How to annotate a seaborn barplot with the aggregated value

bar-chart, matplotlib, pandas, python, seaborn

Solution

- Given the example data, for a `seaborn.barplot` with capped error bars, `data_df` must be converted from a wide format, to a tidy (long) format, which can be accomplished with `pandas.DataFrame.stack` or `pandas.DataFrame.melt`

- It is also important to keep in mind that a bar plot shows only the mean (or other estimator) value

Sample Data and DataFrame

- `.iloc[:, 1:]` is used to skip the `'stages'` column at column index 0.

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

# given data_df from the OP, select the columns except stage and reshape to long format
df = data_df.iloc[:, 1:].melt(var_name='set', value_name='val')

# display(df.head())
  set        val
0  S1  43.340440
1  S1  43.719898
2  S1  46.015958
3  S1  54.340597
4  S2  61.609735

Updated as of `matplotlib v3.4.2`

- Use `matplotlib.pyplot.bar_label`

- See How to add value labels on a bar chart for additional details and examples with `.bar_label`.

- Some formatting can be done with the `fmt` parameter, but more sophisticated formatting should be done with the `labels` parameter, as show in How to add multiple annotations to a barplot.

- Tested with `seaborn v0.11.1`, which is using `matplotlib` as the plot engine.

fig, ax = plt.subplots(figsize=(8, 6))

# add the plot
sns.barplot(x='set', y='val', data=df, capsize=0.2, ax=ax)

# add the annotation
ax.bar_label(ax.containers[-1], fmt='Mean:\n%.2f', label_type='center')

ax.set(ylabel='Mean Time')
plt.show()

plot with `seaborn.barplot`

- Using `matplotlib` before version 3.4.2

- The default for the `estimator` parameter is `mean`, so the height of the bar is the mean of the group.

- The bar height is extracted from `p` with `.get_height`, which can be used to annotate the bar.

fig, ax = plt.subplots(figsize=(8, 6))
sns.barplot(x='set', y='val', data=df, capsize=0.2, ax=ax)

# show the mean
for p in ax.patches:
    h, w, x = p.get_height(), p.get_width(), p.get_x()
    xy = (x + w / 2., h / 2)
    text = f'Mean:\n{h:0.2f}'
    ax.annotate(text=text, xy=xy, ha='center', va='center')

ax.set(xlabel='Delay', ylabel='Time')
plt.show()

Problem

Original source

Related problems

• How to add value labels on a bar chart
• How to add multiple annotations to a bar plot