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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.

martineau
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Lisle
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  • I think you might be able adapt my [answer](https://stackoverflow.com/questions/44238581/interpolate-list-to-specific-length/44241285#44241285) to the question [Interpolate list to specific length?](https://stackoverflow.com/questions/44238581/interpolate-list-to-specific-length) – martineau Nov 19 '21 at 20:56

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