https://www.sthda.com (C) 2005-2026 PHPBoost en PHPBoost https://www.sthda.com/english/web/7-ebook/36-an-introduction-to-statistical-and-data-sciences-via-r/ https://www.sthda.com/english/web/7-ebook/36-an-introduction-to-statistical-and-data-sciences-via-r/
This book will help you develop your “data science toolbox”, including tools such as data visualization, data formatting, data wrangling, and data modeling using regression.]]> Sat, 05 Aug 2017 10:53:00 +0200 https://www.sthda.com/english/web/7-ebook/26-plotly-for-r-book/ https://www.sthda.com/english/web/7-ebook/26-plotly-for-r-book/
The R package already has numerous examples and documentation on https://plot.ly/r and https://plot.ly/ggplot2, but this website provides more of a cohesive narrative to help explain fundamental concepts and recent developments.

By reading from start to finish, readers new to R and plotly should be able to get up and running fairly quickly.

That being said, advanced R and plotly users should still find the majority of this material useful and informative.]]> Wed, 02 Aug 2017 16:19:00 +0200 https://www.sthda.com/english/web/7-ebook/23-blogdown-creating-websites-with-r-markdown/ https://www.sthda.com/english/web/7-ebook/23-blogdown-creating-websites-with-r-markdown/ blogdown R package to create websites using R Markdown and Hugo. There are two major highlights of blogdown:

1) It produces a static website, meaning the website only consists of static files such as HTML, CSS, JavaScript, and images, etc. You can host the website on any web servers. The website does not require server-side scripts such as PHP or databases like WordPress does.

2) The website is generated from R Markdown documents. This brings a huge amount of benefits, especially if your website is related to data analysis or (R) programming. Being able to use Markdown implies simplicity and more importantly, portability (e.g., you are giving yourself the chance to convert your blog posts to PDF and publish to journals or even books in the future).

R Markdown gives you the benefits of dynamic documents — all your results, such as tables, graphics, and inline values, can be computed and rendered dynamically from R code, hence the results you present on your website are more likely to be reproducible.

Author: Yihui Xie, Amber Thomas, Alison Presmanes Hill]]> Tue, 01 Aug 2017 21:08:00 +0200 https://www.sthda.com/english/web/7-ebook/22-bookdown-create-books-and-technical-documents-with-r-markdown/ https://www.sthda.com/english/web/7-ebook/22-bookdown-create-books-and-technical-documents-with-r-markdown/ bookdown, to change your workflow of writing books.

With bookdown,

- It should be technically easy to write a book,

- visually pleasant to view the book,

- fun to interact with the book,

- convenient to navigate through the book,

- straightforward for readers to contribute or leave feedback to the book author(s),

- and more importantly, authors should not always be distracted by typesetting details.


Despite the package name containing the word “book”, bookdown is not only for books.

The “book” can be anything that consists of multiple R Markdown documents meant to be read in a linear sequence, such as course handouts, study notes, a software manual, a thesis, or even a diary.

Author: Yihui Xie]]> Tue, 01 Aug 2017 21:01:00 +0200 https://www.sthda.com/english/web/7-ebook/21-r-packages/ https://www.sthda.com/english/web/7-ebook/21-r-packages/
Contents:

1. Getting started
- Introduction
- Package structure

2. Package components
- Code (R/)
- Package metadata (DESCRIPTION)
- Object documentation (man/)
- Vignettes (vignettes/)
- Testing (tests/)
- Namespaces (NAMESPACE)
- Data (data/)
- Compiled code (src/)
- Installed files (inst/)
- Other components

3. Best practices
- Git and GitHub
- Checking
- Release]]> Tue, 01 Aug 2017 17:43:00 +0200 https://www.sthda.com/english/web/7-ebook/20-r-for-data-science/ https://www.sthda.com/english/web/7-ebook/20-r-for-data-science/
Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R.

You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time.

You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.

Author: Garrett Grolemund & Hadley Wickham]]> Tue, 01 Aug 2017 17:38:00 +0200 https://www.sthda.com/english/web/7-ebook/19-advanced-r/ https://www.sthda.com/english/web/7-ebook/19-advanced-r/
What you will get out of this book:

After reading this book, you will:

1) Be familiar with the fundamentals of R. You will understand complex data types and the best ways to perform operations on them. You will have a deep understanding of how functions work, and be able to recognise and use the four object systems in R.

2) Understand what functional programming means, and why it is a useful tool for data analysis.

3) You’ll be able to create functions that use non-standard evaluation in a principled way, saving typing and creating elegant code to express important operations.

4) Have a good intuition for which operations in R are slow or use a lot of memory. You’ll know how to use profiling to pinpoint performance bottlenecks, and you’ll know enough C++ to convert slow R functions to fast C++ equivalents.

5) Be comfortable reading and understanding the majority of R code.

Author: Hadley Wickham]]> Tue, 01 Aug 2017 17:27:00 +0200