data=df, x="col2", y="score", hue='col1', palette=palette)

pos_after_last_x = len(df['col2'].cat.categories) - 1 + 0.05
last_x_cat = df['col2'].cat.categories[-1]
for cat, color in zip(df['col1'].cat.categories, palette):
    mean_score = df[(df['col1'] == cat) & (df['col2'] == last_x_cat)]['score'].mean()
    ax.text(pos_after_last_x, mean_score, cat, color=color)
plt.show()

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