With the massive growth in the importance of big data, machine learning, and data science across the industries, two languages emerged as the most favorable for developers, R and Python. It is hard to pick between these two flexible data science languages, as both are free and open source. Let’s talk about the basics of Python and R, and then move on to Python vs R.
Python is a widely used object-oriented language, easy to learn and debug. Learning Python provides programmers with the skills necessary to work on the business, digital products, open-source projects, and various web applications outside of data science.
Must Read – What is Python?
R Programming is considered the best programming language for any statistician since it has a comprehensive catalog of statistical and graphical methods. R is a powerful and highly flexible scripting language with a vibrant community and resource bank.
Let’s explore more about Python vs R.
Python vs R for Data Science
Final Thoughts on Python vs R
Python is a powerful and versatile language that programmers can use for a variety of computing tasks. Learning Python will help you develop a universal data science toolkit, and it is a versatile programming language that you can learn quite quickly, even as a non-programmer.
On the other hand, R is a programming environment designed specifically for data analysis that is very popular in the data science community. You will need to understand R if you want to go far in your data science career.
R was built as a statistical language; it is much better suited to statistical learning, and anyone with a formal background in statistics can easily use R. Python is among the most popular programming languages in the world and helps to deploy and implement machine learning at a large-scale, especially when data analysis tasks need to be integrated with web applications.
Also explore – Statistical Methods Every Data Scientist Should Know
The reality is that learning both tools and using them to their respective strengths can only improve you as a data scientist. Versatility and flexibility are traits that any data scientist is at the top of their field. The Python vs R debate limits you to one programming language. You should look further and embrace both tools for their respective strengths. Using more tools will only make you better as a data scientist.
Popular Python Online Courses
- Using Databases with Python
- Complete Data Science Training with Python for Data Analysis
- Programming for Everybody (Getting Started with Python)
- Computer Science & Programming Using Python
Popular R Online Courses
- Introduction to R for Data Science
- Data Science: R Basics
- Data Analysis with R
- Essential Math for Machine Learning: R Edition by Microsoft
- R for Data Analysis
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