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Data Visualization with R

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Details

To interpret your data and draw insights, you need to be able to visualise it. R is a programming language enjoyed by data scientists for its ability to process and utilise data. With R, you'll be able to take your data and use it to tell insightful stories with compelling visualisations to convince stakeholders and build trust.

In this course, you will learn:

  • Data visualization principles

  • How to communicate data-driven findings

  • How to use ggplot2 to create custom plots

  • The weaknesses of several widely-used plots and why you should avoid them

Delivery Methods

Leading Training is focusing on providing virtual training courses for the foreseeable future and will only consider in-person and classroom training on request, with a required minimum group size of four delegates. We remain committed to offering training that is fast, focused and effective.

Delivery Method Duration Price (excl. VAT)
Fulltime 4 Days R 11,596.00
Webinar 4 Days R 9,400.00

Discounts Available

Brochure:

Download Brochure


Information may change without notice.

Audience

  • Data scientists
  • Programmers
  • Business analysts 
  • Engineers
  • Scientists

Pre-Requisites

Leading Training's R Programming Course or equivalent knowledge

Course Outline / Curriculum

Introduction to data visualization 

ggplot2 

  •  The components of a graph
  •  ggplot objects
  •  Geometries
  •  Aesthetic mappings
  •  Layers
    • Tinkering with arguments
  •  Global versus local aesthetic mappings
  •  Scales
  •  Labels and titles
  •  Categories as colors
  •  Annotation, shapes, and adjustments
  •  Add-on packages
  •  Putting it all together
  •  Quick plots with qplot
  •  Grids of plots
  •  Exercises

Visualizing data distributions 

  •  Variable types
  •  Case study: describing student heights
  •  Distribution function
  •  Cumulative distribution functions
  •  Histograms
  •  Smoothed density
    • Interpreting the y-axis
    • Densities permit stratification
  •  Exercises
  •  The normal distribution
  •  Standard units
  •  Quantile-quantile plots
  •  Percentiles
  •  Boxplots
  •  Stratification
  •  Case study: describing student heights (continued)
  •  Exercises
  •  ggplot2 geometries
    • Barplots
    • Histograms
    • Density plots
    • Boxplots
    • QQ-plots
    • Images
    • Quick plots
  •  Exercises

Data visualization in practice 

  •  Case study: new insights on poverty
    • Hans Rosling’s quiz
  •  Scatterplots
  •  Faceting
    • facet_wrap
    • Fixed scales for better comparisons
  •  Time series plots
    • Labels instead of legends
  •  Data transformations
    • Log transformation
    • Which base?
    • Transform the values or the scale?
  •  Visualizing multimodal distributions
  •  Comparing multiple distributions with boxplots and ridge plots
    • Boxplots
    • Ridge plots
    • Example: 1970 versus 2010 income distributions
    • Accessing computed variables
    • Weighted densities
  •  The ecological fallacy and importance of showing the data
    • Logistic

Data visualization principles 

  •  Encoding data using visual cues
  •  Know when to include 
  •  Do not distort quantities
  •  Order categories by a meaningful value
  •  Show the data
  •  Ease comparisons
    • Use common axes
    • Align plots vertically to see horizontal changes and horizontally to see
  • vertical changes
    • Consider transformations
    • Visual cues to be compared should be adjacent
    • Use color
  •  Think of the color blind
  •  Plots for two variables
    • Slope charts
    • Bland-Altman plot
  •  Encoding a third variable
  • Avoid pseudo-three-dimensional plots
  • Avoid too many significant digits
  • Know your audience
  • Exercises
  • Case study: vaccines and infectious diseases
  • Exercises

Robust summaries 

  •  Outliers
  •  Median
  •  The inter quartile range (IQR)
  •  Tukey’s definition of an outlier
  •  Median absolute deviation
  •  Exercises
  •  Case study: self-reported student heights

Schedule Dates and Booking

There are currently no scheduled dates.

Please note that this course needs a minimum of 6 delegates to schedule a course. You can choose to be added to the waiting list by clicking the button below and we will contact you when we have enough delegates interested. Should we not get enough delegates, we will refund or credit your paid booking.

Add me to the waiting list

Should you need this course urgently, the following options are available:

  1. Pay for 6 delegates (whether you have them or not) and we will schedule the course as soon as possible.
  2. If you have fewer delegates and cannot pay for 6, we can negotiate a shortened course where some of the time will be spent in blended learning - watching videos and doing tutorials and exercises with some contact time with the trainer. We would want to discuss what your core needs are so that we cover those aspects. You need to have paid for 3 delegates at least.