如何从 seaborn / matplotlib 图中删除或隐藏 x 轴标签

Question

我有一个箱线图，需要删除 x 轴（'user_type' 和 'member_gender'）标签。鉴于以下格式，我该怎么做？

sb.boxplot(x="user_type", y="Seconds", data=df, color = default_color, ax = ax[0,0], sym='').set_title('User-Type (0=Non-Subscriber, 1=Subscriber)')
sb.boxplot(x="member_gender", y="Seconds", data=df, color = default_color, ax = ax[1,0], sym='').set_title('Gender (0=Male, 1=Female, 2=Other)')

Answer 1

• 创建箱线图后，使用.set().
• .set(xticklabels=[]) 应该删除刻度标签。
  • 如果您使用.set_title()，这不起作用，但您可以使用.set(title='')
• .set(xlabel=None) 应该删除轴标签。
• .tick_params(bottom=False) 将去除蜱虫。
• 同样，对于 y 轴：How to remove or hidden y-axis ticklabels from a matplotlib / seaborn plot?

fig, ax = plt.subplots(2, 1)

g1 = sb.boxplot(x="user_type", y="Seconds", data=df, color = default_color, ax = ax[0], sym='')
g1.set(xticklabels=[])
g1.set(title='User-Type (0=Non-Subscriber, 1=Subscriber)')
g1.set(xlabel=None)

g2 = sb.boxplot(x="member_gender", y="Seconds", data=df, color = default_color, ax = ax[1], sym='')
g2.set(xticklabels=[])
g2.set(title='Gender (0=Male, 1=Female, 2=Other)')
g2.set(xlabel=None)

例子

使用 xticks 和 xlabel

import seaborn as sns
import matplotlib.pyplot as plt

# load data
exercise = sns.load_dataset('exercise')
pen = sns.load_dataset('penguins')

# create figures
fig, ax = plt.subplots(2, 1, figsize=(8, 8))

# plot data
g1 = sns.boxplot(x='time', y='pulse', hue='kind', data=exercise, ax=ax[0])

g2 = sns.boxplot(x='species', y='body_mass_g', hue='sex', data=pen, ax=ax[1])

plt.show()

没有 xticks 和 xlabel

fig, ax = plt.subplots(2, 1, figsize=(8, 8))

g1 = sns.boxplot(x='time', y='pulse', hue='kind', data=exercise, ax=ax[0])

g1.set(xticklabels=[])  # remove the tick labels
g1.set(title='Exercise: Pulse by Time for Exercise Type')  # add a title
g1.set(xlabel=None)  # remove the axis label

g2 = sns.boxplot(x='species', y='body_mass_g', hue='sex', data=pen, ax=ax[1])

g2.set(xticklabels=[])  
g2.set(title='Penguins: Body Mass by Species for Gender')
g2.set(xlabel=None)
g2.tick_params(bottom=False)  # remove the ticks

plt.show()