README.md

In sachserf/badval: Reproducible data manipulation

Bad Values

This R-package offers functions to facilitate the handling of bad values.

Introducing the bad value concept

• I choose the term "bad values" for cells in a data frame that should be used under reserve or even removed from the data.
• The bad value concept should enhance the traceability: Instead of simply removing those values after detection they can be marked for later removal.
• Therefore it is straightforward to keep the whole data frame 'as-is' while removing the "bad values" only when needed.

Step-by-step explanation

1. Add a column for indices of bad values to your data frame (e.g. mydata$BADVAL <- NA)

2. Use the following function to add bad value indices to your badval_column. Check output and update the column of your dataframe.

badval_add_index()

1. Clean the bad values of your data. It is possible to clean all bad values at once or specify a pattern or an exact string for specific column names:

badval_rm_data()

1. Remove the bad values from the badval_column if you do not need them anymore:

badval_rm_index()

Further Reading

For a more in depth Introduction read the vignette (either via the package or see: https://sachserf.github.io/vignettes.html)

sachserf/badval documentation built on May 29, 2019, 12:21 p.m.