When it comes to data science programming languages, you have two options: Python and R. Both Python and R will help you analyze data to see valuable business insights, but which one should beginners learn first to maximize their chances of landing a job? We asked Galvanize Lead Data Science Instructor, Sean Reed, to explain the differences between Python versus R, what each language does best, and which language he suggests data science students should learn first.
Sean’s background is in physics, economics, statistics, finance, and web development.
He learned data science techniques on the job, and worked as a data scientist for several years before joining Galvanize.
What are Python and R?
Python is a more traditional programming language
R was originally designed for statistics but has branched out into a more general-purpose language
Python and R – the Similarities
Both Python and R are used for:
Graphing and predictions
The Case for Python
Python is a general purpose programming language
It is used for software development as well as data science
Its flexibility allows Python to easily integrate into production systems
Many people use Python and know how to integrate Python
Developers can import R functions and objects into Python and R’s plotting routine can be used within Python
The Case for R
R was developed in academia for use in STEM subjects
It was originally used for building statistics packages and visualizations for researchers
There are a huge number of statistical packages available in R (more than in Python, though Python is catching up)
Now data scientists can combine both Python and R for a wider range of capabilities
Python and R Developers in the Real World
In the 1990s: Companies previously did not use R in production. Original R statistics packages were developed for individual researchers, not teams
Today: Software and data science has progressed to be team based
Data scientists share code on GitHub
Data scientists push insights into production
Easier to collaborate in Python than in R, but those things are still being done in R by talented programmers.
What can Data Science Bootcamp Students build?
Galvanize students do final projects in Python
Galvanize students often combine Python with Flask, machine learning systems, and neural networks to create apps
One student created a Pet Recommender app. Users can type in dog attributes and find dogs that meet their preferences in local shelters!
Getting a Job in Data Science
Employers hiring data scientists look for:
People who are good programmers
People who can use the whole software engineering toolkit in Python
The Galvanize curriculum integrates the whole toolkit so that graduates are good programmers as well as good data scientists.
Galvanize data science graduates have found jobs as:
AI/Machine learning engineers
The Bottom Line:
Focus on Python and object-oriented programming skills as a beginner. Understand how programming languages are structured. Learning Python brings you closer to the ecosystem of programming – data science techniques are moving towards software engineering.
Imogen is a writer and content producer who loves writing about technology and education. Her background is in journalism, writing for newspapers and news websites. She grew up in England, Dubai and New Zealand, and now lives in Brooklyn, NY.