问题描述
我在熊猫数据框中输入了Yahoo财经的每日股票价格.我想使用.resample()通过获取每月第一个QUOTED每日价格的价格将其转换为每月的股票价格.
I have a Yahoo finance daily stock price imported in a pandas dataframe. I want to use .resample() to convert it to the monthly stock price by taking the price of the first QUOTED daily price of each month.
.resample('MS', how='first')
返回每个月的正确价格，但它会将索引更改为该月的第一天，而通常一个月的第一天的报价可能是该月的2号或3号，因为假期和周末.
returns the correct price of each month but it changes the index to the first day of the month while in general the first day of a month for a quoted price maybe 2nd or 3rd of the month because of holidays and weekends.
如何仅通过对现有日期重新采样而不更改它们来使用resample()?
How can I use resample() by only resampling the existing dates and not changing them?
推荐答案
我认为您想要是 BMS (营业月开始):
I think what you want is BMS (business month start):
.resample('BMS').first()
注意:在熊猫0.18之前，这是使用已弃用的how kwarg完成的:
Note: Prior to pandas 0.18 this was done using the deprecated how kwarg:
.resample('BMS', how='first')
另一种方法是按月份分组，然后以普通的分组方式进行分组(例如，使用第n个以获取每个组中的第一个条目):
An alternative would be to groupby month and take the first with a plain ol' groupby (and e.g. use nth to get the first entry in each group):
.groupby(pd.Grouper(freq='M')).nth(0)
注意:在熊猫0.21之前，此操作已使用已弃用的TimeGrouper:
Note: Prior to pandas 0.21 this was done using the deprecated TimeGrouper:
.groupby(pd.TimeGrouper('M')).nth(0)
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