Val ts year doy interpolat region_id
2000-02-18 NaN 950832000 2000 49 NaN 19987
2000-03-05 NaN 952214400 2000 65 NaN 19987
2000-03-21 NaN 953596800 2000 81 NaN 19987
2000-04-06 0.402539365 954979200 2000 97 NaN 19987
2000-04-22 0.54021746 956361600 2000 113 NaN 19987
The above dataframe has a datetime index. I resample it like so:
df = df.resample('D')
However, this resampling results in this dataframe:
ts year doy interpolat region_id
2000-01-01 1199180160 2008 1 1 19990
2000-01-02 NaN NaN NaN NaN NaN
2000-01-03 NaN NaN NaN NaN NaN
2000-01-04 NaN NaN NaN NaN NaN
2000-01-05 NaN NaN NaN NaN NaN
Why did the 'Val' column disappear? and all the other columns seem messed up too. See Linearly interpolate missing rows in pandas dataframe for an explanation of where the dataframe is coming from.
--EDIT
Based on @unutbu's questions:
df.reset_index().to_dict('list')
{'index': [Timestamp('2000-02-18 00:00:00'), Timestamp('2000-03-05 00:00:00'), Timestamp('2000-03-21 00:00:00'), ... '0.670709965', '0.631584375', '0.562112815', '0.50740686', '0.4447712', '0.47880806', nan, nan]}
-- EDIT: The csv file for the above data frame in its entirety is here:
https://www.dropbox.com/s/dp76hk6yfs6c1og/test.csv?dl=0
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