I have a pandas DataFrame looking like this :
x1 x2 x3 x4
Date Time
2017-01-03 09:00:00 0.000097 0.000259 0.000629 0.000142
09:20:00 0.000046 0.000044 0.000247 0.000134
09:40:00 0.000021 0.000032 0.000171 0.000105
10:00:00 0.000033 0.000040 0.000136 0.000178
10:20:00 0.000079 0.000157 0.000094 0.000083
.....
17:00:00 0.000032 0.000137 0.000024 0.000028
However, i want to reindex the second index, by one 20min bin and I would like it to look like this:
x1 x2 x3 x4
Date Time
2017-01-03 09:20:00 0.000097 0.000259 0.000629 0.000142
09:40:00 0.000046 0.000044 0.000247 0.000134
10:00:00 0.000021 0.000032 0.000171 0.000105
10:20:00 0.000033 0.000040 0.000136 0.000178
10:40:00 0.000079 0.000157 0.000094 0.000083
.....
17:20:00 0.000032 0.000137 0.000024 0.000028
So all the values stay the same, only the second index is renamed, everything else stays the same.
I've tried following code:
x.reindex(pd.date_range(pd.Timestamp('09:20:00'), pd.Timestamp('17:20:00'), freq="20min").time, level=1)
But it just moves the index and the values stay at the same place.
x1 x2 x3 x4
Date Time
2017-01-03 09:20:00 0.000046 0.000044 0.000247 0.000134
09:40:00 0.000021 0.000032 0.000171 0.000105
10:00:00 0.000033 0.000040 0.000136 0.000178
10:20:00 0.000079 0.000157 0.000094 0.000083
.....
17:00:00 0.000032 0.000137 0.000024 0.000028
It does not even ad the bin for 17:20:00.
However, if I also tried to shift the values after grouping them like this:
x.groupby(level=1).shift(1)
or:
x.groupby(level=1).shift(1, freq='20min')
but that did not work at all.
The fastest way I can think of is to overwrite the entire first level (innermost level) of the MultiIndex with a 20-minute-shifted version of itself:
x.index = x.index.set_levels(x.index.levels[1].shift(20, 'min'), level=1)
x = pd.DataFrame(index=pd.MultiIndex.from_product([pd.date_range('2017-01-03', '2017-01-06', freq='1D'),
pd.date_range('09:00', '17:00', freq='20min')]))
x.loc[:, 'x1'] = list(range(len(x)))
x
x1
2017-01-03 2018-06-14 09:00:00 0
2018-06-14 09:20:00 1
2018-06-14 09:40:00 2
2018-06-14 10:00:00 3
2018-06-14 10:20:00 4
... ..
2017-01-06 2018-06-14 15:40:00 95
2018-06-14 16:00:00 96
2018-06-14 16:20:00 97
2018-06-14 16:40:00 98
2018-06-14 17:00:00 99
x.index = x.index.set_levels(x.index.levels[1].shift(20, 'min'), level=1)
x
x1
2017-01-03 2018-06-14 09:20:00 0
2018-06-14 09:40:00 1
2018-06-14 10:00:00 2
2018-06-14 10:20:00 3
2018-06-14 10:40:00 4
... ..
2017-01-06 2018-06-14 16:00:00 95
2018-06-14 16:20:00 96
2018-06-14 16:40:00 97
2018-06-14 17:00:00 98
2018-06-14 17:20:00 99