Question

考虑到这个问题： Pandas conditional groupby count

我希望结果是这样的：

    A       D   Dcount
0   foo     2   2
1   foo     4   2
2   foo     4   2
3   foo     2   2
4   bar     5   NaN
5   bar     4   NaN
6   bar     3   NaN
7   bar     2   NaN

我的意思是，如果满足2个条件（A列=＆＃39; foo＆＃39; B列= 2），我希望在Dcount列中为A =＆＃39; foo＆＃39;的所有行设置此类行（2）的明显计数。

可以修改它以获得所需的结果吗？

import pandas as pd
df = pd.DataFrame(
    {'A' : ['foo', 'foo', 'foo', 'foo',
            'bar', 'bar', 'bar', 'bar'],
     'D' : [2, 4, 4, 2, 5, 4, 3, 2]})

#First, I filter
df2=df.loc[(df['A']=='foo')&(df['D']==2)]
#Then, I use groupby and lambda x to count
df['Dcount']=df2.groupby(['D'])['D'].transform(lambda x: x.count())
df

提前致谢！

Answer 1

您可以在一行中使用where中的numpy：

import numpy as np

df['Dcount'] = np.where(df['A']=='foo', sum((df.A=='foo') & (df.D==2)), np.NaN)

#In [34]: df
#Out[34]:
#     A  D  Dcount
#0  foo  2       2
#1  foo  4       2
#2  foo  4       2
#3  foo  2       2
#4  bar  5     NaN
#5  bar  4     NaN
#6  bar  3     NaN
#7  bar  2     NaN

Pandas Conditional Groupby Count Part 2

1 个答案: