DataWrangler.lj has been created in the process of decoupling functionality from Forecast.jl . The package contains a collection of basic tools to prepare data for analytics and specially so for time series analysis and regressions.
Next follows a list of the available tools to wrangle data:
- Box-Cox and inverse Box-Cox transformation and estimation:
- Data imputation (loess inter/extra-polation, random local density):
- Data normalization (z-score, min-max, softmax, sigmoid):
- Finite lagged difference and partial difference and its inverse:
- Outlier detection and removal:
Note: Although there are still a couple of packages to be finished before the decoupling is completed, this announcement will most likely be the last one before all the decoupled packages are fully integrated in
Forecast.jl v.0.2.0. This integration might take a while but I believe the packages decoupled so far are useful in their own, hence the announcements.