如何在Plotly Express中强制显示每个子图的X轴与Y轴

使用plotly.express.histogram()绘制带行分面（facet_row）和列分面（facet_col）的直方图时，希望每个子图都显示独立的X轴与Y轴以提升可读性，但默认生成的图表中仅边缘子图显示轴，内部子图的轴被隐藏。测试代码如下：

import numpy as np
import pandas as pd
import plotly.express as px

# create a dummy dataframe with lots of variables
rng = np.random.default_rng(42)
n_vars = 3
n_samples = 10
random_vars = [rng.normal(size=n_samples) for v in range(n_vars)]
m = np.vstack(random_vars).T
columns = pd.MultiIndex.from_tuples([('a','b'),('a','c'),('b','c')],names=['src','tgt'])
df = pd.DataFrame(m,columns=columns)

# convert to long format
df_long = df.melt()

# plot with plotly
fig = px.histogram(df_long,x='value',facet_row='src',facet_col='tgt')
fig.update_layout(yaxis={'side': 'left'})
fig.show()

解决方案 #

通过update_xaxes()和update_yaxes()统一配置所有分面子图的轴显示属性，即可让每个子图都显示X轴与Y轴：

import numpy as np
import pandas as pd
import plotly.express as px

# 创建测试数据
rng = np.random.default_rng(42)
n_vars = 3
n_samples = 10
random_vars = [rng.normal(size=n_samples) for v in range(n_vars)]
m = np.vstack(random_vars).T
columns = pd.MultiIndex.from_tuples([('a','b'),('a','c'),('b','c')],names=['src','tgt'])
df = pd.DataFrame(m,columns=columns)

# 转换为长格式
df_long = df.melt()

# 绘制直方图
fig = px.histogram(df_long,x='value',facet_row='src',facet_col='tgt')
fig.update_layout(yaxis={'side': 'left'})

# 配置所有子图显示X/Y轴
fig.update_xaxes(showticklabels=True, matches=None)
fig.update_yaxes(showticklabels=True, matches=None)

fig.show()

• showticklabels=True：强制每个子图显示轴刻度标签与轴线
• matches=None：取消默认的轴共享机制，让每个子图的轴刻度范围可独立调整（若不需要独立范围，仅保留showticklabels=True即可）

内容的提问来源于stack exchange，提问作者Johannes Wiesner