本文介绍了如何在Pandas的群组中使用cumsum?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有
df = pd.DataFrame.from_dict({'id': ['A', 'B', 'A', 'C', 'D', 'B', 'C'], 'val': [1,2,-3,1,5,6,-2], 'stuff':['12','23232','13','1234','3235','3236','732323']})
id stuff val
0 A 12 1
1 B 23232 2
2 A 13 -3
3 C 1234 1
4 D 3235 5
5 B 3236 6
6 C 732323 -2
我想为每个id
运行一些val
,所以所需的输出如下所示:
I'd like to get running some of val
for each id
, so the desired output looks like this:
id stuff val cumsum
0 A 12 1 1
1 B 23232 2 2
2 A 13 -3 -2
3 C 1234 1 1
4 D 3235 5 5
5 B 3236 6 8
6 C 732323 -2 -1
这是我尝试过的:
df['cumsum'] = df.groupby('id').cumsum(['val'])
和
df['cumsum'] = df.groupby('id').cumsum(['val'])
这是我得到的错误:
ValueError: Wrong number of items passed 0, placement implies 1
推荐答案
您可以致电 transform
并传递 cumsum
函数将该列添加到您的df中:
You can call transform
and pass the cumsum
function to add that column to your df:
In [156]:
df['cumsum'] = df.groupby('id')['val'].transform(pd.Series.cumsum)
df
Out[156]:
id stuff val cumsum
0 A 12 1 1
1 B 23232 2 2
2 A 13 -3 -2
3 C 1234 1 1
4 D 3235 5 5
5 B 3236 6 8
6 C 732323 -2 -1
关于您的错误,您不能在Series groupby对象上调用cumsum
,其次,您将列名作为无意义的列表传递.
With respect to your error, you can't call cumsum
on a Series groupby object, secondly you're passing the name of the column as a list which is meaningless.
这可行:
In [159]:
df.groupby('id')['val'].cumsum()
Out[159]:
0 1
1 2
2 -2
3 1
4 5
5 8
6 -1
dtype: int64
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