pandas 箱图中每个子图的独立轴 [英] Independent axis for each subplot in pandas boxplot

问题描述

以下代码有助于获得带有唯一彩色框的子图.但是所有子图共享一个公共的x和y轴集.我期待每个子图具有独立的轴:

The below code helps in obtaining subplots with unique colored boxes. But all subplots share a common set of x and y axis. I was looking forward to having independent axis for each sub-plot:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import PathPatch

df = pd.DataFrame(np.random.rand(140, 4), columns=['A', 'B', 'C', 'D'])

df['models'] = pd.Series(np.repeat(['model1','model2', 'model3', 'model4',     'model5', 'model6', 'model7'], 20))

bp_dict = df.boxplot(
by="models",layout=(2,2),figsize=(6,4),
return_type='both',
patch_artist = True,
)

colors = ['b', 'y', 'm', 'c', 'g', 'b', 'r', 'k', ]
for row_key, (ax,row) in bp_dict.iteritems():
    ax.set_xlabel('')
    for i,box in enumerate(row['boxes']):
        box.set_facecolor(colors[i])

plt.show()

这是上面代码的输出:

Here is an output of the above code:

我正在尝试为每个子图分别设置x和y轴...

I am trying to have separate x and y axis for each subplot...

推荐答案

您需要先创建图形和子图，并将其作为参数传递给df.boxplot().这也意味着您可以删除参数layout=(2,2):

You need to create the figure and subplots before hand and pass this in as an argument to df.boxplot(). This also means you can remove the argument layout=(2,2):

fig, axes = plt.subplots(2,2,sharex=False,sharey=False)

然后使用:

bp_dict = df.boxplot(
by="models", ax=axes, figsize=(6,4),
return_type='both',
patch_artist = True,
)

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