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# Basic Introduction To R In this article we will cover the intro basics to R Programming Language. This article is meant for people willing to start programming in R, beginners in R who are willing to expand their already gained knowledge in R, or people willing to start their Data Science journey using R programming language. If you are familiar with other programming languages, getting to understand R programming language will be as easy as drinking water. # What is R?

Well! It is a programming language, often used in statistics and data science, but let's get a clear definition from Wikipedia R (programming language)

R is a programming language for statistical computing and graphics supported by the R Core Team and the R Foundation for Statistical Computing. Created by statisticians Ross Ihaka and Robert Gentleman, R is used among data miners, bioinformaticians and statisticians for data analysis and developing statistical software. Users have created packages to augment the functions of the R language.

According to Wikipedia: R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis.

R language provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. READ MORE>>

# How to Install and Getting Started With R

Since this article focuses on the basics of R programming language, for instruction on how to install R and R studio please Check this Edx Article

Once you have R and Rstudio installed, let's proceed to the business of the Day.

# Intro To R Basics

## Hello, World!

It's now like a rule that the first code you write when beginning to learn a programming language is a code that will display `Hello, World!` on the screen.

In order to display on the screen, R provides the `print()` function.

`print` prints its argument and returns it invisibly

In order to print `Hello, World!` in R, you need to pass the string `"Hello, World!"` in the `print()` function. the strings can be in double quotes `""` or single quotes `''`.

``````print("Hello, World!")
``````

the output will be as follows:

`````` "Hello, World!"
``````

## Creating and Naming Variables

Variables helps your program claim a piece of memory when it's running. In R, variables allow you to store a value or an object. In simple terms, a variable is a named storage space. The variables created can later on be used in your program to perform various operations.
In R, `<-`, `=` or `->` are used as the Assignment Operator to assign values to a variable name. Before creating variables, you must adhere to the rules of creating a Variable in R.

### Rules for Naming Variables in R

• Variable names MUST start with a letter, it can contain a letter, number, underscore (`_`) and period (`.`).

unlike other languages, Underscore(`_`) at the beginning of the variable name are NOT allowed in R

• Keywords CANNOT be used to name variables

• Special Character like `#`, or `&` and whitespace eg tab or space CANNOT be used in variable names

• Variable names are Case Sensitive, therefore, `my_name` is different from `my_Name`.

Below are examples of correct variable names and assignment in R

``````age <- 17
age
``````
`````` 17
``````
``````name.first = "Victor"
name.first
``````
`````` "Victor"
``````
``````17347.3847 -> weight_kgs
weight_kgs
``````
`````` 17347.38
``````

## R Arithmetic Operators

An operator is a symbol that tells the compiler to perform specific mathematical or logical manipulations. R Arithmetic Operators are symbols that tells the compiler which mathematical operation to perform. R language supports the following arithmetic operators:

Arithmetic Operator Function Description Example Output
`+` Addition adds a number to another number `3+2` ` 5`
`-` Subtraction subtracts a number from another number `3 - 2` ` 1`
`*` Multiplication multiplies number with another number `3 * 2` ` 6`
`/` Division splits a number into equal parts `3/2` ` 1.5`
`^` Exponentiation raising a number to the power of another number `3 ** 2` ` 9`
`%%` Modulo The modulo returns the remainder of the division of the number to the left by the number on its right `3 %% 2` ` 1`

Let us use R arithmetic operators to calculate my age. We will use the already gained knowledge of variables and arithmetic operations we've discussed above.

``````year_of_birth = 2001
current_year = 2020
age = current_year - year_of_birt
age
``````
`````` 19
``````

As you can see `age` is a variable that stores the computations done when subtracting `year_of_birth` from `current_year`.

R makes use of the `#` sign to add comments. Comments are added to a source code so that you and others can understand what the R code is about. Comments are not run as R code, so they will not influence your programs computation computations.

``````# My year of Birth
year_of_birth = 2001

# The Current Year
current_year = 2020

# Calculating my age by subtracting year_of_birth from the current_year
age = current_year - year_of_birth
age
``````
`````` 19
``````

## Basic Data Types in R

There are numerous data types in R programming language, we will cover the `4` basic types, that is, numerics, integers, logical and characters

Data type is the classification/categorization of data item. Everything in python is an object therefore, data types are classes and variables are the instance (object) of the data type.
Use `class(variable_name)` in order to understand to which data type a variable belongs.

To get you started with R Basic Data types, note the following:

• Decimal values are called numerics
• Natural Numbers are called Integers, Integers are also numerics
• Boolean values, eg( `FALSE` or `TRUE`) are called logical. R is case sensitive, logicals must be in UPPERCASE
• String values/text values are called characters

In the following code, we will create variables then use `class()` to check to which data type they belong.

``````my_age = 14
class(my_age)

my_weight = 90.6
class(my_weight)

my_name = "Victor" #Note how the quotation marks on the right indicate that "Victor" is a character
class(my_name)

is_teenager = TRUE
class(is_teanager)
``````
`````` "numeric"
 "numeric"
 "character"
 "logical"
``````

# More Resources

• R Introduction | R Tutorial: link
• Introduction to R Online Course | DataCamp: link 