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Real world data can present a number of challenges to data science workflows. Even properly structured data (each interesting measurement already landed in distinct columns), can present problems, such as missing values and high cardinality categorical variables. In this note we describe some great tools for working with such data. ... [...Read more...]

Nina Zumel has been polishing up new vtreat for Python documentation and tutorials. They are coming out so good that I find to be fair to the R community I must start to back-port this new documentation to vtreat for R. vtreat is a package for systematically preparing data for ... [...Read more...]

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This note is a simple data wrangling example worked using both the Python data_algebra package and the R cdata package. Both of these packages make data wrangling easy through he use of coordinatized data concepts (relying heavily on Codd’s “rule of access”). The advantages of data_algebra and ... [...Read more...]

Win Vector LLC‘s Dr. Nina Zumel has just released some new vtreat documentation. vtreat is a an all-in one step data preparation system that helps defend your machine learning algorithms from: Missing values Large cardinality categorical variables Novel levels from categorical variables I hoped she could get the Python ... [...Read more...]