如何在 Pandas 中使用 groupby 创建新列？

Question

我有一个像这样的熊猫数据框，

>>> data = {
    'hotel_code': [1, 1, 1, 1, 1],
    'feed': [1, 1, 1, 1, 2],
    'price_euro': [100, 200, 250, 120, 130],
    'client_nationality': ['fr', 'us', 'ru,de', 'gb', 'cn,us,br,il,fr,gb,de,ie,pk,pl']
}
>>> df = pd.DataFrame(data)
>>> df
   hotel_code  feed  price_euro             client_nationality
0           1     1         100                             fr
1           1     1         200                             us
2           1     1         250                          ru,de
3           1     1         120                             gb
4           1     2         130  cn,us,br,il,fr,gb,de,ie,pk,pl

这是预期的输出，

>>> data = {
    'hotel_code': [1, 1],
    'feed': [1, 2],
    'cluster1': ['fr', 'cn,us,br,il,fr,gb,de,ie,pk,pl'],
    'cluster2': ['us', np.nan],
    'cluster3': ['ru,de', np.nan],
    'cluster4': ['gb', np.nan],
}
>>> df = pd.DataFrame(data)
>>> df
   hotel_code  feed                       cluster1 cluster2 cluster3 cluster4
0           1     1                             fr       us    ru,de       gb
1           1     2  cn,us,br,il,fr,gb,de,ie,pk,pl      NaN      NaN      NaN

我想通过 unique 创建簇列hotel_code，feed但我不知道。簇号是可变的。任何的想法？提前致谢。

Answer 1

使用GroupBy.cumcount每团体柜台，通过创建多指标hotel_code与feed和计数器Series通过与再塑Series.unstack，最后rename列和DataFrame.reset_index用于MultiIndex给列：

g = df.groupby(["hotel_code", "feed"]).cumcount()

df1 = (df.set_index(["hotel_code", "feed", g])['client_nationality']
         .unstack()
         .rename(columns = lambda x: f'cluster_{x+1}')
         .reset_index())
print (df1)
   hotel_code  feed                      cluster_1 cluster_2 cluster_3  \
0           1     1                             fr        us     ru,de   
1           1     2  cn,us,br,il,fr,gb,de,ie,pk,pl       NaN       NaN   

  cluster_4  
0        gb  
1       NaN