#### Learn Python Interactively

Try for FreeR is a language and environment for statistical computing and graphics. It is a powerful language in the field of data science. You can perform complex data manipulations, build machine-learning models, and create stunning data visualizations with R.

Our R tutorial is designed to make your data science journey smooth. It covers everything you need to know, from the basics of R programming to advanced techniques.

### Page Index

### R Introduction

### R Flow Control

### R Functions

### R Data Structure

### R Object & Class

### R Graphs & Charts

### R Advanced Topics

## R Application

R is primarily used in the field of data science. Some areas where R is used are:

**Data Analysis**: R is a great choice for data science related tasks such as data wrangling, visualization, and analysis, thanks to its extensive libraries like dplyr, tidyr, ggplot2, Shiny, etc.**Statistical Modeling**: R provides extensible statistical and graphical techniques making it easy for researchers and statisticians.**Machine Learning**: R's growing machine learning libraries and packages help data scientists build complex models and algorithms for machine learning.

## How to Learn R?

R Programming can be useful for professionals seeking a career in data analysis, statistics, or data visualization. Here's how to get started with R:

**Learn R basics**: The first step in learning R is to be comfortable with its syntax and fundamentals.
It is important to be able to read and write R to get started with it.

**Practice coding**: After getting acquainted with the fundamentals, it is important to practice them.
Start with simple exercises and work your way up to more complex challenges.

**Build projects**: The best way to learn R is by building projects. Think of projects that interest you
and try to build them using R. Start with basic projects and move on to more advanced ones.

### Best Resources to Learn R

- Datamentor.io for a step-by-step guide to R.
- Official R documentation for reference and advanced topics.