Rintro.Rmd

# R

<img src="images/R_logo.png" alt="rstudio check packages" width="300"/>


## What is R ?

* Programming language and environment for **data manipulation**, **statistical computing**, and **graphical display**.

* Implementation of the S programming language

* Created at the University of Auckland, New Zealand:
	+ Initial version released in 1995
	+ Stable version released in 2000
* **Free and open source !**
	+ https://www.r-project.org/

* Interactive, flexible

* Very active community of developers and users!
	+ Many resources and forums available

## Functions & packages

### Functions

A function in R is a piece of code that takes an **input** (user data, **parameters**), processes some **calculation**, and **outputs** data.

For example: the **mean()** function would take a vector / series of numbers as an input, calculate and output their average.

Functions can take **arguments/parameters**. In the example above, the main argument to mean() would be a series of numbers given by the user.

In R code, you can recognize functions because of the parenthesis ("round brackets") following their name.


### Packages

#### What are packages?

A package in R stores, in standardized format, a set of functions, data and documentation.

They are developed and shared by the community, and vary in size and complexity.

Packages are stored in a **library**.

<img src="images/R_packages_logos.png" alt="rstudio logo" width="500"/>

[source](https://www.mitchelloharawild.com/blog/2018-07-10-hexwall_files/figure-html/final-1.png)

Packages are usually found in public **repositories** such as:

- CRAN (general repository for any type of data analysis).
- Bioconductor (initially specialized in high throughput data analysis / bioinformatics)

Anyone can create a package and stored it locally; creating packages is a great way to **share code**.


The previous function, **mean()**, is part of the **{base}** package that is available by default.

#### The "tidyverse"

*The [tidyverse](https://www.tidyverse.org/) is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.*

<img src="images/R_packages_tidyverse.png" alt="rstudio logo" width="600"/>

[source](hhttps://ajsmit.github.io/Intro_R_Official/tidy.html)

**Why do we use the tidyverse packages in this course?**

* Easier to understand / more intuitive vocabulary: better for beginners.
* More "modern" style of coding.
* Uniform in style and logic across data manipulation and visualization.

In this course, we will use in particular, and in that order:

* [{readr}](https://readr.tidyverse.org/) for importing / exporting files.
* [{ggplot2}](https://ggplot2.tidyverse.org/) for data visualization.
* [{dplyr}](https://dplyr.tidyverse.org/) for (simple) data manipulation and selection.