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R Programming for Data Analysis - Advanced

  • Length 1 day
Course overview
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Why study this course

Build on your base knowledge of R. There are often many ways to achieve a result using R, learn how to run analysis more efficiently:

  • create your own functions

  • control structures

  • loops and loop alternatives

  • tidyverse piping syntax

  • create visualisations with ggplot2

You will work alongside the Data Analytics lead as you complete exercises throughout the day to cement your understanding of these concepts. The skills you learn on the day will empower you to build your own solutions in R.

Nexacu Public Schedule

With Lumify Group's acquisition of Nexacu, we're pleased to now offer you the largest public schedule of end user applications training in Australia and New Zealand. As we move to consolidate our end user offering with Nexacu, as an interim measure you can now access the schedule of the most closely aligned courses and book, by clicking on the link below.

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What you’ll learn

After completing this course, students will be able to:

  • Use functionals, loops, and other control structures

  • Create graphics with ggplot2

  • Write custom functions

  • Write more concise code

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R Programming at Lumify Work

Learn R programming to analyse, manipulate, and visualise data more effectively.

Course subjects

Working more efficiently in R

  • How to work more efficiently in R

  • Vectorisation

  • Using better functions

  • Concise code

  • Reusable scripts

  • Custom functions

  • Loops and other control structures

  • Loop alternatives

Functions to reduce typing

  • Printing objects after creating

  • with and within

  • Inserting multiple quotation marks

Create your own functions

  • Why write your own functions?

  • Basics of functions

  • What is a function?

  • Creating your own functions

  • Syntax for writing your own function

  • More complex functions

  • Ellipses and further arguments

  • Scope

  • Loading your functions

Loops and control structures in R

  • If and if else

  • Loops for loops

  • Saving results from a loop

Improving your code

  • While loops

  • Repeat loops

Loop alternatives

  • Functionals

  • Apply functions

  • Split

  • Map functions

  • Map variants

  • Returning a vector

  • Walk

  • Loop, apply or map?

Tidyverse piping syntax

  • Purpose

  • Using the pipe

  • Pipe variants

  • The tee operator

  • The exposition operator

Plotting with ggplot2

  • The grammar of graphics

  • Required components

  • Using ggplot()

  • Scatterplot

  • Line chart

  • ggplot2 resources


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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