我喜欢人们包括样本数据集！

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')

基于ShikharDua的方法，我创建了一个独立于价格点位置的版本。这在处理海运中的分组数据时很方便（即色调=参数）。此外，我还添加了飞行器和方向检测。

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")

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

这也可以通过从图本身导出中值来实现，而不是专门从数据中计算中值

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()