Python for R Users

This course is for R users who want to get up to speed with Python!
Start Course for Free
5 Hours15 Videos57 Exercises9,600 Learners
4950 XP

Create Your Free Account

GoogleLinkedInFacebook
or
By continuing you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.

Loved by learners at thousands of companies


Course Description

Python and R have seen immense growth in popularity in the "Machine Learning Age". They both are high-level languages that are easy to learn and write. The language you use will depend on your background and field of study and work. R is a language made by and for statisticians, whereas Python is a more general purpose programming language. Regardless of the background, there will be times when a particular algorithm is implemented in one language and not the other, a feature is better documented, or simply, the tutorial you found online uses Python instead of R. In either case, this would require the R user to work in Python to get his/her work done, or try to understand how something is implemented in Python for it to be translated into R. This course helps you cross the R-Python language barrier.

  1. 1

    The Basics

    Free
    Learn about some of the most important data types (integers, floats, strings, and booleans) and data structures (lists, dictionaries, numpy arrays, and pandas DataFrames) in Python and how they compare to the ones in R.
    Play Chapter Now
  2. 2

    Control flow, Loops, and Functions

    This chapter covers control flow statements (if-else if-else), for loops and shows you how to write your own functions in Python!
    Play Chapter Now
  3. 3

    Pandas

    In this chapter you will learn more about one of the most important Python libraries, Pandas. In addition to DataFrames, pandas provides several data manipulation functions and methods.
    Play Chapter Now
  4. 4

    Plotting

    You will learn about the rich ecosystem of visualization libraries in Python. This chapter covers matplotlib, the core visualization library in Python along with the pandas and seaborn libraries.
    Play Chapter Now
  5. 5

    Capstone

    As a final capstone, you will apply your Python skills on the NYC Flights 2013 dataset.
    Play Chapter Now
Datasets
Air qualityCountry timeseriesFlights (sample)InflammationNYC Flights 2013Tips
Collaborators
Sumedh PanchadharHugo Bowne-AndersonEunkyung Park
Daniel Chen Headshot

Daniel Chen

Data Science Consultant at Lander Analytics
Daniel is a Software Carpentry instructor and a doctoral student in Genetics, Bioinformatics, and Computational Biology at Virginia Tech, where he works in the Social and Decision Analytics Laboratory under the Biocomplexity Institute. He received his MPH at the Mailman School of Public Health in Epidemiology and is interested in integrating hospital data in order to perform predictive health analytics and build clinical support tools for clinicians. An advocate of open science, he aspires to bridge data science with epidemiology and health care.
See More

What do other learners have to say?

I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.

Devon Edwards Joseph
Lloyds Banking Group

DataCamp is the top resource I recommend for learning data science.

Louis Maiden
Harvard Business School

DataCamp is by far my favorite website to learn from.

Ronald Bowers
Decision Science Analytics, USAA

Join over 7 million learners and start Python for R Users today!

Create Your Free Account

GoogleLinkedInFacebook
or
By continuing you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.