In this video we walk through some examples of what not to do when creating visualizations.

The themes that come out of the examples are:
- Avoid information overload
- Don’t be misleading
- Make your graphs easy to read

Next we address techniques to fix these common issues. Some strategies to implement include stepping your audience one-by-one through components of a graph, smartly using coloring & opacity to highlight what’s important, and maximizing your data-ink ratio.

Some other tips can be summarized as:
- Line charts are good for showing trends over time (but avoid spaghetti graphs!)
- Bar charts are best to highlight differences between categorical variables
- Generally avoid pie charts, donut charts, and 3d charts

In preparing for this lecture, a few different sources were consulted...

Storytelling with Data (Cole Nussbaumer Knaflic): https://www.storytellingwithdata.com/books
How to Speak (Professor Patrick Winston): https://youtu.be/Unzc731iCUY

Other resources:

Keith’s YouTube channel: https://www.youtube.com/@keithgalli
Reddit (Data is Beautiful): https://www.reddit.com/r/dataisbeautiful
Reddit (Data is Ugly): https://www.reddit.com/r/dataisugly

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Video timeline:
0:00 - Introduction & video overview
1:24 - 1. Avoid Information Overload
4:42 - 2. Don't be misleading
6:44 - 3. No hard-to-read graphs
8:15 - Fix information overload (step through components one-by-one)
10:30 - Strategic use of color & opacity
12:05 - Maximize the data-ink ratio
14:23 - Being honest with your visualizations
15:42 - Improving hard-to-read visuals (graph selection, z-pattern)
17:55 - Resources used to prepare this lecture
20:07 - Final thoughts!
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