Dataframe timestamp interpolation for multiple variables
Something like

df.loc[:, ['timestamp','variable_name','values']].pivot(index='timestamp',columns='variable_name')

should do the trick
I have a dataframe with three columns: timestamp, variable_name and value. There is a total of 10 variables whose names are in the variable_name column.
I would like to have a single dataframe, indexed by timestamp, with one column per variable. Ideally, the dataframe should be "full", i.e. each timestamp should have an interpolate value for each variable.
I'm struggling to find a direct way to do that (without looping over the variable list, etc.). The dataframe comes from Spark but is small enough to be converted to Pandas. Any pointers will be most welcome.