<span>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
R Data Science Quick Reference: A Pocket Guide to APIs, Libraries, and Packages
โ Scribed by Thomas Mailund
- Publisher
- Apress
- Year
- 2019
- Tongue
- English
- Leaves
- 246
- Edition
- 1st ed.
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them.
In this book, youโll learn about the following APIs and packages that deal specifically with data science applications: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more.
After using this handy quick reference guide, 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.
What You Will Learn
- 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.
โฆ Table of Contents
Front Matter ....Pages i-ix
Introduction (Thomas Mailund)....Pages 1-3
Importing Data: readr (Thomas Mailund)....Pages 5-31
Representing Tables: tibble (Thomas Mailund)....Pages 33-43
Reformatting Tables: tidyr (Thomas Mailund)....Pages 45-69
Pipelines: magrittr (Thomas Mailund)....Pages 71-81
Functional Programming: purrr (Thomas Mailund)....Pages 83-107
Manipulating Data Frames: dplyr (Thomas Mailund)....Pages 109-160
Working with Strings: stringr (Thomas Mailund)....Pages 161-180
Working with Factors: forcats (Thomas Mailund)....Pages 181-193
Working with Dates: lubridate (Thomas Mailund)....Pages 195-203
Working with Models: broom and modelr (Thomas Mailund)....Pages 205-218
Plotting: ggplot2 (Thomas Mailund)....Pages 219-238
Conclusions (Thomas Mailund)....Pages 239-239
Back Matter ....Pages 241-246
โฆ Subjects
Computer Science; Programming Languages, Compilers, Interpreters; Programming Techniques; Big Data; Data Mining and Knowledge Discovery
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