Labeling boxplot in seaborn with median value

Question

How can I label each boxplot in a seaborn plot with the median value?

E.g.

import seaborn as sns
sns.set_style("whitegrid")
tips = sns.load_dataset("tips")
ax = sns.boxplot(x="day", y="total_bill", data=tips)

How do I label each boxplot with the median or average value?

Answer 1

I love when people include sample datasets!

import seaborn as sns

sns.set_style("whitegrid")
tips = sns.load_dataset("tips")
box_plot = sns.boxplot(x="day",y="total_bill",data=tips)

medians = tips.groupby(['day'])['total_bill'].median()
vertical_offset = tips['total_bill'].median() * 0.05 # offset from median for display

for xtick in box_plot.get_xticks():
    box_plot.text(xtick,medians[xtick] + vertical_offset,medians[xtick], 
            horizontalalignment='center',size='x-small',color='w',weight='semibold')

Answer 2

This can also be achieved by deriving median from the plot itself without exclusively computing median from data

box_plot = sns.boxplot(x="day", y="total_bill", data=tips)

ax = box_plot.axes
lines = ax.get_lines()
categories = ax.get_xticks()

for cat in categories:
    # every 4th line at the interval of 6 is median line
    # 0 -> p25 1 -> p75 2 -> lower whisker 3 -> upper whisker 4 -> p50 5 -> upper extreme value
    y = round(lines[4+cat*6].get_ydata()[0],1) 

    ax.text(
        cat, 
        y, 
        f'{y}', 
        ha='center', 
        va='center', 
        fontweight='bold', 
        size=10,
        color='white',
        bbox=dict(facecolor='#445A64'))

box_plot.figure.tight_layout()

Answer 3

Based on ShikjarDua's approach, I created a version which works independent of tick positions. This comes in handy when dealing with grouped data in seaborn (i.e. hue=parameter). Additionally, I added a "flier-detection", which changes the lines per drawn box.

import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.patheffects as path_effects


def add_median_labels(ax, fmt='.1f'):
    lines = ax.get_lines()
    boxes = [c for c in ax.get_children() if type(c).__name__ == 'PathPatch']
    lines_per_box = int(len(lines) / len(boxes))
    for median in lines[4:len(lines):lines_per_box]:
        x, y = (data.mean() for data in median.get_data())
        # choose value depending on horizontal or vertical plot orientation
        value = x if (median.get_xdata()[1] - median.get_xdata()[0]) == 0 else y
        text = ax.text(x, y, f'{value:{fmt}}', ha='center', va='center',
                       fontweight='bold', color='white')
        # create median-colored border around white text for contrast
        text.set_path_effects([
            path_effects.Stroke(linewidth=3, foreground=median.get_color()),
            path_effects.Normal(),
        ])


sns.set_style("darkgrid")
tips = sns.load_dataset("tips")

# simple example
ax = sns.boxplot(data=tips, x='day', y='total_bill', hue="sex")
add_median_labels(ax)
plt.show()

# all possible orientation and flier combinations
fig, axes = plt.subplots(2, 2, figsize=(10, 10))
for i_fly, show_fliers in enumerate([True, False]):
    for i_data, data_kwargs in enumerate([{'x': 'day', 'y': 'total_bill'},
                                          {'y': 'day', 'x': 'total_bill'}]):
        ax = sns.boxplot(ax=axes[i_fly, i_data], **data_kwargs, data=tips,
                         showfliers=show_fliers, hue="sex")
        add_median_labels(ax)
        ax.set_title((
            f"{['Fliers', 'No fliers'][i_fly]}, "
            f"{['vertical', 'horizontal'][i_data]}"))
plt.show()