Pandas多索引DataFrame:在对1级索引进行分组时，保留列的N个最大条目 [英] Pandas multi index DataFrame: keep the N biggest entries of a column while grouping on level 1 index

问题描述

这是具有多个索引行的示例DataFrame.

This is an example DataFrame with multi index rows.

row_idx_arr = list(zip(['r0', 'r0', 'r0', 'r1', 'r1', 'r1', 'r2', 'r2', 'r2', 'r3', 'r3', 'r3'], ['r-00', 'r-01', 'r-02', 'r-00', 'r-01', 'r-02', 'r-00', 'r-01', 'r-02', 'r-00', 'r-01', 'r-02', ]))
row_idx = pd.MultiIndex.from_tuples(row_idx_arr)

d = pd.DataFrame((np.random.randn(36)*10).reshape(12,3), index=row_idx, columns=['c0', 'c1', 'returns'])


                c0         c1    returns
r0 r-00   3.553446   5.434018   5.141394
   r-01  10.045250  18.453873  13.170396
   r-02  -7.231743 -11.695715   5.303477
r1 r-00  -1.302917   6.461693  15.016544
   r-01  13.348552  -9.133629  -2.464875
   r-02  11.157144  16.833344  -8.745151
r2 r-00 -10.937900 -14.829996  -8.457521
   r-01  -7.495922   9.269724  -5.001560
   r-02  -8.966551  11.063291  -2.420552
r3 r-00 -21.434668  -0.730560   5.550830
   r-01  16.590447  -0.432384  -0.396881
   r-02  -0.636957  -2.765959   2.591906

我想创建一个新的DataFrame，其中对于每个1级索引值(r0，r1，r2，r3)，我保留2个条目(2级行:r-00，r-01，r- 02)具有最高的回报率".

I'd like to create a new DataFrame where, for each level 1 index value (r0, r1, r2, r3), I keep the 2 entries (level 2 rows: r-00, r-01, r-02) with highest 'returns'.

请注意，这是一个示例，在我的程序中，我有数千行.

Please note that this is an example, in my program I have thousands of rows.

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