R 4 Data Science Quick Reference (2nd Edition)

A Pocket Guide to APIs, Libraries, and Packages

R 4 Data Science Quick Reference  (2nd Edition)
Thomas Mailund
RRP:
NZ$ 74.99
Our Price:
NZ$ 59.99
Paperback
h254 x 178mm - 240pg
11 Nov 2022 US
International import eta 7-19 days
9781484287798
Out Of Stock
Currently no stock in-store, stock is sourced to your order
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 LearnImplement applicable R 4 programming language specification featuresImport data with readrWork with categories using forcats, time and dates with lubridate, and strings with stringrFormat data using tidyr and then transform that data using magrittr and dplyrWrite functions with R for data science, data mining, and analytics-based applicationsVisualize data with ggplot2 and fit data to models using modelrWho 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.
Thomas Mailund is an associate professor at Aarhus University, Denmark. He has a background in math and computer science. For the last decade, his main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R, Functional Programming in R, and Metaprogramming in R with Apress as well as other books on R and C programming.

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