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Top 10 Reasons To Learn R Programming
You might have come across the term “R programming” quite a few times and numerous questions would have popped into your head. Is it just another programming language? How is it different from other programming languages? What is the future of it? How much will I earn if I know this language? All your queries will be answered in this blog, which gives you the top 10 reasons to learn R Programming.
These are the reasons, which make R Programming such an in-demand skill:
- R Programming gets you High Paying Jobs
- R is Lingua Franca for Statistical Analysis and Data Science
- R is used by Top Companies
- R is used to Create Interactive Web-Apps
- R is used to Create Stunning Visualizations
- R provides a Comprehensive Library
- R has Huge Community
- R is used by Multiple Domains and Industries
- R is Cross-Platform Compatible
- R is Open Source
10. Open Source
R is a free, open source software. Its plug and play, install R once and start having fun with it. What more? You can even modify the code and add your own innovations to it. R language has no license restrictions as it is issued under the GNU (General Public License).
9. Cross-Platform Compatible
One of the biggest advantages of R is that you can run R on several operating systems and varied Software/Hardware. R will run seamlessly irrespective of whether you are working on a Linux based, Mac or a Windows system.
So, if you’re working on a Windows system and your client is working on a Linux system, don’t worry, your R code will definitely run on his system!
8. Industries/Domains using R
- R Programming is used in the financial domain to build econometric models, analyze fraudulent transactions.
- R programming is used by telecom sectors for Subscriber Profiling, Churn Management, and Personalised advertising
- R programming is used in computational biology to perform genomic analysis.
7. Huge Community
Let’s say you are working on a financial project to find out how many of the credit card transactions are fraudulent and reach a roadblock while building the classification model. Thankfully, R boasts of a huge community to tap into whenever you need help. So, you can always seek help from people who have worked on similar projects. You can also collaborate with others to share ideas, work on projects and compete in Data Science contests.
6. Comprehensive library
R provides more than 10,000 packages and lakhs of inbuilt functions catering to diverse needs. There are packages for Data Manipulation, Data Visualization, Machine Learning, Statistical Modeling, Imputation and a whole lot of other packages to play around with. So, whatever your need is, R springs up a package from its hat to help you out.
Since R is open source, you can create your own package and contribute to the community.
5. Great Visualization
R provides packages such as ggplot2, ggvis and plotly to create stunning visualizations. These packages help in creating print-quality graphs which can be published in any international magazine.
The below graph is a scatter-plot made with the help of plotly.
This is a bar-plot created with ggplot2
R is widely used in the pharma industry because of its high-quality graphics, which come in handy during experimental procedures.
4. Interactive Web apps
Ever wondered if there is a tool which helps in creating stunning web applications directly from your data analysis software?
R provides a package called shiny, just for that. With the help of shiny, you can create interactive web pages and impressive dashboard designs directly from your R Console.
You can create a shiny web app and host it on any cloud service such as AWS.
3. Major Companies using R
R is used by the top companies:
- Facebook uses R for behavioral analysis related to status updates and profile pictures.
- Google uses R for advertising effectiveness and economic forecasting
- Twitter uses R for data visualization and semantic clustering
- Ford uses R to improve vehicle designs
2. Lingua Franca for Statistical Analysis & Data Science
R is a statistical software created by statisticians for statisticians. From finding simple measures of central tendency to building complex statistical models, R is the go-to language for any type of statistical analysis.
Fitting a linear model with R:
Fitting a bell-curve with R:
Complex machine learning models such as Gaussian Process Regression, Poisson Regression, and Random Forest can be built with simple R Functions.
1. High Paying Jobs
In a Survey done by Dice Tech of over 17,000 technology professionals, the highest-paid IT skill was R programming. R language skills attract median salaries in excess of $110,000.
With R language as a skill-set, one can find jobs such as:
- Data Analyst
- Data Scientist
- Quantitative Analyst
- Financial Analyst
Hoping that this blog will get you started in learning R. You can check out the R Certification Training by Edureka, a trusted online learning company with a network of more than 250,000 satisfied learners spread across the globe. Edureka’s Data Analytics with R training will help you gain expertise in R Programming, Data Manipulation, Exploratory Data Analysis, Data Visualization, Data Mining, Regression, Sentiment Analysis and using RStudio for real life case studies on Retail, Social Media.