A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R
Ulrike Grömping · Journal of Statistical Software · 2018
A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R" covers topics that have always been very important and time-consuming prerequisites of statistical data analysis, even before the term "Data Science" was coined.In the following, I will use "data handling" as a shorthand expression for the book's topics.The book's cover rightly states both tediousness and importance of data handling, as well as a lack of systematic education on the topic for many modelers; it promises no less than the "only how-to guide offering a unified, systematic approach to acquiring, cleaning, and managing data in R".I decided to review this book, because I currently prepare a lecture in which I, for the first time, want to teach efficient techniques for data handling -so far, my focus in teaching has been on R for statistical analysis, taking the usual nice and pre-cleaned data sets for examples, and I am one of those people who lack systematic training on data handling.