pandas 的变迁 [英] Variable shift in Pandas

问题描述

在数据框中具有两列A和B:

having two columns A and B in a dataframe:

   A   B
0  1   6
1  2   7
2  1   8
3  2   9
4  1  10

我想创建一列C.C必须将B的值偏移A的值:

I would like to create a column C. C must have values of B shifted by value of A:

   A   B   C 
0  1   6 NaN
1  2   7 NaN
2  1   8   7
3  2   9   7
4  1  10   9

命令:

df['C'] = df['B'].shift(df['A'])

不起作用. 您还有其他想法吗?

does not work. Do you have any other ideas?

推荐答案

由于索引对齐，这很棘手，您可以在df上定义用户func和apply按行，此处该函数将在B列并返回已移位列的索引值(使用.name属性返回索引):

This is tricky due to index alignment, you can define a user func and apply row-wise on your df, here the function will perform a shift on the B column and return the index value (using .name attribute to return the index) of the shifted column:

In [134]:    
def func(x):
    return df['B'].shift(x['A'])[x.name]
df['C'] = df.apply(lambda x: func(x), axis=1)
df

Out[134]:
   A   B    C
0  1   6  NaN
1  2   7  NaN
2  1   8  7.0
3  2   9  7.0
4  1  10  9.0

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