绘制子图时如何修复“numpy.ndarray"对象没有属性“get_figure" [英] How to fix 'numpy.ndarray' object has no attribute 'get_figure' when plotting subplots

问题描述

我编写了以下代码来在不同的子图中绘制6个饼图，但出现错误.如果我只使用它来绘制 2 个图表，则此代码可以正常工作，但除此之外还会产生错误.

我的数据集中有 6 个分类变量，它们的名称存储在列表 cat_cols 中.图表将根据训练数据 train 绘制.

代码

  fig，axes = plt.subplots(2，3，figsize =(24，10))对于 i, c in enumerate(cat_cols):train[c].value_counts()[::-1].plot(kind = 'pie', ax=axes[i], title=c, autopct='%.0f', fontsize=18)轴[i].set_ylabel('')plt.tight_layout()

错误

  AttributeError:'numpy.ndarray'对象没有属性'get_figure'

我们如何纠正这个问题?

解决方案

• 问题在于 plt.subplots(2, 3, figsize=(24, 10)) 创建两组 3 个子图，而不是一组 6 个子图.

  array([[< AxesSubplot:xlabel ='radians'> ;,< AxesSubplot:xlabel ='radians'> ;,< AxesSubplot:xlabel ='radians'>]，[<AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>]], dtype=object)

• 使用 axes.ravel()从 axes 解压缩所有子图数组.

  • I have written the following code to plot 6 pie charts in different subplots, but I get an error. This code works correctly if I use it to plot only 2 charts, but produces an an error for anything more than that.

    I have 6 categorical variables in my dataset, the names of which are stored in the list cat_cols. The charts are to be plotted from the training data train.

    CODE

    fig, axes = plt.subplots(2, 3, figsize=(24, 10))
    
    for i, c in enumerate(cat_cols):
      
      train[c].value_counts()[::-1].plot(kind = 'pie', ax=axes[i], title=c, autopct='%.0f', fontsize=18)
      axes[i].set_ylabel('')
        
    plt.tight_layout()
    

    ERROR

    AttributeError: 'numpy.ndarray' object has no attribute 'get_figure'
    

    How do we rectify this?

    解决方案

    • The issue is plt.subplots(2, 3, figsize=(24, 10)) creates two groups of 3 subplots, not one group of six subplots.

    array([[<AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>],
           [<AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>, <AxesSubplot:xlabel='radians'>]], dtype=object)
    

    • Unpack all of the subplot arrays from axes, using axes.ravel().
      • numpy.ravel, which returns a flattened array.
      • A list comprehension will also work, axe = [sub for x in axes for sub in x]
    • Assign each plot to one of the subplots in axe.
    • How to resolve AttributeError: 'numpy.ndarray' object has no attribute 'get_figure' when plotting subplots is a similar issue.

    import pandas as pd
    import numpy as np
    
    # sinusoidal sample data
    sample_length = range(1, 6+1)
    rads = np.arange(0, 2*np.pi, 0.01)
    data = np.array([np.sin(t*rads) for t in sample_length])
    df = pd.DataFrame(data.T, index=pd.Series(rads.tolist(), name='radians'), columns=[f'freq: {i}x' for i in sample_length])
    
    # crate the figure and axes
    fig, axes = plt.subplots(2, 3, figsize=(24, 10))
    
    # unpack all the axes subplots
    axe = axes.ravel()
    
    # assign the plot to each subplot in axe
    for i, c in enumerate(df.columns):
        df[c].plot(ax=axe[i])
    

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