我的数据框如下所示：
time price macd signal macd_histogram cross output direction
49 2019-01-01 12:00:07.865 0.00225919 4.578325e-06 4.294706e-06 2.836196e-07 False up
50 2019-01-01 12:00:09.286 0.00226142 4.622147e-06 4.360194e-06 2.619531e-07 False up
51 2019-01-01 12:03:22.676 0.00225699 4.272353e-06 4.342626e-06 -7.027294e-08 False down
52 2019-01-01 12:05:36.318 0.00225908 4.106013e-06 4.295303e-06 -1.892901e-07 False down
53 2019-01-01 12:11:42.492 0.00225479 3.607286e-06 4.157700e-06 -5.504139e-07 False down
我需要做的是，当列
direction从值up变为down时，会在值event的新列crossing中通知它。当列direction从down移到up时，请执行相同的操作。我尝试了一个if语句，但是没有用……还有其他想法吗？谢谢！ 最佳答案
您可以尝试DataFrame.Series.shift和np.where：
df = pd.DataFrame({'direction':['up', 'up', 'down', 'down', 'up', 'up']})
df
direction
0 up
1 up
2 down
3 down
4 up
5 up
df['event'] = np.where(df['direction'] != df['direction'].shift(1), 'crossing', df['direction'])
df
direction event
0 up crossing
1 up up
2 down crossing
3 down down
4 up crossing
5 up up
如果不相交，则可以添加任何其他值：
df['event'] = np.where(df['direction'] != df['direction'].shift(1), 'crossing', 'no event')
df
direction event
0 up crossing
1 up no event
2 down crossing
3 down no event
4 up crossing
5 up no event
由于您有多个条件，请使用np.select：
condition1 = (df['direction'] != df['direction'].shift(1)) & (df['direction'] == 'up')
condition2 = (df['direction'] != df['direction'].shift(1)) & (df['direction'] == 'down')
df['event']= np.select([condition1, condition2], ['crossing up', 'crossing down'], default='no event')
df
direction event
0 up crossing up
1 up no event
2 down crossing down
3 down no event
4 up crossing up
5 up no event
关于python - Pandas :列值更改时在另一列中记录，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/54787790/