如何使用 Pandas groupby 在组上添加顺序计数器列 [英] How to add sequential counter column on groups using Pandas groupby
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问题描述
我觉得还有比这更好的方法:
I feel like there is a better way than this:
import pandas as pd
df = pd.DataFrame(
columns=" index c1 c2 v1 ".split(),
data= [
[ 0, "A", "X", 3, ],
[ 1, "A", "X", 5, ],
[ 2, "A", "Y", 7, ],
[ 3, "A", "Y", 1, ],
[ 4, "B", "X", 3, ],
[ 5, "B", "X", 1, ],
[ 6, "B", "X", 3, ],
[ 7, "B", "Y", 1, ],
[ 8, "C", "X", 7, ],
[ 9, "C", "Y", 4, ],
[ 10, "C", "Y", 1, ],
[ 11, "C", "Y", 6, ],]).set_index("index", drop=True)
def callback(x):
x['seq'] = range(1, x.shape[0] + 1)
return x
df = df.groupby(['c1', 'c2']).apply(callback)
print df
要实现这一点:
c1 c2 v1 seq
0 A X 3 1
1 A X 5 2
2 A Y 7 1
3 A Y 1 2
4 B X 3 1
5 B X 1 2
6 B X 3 3
7 B Y 1 1
8 C X 7 1
9 C Y 4 1
10 C Y 1 2
11 C Y 6 3
有没有办法避免回调?
推荐答案
使用 cumcount()
,参见文档 这里
In [4]: df.groupby(['c1', 'c2']).cumcount()
Out[4]:
0 0
1 1
2 0
3 1
4 0
5 1
6 2
7 0
8 0
9 0
10 1
11 2
dtype: int64
如果您想要从 1 开始的订单
If you want orderings starting at 1
In [5]: df.groupby(['c1', 'c2']).cumcount()+1
Out[5]:
0 1
1 2
2 1
3 2
4 1
5 2
6 3
7 1
8 1
9 1
10 2
11 3
dtype: int64
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