Python 如何将在数据帧上执行groupby操作后获得的数据结构转换为数据帧？

假设我拥有示例中的数据集：

我想做一个

团

与

预测试分数

的方框图。为此，我需要找出这两个变量的相对分布。因此，我将

团

分组为

预测试分数

：

df1 = df['regiment'].groupby(df['preTestScore']).count()
df1

preTestScore
2     3
3     3
4     2
24    2
31    2
Name: regiment, dtype: int64

如果我现在尝试进行箱线图，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

这产生了一个箱线图，但其分布不是

军团

与

测试前得分

的分布（事实上，这个箱线图对我来说没有意义；我不知道它的

y

轴值代表什么）。为此，我们需要在箱线图中指定

x

和

y

参数。但是，由于groupby对象不是数据帧，因此会产生以下错误：

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'

当我获取

df1

中的值并将它们放入新的数据帧

df2

，然后再次尝试箱线图时，它会工作：

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

---

因此，与其复制groupby对象的内容并将其粘贴到新的数据框中，如何直接获取数据框来存储数据框中两个变量的相对分布？

使用

到\u frame

将序列转换为数据框，然后在打印前重置索引：

df1 = df['regiment'].groupby(df['preTestScore']).count().to_frame().reset_index()
sns.boxplot(x='regiment', y='preTestScore', data=df1)

---

不相关，但您能否告诉我如何使用固定数量的垃圾箱来使用

groupby

？这在以下情况下会很有帮助，例如，

community

具有>10个值，并且我们希望将数据帧分组到3个bins

community

值中。@Kristada673:只需创建一个包含已装箱值的新列并按该列分组即可。请参见此处有关如何进行装箱的示例：

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'

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

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

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

df1 = df['regiment'].groupby(df['preTestScore']).count().to_frame().reset_index()
sns.boxplot(x='regiment', y='preTestScore', data=df1)