How Duolingo Plans to Reach 100M Users

Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

DataCamp

Writing Efficient R Code

via DataCamp

Go to class Write review

Overview

Get Certified in Python, SQL & AI — 50% Off This May
690+ courses, career tracks, and industry-leading certifications trusted by 19M+ learners and 80% of the Fortune 1000.
Start Learning Today
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

The beauty of R is that it is built for performing data analysis. The downside is that sometimes R can be slow, thereby obstructing our analysis. For this reason, it is essential to become familiar with the main techniques for speeding up your analysis, so you can reduce computational time and get insights as quickly as possible.

Syllabus

  • The Art of Benchmarking
    • In order to make your code go faster, you need to know how long it takes to run. This chapter introduces the idea of benchmarking your code.
  • Fine Tuning: Efficient Base R
    • R is flexible because you can often solve a single problem in many different ways. Some ways can be several orders of magnitude faster than the others. This chapter teaches you how to write fast base R code.
  • Diagnosing Problems: Code Profiling
    • Profiling helps you locate the bottlenecks in your code. This chapter teaches you how to visualize the bottlenecks using the profvis package.
  • Turbo Charged Code: Parallel Programming
    • Some problems can be solved faster using multiple cores on your machine. This chapter shows you how to write R code that runs in parallel.

Taught by

Colin Gillespie

Reviews

4.3 rating at DataCamp based on 27 ratings

Start your review of Writing Efficient R Code

Go to class

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free
Someone learning on their laptop while sitting on the floor.