An introduction to data cleaning with R by Edwin de Jonge and Mark van der Loo.
Summary:
Data cleaning, or data preparation is an essential part of statistical analysis. In fact, in practice it is often more time-consuming than the statistical analysis itself. These lecture notes describe a range of techniques, implemented in the R statistical environment, that allow the reader to build data cleaning scripts for data suffering from a wide range of errors and inconsistencies, in textual format. These notes cover technical as well as subject-matter related aspects of data cleaning. Technical aspects include data reading, type conversion and string matching and manipulation. Subject-matter related aspects include topics like data checking, error localization and an introduction to imputation methods in R. References to relevant literature and R packages are provided throughout.
These lecture notes are based on a tutorial given by the authors at the useR!2013 conference in Albacete, Spain.
Pure gold!
Plus this tip (among others):
Tip. To become an R master, you must practice every day.
The more data you clean, the better you will become!
Enjoy!