熊猫Groupby Month从两个工作日开始

Question

I have a DataFrame that is indexed by date and has daily data.

As described I wish to group and aggregate this data by calendar month start minus 2 business days. My idea is to use groupby and MonthBegin with a 2 days BDay offset to this.

When I try run the code

import pandas as pd
import pandas.tseries.offsets as of
days = of.MonthBegin() - of.BDay(2)
g = df.groupby(pd.Grouper(freq=days, level='Date')).sum()

I get an error

TypeError: Argument 'other' has incorrect type (expected datetime.datetime, got BusinessDay)

Perhaps I need to use the rollback method on MonthBegin but when I try

days = of.MonthBegin()
days.rollback(of.BDay(2))
g_df = df.groupby(pd.Grouper(freq=days, level='Date')).sum()

TypeError: Cannot convert input [<2 * BusinessDays>] of type to Timestamp

Does anyone have any ideas how to correctly use the offsets to groupby MonthBegin - 2BDay ?

Answer 1

It is hard to tell, what you want to achieve without any data of yours, but here is how you could do it:

df = pd.DataFrame({"dates": ["2018-01-02", "2018-01-03", "2018-02-02", "2018-01-04"],
                "vals": [10, 20, 10, 5]})

df.groupby((pd.to_datetime(df.dates) - of.MonthBegin() - of.BDay(2)).dt.month).vals.sum()

Output:

dates
1    10
12   35
Name: vals, dtype: int64