如何调整 Seaborn 箱线图中胡须的大小？

我想在下面的箱线图中使须线更宽。

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

data = pd.DataFrame({'Data': np.random.random(100), 'Type':['Category']*100})

fig, ax = plt.subplots()

# Plot boxplot setting the whiskers to the 5th and 95th percentiles
sns.boxplot(x='Type', y='Data', data=data, color = 'gray', whis = [5,95])

# Adjust boxplot and whisker line properties
for p, artist in enumerate(ax.artists):
    artist.set_edgecolor('blue')
    for q in range(p*6, p*6+6):
        line = ax.lines[q]
        line.set_color('pink')

我知道如何调整晶须颜色和线宽，但我一直无法弄清楚如何增加晶须的长度。我最接近的是尝试使用line.set_xdata([q/60-0.5, q/60+0.5])但我得到了错误

ValueError: shape mismatch: objects cannot be broadcast to a single shape    

理想情况下，我希望胡须百分位线与盒子的宽度相同。我怎样才能做到这一点？

正如您所注意到的，每个框绘制了 6 条线（因此您的p*6索引）。

带索引的行p*6+4具有盒子的宽度（即盒子内的中线）。所以我们可以用它来设置其他线的宽度。

您要更改的行有索引p*6+2 and p*6+3.

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

data = pd.DataFrame({'Data': np.random.random(100), 'Type':['Category']*100})

fig, ax = plt.subplots()

# Plot boxplot setting the whiskers to the 5th and 95th percentiles
sns.boxplot(x='Type', y='Data', data=data, color = 'gray', whis = [5,95])

# Adjust boxplot and whisker line properties
for p, artist in enumerate(ax.artists):
    artist.set_edgecolor('blue')
    for q in range(p*6, p*6+6):
        line = ax.lines[q]
        line.set_color('pink')

    ax.lines[p*6+2].set_xdata(ax.lines[p*6+4].get_xdata())
    ax.lines[p*6+3].set_xdata(ax.lines[p*6+4].get_xdata())

这也适用于具有多个框的示例：

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

sns.set(style="whitegrid")
tips = sns.load_dataset("tips")
ax = sns.boxplot(x="day", y="total_bill", data=tips)

# Adjust boxplot and whisker line properties
for p, artist in enumerate(ax.artists):
    artist.set_edgecolor('blue')
    for q in range(p*6, p*6+6):
        line = ax.lines[q]
        line.set_color('pink')

    ax.lines[p*6+2].set_xdata(ax.lines[p*6+4].get_xdata())
    ax.lines[p*6+3].set_xdata(ax.lines[p*6+4].get_xdata())