滚动标准偏差附加数据帧

Question

后不工作，我有一个大的数据帧temp_history：

Date    Temp 
2017-09-14 00:00:00 38.91588479 
2017-09-13 00:00:00 38.69563395 
2017-09-12 00:00:00 39.25504775 
2017-09-11 00:00:00 40.5487144 
2017-09-08 00:00:00 41.23372428 
2017-09-07 00:00:00 41.5960891 
2017-09-06 00:00:00 41.61939397 
... 
2016-11-30 00:00:00 37.32206175 
2016-11-29 00:00:00 36.04661564 
2016-11-28 00:00:00 35.70612757 
2016-11-25 00:00:00 35.15249571 
2016-11-23 00:00:00 36.77833439 
... 

而且我有今天的数据帧temp_today：

Date    Temp 
2017-09-15 08:59:02 62.85 

现在我附上今日数据使用历史记录

temp_history = temp_history.append(temp_today) 

这给合并数据框：

Date    Temp 
2017-09-15 08:59:02 62.85 
2017-09-14 00:00:00 38.91588479 
2017-09-13 00:00:00 38.69563395 
2017-09-12 00:00:00 39.25504775 
2017-09-11 00:00:00 40.5487144 
2017-09-08 00:00:00 41.23372428 
2017-09-07 00:00:00 41.5960891 
2017-09-06 00:00:00 41.61939397 
... 

现在，当我试图计算7天滚动STD它不工作：

temp_history['ST_std'] = temp_history['Temp'].resample('D').ffill().rolling('7D', min_periods=2).std() #rolling 3 mth std 

它计算的一切，但忽略了今天的追加值在滚动std：

Date    Temp  ST_std 
2017-09-15 13:59:02 62.85 
2017-09-14 00:00:00 38.91588479 1.163391429 
2017-09-13 00:00:00 38.69563395 1.126344307 
2017-09-12 00:00:00 39.25504775 0.83068272 
2017-09-11 00:00:00 40.5487144 0.831276056 
2017-09-08 00:00:00 41.23372428 1.086552698 
2017-09-07 00:00:00 41.5960891 0.93493231 
2017-09-06 00:00:00 41.61939397 0.897336665 

我该如何克等待滚动标准以包括今天的价值？

Answer 1

不幸的是，我没有足够的声望点来回答评论。但它可能是每一行的索引？尝试：ignore_index = true在DataFrame.append

https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.append.html