Python VS R (Which is Better?)
It’s been more than half a century since computer technology was created. Now the software world is flooding with many programming languages. Almost all of the languages are unique in their own ways. They have varying strengths and weaknesses.
This article will give you a strong overview of both programming languages and will give you clarity on which one is more suitable for you.
1. Versatility
Python easily steals the show when it comes to versatility. It is used in data science, web development , SEO, programming applications, ethical hacking, game development and many more. It is a highly compatible programming language and is easy to plug in with others e.g AWS Azure.
Though not naturally fast, its speed can be increased by using libraries like NumPy (which has been coded with the help of C), compensating its relatively slower speed.
R is used primarily for hardcore statistical computing and graphics. R is used among data miners and statisticians for data analysis and developing statistical software.
R is one of the most powerful and capable languages for statistical analysis. It is mostly seen to be used by researchers and professors in universities.
2. Ease
It is quite impressive that despite being a high-level programming language Python is still one of the easiest languages out there. Its syntaxes are easy to understand and are almost similar to normal English texts.
What takes 10 line of codes in Java can be done by python in just one or two.
R tends to have a steeper learning curve at the beginning, but once you understand how to use its features, it gets significantly easier. Tip: Once you’ve learned one programming language, it’s typically easier to learn another one.
3. Research and Data Visualization
It’s no surprise that R is taught over python on many platforms and universities. Even Google encourages data analyst enthusiasts to use R. R is extremely powerful when it comes to hardcore statistical analysis.
A true data analyst enthusiast knows the importance of data visualization.
Python has a few data visualization libraries like matplotlib and seaborn. But overall, it isn’t as good as R. Python users try to compensate the lacking data visualization by using external tools and software like Power BI and Hadoop. Still, even today R stands superior.
4. Developer Community
Python is the second most loved programming language as in 2022. It is due to this that it has a strong and huge team of developers and users. This has numerous benefits. If you ever get stuck when coding in python and try researching a solution, you are very likely to easily find one.
Ever since Python started winning the hearts of programmers, languages like R are starting to lose their popularity. Bitter words, but the developer community of R is nowhere close to Python’s.
4. Modules/Libraries
Due to the huge developer community many libraries have been made for python. It has sklearn made by Google for machine learning, Pytorch, Keras and TensorFlow for deep learning, Flask and Django for web frameworks in web development, Tkinter for GUI and the list goes on…
R is no match for python in this area.
5. Future Scope
Both the languages have a high scope. However, one must keep in mind that learning these programming languages alone will not be a right choice. Understand this:
· Python is rapidly increasing its libraries and reach. It is becoming something of a universal programming language. Learning it opens many new pathways for you.
· Since the last decade the demand for data scientists and analysts just keeps on rising. Ever year lakhs of vacancies are increasing. Market is in huge shortage of capable data analysts and scientists. So, R is something that one cannot miss is he/she is planning to pursue one of those fields.
