Python 熊猫中数据帧的上采样

给定一个按月索引的数据帧，我想按天重新索引（向上采样）。以前按月份索引的值现在应除以该月的天数。

尝试：

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')

屈服

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

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如果groupby中还需要一列，是否也可以这样做？换言之，只有索引加上这个附加列，日期才是唯一的