In this handy quick reference book you'll be introduced to several R data science packages
with examples of how to use each of them. All concepts will be covered concisely with many
illustrative examples using the following APIs: readr dibble forecasts lubridate stringr
tidyr magnittr dplyr purrr ggplot2 modelr and more. With R 4 Data Science Quick Reference
you'll have the code APIs and insights to write data science-based applications in the R
programming language. You'll also be able to carry out data analysis. All source code used in
the book is freely available on GitHub.. What You'll Learn Implement applicable R 4 programming
language specification features Import data with readr Work with categories using forcats time
and dates with lubridate and strings with stringr Format data using tidyr and then transform
that data using magrittr and dplyr Write functions with R for data science data mining and
analytics-based applications Visualize data with ggplot2 and fit data to models using modelr
Who This Book Is For Programmers new to R's data science data mining and analytics packages.
Some prior coding experience with R in general is recommended.
