The Difference Between Python and R



If you're interested in a career in data science and have the understanding of what skills are needed. You know that R and Python are the leading computer programming languages of this field. This article will help you make the right choice to start your learning.

Python and R are free, easy to learn, and simple to install. For a beginner in data science, with no experience with computer languages, or programming in general, brings the obvious uncertainty to choose to learn Python or R.



R has a long history of the data industry, great online support from others in the field if you need assistance or have questions about using the language. They have 5,000+ packages that can be downloaded and be used with R to extend its functionality. R can also integrate with other languages like C++, Java and C.


When you need heavy-duty statistical analysis and graphing, R is the go-to language. Mathematical operations like matrix multiplication come straight out-of-the-box. R's array oriented syntax makes math to code translation easy for newbs.



Python is a general purpose language that can do anything you want it to do. It's used in data munging, data engineering, web scraping, web apps, and more. It's a more simpler language to master than R and other languages. Python is an object-oriented programming language like Java, and C++. It's easier to right large-scale, and maintainable code than with R. Although R has a more comprehensive set of packages available to data professionals, Python's tools like Pandas, Numpy, Scipy, Scikit-Learn, and Seaborn are definitely up to par.



To determine whether to begin with Python or R, choose the language that feels natural to you and easy to grasp from the beginning. You can make a choice based on a on data project you'll be working on. If you're working with a project that has been already gathered and cleaned for you, and your main focus to is to analyze that data, then R will be the appropriate choice. If your projects deal with unorganised data, or to scrape data from websites, files, or other data sources, then you should start learning with Python.


The job market for Python compared to R have increased over the past few years.


Graph via rstats


Due to Python’s vast toolset, and adaptability to be used in web development, data science, and IT. It enables companies to traverse between employing Python developers and data scientists.



There is no mistake, whether you take the Python or R path to learning. Each language has its strengths and weaknesses. In addition, you can use certain libraries to use Python with R if you want to learn use both. My advice is to choose one to start with, and when you have a good grasp of the language, then you can start with the other.





 Jaime Gabriel Jingco

Software Engineer/ Applied Labs Assistant Instructor 

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