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[HierarchicalForecast package](https://github.com/Nixtla/hierarchicalforecast) that mirrors [hts](https://cran.r-project.org/web/packages/hts/vignettes/hts.pdf) that is now part of fable. The same with previous comment on efficient implementations of ARIMA and ETS on the [StatsForecast package](https://github.com/Nixtla/statsforecast).
[HierarchicalForecast package](https://github.com/Nixtla/hierarchicalforecast) that mirrors [hts](https://cran.r-project.org/web/packages/hts/vignettes/hts.pdf) that is now part of fable. The same with previous comment on efficient implementations of ARIMA and ETS on the [StatsForecast package](https://github.com/Nixtla/statsforecast).
I started my career in Data Science in R, but since my first job required Python, I switched. What I miss the most is ggplot; Python plotting is not there in terms of usability. There are quite a few statistical modeling packages that you can only find in R because that's the language that the author knows. Fortunately R <> Python interoperability is getting better by the day with projects like parquet; so now it has become simpler to write pipelines that have some R scripts and some Python scripts. I like this approach a lot better than rpy.
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