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Web15 mrt. 2013 · You could always grab the hourly data_array and flatten it. You would generate a new DatetimeIndex with hourly freq. df = df.asfreq ('D') hourly_data = df.values [:, :] new_ind = pd.date_range (start=df.index [0], freq="H", periods=len (df) * 24) # create Series. s = pd.Series (hourly_data.flatten (), index=new_ind) I'm assuming that read_csv ... Web1,843 Followers, 1,102 Following, 402 Posts - See Instagram photos and videos from M Mas'ud Said (@mmasudsaid) M Mas'ud Said (@mmasudsaid) • Instagram photos and … flying with hip replacement
How to rearrange a python pandas dataframe? - Stack Overflow
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