Matplotlib绘制饼图遇'tuple'无sum属性错误，求解决方案

问题描述 #

尝试用Matplotlib绘制饼图时触发AttributeError: 'tuple' object has no attribute 'sum'错误，相关代码及错误回溯如下：

原代码 #

import matplotlib.pyplot as plt
import numpy

labels = 'Updated', 'Coverage (overall)', 'last 24 hours', 'Deleted', 'Deleted last 24 hours', 'Banned', 'Banned last 24 hours'
sizes = (6, 5.04, 0, 12, 0, 7, 7)
colors = ['yellowgreen', 'gold', 'lightskyblue', 'green', 'black', 'red', 'grey']

def absolute_value(val):
    a  = numpy.round(val/100.*sizes.sum(), 0)
    return a

plt.pie(sizes, labels=labels, colors=colors,
        autopct=absolute_value)

plt.axis('equal')
plt.show()

错误回溯 #

AttributeError                            Traceback (most recent call last)
Cell In[46], line 12
      9     a  = numpy.round(val/100.*sizes.sum(), 0)
     10     return a
---> 12 plt.pie(sizes, labels=labels, colors=colors,
     13         autopct=absolute_value)
     15 plt.axis('equal')
     16 plt.show()

File ~\AppData\Roaming\Python\Python39\site-packages\matplotlib\pyplot.py:2715, in pie(x, explode, labels, colors, autopct, pctdistance, shadow, labeldistance, startangle, radius, counterclock, wedgeprops, textprops, center, frame, rotatelabels, normalize, data)
   2708 @_copy_docstring_and_deprecators(Axes.pie)
   2709 def pie(
   2710         x, explode=None, labels=None, colors=None, autopct=None,
   2711         pctdistance=0.6, shadow=False, labeldistance=1.1, startangle=0,
   2712         radius=1, counterclock=True, wedgeprops=None, textprops=None, center=(0, 0), frame=False,
   2713         rotatelabels=False, *, normalize=True, data=None):
-> 2715     return gca().pie(
   2716         x, explode=explode, labels=labels, colors=colors,
   2717         autopct=autopct, pctdistance=pctdistance, shadow=shadow,
   2718         labeldistance=labeldistance, startangle=startangle,
   2719         radius=radius, counterclock=counterclock,
   2720         wedgeprops=wedgeprops, textprops=textprops, center=center,
   2721         frame=frame, rotatelabels=rotatelabels, normalize=normalize,
   2722         **({"data": data} if data is not None else {}))

File ~\AppData\Roaming\Python\Python39\site-packages\matplotlib\__init__.py:1423, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
   1420 @functools.wraps(func)
   1421 def inner(ax, *args, data=None, **kwargs):
   1422     if data is None:
-> 1423         return func(ax, *map(sanitize_sequence, args), **kwargs)
   1425     bound = new_sig.bind(ax, *args, **kwargs)
   1426     auto_label = (bound.arguments.get(label_namer)
   1427                   or bound.kwargs.get(label_namer))

File ~\AppData\Roaming\Python\Python39\site-packages\matplotlib\axes\_axes.py:3236, in Axes.pie(self, x, explode, labels, colors, autopct, pctdistance, shadow, labeldistance, startangle, radius, counterclock, wedgeprops, textprops, center, frame, rotatelabels, normalize)
   3234     s = autopct % (100. * frac)
   3235 elif callable(autopct):
-> 3236     s = autopct(100. * frac)
   3237 else:
   3238     raise TypeError(
   3239         'autopct must be callable or a format string')

Cell In[46], line 9, in absolute_value(val)
      8 def absolute_value(val):
----> 9     a  = numpy.round(val/100.*sizes.sum(), 0)
     10     return a

AttributeError: 'tuple' object has no attribute 'sum'

错误原因 #

sizes是Python原生**元组(tuple)**类型，元组没有sum()方法，调用sizes.sum()直接触发属性错误。

解决方法 #

方法1：将元组转为NumPy数组 #

把sizes定义为NumPy数组，即可调用sum()方法：

sizes = numpy.array([6, 5.04, 0, 12, 0, 7, 7])

方法2：用Python内置sum()函数计算总和 #

不修改sizes类型，直接用内置sum()函数计算元组总和，修改absolute_value函数：

def absolute_value(val):
    a = numpy.round(val/100. * sum(sizes), 0)
    return a

额外优化（可选） #

autopct要求返回字符串才能在饼图上正常显示，当前返回数值可能显示异常，建议转为字符串：

def absolute_value(val):
    a = numpy.round(val/100. * sum(sizes), 0)
    return f'{a}'

修正后的完整代码 #

import matplotlib.pyplot as plt
import numpy

labels = 'Updated', 'Coverage (overall)', 'last 24 hours', 'Deleted', 'Deleted last 24 hours', 'Banned', 'Banned last 24 hours'
sizes = (6, 5.04, 0, 12, 0, 7, 7)
colors = ['yellowgreen', 'gold', 'lightskyblue', 'green', 'black', 'red', 'grey']

def absolute_value(val):
    a = numpy.round(val/100. * sum(sizes), 0)
    return f'{a}'

plt.pie(sizes, labels=labels, colors=colors,
        autopct=absolute_value)

plt.axis('equal')
plt.show()

内容的提问来源于stack exchange，提问作者maria bandoria