Gain insights into R, the leading language for data analysis. Learn about its basics, advanced concepts, and practical coding to drive valuable insights from large datasets.

The digital world we live in has given companies and people access to staggering amounts of data, and anyone that can make use of that to drive valuable insights stands to benefit. The ability to work with large amounts of data is becoming a standard requirement for countless jobs across multiple industries.

Enter R, probably the most well-known language for data analysis. It's been used for years due to its robust statistical functionality, outstanding graphing ability, and extensibility through packages.

This interactive course will get you up to speed and assumes no prior knowledge of R. You'll start with the very basics and work your way up to advanced concepts like exception handling. By the time you're done, you'll be able to write detailed, useful code in R yourself.

Learn R from Scratch

## Packages in R language

Learning to program in **R** is important if you’re serious about understanding data. In this course, we have mentioned the basics to get you started with **R** language but rest assured there is much much more to learn. 

However, the major ease that R language provides to programmers is the vast number of packages that can be imported in our programs. Many programmers and statisticians use R to design tools. These tools are then freely available as open source to the community. We can download these, import them as **packages** and easily use in our code.

> Packages are pre-assembled collections of functions and objects.  

We can import packages using the simple method:
```
install.packages("<nameOfPackage>")
```

### Loading a package
Once you have installed a package, we can load it in our program using the `library()` function.

```r
library(<package name>)
# Notice that we do not need the quotation marks now
```
Now you can simply use all the functions and objects of the respective package in our R program.

---

We have come to the end of this course. We have covered all the introductory concepts to get you started in programming with R. Remember, practice makes perfect. So keep practicing the concepts we have learned in this course. Keep learning and have fun with it.

# Packages in R language

Learning to program in **R** is important if you’re serious about understanding data. In this course, we have mentioned the basics to get you started with **R** language but rest assured there is much much more to learn. 

However, the major ease that R language provides to programmers is the vast number of packages that can be imported in our programs. Many programmers and statisticians use R to design tools. These tools are then freely available as open source to the community. We can download these, import them as **packages** and easily use in our code.

> Packages are pre-assembled collections of functions and objects.  

We can import packages using the simple method:
```
install.packages("<nameOfPackage>")
```

## Loading a package
Once you have installed a package, we can load it in our program using the `library()` function.

```r
library(<package name>)
# Notice that we do not need the quotation marks now
```
Now you can simply use all the functions and objects of the respective package in our R program.

---

We have come to the end of this course. We have covered all the introductory concepts to get you started in programming with R. Remember, practice makes perfect. So keep practicing the concepts we have learned in this course. Keep learning and have fun with it.

In this lesson, we briefly touch upon installing packages in R language.

Getting Started

Variables

Exploring R Objects

R Operators and Notation

Conditional Statements

Loops

Functions

Input/Output

Exception Handling

Classes

Fun Challenges

Conclusion

More on R Language

Packages in R language

Loading a package