Pandas：基于组聚合筛选DataFrameGroupBy（df.groupby）

Question

df
| a  | b |
|----|---|
| 10 | 1 |
| 10 | 5 |
| 11 | 1 |

直接使用

grouped = df.groupby('a')

让我们只获得

selector = grouped.b.max() - grouped.b.min() >= 3

屈服

df
| a  |       |
|----|-------|
| 10 | True  |
| 11 | False |

我的问题是，当使用DataFrameGroupBy元素时df = df.loc[<filter condition>]的等价物是什么

^{} returns a ^{}

在基于.aggreate()函数进行过滤时，是否有办法保留组？谢谢

Answer 1

遗憾的是，我没有找到一个直接的解决办法。。所以我用2groupby解决了这个问题：

# Build True/False Series for filter criteria
selector = df.groupby('a').b.agg(np.ptp) > 3

# Only select those 'a' which have True in filter criteria
selector = selector.loc[selector == True]

# Re-Create groups of 'a' with the filter criteria in place
# Only those groups for 'a' will be created, where the MAX-MIN of 'b' are > 3.
grouped = df.loc[df['a'].isin(selector.index)].groupby('a')