Skip to content

Latest commit

 

History

History
269 lines (170 loc) · 4.56 KB

first_steps.md

File metadata and controls

269 lines (170 loc) · 4.56 KB
Raw

Getting started

Najko Jahn
3. October 2015

Attribution: Adapted from the Data Carpentry R intro material

Expected outcome

  • R installation running
  • participants are familiar with RStudio
  • Installing packages
  • Passing vectors to functions

Installing R

R is available for Linux, Mac and Windows users. Many Linux distributions already have R installed.

  1. Download R from the R Archive Network CRAN:

https://cran.r-project.org/

2 . Download RStudio:

https://www.rstudio.com/products/rstudio/download/

RStudio is a powerful Integrated Development Environment (IDE) for the R language. It helps you to write, store and share your coding activities. RStudio also provide syntax highlighting and code completion.

RStudio overview

  • Interactively run commands in the console
  • Source code editor
  • Workspace Environment
  • File Browser
  • Integrated help

TASK 1 Create a working directory alm_hack

Packages

R comes with more than 20 essential packages. However, for many task, you will find it useful to check, if someone already has contributed her solution as a package to the R community. R packages are available through CRAN.

https://cran.r-project.org/web/packages/available_packages_by_name.html

Packages can be installed with ìnstall.packages().

Example, installing devtoolspackage from the RStudio mirror.

install.packages("devtools",  repos="http://cran.rstudio.com/")

To load a package, type:

library(devtools)
## Warning: package 'devtools' was built under R version 3.2.2

Please note, packages need to be loaded with every new session.

To get familiar with what a package offers, please read the vignettes and documentation.

Sometimes, packages are only available on GitHub. The devtools package makes it possible to install from GitHub. For instance, we want to use the rOpenSci client for the ORCID API.

devtools::install_github("ropensci/rorcid")
library(rorcid)

TASK 2: Choose one package from the rOpenSci initative: https://ropensci.org/packages/. Download the package from CRAN or, if it is not available on CRAN, from GitHub.

R language essentials

R as a calculator

(1 + 3) ^ 2
## [1] 16

sqrt(64)
## [1] 8

log(2)
## [1] 0.6931472

Vectors

Numeric

my_data <- c(1, 3, 5, 9)
my_data
## [1] 1 3 5 9

sum(my_data)
## [1] 18

mean(my_data)
## [1] 4.5

Generate 100 uniform random numbers between 1 and 5.

my_sample <- runif(100, 1, 5)

Character

my_friends <- c("John", "Martin", "Sue", "Linda")
your_friends <- c("John", "Rita", "Paul", "Sue")

Get the third element in my_friends

my_friends[3]
## [1] "Sue"

Exclude the first element

my_friends[-1]
## [1] "Martin" "Sue"    "Linda"

Passing vectors to functions

How many elements are in a vector?

length(your_friends)
## [1] 4

R offers a wide range of mathematical functions. For instance, if you want to calculate the intersection between my_friends and your_friends try ìntersect.

intersect(my_friends, your_friends)
## [1] "John" "Sue"

To calculate the square root of each element in my_data

sqrt(my_data)
## [1] 1.000000 1.732051 2.236068 3.000000

What type is the vector?

class(your_friends)
## [1] "character"

class(my_data)
## [1] "numeric"

Check, if vector is of type character

is.character(my_friends)
## [1] TRUE

is.character(my_data)
## [1] FALSE

We just saw 3 of the 6 data types that R uses: "character" "numeric" and "logical" for TRUE and FALSE (the Boolean data type). The other 3 are:

  • "integer" for integer numbers (e.g., 2L, the L indicates to R that it's an integer)
  • "complex" to represent complex numbers with real and imaginary parts (e.g., 1+4i) and that's all we're going to say about them
  • "raw" that we won't discuss further

Vectors are one of the many data structures that R uses. Other important ones are lists (list), matrices (matrix), data frames (data.frame) and factors (factor).

In this course, we will only work with data.frame.

**Task 3: Create two vectors: One of type character and one of type numeric. Get the number of elements for each vector. **

Task 4: Assign 500 uniform random numbers on the interval [-2, 9] to a vector a and calculate the mean value