Convert daily pandas stock data to monthly data using first trade day of the month

Question

I have a set of calculated OHLCVA daily securities data in a pandas dataframe like this:

>>> type(data_dy)


        

Answer 1

Instead of M you can pass MS as the resample rule:

df =pd.DataFrame( range(72), index = pd.date_range('1/1/2011', periods=72, freq='D'))

#df.resample('MS', how = 'mean')    # pandas <0.18
df.resample('MS').mean()  # pandas >= 0.18

Updated to use the first business day of the month respecting US Federal Holidays:

df =pd.DataFrame( range(200), index = pd.date_range('12/1/2012', periods=200, freq='D'))

from pandas.tseries.offsets import CustomBusinessMonthBegin
from pandas.tseries.holiday import USFederalHolidayCalendar
bmth_us = CustomBusinessMonthBegin(calendar=USFederalHolidayCalendar())

df.resample(bmth_us).mean()

if you want custom starts of the month using the min month found in the data try this. (It isn't pretty, but it should work).

month_index =df.index.to_period('M')

min_day_in_month_index = pd.to_datetime(df.set_index(new_index, append=True).reset_index(level=0).groupby(level=0)['level_0'].min())

custom_month_starts =CustomBusinessMonthBegin(calendar = min_day_in_month_index)

Pass custom_start_months to the fist parameter of resample