Python-GroupBy对象的滚动功能 [英] Python - rolling functions for GroupBy object

问题描述

我有一个类型为<pandas.core.groupby.SeriesGroupBy object at 0x03F1A9F0>的时间序列对象grouped. grouped.sum()给出了所需的结果，但是我无法获得rolling_sum与groupby对象一起使用.有什么方法可以将滚动功能应用于groupby对象?例如:

I have a time series object grouped of the type <pandas.core.groupby.SeriesGroupBy object at 0x03F1A9F0>. grouped.sum() gives the desired result but I cannot get rolling_sum to work with the groupby object. Is there any way to apply rolling functions to groupby objects? For example:

x = range(0, 6)
id = ['a', 'a', 'a', 'b', 'b', 'b']
df = DataFrame(zip(id, x), columns = ['id', 'x'])
df.groupby('id').sum()
id    x
a    3
b   12

但是，我想要这样的东西:

However, I would like to have something like:

  id  x
0  a  0
1  a  1
2  a  3
3  b  3
4  b  7
5  b  12

推荐答案

注意:由@kekert标识，以下熊猫模式已被弃用.请在下面的答案中查看当前的解决方案.

Note: as identified by @kekert, the following pandas pattern has been deprecated. See current solutions in the answers below.

In [16]: df.groupby('id')['x'].apply(pd.rolling_mean, 2, min_periods=1)
Out[16]: 
0    0.0
1    0.5
2    1.5
3    3.0
4    3.5
5    4.5

In [17]: df.groupby('id')['x'].cumsum()
Out[17]: 
0     0
1     1
2     3
3     3
4     7
5    12

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