Feat/tft static categorical

[dennisbader]

Fixes #1058, fixes #1082, addresses #1016.

Summary

• StaticCovariatesTransformer to scale/transform/encode numeric and categorical static covariates
• categorical static covariate support for TFTModel
• notebook example showing how to use static covariates
• updated Covariates.md user guide (to some extent) with static covariates.

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Codecov Report

Merging #1081 (81be526) into master (7f32ef6) will increase coverage by 0.47%.
The diff coverage is 97.27%.

@@            Coverage Diff             @@
##           master    #1081      +/-   ##
==========================================
+ Coverage   93.17%   93.64%   +0.47%     
==========================================
  Files          78       79       +1     
  Lines        7956     8124     +168     
==========================================
+ Hits         7413     7608     +195     
+ Misses        543      516      -27     

Impacted Files	Coverage Δ
darts/models/forecasting/nhits.py	98.55% <66.66%> (-0.72%)	⬇️
darts/models/forecasting/tft_submodels.py	91.03% <85.71%> (+9.30%)	⬆️
...arts/models/forecasting/torch_forecasting_model.py	89.54% <90.90%> (-0.02%)	⬇️
...sing/transformers/static_covariates_transformer.py	98.44% <98.44%> (ø)
darts/dataprocessing/transformers/__init__.py	100.00% <100.00%> (ø)
darts/models/forecasting/block_rnn_model.py	98.24% <100.00%> (+0.06%)	⬆️
darts/models/forecasting/forecasting_model.py	96.81% <100.00%> (+0.03%)	⬆️
darts/models/forecasting/nbeats.py	98.11% <100.00%> (+0.03%)	⬆️
darts/models/forecasting/rnn_model.py	97.56% <100.00%> (+0.09%)	⬆️
darts/models/forecasting/tcn_model.py	96.96% <100.00%> (+0.09%)	⬆️
... and 8 more

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[hrzn]

Super nice, well done! Only got a few minor comments.