如何将对pandas数据帧执行groupby操作后获得的数据结构转换为数据帧？

Question

假设我有来自示例here的数据集：

import pandas as pd

raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'], 
        'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'], 
        'name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze', 'Jacon', 'Ryaner', 'Sone', 'Sloan', 'Piger', 'Riani', 'Ali'], 
        'preTestScore': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],
        'postTestScore': [25, 94, 57, 62, 70, 25, 94, 57, 62, 70, 62, 70]}
df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'name', 'preTestScore', 'postTestScore'])
df

我想做一个regimentvspreTestScore的盒线图。为此，我需要找出这两个变量的相对分布。因此，我将regiment按preTestScore分组：

^{pr2}$

如果我现在尝试绘制盒形图，它会给出一个错误：

import seaborn as sns
sns.boxplot(data=df1)

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-131-8296ca940a25> in <module>()
      1 df1 = df['regiment'].groupby(df['preTestScore']).count()
      2 df1
----> 3 sns.boxplot(data=df1)

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in boxplot(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, notch, ax, **kwargs)
   2209     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,
   2210                           orient, color, palette, saturation,
-> 2211                           width, dodge, fliersize, linewidth)
   2212 
   2213     if ax is None:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)
    439                  width, dodge, fliersize, linewidth):
    440 
--> 441         self.establish_variables(x, y, hue, data, orient, order, hue_order)
    442         self.establish_colors(color, palette, saturation)
    443 

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)
     94                 if hasattr(data, "shape"):
     95                     if len(data.shape) == 1:
---> 96                         if np.isscalar(data[0]):
     97                             plot_data = [data]
     98                         else:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
    765         key = com._apply_if_callable(key, self)
    766         try:
--> 767             result = self.index.get_value(self, key)
    768 
    769             if not is_scalar(result):

~\AppData\Local\Continuum\anaconda3\lib\site-packages\pandas\core\indexes\base.py in get_value(self, series, key)
   3116         try:
   3117             return self._engine.get_value(s, k,
-> 3118                                           tz=getattr(series.dtype, 'tz', None))
   3119         except KeyError as e1:
   3120             if len(self) > 0 and self.inferred_type in ['integer', 'boolean']:

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_value()

pandas\_libs\index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

pandas\_libs\hashtable_class_helper.pxi in pandas._libs.hashtable.Int64HashTable.get_item()

KeyError: 0

因此，我将groupby对象转换为dataframe并再次尝试boxplot：

df1 = pd.DataFrame(df1)
df1

sns.boxplot(data=df1)

这会生成一个boxplot，但其分布不是regimentvspreTestScore（事实上，这个boxplot对我没有意义；我不知道它的y轴值代表什么）。为此，我们需要在boxplot中指定x和{}参数。但是，由于groupby对象不是dataframe，它会产生以下错误：

sns.boxplot(x='regiment', y='preTestScore', data=df1)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-132-fc8036eb7d0b> in <module>()
----> 1 sns.boxplot(x='regiment', y='preTestScore', data=df1)

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in boxplot(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, notch, ax, **kwargs)
   2209     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,
   2210                           orient, color, palette, saturation,
-> 2211                           width, dodge, fliersize, linewidth)
   2212 
   2213     if ax is None:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)
    439                  width, dodge, fliersize, linewidth):
    440 
--> 441         self.establish_variables(x, y, hue, data, orient, order, hue_order)
    442         self.establish_colors(color, palette, saturation)
    443 

~\AppData\Local\Continuum\anaconda3\lib\site-packages\seaborn\categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)
    149                 if isinstance(input, string_types):
    150                     err = "Could not interpret input '{}'".format(input)
--> 151                     raise ValueError(err)
    152 
    153             # Figure out the plotting orientation

ValueError: Could not interpret input 'regiment'

我们可以通过执行以下操作来检查df1的数据类型：

df1.dtype
>>> dtype('int64')

当我把df1中的值放入一个新的数据帧df2中，并再次尝试boxplot时，它起作用了：

df2 = pd.DataFrame({'preTestScore': [2,3,4,24,31], 'regiment': [3,3,2,2,2]})
df2

sns.boxplot(x='regiment', y='preTestScore', data=df2)

所以，与其复制groupby对象的内容并将其粘贴到一个新的dataframe中，我如何直接获得一个dataframe来存储一个dataframe中两个变量的相对分布呢？在

Answer 1

使用to_frame将序列转换为数据帧，然后在绘图之前重置索引：

^{1}$