A B C D
0 2002-01-13 15:00:00 X 110 3.9
1 2002-01-13 15:00:00 Y 120 1.9
2 2002-01-13 15:00:00 X 130 8.0
3 2002-01-13 15:00:00 X 140 9.0
4 2002-01-14 16:00:00 X 110 0.2
5 2002-01-14 16:00:00 Y 120 7.0
6 2002-01-14 16:00:00 X 130 1.6
7 2002-01-14 16:00:00 X 140 3.4
我想创建一个新列df["E"]，当 B = Y 时，该列 D值，并为每个 A组保留此值< / em>的
输出应为：
A B C D E
0 2002-01-13 15:00:00 X 110 3.9 1.9
1 2002-01-13 15:00:00 Y 120 1.9 1.9
2 2002-01-13 15:00:00 X 130 8.0 1.9
3 2002-01-13 15:00:00 X 140 9.0 1.9
4 2002-01-14 16:00:00 X 110 0.2 7.0
5 2002-01-14 16:00:00 Y 120 7.0 7.0
6 2002-01-14 16:00:00 X 130 1.6 7.0
7 2002-01-14 16:00:00 X 140 3.4 7.0
答案 0 :(得分：1)
选项1：
In [8]: df.merge(df.loc[df.B=='Y', ['A', 'D']].rename(columns={'D':'E'}))
Out[8]:
A B C D E
0 2002-01-13 15:00:00 X 110 3.9 1.9
1 2002-01-13 15:00:00 Y 120 1.9 1.9
2 2002-01-13 15:00:00 X 130 8.0 1.9
3 2002-01-13 15:00:00 X 140 9.0 1.9
4 2002-01-14 16:00:00 X 110 0.2 7.0
5 2002-01-14 16:00:00 Y 120 7.0 7.0
6 2002-01-14 16:00:00 X 130 1.6 7.0
7 2002-01-14 16:00:00 X 140 3.4 7.0
选项2：
In [35]: df['E'] = df['A'].map(df.loc[df.B=='Y', ['A', 'D']].set_index('A')['D'])
In [36]: df
Out[36]:
A B C D E
0 2002-01-13 15:00:00 X 110 3.9 1.9
1 2002-01-13 15:00:00 Y 120 1.9 1.9
2 2002-01-13 15:00:00 X 130 8.0 1.9
3 2002-01-13 15:00:00 X 140 9.0 1.9
4 2002-01-14 16:00:00 X 110 0.2 7.0
5 2002-01-14 16:00:00 Y 120 7.0 7.0
6 2002-01-14 16:00:00 X 130 1.6 7.0
7 2002-01-14 16:00:00 X 140 3.4 7.0