What is R?
This is an easy question to answer. R is a dialect of S.
What is S?
S is a language that was developed by John Chambers and others at the old Bell Telephone Laboratories, originally part of AT&T Corp. S was initiated in 1976⁷ as an internal statistical analysis environment—originally implemented as Fortran libraries. Early versions of the language did not even contain functions for statistical modeling.
R has been one of the fastest growing programming languages of the last decade. But when coming to the people who are just starting to learn data science, there’s a frustration that comes up:
“I really don’t know which programming language to start with!!”
This frustration comes up because of ever widening range of tools and programming languages available in the market and it’s difficult to know which one to select.
My suggestion is focus on one language and learn R first as your data science programming language.
R is sometimes called the ‘golden child’ of data science!!
Big players like Facebook, Google, Microsoft, Bank of America, and the New York Times etc. also uses R.
R consistently ranks among Top Ten languages
IEEE Spectrum has just published its The 2017 Top Programming Languages, and the R Language is once again in the top ten of the list, it got 6th position.
Here is the list of top ten languages:
If we look at R’s performance on the TIOBE index, we can see a solid upward trend for almost a decade. TIOBE index is a similar ranking which ranks programming languages by the number of search engine searches.
Here are some reasons why you should add R to your data science skill matrix:
1. R is Free!!!
A major advantage that R has over many other statistical packages and is that it’s free in the sense of free software. The copyright for the primary source code for R is held by the R Foundation¹⁰ and is published under the GNU General Public License version http://www.r-project.org/foundation/ History and Overview of R .
2. R is both flexible and powerful.
According to the Free Software Foundation, with free software, you are granted the following four freedoms
- The freedom to run the program.
- The freedom to study how the program works, and adapt it to your needs and also access to the source code.
- The freedom to redistribute copies so you can help others
- The freedom to improve the program, and release your improvements to the public, so that the whole community benefits.
3. It has a best development environments – Rstudio
In terms of ease development, it provides Rstudio as best development environment.
4. It’s very easy to install packages and play as you want
The “base” R system that you download from CRAN for Linux, Windows, Mac.
5. Close to 10,000 free packages are available on CRAN
- There are over 10,000 packages on CRAN that have been developed by users and programmers around the world.
- There are also many packages associated with the Bioconductor project.
- People often make packages available on their personal websites; there is no reliable way to keep track of how many packages are available in this fashion.
- There are a number of packages being developed on repositories like GitHub and BitBucket but there is no reliable listing of all these packages
6. It has an amazing ecosystem for developers
Through out years R has an amazing and awesome ecosystem for developer.
7. It has wide range of packages for
- Data access
- Data cleaning or munging
- Performing Analysis
- Creating Reports etc.
What are you waiting for? Start Learning R.