我正在检索以下数据帧的 cummax() 值，
exit_price trend netgain high low MFE_pr
exit_time
2000-02-01 01:00:00 1400.25 -1 1.00 1401.50 1400.25 1400.25
2000-02-01 01:30:00 1400.75 -1 0.50 1401.00 1399.50 1399.50
2000-02-01 02:00:00 1400.00 -1 1.25 1401.00 1399.75 1399.50
2000-02-01 02:30:00 1399.25 -1 2.00 1399.75 1399.25 1399.25
2000-02-01 03:00:00 1399.50 -1 1.75 1400.00 1399.50 1399.25
2000-02-01 03:30:00 1398.25 -1 3.00 1399.25 1398.25 1398.25
2000-02-01 04:00:00 1398.75 -1 2.50 1399.00 1398.25 1398.25
2000-02-01 04:30:00 1400.00 -1 1.25 1400.25 1399.00 1398.25
2000-02-01 05:00:00 1400.25 -1 1.00 1400.50 1399.25 1398.25
2000-02-01 05:30:00 1400.50 -1 0.75 1400.75 1399.50 1398.25
使用以下公式
trade ['MFE_pr'] = np.nan
trade ['MFE_pr'] = trade ['MFE_pr'].where(trade ['trend']<0, trade.high.cummax())
trade ['MFE_pr'] = trade ['MFE_pr'].where(trade ['trend']>0, trade.low.cummin())
有没有办法检索每行的 cummax() 所在行的时间戳？类似于 .idxmax() 但对于 cummax() ？
最佳答案
这可能就是您正在寻找的内容。
import pandas as pd
import datetime
df = pd.DataFrame({'a': [1, 2, 1, 3, 2, 5, 4, 3, 5]},
index=pd.DatetimeIndex(start=
datetime.datetime.fromtimestamp(0),
periods=9, freq='D'))
df['cummax'] = df.a.cummax()
df['timestamp'] = df.index
df = df.merge(df.groupby('cummax')[['timestamp']].first().reset_index(), on='cummax')
df.rename(columns={'timestamp_y': 'max_timestamp'}, inplace=True)
df.index=df.timestamp_x.values
del df['timestamp_x']
print(df)
a cummax max_timestamp
1970-01-01 03:00:00 1 1 1970-01-01 03:00:00
1970-01-02 03:00:00 2 2 1970-01-02 03:00:00
1970-01-03 03:00:00 1 2 1970-01-02 03:00:00
1970-01-04 03:00:00 3 3 1970-01-04 03:00:00
1970-01-05 03:00:00 2 3 1970-01-04 03:00:00
1970-01-06 03:00:00 5 5 1970-01-06 03:00:00
1970-01-07 03:00:00 4 5 1970-01-06 03:00:00
1970-01-08 03:00:00 3 5 1970-01-06 03:00:00
1970-01-09 03:00:00 5 5 1970-01-06 03:00:00
关于python pandas - 在 cummax() 处检索索引时间戳值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/40819246/