按层次索引展平Pandas.DataFrame从groupby和多重聚合

Question

我将按多个列对数据帧进行分组，并进行聚合以获得多个统计信息。如何获得一个完全平坦的结构，每个可能的组键组合都被枚举为行，而每个统计信息作为列显示？在

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])

这样我就能得到：

^{pr2}$

我要把它弄平：

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