Mejora del dataframe en Pandas

Dado un dataframe indexado por mes, me gustaría reindexar por día (muestra). Los valores que se indexaron previamente por mes ahora se deben dividir por el número de días en el mes.

tratar:

tidx_m = pd.date_range('2011-01-31', periods=2, freq='M') tidx_d = pd.date_range('2011-01-01', '2011-02-28', freq='D') d = pd.Series(100, tidx_m) d.reindex(tidx_d, fill_value=0).groupby(pd.TimeGrouper('M')).transform('mean') 

rendimientos

 2011-01-01 3.225806 2011-01-02 3.225806 2011-01-03 3.225806 2011-01-04 3.225806 2011-01-05 3.225806 2011-01-06 3.225806 2011-01-07 3.225806 2011-01-08 3.225806 2011-01-09 3.225806 2011-01-10 3.225806 2011-01-11 3.225806 2011-01-12 3.225806 2011-01-13 3.225806 2011-01-14 3.225806 2011-01-15 3.225806 2011-01-16 3.225806 2011-01-17 3.225806 2011-01-18 3.225806 2011-01-19 3.225806 2011-01-20 3.225806 2011-01-21 3.225806 2011-01-22 3.225806 2011-01-23 3.225806 2011-01-24 3.225806 2011-01-25 3.225806 2011-01-26 3.225806 2011-01-27 3.225806 2011-01-28 3.225806 2011-01-29 3.225806 2011-01-30 3.225806 2011-01-31 3.225806 2011-02-01 3.571429 2011-02-02 3.571429 2011-02-03 3.571429 2011-02-04 3.571429 2011-02-05 3.571429 2011-02-06 3.571429 2011-02-07 3.571429 2011-02-08 3.571429 2011-02-09 3.571429 2011-02-10 3.571429 2011-02-11 3.571429 2011-02-12 3.571429 2011-02-13 3.571429 2011-02-14 3.571429 2011-02-15 3.571429 2011-02-16 3.571429 2011-02-17 3.571429 2011-02-18 3.571429 2011-02-19 3.571429 2011-02-20 3.571429 2011-02-21 3.571429 2011-02-22 3.571429 2011-02-23 3.571429 2011-02-24 3.571429 2011-02-25 3.571429 2011-02-26 3.571429 2011-02-27 3.571429 2011-02-28 3.571429 Freq: D, dtype: float64