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Effective Data Visualization with Altair

Make charts that say something true, clearly, to the reader you have in mind, and finish with one from your own data that you can defend.

You go at your own pace, with a 1:1 tutor on every page. Ask it anything about the course, and it asks you questions too.

29 skills · 12 lessons

$30

Presale · The first module is on its way.

I'm opening the course one module at a time. When every module is out, the course will be $80. What you pay today covers all of them.

Comes with a 1:1 tutor and $15 to spend on it.

What you'll be able to do

Each box is a skill. The base is at the bottom, recognizing and explaining, and you work your way up to building something of your own and judging what works and why.

  1. Evaluate

    • Defend visualization design decisions with reference to principles and audience

      Builds on:

      • Critique a visualization using multiple frameworks simultaneously
      • Analyze audience needs and reading context for a visualization

      Your tutor asks you to judge when it fits and why and saves it as evidence when you do.

  2. Synthesize

    • Revise and improve a visualization in response to critique

      Builds on:

      • Critique a visualization using multiple frameworks simultaneously
      • Customize chart aesthetics in Altair: themes, colors, titles, axis labels

      Your tutor asks you to build something of your own with it and saves it as evidence when you do.

    • Articulate effective visualization norms and expectations within one's own field

      Builds on:

      • Encode provenance, uncertainty, and human context into a visualization
      • Critique a visualization using multiple frameworks simultaneously

      Your tutor asks you to build something of your own with it and saves it as evidence when you do.

    • Produce a portfolio-ready visualization with written defense of design decisions

      Builds on:

      • Revise and improve a visualization in response to critique
      • Defend visualization design decisions with reference to principles and audience

      Your tutor asks you to build something of your own with it and saves it as evidence when you do.

  3. Analyze

    • Analyze audience needs and reading context for a visualization

      Builds on:

      • Explain why visual encoding aids cognition over text or tables

      Your tutor asks you to break a problem down with it and saves it as evidence when you do.

    • Identify chartjunk and non-data ink in real-world visualizations

      Builds on:

      • Explain Tufte's data-ink ratio and its implications for design

      Your tutor asks you to break a problem down with it and saves it as evidence when you do.

    • Critique a visualization using multiple frameworks simultaneously

      Builds on:

      • Apply Tufte's principles to simplify and clarify a chart
      • Match chart type and encoding to communicative intent and data structure
      • Apply humanizing strategies — context, individuality, emotion — to a dataset
      • Customize chart aesthetics in Altair: themes, colors, titles, axis labels

      Your tutor asks you to break a problem down with it and saves it as evidence when you do.

  4. Apply

    • Create a basic chart in Altair from a tidy dataset

      Builds on:

      • Explain the grammar of graphics: marks, encodings, scales, and coordinate systems

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

    • Use Altair encoding channels: x, y, color, size, shape, tooltip, facet

      Builds on:

      • Create a basic chart in Altair from a tidy dataset

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

    • Select appropriate mark types in Altair for the data and intent

      Builds on:

      • Create a basic chart in Altair from a tidy dataset

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

    • Apply Tufte's principles to simplify and clarify a chart

      Builds on:

      • Identify chartjunk and non-data ink in real-world visualizations

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

    • Match chart type and encoding to communicative intent and data structure

      Builds on:

      • Explain Cairo's framing of chart types as a visual language with dialects
      • Explain how human perceptual limits affect chart comprehension
      • Analyze audience needs and reading context for a visualization

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

    • Apply humanizing strategies — context, individuality, emotion — to a dataset

      Builds on:

      • Articulate Lupi's Data Humanism philosophy and its critique of pure efficiency

      Your tutor asks you to use it on a new case and saves it as evidence when you do.

  5. Understand

    • Explain why visual encoding aids cognition over text or tables

      Builds on:

      • Define data visualization and its communicative purpose

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

    • Explain the grammar of graphics: marks, encodings, scales, and coordinate systems

      Builds on:

      • Define data visualization and its communicative purpose

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

    • Survey Tufte, Cairo, and Lupi as complementary frameworks

      Builds on:

      • Define data visualization and its communicative purpose
      • Explain why visual encoding aids cognition over text or tables

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

    • Explain Tufte's data-ink ratio and its implications for design

      Builds on:

      • Survey Tufte, Cairo, and Lupi as complementary frameworks

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

    • Identify and explain visual variables: position, color, size, shape, texture

      Builds on:

      • Survey Tufte, Cairo, and Lupi as complementary frameworks

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

    • Explain how human perceptual limits affect chart comprehension

      Builds on:

      • Identify and explain visual variables: position, color, size, shape, texture

      Your tutor asks you to explain it in your own words and saves it as evidence when you do.

  6. Remember

    • Define data visualization and its communicative purpose

      Your tutor asks you to recognize and recall it and saves it as evidence when you do.

What we'll cover

  1. 1. What is Effective Data Visualization?

    4 pages to come

    Opens as soon as it's ready.

    1. Welcome
    2. The four questions
    3. A gallery of the unexpected
    4. Your working definition

  2. 2. The Anatomy of a Chart and Hello Altair

    4 pages to come

    Opens as soon as it's ready.

    1. Set up Altair and the dataset
    2. The anatomy of a chart
    3. Altair as sentences
    4. Write your first chart

  3. 3. Grammar of Graphics

    3 pages to come

    Opens as soon as it's ready.

    1. The grammar of graphics
    2. First exploration: life expectancy
    3. Data types in practice

  4. 4. Who Are You Making This For?

    3 pages to come

    Opens as soon as it's ready.

    1. The same chart, different audiences
    2. Meet the three lenses
    3. The portfolio seed

  5. 5. The Efficiency Lens — Tufte

    3 pages to come

    Opens as soon as it's ready.

    1. The data-ink ratio
    2. Identifying chartjunk
    3. Apply the lens to your own chart

  6. 6. The Language Lens — Cairo

    4 pages to come

    Opens as soon as it's ready.

    1. Visual variables
    2. How humans perceive charts
    3. Chart types as vocabulary
    4. Choose and defend

  7. 7. The Human Lens — Lupi

    4 pages to come

    Opens as soon as it's ready.

    1. What is Data Humanism?
    2. What a correct chart leaves out
    3. Add humanity to your chart
    4. Carry forward: your field and the three lenses

  8. 8. Shaping Your Data in Altair

    4 pages to come

    Opens as soon as it's ready.

    1. Transforms as questions
    2. Filter, aggregate, calculate
    3. A table is a display too
    4. Layering

  9. 9. Color, Annotation, and Finishing

    3 pages to come

    Opens as soon as it's ready.

    1. Color with purpose
    2. Annotation and titles
    3. Finishing in Altair

  10. 10. Critique and Iteration

    4 pages to come

    Opens as soon as it's ready.

    1. How to critique
    2. Critique a published chart
    3. Critique your own chart
    4. Iterate

  11. 11. Effective Visualization in Your Field

    3 pages to come

    Opens as soon as it's ready.

    1. What good looks like in your field
    2. Finding your dataset
    3. A first sketch with your data

  12. 12. Produce and Defend

    4 pages to come

    Opens as soon as it's ready.

    1. Production
    2. The written defense
    3. The Socratic defense
    4. The return to Lesson 1

A tutor that knows this course

  • It always knows which page you're on.
  • It works from the skills I picked for this course, the ones on the map above.
  • Ask it how you're doing, and it tells you what you've already shown and what comes next.

What you get

  • 12 lessons, 43 pages. I'll open the next modules as each one is ready.

  • A 1:1 tutor, and $15 of credit for your questions.

    Each question uses a little, more when the conversation runs long. When the credit runs out, the course material stays open to you.

Who's teaching you

Sergio Sánchez

Data visualization is what I love most. It's how I get an idea from my head into yours as clearly as I can, so that's where I started. With a tutor on every page, this is the first time I feel we can teach well at scale, and I'm excited to share this course with you.

I'm Sergio, chekos online. I've worked with data for about ten years, mostly at mission-driven organizations: policy research first, then education, and now early childhood services. In 2018 I started tacosdedatos to share what I was learning, and since then it's been a blog, a podcast, courses, guides, and a community. These days I spend a lot of my time building with AI agents and writing about how I organize my work around them. I share what I've learned; you take what's useful and make it yours.

See you in the course

Effective Data Visualization with Altair

$30

Presale · The first module is on its way.

I'm opening the course one module at a time. When every module is out, the course will be $80. What you pay today covers all of them.

Comes with a 1:1 tutor and $15 to spend on it.