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Writing Efficient R Code

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

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4 Horas14 Videos43 Exercises
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Descrição do Curso

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.
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  1. 1

    The Art of Benchmarking

    Livre

    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.

    Reproduzir Capítulo Agora
    Welcome!
    50 xp
    R version
    100 xp
    Benchmarking
    50 xp
    Comparing read times of CSV and RDS files
    100 xp
    Operational differences: "<-" and "="
    50 xp
    Elapsed time
    100 xp
    Relative time
    50 xp
    How good is your machine?
    50 xp
    DataCamp hardware
    100 xp
    Benchmark DataCamp's machine
    100 xp
  2. 3

    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.

    Reproduzir Capítulo Agora
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

Nas seguintes faixas

Big Data com R

Ir para a trilha

Desenvolvedor R

Ir para a trilha

Programação R

Ir para a trilha

Datasets

Information on 45,000 movies

Collaborators

Collaborator's avatar
Tom Jeon
Collaborator's avatar
Richie Cotton

Prerequisites

Intermediate R
Colin Gillespie HeadshotColin Gillespie

Assoc Prof at Newcastle University, Consultant at Jumping Rivers

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