Category Archives: data cleaning

stringdist 0.9.5.1: now with C API

Version 0.9.5.1 of stringdist is on CRAN. The main new feature, with a huge thanks to our awesome new contributor Chris Muir, is that we made it easy to call stringdist functionality from your package's C or C++ code. The … Continue reading

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Track changes in data with the lumberjack %>>%

So you are using this pipeline to have data treated by different functions in R. For example, you may be imputing some missing values using the simputation package. Let us first load the only realistic dataset in R > data(retailers, … Continue reading

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Announcing the simputation package: make imputation simple

I am happy to announce that my simputation package has appeared on CRAN this weekend. This package aims to simplify missing value imputation. In particular it offers standardized interfaces that make it easy to define both imputation method and imputation … Continue reading

Posted in data cleaning, data correction methods, imputation, programming, R | 5 Comments

validate version 0.1.5 is out

A new version of the validate package for data validation was just accepted on CRAN and will be available on all mirrors in a few days. The most important addition is that you can now reference the data set as … Continue reading

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Easy data validation with the validate package

The validate package is our attempt to make checking data against domain knowledge as easy as possible. Here is an example. library(magrittr) library(validate) iris %>% check_that( Sepal.Width > 0.5 * Sepal.Length , mean(Sepal.Width) > 0 , if ( Sepal.Width > … Continue reading

Posted in data cleaning, programming, R | 11 Comments