STLDecompose
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jrmontag
A Python implementation of Seasonal and Trend decomposition using Loess (STL) for time series data.
Python version: 3.7.* Statsmodel version: statsmodels==0.11.0 Stldecompose version: stldecompose==0.0.5 Error: ImportError: cannot import name '_maybe_get_pandas_wrapper_freq' from 'statsmodels.tsa.filters._utils'
Dear jrmontag: Hello! I'd like to research if there are some decomposition methods which can process embedded data. These data's dimension is transfer from (length,) to (length, embedding). So STL...
It appears statsmodels has merged a PR to implement this years-old request! https://github.com/statsmodels/statsmodels/issues/4044 Since this library primarily extends the existing statsmodels internals, they will probably do this more robustly and...
> Dear Josh, > > I’m working with timeseries of water supply for a city of more than 8 millions of inhabitants. > Really you project has a high interest...
Currently, [the decompose method takes a single period value](https://github.com/jrmontag/STLDecompose/blob/2449bc068278245edf7eb630215ac4070a7d4a64/stldecompose/stl.py#L51) for the decomposition. This could be extended to accept an iterable of frequency values which are sequentially factored out of the...
It'd be nice to have some guidance for how others can best contribute to this project e.g. a dev `requirements.txt` file (twine, wheel, ?), tests to check before submitting a...
The [pandas wrapper](https://github.com/jrmontag/STLDecompose/blob/2449bc068278245edf7eb630215ac4070a7d4a64/stldecompose/stl.py#L38) in ``decompose()`` keeps track of the observation DatetimeIndex so it can be used properly in the ``forecast()`` method. There are two potential issues here: - while the...