Are you ready for the one thing no one tells you about “What is R programming?”
You are the lucky one who gets the learning ability behind an amazing field like data science and ensures none of the opportunities you’re driving fall behind in R programming.
Are you working in the IT Field? Do you have zeal towards exploring what this field is, but still feel skeptical?
Being a non-expertise in advanced coding concepts and programming languages, I really was not motivated to take my coding skill to next level until I gave a try to hit R programming wherein I realized programming is not a haunting word anymore.
Anyone among us can excel in R programming as it has in-built functions and al you need to apply is LOGIC!
“The secret of getting ahead is getting started.”
– Mark Twain.
You may be perplexed about what she is talking about! No worries, you have come to the right place! It’s time to gear up your career in an interesting field.
If you have a craving interest in technology, number handling, and interpretation through data analysis, then accelerate your career towards Data Science.
Most of the interaction with technology includes data such as your Amazon purchases, Facebook feed, Netflix recommendations, and even the facial recognition required to sign in to your phone.
If you’re a newbie data analyst looking for the right language to start with and confused with the opportunity to indulge in your career, let us have a deeper look.
“The big technology trend is to make systems intelligent and data is the raw material”
– Amod Malviya
The programming language rankings that analyst firms such as Stack overflow, TIOBE programming community index, and pypl popularity of programming language index that regularly publish, the languages in those rankings rarely change much in the short term.
With these insights, R programming has the ratings of 2.37% and ranks one of the top 10 programming languages.
Do you want to acquire skills on how R programming works?
R is a programming language and environment for statistical computing and graphics. In 1991, it was created in New Zealand by two gentlemen named Ross Ihaka and Robert Gentleman. It is an implementation of the S language.
“No great marketing decisions have ever been made on qualitative data”
– John Sculley
What is R programming?
R programming is a powerful language that provides all the tools required to build probabilistic models, perform data analysis, and build machine learning algorithms.
R packages are collections of functions and data sets. They increase the power of R by improving existing functionalities. It has over 10,000 packages in the Comprehensive R Archive Network(CRAN) repository whaqsx6ich extends the capability of R.
R Programming is predominant than other programming languages and can run quite easily on Windows, Linux, and Mac.
I hope now you have the precision of “What is R programming?”. Let us discover the 4 fascinating motives to specialize in the R programming language.
1) Career Prospects in R programming
Do you want to step into the ever-growing field of data science?
Do you wish to equip yourself with one of the most widely used languages like R Programming?
We can analyze and proceed further to change your career in the ever-growing field of data science. Data are becoming the new raw material of business. Analysts and statisticians work towards the decision-making process.
Every day billions of people around the world are generating new data. Data scientists are required to sift through this massive amount of data and make use of it. R has become the primary tool for statistical analysis and data science due to its open-source nature and its extreme versatility.
There are around 1 million job openings for R programmers in job portals like LinkedIn, Glassdoor, Indeed, Monster, etc. The average salary for “R programmer” ranges from approximately $74,626 yearly for Programmer to $126,509 yearly for Senior Programmer.
Here are some of the top profile data science careers in R programming,
- R programmer
- Data Architect
- Data Engineer
- Data Scientist
- Data Visualization Analyst
- Geo Statisticians
- Database Administrator
- Quantitative Analysis with R
2)Upsurge of R programming
A free and open-source development environment for statistical computing and graphics, R has been gaining in popularity and interest over the past years.
TIOBE surmised that more universities and research institutes are embracing R and Python for statistical analyses rather than commercial packages such as SAS, Strata, and SPSS.
Do you know why there was a drastic change in demand for R language from the period of 2019 – 2020?
According to the survey of Stack overflow, TIOBE programming community index, and Pypl popularity of programming language index 2019, R programming ranks 20th place whereas in 2020 it ranks at 8th place.
Its boom has been especially felt since the start of 2020, surging from 0.81% the ratings in January to 2.79% last month. COVID-19 vaccine research is driving R programming popularity.
R Programming has benefited from demand in universities and from global efforts to find a vaccine for the COVID-19 virus.
TIOBE cited the possibility of a spike in statistical computing and data mining associated with the search for a vaccine for the COVID-19 virus.
3) Compatability of R programming
R programming is used by even novice R users to perform simple data analyses within a few seconds. By comparing to other programming languages like Python, R has multiple Object-Oriented Programming paradigms, while Python has only one.
Why should we learn R programming?
Well, Many data scientists prefer only R as it has the feature of meta-programming (a program can be designed to read, generate, analyze or transform other programs, and even modify itself while running).
Installing R is pretty straightforward. Once R is installed, you should consider installing one of R’s integrated development environment (IDE). Two fairly established IDE’s are RStudio and Architect.
you may compile R on different operating systems and various Software/Hardware. It is mostly used on Microsoft Windows, GNU/Linux, Macintosh, UNIX, and its derivatives such as FreeBSD, Mac OS X, Darwin, Solaris, etc.
Let’s dive into the few populous e-learning platforms in R programming
- The swirl package in R studio has interactive R coding exercises.
- edX has Introduction to R programming by Microsoft.
- Coursera provides “The R programming course” by John Hopkins University.
- DataCamp provides a “Free introduction to R tutorial” and the follow-up course “Intermediate R programming”.
4) Fool-proof learning techniques
R is a cross-platform (Platform independent) programming language with highly advanced interface packages that are available to communicate with open-source language. It is used for data analysis and facilitates the programmers to be secure with their workflows together.
Does R programming have the feature of versatility?
Yes, R programming provides various packages and features for developing the artificial neural network in machine learning, artificial intelligence, data science etc.
It sustains even machine learning and artificial intelligence. With the help of R programming packages, machine learning techniques such as gradient boosting, random decision forest, classification, regression, clustering and so on can be executed.
R programming rationalizes the quality in plotting and graphing with the help of R libraries such as ggplot2 and plotly. It prescribes for enhancing data visualization and aesthetic graphs. It provides exemplary support to perform data wrangling.
The R programmers can transform the messy data into a structured form with the help of R packages such as dplyr, reader. For instance, Tech giants like Google uses R to measure the effectiveness of its advertising campaigns and Facebook uses R for behavior analysis related to status updates.
Thus, learning how to code in R is a valuable investment. R comes with many tools that you can use to perform comprehensive statistical analysis on a data set.
Of course, knowing other tools like Python, MySQL and Tableau can be incredibly useful as the more tools you know, the more effective of a data scientist you will be. However, if you are looking to choose one programming language to learn, R is definitely worth your time building high scope to your profile.
“Things get done only if the data we gather can inform and inspire those in a position to make a difference”