I'm facing a problem with a pandas dataframe. Actually my Dataframe contains 3 columns:
SITE_NB there are missing rows. For example:
DATE_TIME;SITE_NB; VALUE 2011-01-03 01:00; 1; 10.7 2011-01-03 04:00; 1; 3.2 2011-01-03 05:00; 1; -2.1
So here, rows for
2011-01-03 02:00 and
2011-01-03 03:00 are missing. What I want is add these rows with the same
SITE_NB (=1) and with
I want to do the same for all different
SITE_NB in my dataframe. So for each
SITE_NB, add missing rows based on
DATE_TIME with a frequency of 1 Hour, and putting
VALUE for freshly added rows.
I tried resampling but did not get the right output...
Can somebody help me to solve this issue?