pandas groupby()，agg()-如何在没有多重索引的情况下返回结果? [英] Pandas groupby(),agg() - how to return results without the multi index?

问题描述

我有一个数据框:

pe_odds[ [ 'EVENT_ID', 'SELECTION_ID', 'ODDS' ] ]
Out[67]: 
     EVENT_ID  SELECTION_ID   ODDS
0   100429300       5297529  18.00
1   100429300       5297529  20.00
2   100429300       5297529  21.00
3   100429300       5297529  22.00
4   100429300       5297529  23.00
5   100429300       5297529  24.00
6   100429300       5297529  25.00

当我使用groupby和agg时，我得到了具有多索引的结果:

When I use groupby and agg, I get results with a multi-index:

pe_odds.groupby( [ 'EVENT_ID', 'SELECTION_ID' ] )[ 'ODDS' ].agg( [ np.min, np.max ] )
Out[68]: 
                         amin   amax
EVENT_ID  SELECTION_ID              
100428417 5490293        1.71   1.71
          5881623        1.14   1.35
          5922296        2.00   2.00
          5956692        2.00   2.02
100428419 603721         2.44   2.90
          4387436        4.30   6.20
          4398859        1.23   1.35
          4574687        1.35   1.46
          4881396       14.50  19.00
          6032606        2.94   4.20
          6065580        2.70   5.80
          6065582        2.42   3.65
100428421 5911426        2.22   2.52

我尝试使用as_index返回没有multi_index的结果:

I have tried using as_index to return the results without the multi_index:

pe_odds.groupby( [ 'EVENT_ID', 'SELECTION_ID' ], as_index=False )[ 'ODDS' ].agg( [ np.min, np.max ], as_index=False )

但是它仍然给了我多重索引.

But it still gives me a multi-index.

我可以使用.reset_index()，但是它非常慢:

I can use .reset_index(), but it is very slow:

pe_odds.groupby( [ 'EVENT_ID', 'SELECTION_ID' ] )[ 'ODDS' ].agg( [ np.min, np.max ] ).reset_index()

pe_odds.groupby( [ 'EVENT_ID', 'SELECTION_ID' ] )[ 'ODDS' ].agg( [ np.min, np.max ] ).reset_index()
Out[69]: 
     EVENT_ID  SELECTION_ID   amin   amax
0   100428417       5490293   1.71   1.71
1   100428417       5881623   1.14   1.35
2   100428417       5922296   2.00   2.00
3   100428417       5956692   2.00   2.02
4   100428419        603721   2.44   2.90
5   100428419       4387436   4.30   6.20

如何使用groupby和/或agg函数的参数在没有多索引的情况下返回结果.而且不必诉诸使用reset_index()吗?

How can I return the results, without the Multi-index, using parameters of the groupby and/or agg function. And without having to resort to using reset_index() ?

推荐答案

以下通话:

>>> gr = df.groupby(['EVENT_ID', 'SELECTION_ID'], as_index=False)
>>> res = gr.agg({'ODDS':[np.min, np.max]})
>>> res
    EVENT_ID SELECTION_ID ODDS     
                          amin amax
0  100429300      5297529   18   25
1  100429300      5297559   30   38

返回索引为列的框架.如果您不希望列成为多索引，则可以执行以下操作:

returns a frame with mulit-index columns. If you do not want columns to be multi-index either you may do:

>>> res.columns = list(map(''.join, res.columns.values))
>>> res
    EVENT_ID  SELECTION_ID  ODDSamin  ODDSamax
0  100429300       5297529        18        25
1  100429300       5297559        30        38

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