In this chapter, we focus on visualizing proportions of a whole; we see that pie charts really aren't so bad, along with discussing the waffle chart and stacked bars for comparing multiple proportions.

Introductie tot Grammar of Graphics

Bekend raken met ziektegegevens

Opwarmen met data-wrangling

Het cirkeldiagram en zijn vrienden

De beruchte P-I-E

De taartdiagram opschonen

Zin in een waffle?

Wanneer gebruik je staafdiagrammen

Basis gestapelde staven

Stapels ordenen voor leesbaarheid

Categorische x-as

Proportions of a whole

We shift our focus now to single-observation or point data and go over when bar charts are appropriate and when they are not, what to use when they are not, and general perception-based enhancements for your charts.

Bars and dots: point data

Are bars appropriate?

Working with geom_col

Wrangling geom_bar

Point charts

Ordered point chart

Adding visual anchors

Faceting to show structure.

Tuning your charts

Let's flip some axes

Cleaning up the bars

Converting to point chart

Point data

We now move on to visualizing distributional data, we expose the fragility of histograms, discuss when it is better to shift to a kernel density plots, and how to make both plots work best for your data.

Importance of distributions

Orienting with the data

Looking at all data

Changing y-axis to density

Histogram nuances

Adjusting the bin numbers

More bars

Bin width by context

The kernel density estimator

Histogram to KDE

Putting a rug down

KDE with lots of data

Single distributions

Finishing off we take a look at comparing multiple distributions to each other. We see why the traditional box plots are very dangerous and how to easily improve them, along with investigating when you should use more advanced alternatives like the beeswarm plot and violin plots.

Intro to comparing distributions

A simple boxplot

Adding some jitter

Faceting to show all colors

Beeswarms and violins

Your first beeswarm

Fiddling with a violin plot

Violins with boxplots

Comparing lots of distributions

Comparing spatially-related distributions

A basic ridgeline plot

Cleaning up your ridgelines

Making it rain (data points)

Wrap-up

Comparing distributions

World Health Organization Disease Dataset

Deze cursus helpt je je datavisualisatievaardigheden verder te brengen dan de basis en te ontwikkelen tot een krachtig onderdeel van je data science-toolkit. In de lessen gebruiken we twee interessante open datasets om verschillende soorten data te behandelen (verhoudingen, puntdata, enkele verdelingen en meerdere verdelingen) en bespreken we de voor- en nadelen van de meestgebruikte visualisaties. Daarnaast bekijken we minder gangbare alternatieven voor deze datatypes en hoe je standaardinstellingen van ggplot kunt finetunen om je boodschap zo efficiënt en effectief mogelijk over te brengen.

Introduction to Data Visualization with ggplot2

Leer effectief gegevens over te brengen met grafieken, alternatieve visualisaties en stijlaanpassingen.

Wanneer gebruik je staafdiagrammen

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