如何将 seaborn 条形图绘制为子图?

How to plot seaborn barplots as subplot?

我想为数据框中的列列表创建子图。但是,当我 运行 下面的代码时,出现与轴相关的索引错误

TypeError: 'AxesSubplot' object does not support indexing

%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
nr_rows = 1
nr_cols = 3

cols_review = ['home_ownership', 'verification_status', 'loan_status']
li_col_reviews = list(cols_review)

fig, axs = plt.subplots(nr_rows, nr_cols, figsize=(nr_cols*4,nr_rows*3))

for r in range(0,nr_rows):
    for c in range(0, nr_cols):  
        col = r*nr_cols+c
        if col < len(li_col_reviews):
            col_count = pdf[li_col_reviews[col]].value_counts()
            sns.set(style="darkgrid")
            sns.barplot(col_count.index, col_count.values, alpha=0.9,ax = axs[r][c])
            plt.ylabel('Number of Occurrences', fontsize=12)
            plt.xlabel(col, fontsize=12)
            plt.tight_layout()    
            plt.show() 

您需要将 squeeze=False 添加到行 plt.subplots

我在这里修改了您的代码并使用了一些虚拟数据。此外,您必须将 plt.show() 置于循环之外。

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

nr_rows = 1
nr_cols = 3

cols_review = ['home_ownership', 'verification_status', 'loan_status']

fig, axs = plt.subplots(nr_rows, nr_cols, figsize=(nr_cols*4,nr_rows*3), squeeze=False)

for r in range(0,nr_rows):
    for c in range(0, nr_cols):  
        col = r*nr_cols+c
        if col < len(cols_review):
            x=np.random.rand(5) * 10
            y=np.random.rand(5)
            sns.set(style="darkgrid")
            sns.barplot(x, y, alpha=0.9,ax = axs[r][c])
            plt.ylabel('Number of Occurrences', fontsize=12)
            plt.xlabel(col, fontsize=12)
plt.tight_layout()    
plt.show()

Squeeze默认设置为True,这意味着: extra dimensions are squeezed out from the returned array axs。因此不能用 [r][c] 索引。通过不挤压 (squeeze=False),您可以确保 axs 作为二维数组返回,然后可以使用 [r][c]

对其进行索引

您可能想阅读 squeeze 参数 here