Question

具有以下数据框。

A = pd.Series([2, 3, 4, 5], index=[1, 2, 3, 4])
B = pd.Series([6, 7, 8, 9], index=[1, 2, 3, 4])
Aw = pd.Series([0.25, 0.3, 0.33, 0.36], index=[1, 2, 3, 4])
Bw = pd.Series([0.75, 0.7, 0.67, 0.65], index=[1, 2, 3, 4])
df = pd.DataFrame({'A': A, 'B': B, 'Aw': Aw, 'Bw', Bw})
df

Index A B Aw   Bw
1     2 6 0.25 0.75
2     3 7 0.30 0.70
3     4 8 0.33 0.67
4     5 9 0.36 0.64

我想做的就是将“ A”和“ Aw”的滞后乘以“ Bw”。生成的数据帧将如下所示：

Index A B Aw   Bw   A_ctr B_ctr
1     2 6 NaN  NaN  NaN   NaN
2     3 7 0.25 0.75 0.75  5.25
3     4 8 0.3  0.7  1.2   5.6
4     5 9 0.33 0.64 1.65  5.76

提前谢谢

Answer 1

要获得所需的输出，请先移动Aw和Bw，然后将它们乘以A和B：

df[['Aw','Bw']] = df[['Aw','Bw']].shift()

df[['A_ctr','B_ctr']] = df[['A','B']].values*df[['Aw','Bw']]

   A  B    Aw    Bw  A_ctr  B_ctr
1  2  6   NaN   NaN    NaN    NaN
2  3  7  0.25  0.75   0.75   5.25
3  4  8  0.30  0.70   1.20   5.60
4  5  9  0.33  0.67   1.65   6.03

带滞后的数据帧中的列乘积

1 个答案: