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:
`boxcox`

,`iboxcox`

- Data imputation (loess inter/extra-polation, random local density):
`impute`

,`impute!`

- Data normalization (z-score, min-max, softmax, sigmoid):
`normalize`

,`normalize!`

- Finite lagged difference and partial difference and its inverse:
`d`

,`p`

- Outlier detection and removal:
`outlie`

,`outlie!`

**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.