I have a large dataset of hourly electric consumption data, which is highly correlated to temperature data (especially during the summer months). I want to find a fairly simple interpolation method that can build upon the relationship between consumption and temperature. I have a large set of "perfect" data points with no missing data. When I am missing data, I may miss an hour of data here and there, other times I'm missing days worth of data in a row.
I would prefer to interpolate the missing components for an entire series (annual) at once. However, I have flexibility and could perform at monthly levels.
Looking for reliable methods that are fairly easy to implement in Python.