Groupby并在熊猫，Python中转置

Groupby并在熊猫，Python中转置

我认为需要

set_index

有

unstack

：

df['COUNT'] = df.groupby(['ID','col']).cumcount()+1df = df.set_index(['ID','col', 'COUNT'])['col2'].unstack().add_prefix('col').reset_index()print (df)COUNT  ID col  col1  col20       1   A  50.0  52.01       1   B  45.0   NaN2       1   C  18.0   NaN

要么：

c = df.groupby(['ID','col']).cumcount()+1df = df.set_index(['ID','col', c])['col2'].unstack().add_prefix('col').reset_index()print (df)   ID col  col1  col20   1   A  50.0  52.01   1   B  45.0   NaN2   1   C  18.0   NaN

编辑：

对于多列，解决方案有所更改，因为在

MultiIndex

in列中进行处理：

df['COUNT'] = (df.groupby(['ID','col']).cumcount()+1).astype(str)#remove col2df = df.set_index(['ID','col', 'COUNT']).unstack()#flatten Multiindexdf.columns = df.columns.map('_'.join)df = df.reset_index()print (df)   ID col  col2_1  col2_2 col3_1 col3_2  col4_1  col4_20   1   A    50.0    52.0      S      M     1.0     4.01   1   B    45.0     NaN      N   None     8.0     NaN2   1   C    18.0     NaN      S   None     7.0     NaN