Books [Thomas Mailund] R Data Science Quick Reference

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DESCRIPTION:

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.

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