Coming from a Python data analysis background with SciPy, I have always been curious about R.
I decided to check out R and found a handy R package swirl. Swirl "teaches you R programming and data science interactively, at your own pace, and right in the R console".
Installing Swirl from CRAN
The easiest way to install and run swirl is by typing the following commands in the R console:
install.packages("swirl") library(swirl) swirl()
Swirl comes with interactive lessons for the following R topics:
- Basic Building Blocks
- Sequences of Numbers
- Missing Values
- Subsetting Vectors
- Matrices and Data Frames
- lapply and sapply
- vapply and tapply
- Looking at Data
- Dates and Times
You can also install the lessons described below from their GitHub repo.
- R Programming: The basics of programming in R
- Data Analysis: Basic ideas in statistics and data visualization
- Mathematical Biostatistics Boot Camp: One- and two-sample t-tests, power, and sample size
- Open Intro: A very basic introduction to statistics, data analysis, and data visualization
- Regression Models: The basics of regression modeling in R
- Getting and Cleaning Data: dplyr, tidyr, lubridate
- Statistical Inference: Introduces the student to basic concepts of statistical inference including probability, hypothesis testing, confidence intervals and p-values. It concludes with an initiation to topics of particular relevance to big data, issues of multiple testing and resampling.
Installing Additional Lessons
library(swirl) install_from_swirl("Course Name Here") swirl()
Swirl in R Studio
Below is an output of the "Dates and Times" lesson: