In this video, we will give a brief overview of the R programming language.
After our last video on Python, where we discussed its wide adoption, you might be wondering
why on earth you should consider learning any other language.
Well, according to the results of the 2019 Kaggle Data Science survey, which had over
10k respondents from around the world, learning up to three languages can increase your salary!
And R has a lot to offer you.
Like Python, R is free to use, but it's a GNU project -- instead of being open source,
it's actually free software.
So if Python is open source and R is free software, what’s the difference?
Well, Both open source and free software commonly refer to the same set of licenses.
Many open source projects use the GNU General Public License, for example.
Both open source and free software support collaboration.
In many cases (but not all), these terms can be used interchangeably.
The Open Source Initiative (OSI) champions open source while the Free Software Foundation
(FSF) defines free software.
Open source is more business focused, while free software is more focused on a set of
values.
Back to why you should learn R. Because this is a free software project, you can use the
language in the same way that you contribute to open source, and it allows for public collaboration
and private and commercial use.
Plus, R is another language supported by a wide global community of people passionate
about making it possible to use the language to solve big problems.
Who is R for?
It's most often used by statisticians, mathematicians, and data miners for developing statistical
software, graphing, and data analysis.
The language’s array-oriented syntax makes it easier to translate from math to code,
especially for someone with no or minimal programming background.
According to Kaggle’s Data Science and Machine Learning Survey, most folks learn R when they're
a few years into their data science career, but it remains a welcoming language to those
who don’t have a software programming background.
R is popular in academia but companies that use R include IBM, Google, Facebook, Microsoft,
Bank of America, Ford, TechCrunch, Uber, and Trulia.
● R has become the world’s largest repository of statistical knowledge.
● As of 2018, R has more than 15,000 publicly released packages, making it possible to conduct
complex exploratory data analysis.
● R integrates well with other computer languages, such as C++, Java, C, .Net, and
Python.
● Common mathematical operations such as matrix multiplication work straight out of
the box.
● R has stronger object-oriented programming facilities than most statistical computing
languages.
There are many ways to connect with other R users around the globe.
Communities such as user!, WhyR?, SatRdays, and R-Ladies are all great to connect with.
And you can also check out the R project website for R conferences and events.