在熊猫的分组条上绘制误差线

Question

我可以像这样在单系列条形图上绘制误差线：

import pandas as pd
df = pd.DataFrame([[4,6,1,3], [5,7,5,2]], columns = ['mean1', 'mean2', 'std1', 'std2'], index=['A', 'B'])
print(df)
     mean1  mean2  std1  std2
A      4      6     1     3
B      5      7     5     2

df['mean1'].plot(kind='bar', yerr=df['std1'], alpha = 0.5,error_kw=dict(ecolor='k'))

正如预期的那样，指数A的平均值与同一指数的标准差配对，误差条显示该值的+/-。

但是，当我尝试在同一个图中同时绘制“mean1”和“mean2”时，我无法以相同的方式使用标准差：

df[['mean1', 'mean2']].plot(kind='bar', yerr=df[['std1', 'std2']], alpha = 0.5,error_kw=dict(ecolor='k'))

    Traceback (most recent call last):

  File "<ipython-input-587-23614d88a3c5>", line 1, in <module>
    df[['mean1', 'mean2']].plot(kind='bar', yerr=df[['std1', 'std2']], alpha = 0.5,error_kw=dict(ecolor='k'))

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\tools\plotting.py", line 1705, in plot_frame
    plot_obj.generate()

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\tools\plotting.py", line 878, in generate
    self._make_plot()

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\tools\plotting.py", line 1534, in _make_plot
    start=start, label=label, **kwds)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\tools\plotting.py", line 1481, in f
    return ax.bar(x, y, w, bottom=start,log=self.log, **kwds)

  File "C:\Users\nameDropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\matplotlib\axes.py", line 5075, in bar
    fmt=None, **error_kw)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\matplotlib\axes.py", line 5749, in errorbar
    iterable(yerr[0]) and iterable(yerr[1])):

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\frame.py", line 1635, in __getitem__
    return self._getitem_column(key)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\frame.py", line 1642, in _getitem_column
    return self._get_item_cache(key)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\generic.py", line 983, in _get_item_cache
    values = self._data.get(item)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\internals.py", line 2754, in get
    _, block = self._find_block(item)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\internals.py", line 3065, in _find_block
    self._check_have(item)

  File "C:\Users\name\Dropbox\Tools\WinPython-64bit-2.7.6.2\python-2.7.6.amd64\lib\site-packages\pandas\core\internals.py", line 3072, in _check_have
    raise KeyError('no item named %s' % com.pprint_thing(item))

KeyError: u'no item named 0'

最接近我想要的输出的是：

df[['mean1', 'mean2']].plot(kind='bar', yerr=df[['std1', 'std2']].values.T, alpha = 0.5,error_kw=dict(ecolor='k'))

但现在误差线不是对称绘制的。相反，每个系列中的绿色和模糊条使用相同的正负错误，这就是我卡住的地方。如何让我的多系列条形图的误差条具有与我只有一个系列时相似的外观？

更新： 似乎这是在pandas 0.14 中修复的，我之前正在阅读 0.13 的文档。不过，我现在无法升级我的熊猫。稍后再做，看看结果如何。

Answer 1

• OP 中的yerr=df[['std1', 'std2']] 不起作用，因为列名与df[['mean1', 'mean2']] 不同
  • 将值作为数据框传递给yerr 时，列名必须与数据列相同（例如mean1 和mean2）
  • 见Adding error bars to grouped bar plot in pandas
• 使用 df[['std1', 'std2']].to_numpy().T 通过传递不带命名列的错误数组来绕过问题
• 在python 3.8.11、pandas 1.3.3、matplotlib 3.4.3 测试

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame([[4,6,1,3], [5,7,5,2]], columns = ['mean1', 'mean2', 'std1', 'std2'], index=['A', 'B'])

   mean1  mean2  std1  std2
A      4      6     1     3
B      5      7     5     2

# convert the std columns to an array
yerr = df[['std1', 'std2']].to_numpy().T

# print(yerr)
array([[1, 5],
       [3, 2]], dtype=int64)

df[['mean1', 'mean2']].plot(kind='bar', yerr=yerr, alpha=0.5, error_kw=dict(ecolor='k'))
plt.show()