R Programming language

r-language-jobitfreshers
Jobitfreshers
Technology Feb 19, 2020 0

what is R Programming language and the definition of R language?

R is a programming language used for computing statistics and graphics. R provides wide variety of graphics and statistical computing. R Programming language is open source software available for free. And compiles and run on wide variety of UNIX platforms. R is a collection of features like calculation, manipulation and graphical display.

R used by Statisticians, Data Miners and Software Developers. For analyzing huge data reports and various statistics.

R is popularly known as lingua franca of Data Science and statistics.

Features of R programming language:

  1. Robust Visualization library.
  2. Independent platform.
  3. Cutting edge technology.
  4. Free and open source tool.
  5. Huge community support.
  6. Provides cross platform support.
  7. R is suitable for GNU/Linux and Microsoft Windows.

Pre – requisites to learn R programming language:

Before learning R programming language you should have some prior language to programming. You must able to understand graphs for data representation. Solid understanding of math with statics needed to learn R.

Tools to use R programming language:

  1. Visual Studio
  2. Eclipse
  3. R Studio

Use cases of R language in real life:

  • Facebook
  • Ford Motors
  • Google
  • FourSquare
  • Mozilla
  • Microsoft
  • New York Times
  • Twitter
  • ANZ Bank
  • Trulia
  • National Weather Service

How to install R in windows computer? – Installation guide of R

R is an open source software tool that can downloaded for free. It helps in carrying out the analyses in an interactive way. So you have to find the latest version of R to start the download process.

  • Initially navigate to CRAN website to download the latest version of R tool.
  • Then under the heading of Download and Install R, click Windows link.
  • Once you see the downloaded .exe file, double click on the file.
  • The file gets installed and asks you to choose the language.
  • Simply follow the instruction displayed on the Windows Setup Wizard.
  • In the following page, go through the license agreement to agree the terms and conditions.
  • Then click next. You can select the destination of the file to get stored in your computer.
  • Follow the guidelines and the download will start in the windows screen.
  • Once you see the completing the R for Windows Setup wizard window, you can click Finish.

Industrial sectors using R:

  • Government sectors.
  • Banking Sectors.
  • Health centers.
  • Educational institutions
  • Financial Sectors.

How to get a job as a fresher in R programming language?

R is a tool and it is available for free. Anyone can trained to use the tool But what makes you unique in the crowd is learning the basic concepts. Like Statistics, data mining, Forecasting, Predictive analysis, simulation and optimizing. So knowledge and understanding in the above concepts with basic knowledge about R programming tool can get you a job in this sector.

Job roles for R Programmers:

  • Data Analyst.
  • Data Visualization Expert.
  • Quantitative Analyst.
  • Business Analyst.
  • Data Scientist.

Difference between python and R:

  1. R is a low level programming language whereas Python is a high-level programming language.
  2. Data reading is same in both the languages.
  3. R is bit slower compared to Python.
  4. Graphical interpretation is clearer than python.
  5. Python stand out in deep learning are compared to R.
  6. R is more powerful in the area of statistics.
  7. Python is more powerful in development and deployment.
  8. R has simple libraries whereas Python libraries are little bit complex to start with.
  9. Python codes need less maintenance compared to R codes.
  10. R has command line interpreted language while Python is similar to English language literally.

Advantages of R Programming languages:

  1. Open source programming language.
  2. Ideal support for data wrangling
  3. Rich graphing and plotting facilities.
  4. Highly compatible.
  5. Clear Reports.
  6. Developing artificial Neural Networks
  7. Lingua franca of statistics.
  8. Continuous growth phase.
  9. Integrated technologies like Hadoop.

Disadvantages of R Programming languages:

  1. Requires prior package knowledge.
  2. Difficult to implement algorithms.
  3. R is slower than Python and Matlab.
  4. Not an easy language to learn.
  5. Security is at risk.
  6. Not suitable for BigData.
  7. Utilize more memory compared to python.
  8. R doesn’t have proper basic package.

Conclusion:

R is a tool to explore the data. So the detailed correlation, clustering and data reduction done with R. Data is one of the constantly growing industries in the today world. So there will be huge demand for the data scientist in the future. R vacancies fulfilled by the data scientists.