Data Visualization Basics
Lesson 1 of 2
  1. 1
    Welcome! The field of data visualization has taken off in the last twenty years or so. People in all kinds of professional fields make data viz – from news media to business analysis – and most o…
  2. 2
    The first step of making a data visualization is choosing a chart type. Chart type isn’t our only tool when it comes to visualizing data, but it’s an important one for communicating about the relat…
  3. 3
    One big consideration when choosing a chart type is how many variables we’re comparing. Univariate charts help us visualize a change in one variable. Often that means measuring “how much,”…
  4. 4
    Next up, bivariate and multivariate charts! These charts show the relationships between two or more variables. The classic bivariate example is the scatter plot – one variable on the x-axis, anot…
  5. 5
    We’ve covered how we use chart type to highlight a relationship in the data. Now we’ll talk about how we use aesthetic properties to further clarify and visualize the “details” of the data. Aesth…
  6. 6
    Let’s take a closer look at this graph. There’s a connection here between size and y-position (how high or low a circle is): they actually tell us the same information twice! This is an example of…
  7. 7
    The best data visualizations help us to understand what’s in the data, draw meaningful conclusions, and make decisions about next steps. This requires context, though, and **different context is ap…
  8. 8
    We tend to think of context as “outside” a data visualization, but Shinji, Paola and Raj had the right idea by including appropriate context using titles and annotations. Each of them also did a gr…
  9. 9
    Now that we can make some visualizations, let’s talk accessibility to make sure our work reaches everyone who wants to interact with it! The most commonly discussed accessibility concern is color,…
  10. 10
    In the last exercise we covered accessibility guidelines specifically related to vision access – using color palettes, fonts, and alt-text to ensure that people across the vision spectrum can acces…
  11. 11
    Last up, we’re talking authorship. When Paola made the visualization for Sir Avon, at first she included fewer details and took out her annotations about points of interest. She assumed there was…
  12. 12
    We made it! This lesson covered everything you need to know to start designing data visualizations that look great, communicate effectively, and treat data ethically. Here’s a recap of what we tal…

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