Visualization Best Practices in R
| Course Details | ||||||||
|---|---|---|---|---|---|---|---|---|
|
||||||||
| Languages | ||||||||
|
||||||||
| Outcomes | ||||||||
|
||||||||
| Price & Terms | ||||||||
|
||||||||
| Technical | ||||||||
|
||||||||
| Specification | ||||||||
|
||||||||
Learn to choose and refine ggplot2 charts in R for proportions, single values and distributions, weighing common plots against less common alternatives.
A chart built on ggplot2’s defaults can still blur the point it is meant to make, and the most familiar chart types each come with trade-offs. Working with two open datasets, one of them on disease, you weigh the strengths and weaknesses of common plots for shares, single values and the spread of data. You also try less common alternatives and adjust default settings so each chart gets its message across quickly and clearly.
What You Will Achieve
- Show the shares of a whole with a tidied pie or waffle chart, and switch to stacked bars when several proportions need comparing.
- Tell when a bar chart suits single-observation data and when an ordered point chart works better.
- Pick a histogram bin width that suits the data and recognize when a smooth density curve tells the story better.
- Compare several groups with plots that show their spread in more detail than a plain box plot.
Program Overview
Charting Proportions of a Whole
Opens with a grammar of graphics refresher and the disease data, then weighs pie charts against waffle charts and stacked bars for showing parts of a whole.
- Grammar of graphics and data wrangling warm-up
- The pie chart and its cleanup
- Waffle charts
- Stacked bars ordered for readability
Point Data and Perception-Based Tuning
Looks at when bar charts suit single-observation data, what to use when they do not, and small changes that make a chart easier to read.
- Bars versus dots for single observations
- geom_col and geom_bar
- Ordered point charts with visual anchors
- Faceting, flipped axes and cleaner bars
Single and Multiple Distributions
Tests how fragile histograms are, when a kernel density plot works better, and how to compare many distributions without relying on a traditional box plot.
- Histogram bins and density scaling
- Kernel density estimates with a rug
- Box plots improved with jitter
- Beeswarm, violin and ridgeline plots
Certificate Awarded (Paid)
Job Outlook
Clear chart choices in R matter wherever analysts and data scientists share findings through plots, such as written reports, research summaries and presentations to colleagues.
Good for: R users who already make ggplot2 charts and want firmer reasons for picking one chart type over another for each kind of data.
Keep in mind: Every exercise is written in R with ggplot2, so learners who chart in other tools take away the reasoning but not code they can reuse directly.
Bottom line: Its strength is a frank look at familiar charts, including a defense of the pie chart and a warning about box plots, with a better option shown for each.
Frequently Asked Questions
What data do the lessons work with?
The lessons work through two open datasets, and the first chapter introduces one of them as disease data. Returning to the same data lets you see how different chart types handle proportions, single observations and distributions.
Does the course defend pie charts?
Yes, in part. The first chapter argues that pie charts are not as bad as their reputation, shows how to clean one up, and sets it beside waffle charts and stacked bars for comparing several proportions.
How does the course handle histograms?
The third chapter shows how fragile histograms can be, then works on bin numbers, bin width chosen by context and a density y-axis. It ends with a move to kernel density plots, including a rug of data points and large datasets.
What does the course do about box plots?
The final chapter calls the traditional box plot dangerous and improves it with jittered points and faceting. It then pairs boxes with violin plots and turns to beeswarm and ridgeline plots for comparing many or spatially related distributions.
User Reviews
Write your review
You must be logged in to post a review.
Reviews can only be posted by registered learners. Log in or create a free account, then you will return here to post.
There are no reviews yet.