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* 27
R TUTORIAL – BE A DATA SCIENCE ROCK STAR WITH R
We offer you a brighter future with FREE online courses - Start Now!!
Today, we are starting a tour of the R programming language in which we will
explore its different and essential concepts. This R DataFlair Tutorial Series
is designed to help beginners to get started with R and experienced to brush up
their R programming skills and gain perfection in the language.
R is one of the most widely used programming languages for statistical modeling.
It has become the lingua franca of Data Science. In this article, we will
provide you with the introduction to R programming language, its examples and we
will also see how R is transforming the Data Science industry. We will also go
through the various editors, environments through which you can run the R code.
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Let’s quickly begin the R tutorial.
WHAT IS R PROGRAMMING LANGUAGE?
R is an open-source programming language that facilitates statistical computing
and graphical libraries. Being open-source, R enjoys community support of avid
developers who work on releasing new packages, updating R and making it a
steadfast programming package for Data Science.
* With the help of R, one can perform various statistical operations.
* You can obtain it for free from the website www.r-project.org.
* It is driven by command lines.
* Each command is executed when the user enters them into the prompt.
Since R is open-source, most of its routines and procedures have been developed
by programmers all over the world. All the packages are available for free at
the R project website called CRAN. It contains over 10,000 packages in R. The
basic installation comprises of a set of tools that various data scientists and
statisticians use for multiple tasks.
CLOSE
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In R, there is a comprehensive environment that facilitates the performance of
statistical operations as well as the generation of data analysis in graphical
or text format. The commands that a console takes in as input are assessed and
subsequently executed. R is incapable of handling auto-formatting characters
such as dashes or quotes, hence, you need to be discreet while copy-pasting
commands from external sources into your R environment.
Do you know – How to Install Packages in R programming
HISTORY OF R
R was conceived at the Bell Laboratories by John Chambers in 1976. R was
developed as an extension as well as an implementation of S programming
language.
The R project was developed by Ross Ihaka and Robert Gentleman and released in
1992, its first version in 1995 and a stable beta version in the year 2000.
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After seeing the history in this R tutorial, now, let’s move on to the reasons
for learning R programming.
WHY LEARN R PROGRAMMING LANGUAGE
* With R, you can perform statistical analysis, data analysis as well as
machine learning. We can create objects, functions and packages in it. R is
platform-independent and can be used across multiple operating systems. R is
free owing to its open-source GNU licensing and can be installed by anyone.
* R consists of a robust and aesthetic collection of graphical libraries
like ggplot2, plotly and many more. With these libraries, you can make
visually appealing and elegant visualisations.
* R is most widely used by the various industries. Only the academic avenues in
the past made use of R but industries are now using R as their primary tool
for statistical modeling. The most profound industry that makes use of R is
the Data Science industry and the several underlying industries that it
comprises of. industries like health, finance, banking, manufacturing and
many more.
* There are about 2 million job openings for R programmers worldwide. Companies
hire R programmers for many roles like data analysts, business analysts, data
visualization experts, and business intelligence experts.
Discover other essential reasons to learn R Programming
FEATURES OF R PROGRAMMING
Now it’s time to discuss the features of R Programming:
* R is a comprehensive programming language that provides support for
procedural programming involving functions as well as object-oriented
programming with generic functions.
* There are more than 10,000 packages in the repository of R programming. With
these packages, one can make use of functions to facilitate easier
programming.
* Being an interpreter based language, R produces a machine-independent code
that is portable in nature. Furthermore, it facilitates easy debugging of
errors in the code.
* R facilitates complex operations with vectors, arrays, data frames as well as
other data objects that have varying sizes.
* R can be easily integrated with many other technologies and frameworks like
Hadoop and HDFS. It can also integrate with other programming languages like
C, C++, Python, Java, FORTRAN, and JavaScript.
* R provides robust facilities for data handling and storage.
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* As discussed in the above section, R has extensive community support that
provides technical assistance, seminars and several boot camps to get you
started with R.
* R is cross-platform compatible. R packages can be installed and used on any
OS in any software environment without any changes.
HOW R IS BETTER THAN OTHER TECHNOLOGIES
There are certain unique aspects of R programming which makes it better in
comparison with other technologies:
* Graphical Libraries – R stays ahead of the curve through its aesthetic
graphical libraries. Libraries like ggplot2, plotly facilitate appealing
libraries for making well-defined plots.
* Availability / Cost – R is completely free to use which means widespread
availability.
* Advancement in Tool – R supports various advanced tools and features that
allow you to build robust statistical models.
* Job Scenario – As stated above, R is the primary tool for Data Science. With
the immense growth in Data Science and rise in demand, R has become the most
in-demand programming language of the world today.
* Customer Service Support and Community – With R, you can enjoy strong
community support.
* Portability – R is highly portable. Many different programming languages and
software frameworks can easily combine with the R environment for the best
results.
You must definitely check the R vs Python for Data Science
R SCRIPTS
R is the primary statistical programming language for performing modeling and
graphical tasks. With its extensive support for performing matrix computation, R
is used for a variety of tasks that involve complex datasets.
There is the entropy of freedom for carrying out the selection of editing tools
to perform an interaction with the native console. In order to perform scripting
in R, you can simply import packages and then use the provided functions to
achieve results with minimal lines of code.
There are several editors and IDEs that facilitate GUI features for executing R
scripts. Some of the useful editors that support the R programming language are:
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* RGui (R Graphical User Interface)
* Rstudio – It is a comprehensive environment for R scripting and has more
features than Rstudio.
1. R GRAPHICAL USER INTERFACE (R GUI)
R GUI is the standard GUI platform for working in R. The R Console Window forms
an essential part of the R GUI. In this window, we input various instructions,
scripts and several other important operations. This console window has several
tools embedded in it to facilitate ease of operations. This console appears
whenever we access the R GUI.
In the main panel of R GUI, go to the ‘File‘ menu and select the ‘New Script‘
option. This will create a new script in R.
In order to quit the active R session, you can type the following code after the
R prompt ‘>’ as follows:
Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
> q()
> q()
> q()
2. RSTUDIO
RStudio is an integrated and comprehensive Integrated Development Environment
for R. It facilitates extensive code editing, development as well as various
features that make R an easy language to implement.
Before proceeding ahead in R tutorial, please confirm, have you checked –
Importing Data in RStudio
Features of RStudio
* RStudio provides various tools and features that allow you to boost your code
productivity.
* It can also be accessed over the web and is cross-platform in nature.
* It facilitates automatic checking of updates so that you don’t have to check
for them manually.
* It provides support for recovery in case of file loss.
* With RStudio, you can manage the data more efficiently.
Components of RStudio
* Source – In the top left corner of the screen is the text editor that allows
you to work within source scripting. You can enter multiple lines in this
source. Furthermore, users can save the R scripts to files that are stored in
local memory.
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* Console – This is present on the bottom left corner of the main window of R
Studio. It facilitates interactive scripting in R.
* Workspace and History – In the top right corner, you will find the R
workspace and the history window. This will give you the list of all the
variables that were created in the environment session. Furthermore, you can
also view the list of past commands that were executed by R.
Files, Plots, Package, and Help at the bottom right corner gives access to the
following tools:
* Files – A user can browse the various files and folders on a computer.
* Plots – We obtain the user plots here.
* Packages – Here, we can view the list of all the installed packages.
* Help – We can browse the built-in help system of R with this command.
SCRIPTING IN R
Let’s start scripting in R.
We will create a script to print “Hello world!” in R. To create scripts in R,
you need to perform the following steps:
Here in R, you will have to enclose some commands in print() to get the same
output as on the command line. So you need to type below command: This takes
“Hello World” as input in R.
Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
print("Hello World") #Author DataFlair
print("Hello World") #Author DataFlair
print("Hello World") #Author DataFlair
SOURCING A SCRIPT IN R
While R console provides an interactive method to perform R programming, R
Studio also provides various features to develop a script in the external
editors and source the script into the console. You can source either selected
lines or the entire code using R GUI and R Studio.
An advantage of writing into the R editor is that multiple lines can be written
at once without prompting R to evaluate them individually. You can source the
script in the following ways:
In order to execute a selected line of code:
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Select the line(s) of code, then press Ctrl + R in R GUI and Ctrl + Enter in
RStudio. For example, we have two lines of code as follows:
Plain text
Copy to clipboard
Open code in new window
EnlighterJS 3 Syntax Highlighter
print("Hello")
print("DataFlair")
print("Hello") print("DataFlair")
print("Hello")
print("DataFlair")
In the above code, if you only want to print “Hello”, then select only the first
line and press Ctrl + Enter in RStudio.
In order to execute the entire script:
In R GUI,
* Go to Edit, and then click Run All.
In the case of R Studio,
* Hold and press Ctrl+Shift+ Enter.
COMPANIES USING R
Some of the companies that are using R programming are as follows:
* Facebook
* Google
* Linkedin
* IBM
* Twitter
* Uber
* Airbnb
* Ford Motor company
* Microsoft
APPLICATIONS OF R PROGRAMMING
* R is used in finance and banking sectors for detecting fraud, reducing
customer churn rate and for making future decisions.
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* R is also used by bioinformatics to analyse strands of genetic sequences, for
performing drug discovery and also in computational neuroscience.
* R is used in social media analysis to discover potential customers in online
advertising. Companies also use social media information to analyse customer
sentiments for making their products better.
* E-Commerce companies make use of R to analyse the purchases made by the
customers as well as their feedbacks.
* Manufacturing companies use R to analyze customer feedback. They also use it
to predict future demand to adjust their manufacturing speeds and maximize
profits.
After completing the R tutorial, get to know about the Different Applications of
R Programming in detail
SUMMARY
In the above article of R tutorial, we discussed about the R programming and its
basic information. R has become a standard name in the world of programming. It
is the most used tool in Data Science and many users are opting R due to its
useful advantages and features. Its open-source nature makes R a much better
choice for many Data Scientists.
Any queries or feedback related to the R tutorial? Share your views in the
comment second. Our experts at DataFlair will be happy to help you.
Did you like this article? If Yes, please give DataFlair 5 Stars on Google
Tags: introduction to rR featuresR tutorialWhat is RWhy learn r
27 RESPONSES
* Comments27
* Pingbacks0
1. Sam says:
March 23, 2017 at 4:14 pm
I constantly spent my half an hour to read this web site’s posts daily.
This is an awesum article on introduction to R programming language.
Reply
* Data Flair says:
August 18, 2018 at 7:00 am
Sam, you are just fabulous. Thank you for visiting Data Flair and
spending time on it. There are more such articles on R Programming
Language, you can check them on our site.
Your review of R Programming Language is so motivating for us.
Keep visiting Data Flair
Reply
2. birhanu says:
August 3, 2017 at 8:03 am
martix operations with its formation
Reply
3. Shahriar Islam says:
March 5, 2018 at 11:20 am
I am interested about R but don’t know how can I start?
Reply
* Nivi.V says:
July 3, 2018 at 7:15 am
i like to study rprogramming,but i dono where to study.seeking for a good
website
Reply
* Data Flair says:
August 18, 2018 at 7:26 am
Hii Nivi,
Hope our article on R Programming Language helped you to clear some of
your concepts on R. As I explained to Shahriar, you can also check our
website for more R learning. There is much more to learn about R and we
have shared that learning material with everyone. You can start your R
learning with this link
https://data-flair.training/blogs/r-data-import-tutorial/
Share your experience of reading the blog with us. So that, we can
offer you more on R.
Thank you for visiting Data Flair
Reply
* Data Flair says:
August 18, 2018 at 7:12 am
Hii Shahriar,
Thank you, for asking the query about R.
You can start your journey of R Programming Language with us. We have
published the complete tutorial for R Programming Language on our
website. Go through all the published blogs and follow all the given
links to get the better understanding of R.
Still, while learning R if you feel any hurdle, you can freely ask the
query with us. We will definitely help you.
Reply
4. Veeresh Rampur says:
July 18, 2018 at 2:06 am
Very lucid explanation. The beneficial part is R is open source, licence
free software. Its platform free. Very informative.
Reply
* Data Flair says:
August 18, 2018 at 7:20 am
Hello Veeresh,
Thank you for sharing the additional information of R Programming with
everyone. If you want to know more about R, then we have many informative
articles for you.
You can start with this link
https://data-flair.training/blogs/r-programming-functions/
Reply
5. Emma kalondu says:
August 27, 2018 at 4:48 pm
Great work
Reply
* Data Flair says:
August 29, 2018 at 11:44 am
Hello Emma,
Very glad to see your review on R programming. Our readers feedback
always motivate us to publish more blogs. If you want to learn any other
topic in R, you can freely tell us.
Keep visiting Data Flair.
Reply
6. Suraj says:
January 18, 2019 at 2:06 am
Thanks for providing all these details in a compact form. This is the best
R tutorial for beginners
Reply
* DataFlair Team says:
January 19, 2019 at 11:22 am
Hi Suraj,
We are enthralled that you liked our R programming Tutorial. Nice
feedback from our loyal readers like this always motivates us to work
harder, so that we can provide you with more great stuff.
Keep connected with us for more R tutorials.
Reply
7. Srinu says:
June 6, 2019 at 10:01 am
Hi DataFlair Team,
This is one of the best R programming tutorial. I have gone through all the
topic and practiced more.
can you please suggest where can i get real time scenario using R.
Reply
* DataFlair Team says:
June 7, 2019 at 6:22 pm
Hello Srinu,
Thanks for connecting DataFlair. R is a beautiful language and highly
used in Data Science. You can learn R easily, just refer our sidebar and
complete all the R tutorials from top to bottom.
Hope, it helps!
Reply
8. Mike030386 says:
July 27, 2019 at 6:13 pm
I find this tutorial very informative. I have just started learning R
programming on my own, and the introduction, so far, considering all the
books I have read, is the best. An overview which gives you a picture of
what R programming is and at the same time gives you an actual practice.
It’s like it’s not only giving me information but also it walks me through
the process. Keep up!
Should I get stuck in some areas while learning this. I’ll let you know.
Thank you for this. =)
Reply
9. Krish says:
July 30, 2019 at 12:05 pm
It is essential to learn any programming language before learning R?
Reply
* DataFlair Team says:
July 31, 2019 at 9:52 am
Hi Krish,
No, it is not necessary. You can choose R to start your career. Learn R
from DataFlair, we have a more than 100 R tutorials from beginners to
experienced. Start from the Introduction to R and towards the end, you
will be able to implement your own Data Science project in R.
Reply
10. Akshay says:
August 12, 2019 at 2:18 pm
hello sir today i saw your blog first time it is fantastic. you give good
information in concise way.
I want to know you provide the video of R programming or not?
Reply
* DataFlair Team says:
August 13, 2019 at 6:01 pm
Hey Akshay,
Thanks for the appreciation. DataFlair is an online platform providing
free tutorial series for everyone from beginners to experts. Soon, we
will work on video tutorials as well. Till then, please refer to our R
tutorial series.
Thanks!
Reply
11. Srinivasa K says:
October 23, 2019 at 8:27 am
Hi,
I want learn learn R programming, but i don’t know where to start please
suggest me or share me details in my whatsapp +91 8971091331
Reply
* DataFlair Team says:
October 24, 2019 at 9:28 am
You can refer to the sidebar and learn the R concepts sequentially. All
the R tutorials are designed from a beginner’s perspective in an easy to
understand language.
Reply
12. Shorai Dzimati says:
October 24, 2019 at 1:52 pm
This is a well structured and simplified learning platform for R. Well done
DataFlair Team, keep it up. I have recently started my journey to learn R
towards a professional transition from being a Data Engineer to a Data
Scientist.
Reply
* DataFlair Team says:
October 25, 2019 at 9:29 am
Thanks for the feedback. Share the R tutorial series with your friends
and colleagues on social media.
Reply
13. Malachi Kaselchumfa says:
May 25, 2020 at 9:30 pm
I just started learning R Programming and I believe it’s one of the best
decision I have made in recent times. I hope to get as much knowledge that
I can to help me in my data science journey.
Reply
14. Julie Lin says:
January 25, 2021 at 6:35 am
HI Data Flair,
I just wanted to let you know you did a great job on making it easy to
understand even for people like me who are coming from a business & sales
background. The sitemap gave me a overall idea about what are covered and
with no fear of learning them because your make it very digestible! Thank
you for providing such a great website and sharing the information to help
people who want to advance their careers!
Reply
15. Bonnie says:
March 14, 2023 at 3:47 pm
Am starting to learn R – programming language, this set of tutorials appear
easy to read and understand. Let me give it a try.
Reply
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