How can I use python to impute timeseries data with seasonality components?
Below is an example of how my data looks like, I am missing data for long periods that includes many cycles and not sure how to solve that.
handling missing data with seasonality in python
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mohamed elhafiz
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The library FEDOT offers a powerful solution for this. Check the notebook:
https://github.com/nccr-itmo/FEDOT/blob/master/notebooks/latest/5_ts_specific_cases.ipynb
Snapshot from the example in the notebook:
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What you can do, is to have a look at Prophet - a Facebook package for time-series analysis. It does not impute data only, but it handles missing-data.
It breaks your data up in three functions; trend, seasonality and "holidays" ("holidays" you can treat as external feature e.g holidays, or days where you have campings, pay-check etc).