R for Data Analysis

Master the basics of data analysis using the R Language
Overview

R is the common language of data science and has long been popular among data scientists. It is highly extensible and provides a wide variety of statistical, machine learning methods and predictive modelling techniques.  Recently due to a focus on data, reporting and big data, R is becoming more common place and this introductory course will teach you the basics to start you off on your R journey.

Course Code
INT2RPG
Duration
2 Days
Delivery Style
Classroom
Course Type
Public or Private
Max Delegates
12
Available as Nutshell
No

Book your virtual training

  • Date
  • Venue
  • Cost
  • More info

Book your place

Purpose of this course

Aimed at beginners this R course is intended to introduce the basics of the R language, but quickly moves on to cover all the key concepts you will need to master it.

Who is this course for

Anyone wishing to learn more about R.  A background in programming will be helpful but by no means essential.

You will learn how to
  • Get started with R and RStudio.
  • Wrangle messy data into shape.
  • Perform Exploratory Data Analysis (EDA) using R.
  • Create R Notebooks.
  • Start using the power of R for your own needs.
Benefits for your organisation

R can deliver huge benefits to your organisation through its reporting & integration capabilities.  All you need are highly trained staff to be able to harness those capabilities.

Benefits for you as an individual

R, once the language of data scientists is becoming far more main stream; or has our changing business world meant we are all becoming data scientists?  Regardless, R is here to stay and knowing how to leverage it’s capability is essential.

Introduction to R and RStudio
  • Alternatives to R for Data Science
  • Compiled vs Interpreted
  • REPLs
  • R IDEs 
  • RStudio
  • R PAckages
  • Updating R
  • Turtle Graphics
  • A Worked Example
Basic Data Input
  • Sydney Beaches Dataset
  • Tidyverse and here Packages
Data Wrangling
  • Clean Up Your Column Names
  • Exploring the Rows
  • Comparing Councils
Visualising Data
  • Time Series Plots
  • Extracting the Date
  • Compare Beaches
  • Flip the Axes
  • Add Colour
  • Display a Third Variable
  • Facet Wrapping
  • Filter to Omit Outliers
  • Saving Your Plots
Box, Violin and Pair Plots
  • The Iris Dataset
  • Data Distributions
  • Box Plots
  • Violin Plots
  • Analyse the Data
Log Transform
  • Box Plots of Beach Data
  • Violin Plots of Beaches Data
Notebooks and Markdown
  • Notebooks
  • Markdown
  • R Notebooks
  • The RStudio Notebook Template
  • An Iris Notebook
Interactive Documents
  • HtmlWidgets
  • Other Languages
  • Reproducible Notebooks
  • Share and Publish
  • Are Scientific Pages Dead?
Prerequisites

None.  Although a programming or data analysis background will be helpful.