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R 4 data science quick reference : a pocket guide to APIs, libraries, and packages / Thomas Mailund.
Mailund, Thomas, author.
2022
QA276.45.R3 M35 2022
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Title
R 4 data science quick reference : a pocket guide to APIs, libraries, and packages / Thomas Mailund.
Author
Mailund, Thomas, author.
Edition
Second edition.
ISBN
9781484287804 electronic book
1484287800 electronic book
9781484287798
1484287797
DOI
https://doi.org/10.1007/978-1-4842-8780-4
Published
New York, NY : Apress, [2022]
Language
English
Description
1 online resource (231 pages) : illustrations
Item Number
10.1007/978-1-4842-8780-4 doi
Call Number
QA276.45.R3 M35 2022
Dewey Decimal Classification
519.50285/536
Summary
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.
Note
Includes index.
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Access limited to authorized users.
Source of Description
Description based on online resource; title from digital title page (viewed on November 10, 2022).
Available in Other Form
Print version: 9781484287798
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1. Introduction. - 2. Importing Data: readr
3. Representing Tables: tibble. - 4. Tidy+select, 5. Reformatting Tables: tidyr
6. Pipelines: magrittr
7. Functional Programming: purrr. - 8. Manipulating Data Frames: dplyr. - 9. Working with Strings: stringr
10. Working with Factors: forcats. - 11. Working with Dates: lubridate. - 12. Working with Models: broom and modelr. - 13. Plotting: ggplot2
14. Conclusions.

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