HT @dataelixir
In continuation to my previous post on #datavizualization
📌When it comes to reading a chart, it’s not only the actual chart but also the other supporting elements such as titles, subtitles, legends, scales, sources, etc. that makes a chart complete.
✍It’s critical to read them carefully to grasp what the chart is about, what is being measured, and how it’s being measured. Alberto Cario, in his book, suggests that to read a chart well, you must focus on:
The features that surround the content and support it —>the chart’s scaffolding—and
on the content itself —> how the data is represented or encoded. The scaffolding consists of features of the chart.
⚡If you struggle to read a chart or think of a suitable chart, you must spend some time developing graph literacy. Basically, you need to learn about visual encoding of the charts.
✍🏻For example, many times after getting some clarity on first step (selecting appropriate charts), learners are aware that they need to create stacked/grouped bar charts while plotting the distribution of two categorical variables.
When I ask them to write ggplot2 (I hope you’re familiar. If not, still you’ll get the context) code for the same, they put one variable on x-axis & other on y-axis. 🤦🏻♀
And of course, it will not work! (🛑 Pause reading & think WHY)
I hope you got it. It's not about the code but your understanding of chart elements 😃 .
👉 In a bar chart, the height/length of the rectangular bars basically represents counts/proportions/percentages.
👉 So one of the axes (usually the y-axis) has to have the counts, while the other axis will represent one of the categorical variables.
👉 As you’re planning to plot 2 categorical variables, you’ll either stack or group the categories of that second variable. Refer Image below 👇
Don’t forget to check the comment section for an awesome book to help you.
Booping absolutely borked my stats tracking
Attention Shapes!⚠️
CinnamationStudios is looking for new artists to come and help us out with an amazing indie animated project!
we will be choosing 20 of the best talented folks who apply to the roles listed in the Google form below^^✨️✨️
NOW'S YOUR CHANCE
optics 🧪
One of the really great ways that we encourage learning at Automattic - a data book club!
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