python - 从 groupby 和多重聚合中展平层次索引 pandas.DataFrame

Question

我按多列对数据框进行分组并聚合以获得多个统计信息。如何获得一个完全扁平的结构，其中每个可能的组键组合都以行的形式枚举，每个统计量以列的形式呈现？

import numpy as np
import pandas as pd

cities = ['Berlin', 'Oslo']
days = ['Monday', 'Friday']

data = pd.DataFrame({
        'city': np.random.choice(cities, 12),
        'day': np.random.choice(days, 12),
        'people': np.random.normal(loc=10, size=12),
        'cats': np.random.normal(loc=6, size=12)})
grouped = data.groupby(['city', 'day']).agg([np.mean, np.std])

这样我得到:

                   cats               people          
                   mean       std       mean       std
city   day                                            
Berlin Friday  6.146924  0.721263  10.445606  0.730992
       Monday  5.239267       NaN   9.022811       NaN
Oslo   Friday  6.322276  0.866899  11.579813  0.114341
       Monday  5.028919  0.815674  10.458439  1.182689

我需要把它弄平:

city   day     cats_mean cats_std  people_mean people_std                                       
Berlin Friday  6.146924  0.721263  10.445606   0.730992
Berlin Monday  5.239267       NaN   9.022811        NaN
Oslo   Friday  6.322276  0.866899  11.579813   0.114341
Oslo   Monday  5.028919  0.815674  10.458439   1.182689

Answer 1

In [36]: grouped.columns = grouped.columns.map('_'.join)

In [37]: grouped = grouped.reset_index()

In [38]: grouped
Out[38]:
     city     day  cats_mean  cats_std  people_mean  people_std
0  Berlin  Friday   5.852991  1.085163    11.078541    0.839688
1  Berlin  Monday   6.978343  0.630983     9.876106    1.846204
2    Oslo  Friday   6.096773  1.278176     9.710216    0.691672