Python or R— Which is the Better Option?
Python and R are probably the two hottest programming languages in the world right now. But which one should you go to more often? Which one can make your life simpler? Let us have a look.
It was in the year 1954 that IBM built the first ever programming language — FORTRAN(FORmula TRANslation). Until then no one ever thought programming would ever become possible. But, look at how far we have come!
The invention of FORTRAN paved the way for many higher level programming languages such as HTML, C, C++.
However, these programming languages had major flaws, such as security issues, lack of exception handling, complexity in debugging etc., which needed ironing out.
People had to wait until the 1980s for the unveiling of the programming language which could solve all their problems — Python.
Python, founded by Guido van Rossum, was officially released in 1989. It had the solution for almost all the problems common people had faced until then. It was versatile, easy to use and fast to develop. Moreover, it was open source, meaning it can be accessed by anyone anywhere across the globe absolutely free of cost!
Now, everyone started having the opinion that there would never be any competition for Python. However, this proved to be wrong.
In 1993, R Programming Language, designed by Ross Ihaka and Robert Gentleman was officially released. Like Python, R offered a plethora of advantages — it was open source, highly compatible and moreover had a vast array of packages.
Enough of history, now lets discuss which programming language we should choose among these two exceptional languages and why?
Why should I choose Python?
- Ever since its discovery, Python has been one of the most fast growing favorites among people on this planet. Why? Well, this is because of its simplicity! Writing a programme in Python is more or less equivalent to writing an article in English(just like the article I have written for you here!). It thus implies that Python is beginner-friendly, meaning you don’t need to necessarily have a background in Computer Science to learn Python.
- Python has a whole lot of libraries. You name anything, you will definitely find a library for it on Python. Some examples of Python libraries are TensorFlow, OpenCV, NumPy, Pandas, Matplotlib. This vast array of libraries is one of the reasons why Python is the preferred programming language in applications like Machine Learning and Data Science, where libraries like NumPy, Pandas, Matplotlib, Seaborn etc. are used.
- It is ideal for building prototypes as ideas can be tested out much quicker in Python as compared to other programming languages. It thus implies that Python is not only fast but at the same time it also saves a lot of money.
- As I had mentioned previously, Python is open-source, and a lot of programmers contribute in making this language better day by day. The Python Programmers Community is one of the largest in the world and this community is filled with people from different parts of the globe!
- It is portable across operating systems, meaning that Windows OS, Linux OS, Mac OS — nothing is a barrier for Python. You can use it anywhere, anytime:)
Looking at all these amazing features of Python, you might be wondering — Does R offer a competition to Python? Well, let us take a look at why you should choose R!
Why should I choose R?
- R offers exemplary support for data wrangling. So, what is data wrangling? It is the process of gathering, selecting and transforming data in order to make it suitable for answering an analytical question. R packages like dplyr and readr are capable of transforming messy data into structured data. This is one of the main reasons why some companies prefer those who are skilled in R over those who are skilled in Python for Data Analyst or Data Scientist roles.
- R facilitates quality plotting and graphing. Some useful visualization packages in R include — ggplot2, Lattice, highcharter, Leaflet and RColorBrewer. These packages help build visually pleasing graphs, one of the features which sets R apart from other programming languages.
- R builds statistical tools a whole lot easier when compared to other programming languages. Statistical tools are used in many applications like sports, analysis and healthcare.
- It is more commonly used for machine learning operations like classification and regression. This is mainly because of the wide variety of statistical variables in R, which is not present in any other programming language.
- It helps in building beautiful reports using packages like Shiny and Markdown. Shiny helps in building web apps straight from R, while Markdown helps in building dynamic documents, high quality presentations and dashboards.
As we conclude the comparison, it is not possible for us to say definitely that one program is better than the other.
We can see this from 2 point of views:
Beginner Point of View(Person who has no prior knowledge in coding) — As we saw earlier, Python is beginner friendly. However, this is not the case for R always. R requires some amount of training and is not as beginner friendly compared to Python.
Note: There can be exceptions, especially if you are a person who finds R more interesting.
Professional Point of View(Person who has prior knowledge in coding and can write codes with relative ease) — From the points that we have seen, it is quite clear that R Programming Language is built especially for those who are interested in Data Analytics, Data Science or Machine Learning. Although Python is also used for these applications, it is vital that a person who knows Python have some knowledge in R.
In conclusion, we can state that there is nothing much which separates these two programming languages. Learning R or Python (or both) would be a wonderful addition to your skillset. R and Python are among the most popular languages in the world right now and learning either or both of these programming languages will go a long way in helping you keep with today’s coding trends!
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