我的數據框如下所示： timestamp2020-03-01 01:11:42.520 -674.02020-03-01 02:00:48.778 -700.02020-03-01 02:00:58.850 -702.02020-03-01 11:45:23.741 -1249.02020-03-02 01:56:51.021 -1229.02020-03-02 01:56:51.021 -917.02020-03-02 01:56:51.021 -837.0我嘗試做的是以下內容：cum = (orders[['cum']] .resample('1S') .bfill() .fillna('ffill') )但是后來我收到標題錯誤消息，知道這意味著什么嗎？謝謝您的幫助！
1 回答
大話西游666
TA貢獻1817條經驗 獲得超14個贊
一個想法是首先過濾重復的索引值以進行重新采樣，就像您的解決方案一樣，然后過濾重復到added系列，按樓層更改索引并通過排序添加到原始索引值：
print (orders)
cum
timestamp
2020-03-01 01:11:42.520 -674.0
2020-03-01 02:00:48.778 -700.0
2020-03-01 02:00:58.850 -702.0
2020-03-01 11:45:23.741 -1249.0
2020-03-02 01:56:51.021 -1229.0
2020-03-02 01:56:51.021 -917.0
2020-03-02 01:56:51.021 -837.0
2020-03-02 01:56:54.021 -67.0
mask = orders.index.duplicated()
cum = (orders.loc[~mask, 'cum']
.resample('1S')
.bfill()
.ffill()
)
added = orders.loc[mask, 'cum']
added.index = added.index.floor('S')
cum = added.append(cum).sort_index()
print (cum.tail(10))
timestamp
2020-03-02 01:56:47 -1229.0
2020-03-02 01:56:48 -1229.0
2020-03-02 01:56:49 -1229.0
2020-03-02 01:56:50 -1229.0
2020-03-02 01:56:51 -1229.0
2020-03-02 01:56:51 -917.0
2020-03-02 01:56:51 -837.0
2020-03-02 01:56:52 -67.0
2020-03-02 01:56:53 -67.0
2020-03-02 01:56:54 -67.0
Name: cum, dtype: float64
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