Coming from a Python data analysis background with SciPy, I have always been curious about R.

## Swirl

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()
```

## Lessons

Swirl comes with interactive lessons for the following R topics:

- Basic Building Blocks
- Sequences of Numbers
- Vectors
- Missing Values
- Subsetting Vectors
- Matrices and Data Frames
- Logic
- lapply and sapply
- vapply and tapply
- Looking at Data
- Simulation
- Dates and Times

You can also install the lessons described below from their GitHub repo.

## Beginner Lessons

**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

## Intermediate Lessons

**Regression Models**: The basics of regression modeling in R**Getting and Cleaning Data**: dplyr, tidyr, lubridate

## Advanced Lessons

**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: