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Choosing R or Python for data analysis? An infographic

May 12th, 2015 in R Programming

I think you'll agree with me if I say: It's HARD to know whether to use Python or R for data analysis. And this is especially true if you're a newbie data analyst looking for the right language to start with. It turns out that there are many good resources that can help you to figure out the strengths and weaknesses of both languages. They often go into great detail, and provide a tailored answer to questions such as "What should I use for Machine Learning?", or "I need a fast solution, should I go for Python or R?". In today's post, I present to you our new Infographic "Data Science Wars: R vs Python", that highlights in great detail the differences betweens these two languages from a data science point of view. So that next time you are debating R vs Python for machine learning, statistics, or maybe even the Internet of Things, you can have a look at the infographic and find the answer.

R vs Python for Data Analysis

At DataCamp, we often get emails asking whether one should use R or Python when performing their day-to-day data analysis tasks. Both Python and R are amongst the most popular languages for data analysis, and have their supporters and opponents. While Python is often praised for being a general-purpose language with an easy-to-understand syntax, R's functionality is developed with statisticians in mind, thereby giving it field-specific advantages such as great features for data visualization. Our new infographic"Data Science Wars: R vs Python" is therefore for everyone interested in how these two (statistical) programming languages relate to each other. The infographic explores what the strengths of R are over Python and vice versa, and aims to provide a basic comparison between these two programming languages from a data science and statistics perspective.

To explore these languages for yourself, try DataCamp's introduction to R programming course or Python for data science course.

R vs Python for data science Interested in some of our other infographics? Check out Statistical Language Wars and How to Become a Data Scientist in 8 Easy Steps

Comments

juanvg1972
Very interesting the comparasion.

I have some questions about this issue. I will apprecite if you can answer:

- Do you have any recomendations for a big company that is thinking in migrating from SAS to R. This company has a lot of analytical ans reporting processses made in SAS (mainly SAS Base)
- Do you know any case of SAS to R migration?
- Do you think that R is good for a big company (like bank, insurance company...)


Thanks in advance
06/08/17 2:15 PM |
mudryandriy
As a CTO of the company who had very little to do with Big Data in the past, I found the infographics very interesting to have a brief overview of Pros and Cons
03/24/17 6:36 PM |
chaddumagas
Ive done this kind of setup before but it was using web applications asp.net, its prolly not as powerful as python but it has somehow the same methodology to do visualization. Now i understand why tableau is a booming tool.....
03/13/17 7:20 AM |
eleonardoro
Hi! Can I translate it for portuguese/BR?
01/20/17 1:53 AM |
karlijn
Hi eleonardoro! Yes of course you can translate :) We usually do ask that you link back to the original article. Feel free to get in touch with me via Twitter or e-mail so that I can also share the article with my network! Thanks for your interest :) - Karlijn
01/22/17 2:42 PM |
mmchamara
Informative for a beginner...
12/07/16 12:09 AM |