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.

Introduzione alla Grammar of Graphics

Prendere confidenza con i dati sulle malattie

Riscaldamento con il data-wrangling

Il grafico a torta e i suoi amici

La famigerata P-I-E

Pulire il grafico a torta

Che ne dici di un waffle?

Quando usare i grafici a barre

Barre impilate di base

Ordinare lo stack per leggibilità

Asse x categorico

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

Questo corso ti aiuterà a portare le tue competenze di visualizzazione dei dati oltre le basi, trasformandole in uno strumento potente del tuo toolkit di data science. Lezioni dopo lezione useremo due interessanti open dataset per coprire diversi tipi di dati (proporzioni, dati puntuali, distribuzioni singole e multiple) e discuteremo pro e contro delle visualizzazioni più comuni. Inoltre, vedremo alcune alternative meno diffuse per questi tipi di dati e come modificare le impostazioni predefinite di ggplot per comunicare il tuo messaggio in modo più efficiente ed efficace.

Introduction to Data Visualization with ggplot2

Impara a comunicare i dati con grafici comuni, visualizzazioni alternative e miglioramenti stilistici.

Il grafico a torta e i suoi amici

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