R Data Science Quick Reference

作者:Thomas Mailund

年份:2019

页数:246

大小:2.2 MB

格式:PDF, ePub

语言:English

年份:2019

页数:246

大小:2.2 MB

格式:PDF, ePub

语言:English

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, you’ll 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.