CSE 163

Data Visualization

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Arpan Kapoor�Summer 2026��💭Icebreaker (discuss with neighbors):

How is your summer going so far?

Add to our Slido!

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Announcements

• Programming Practice 2 and Homework 2: Pokemon due this week (Thu/Fri.)
• Programming Practice 3 and Homework 3: Education due next week (Thu./Fri.)
• Final Project Part 1: Proposal due Sun. July 19th
• Max group of 3
• Make sure to run flake8 on programming practice and homework submission files before submitting!

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Project Part 1

• Original data analysis
• Go beyond what you have shown in the homeworks
• Groups of max 3 people
• Proposal - what data are you using, what questions are you trying to answer, what are the motivations, and what is your plan?
• Due Sunday, July 19th

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Default Parameters

• Python lets you define default values for parameters in case a client does not pass a value for that argument

• This allows libraries such as pandas or seaborn to provide default parameters for their functions and initializer functions!

def greetings(to: str = 'world'):

return 'Hello ' + to + '!'

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greetings('Sarah') # 'Hello Sarah!'

greetings(to='Antonio') # 'Hello Antonio!'

greetings() # 'Hello world!'

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Python Data Visualization

• Many libraries exists for Python that allow you to do graphing and data visualization

• We will encourage seaborn since it is quickly becoming the standard for many data scientists
• We will still rely on matplotlib for some things
• You are welcome to use it in more depth on your project if you want to make more highly customized charts

• Two of the most popular graphing libraries for Python are
• matplotlib: extremely customizable
• seaborn: great out-of-the-box visualizations

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Encoding Effectiveness

[Mackinlay 86]

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Color Encoding Example

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Area Encoding Example

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Readability is Important!

Did the number of deaths go up or down after the law was enacted?

This graphic was posted in an articly by Business Insider

(graphic made by Reuters)

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How to Lie with Data Visualization

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How to Lie with Data Visualization

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Remember…

• Just because seaborn or matplotlib allow you to do something with your visualizations doesn’t mean that’s the most effective way to to present results.

• Be mindful of the ethical and conclusion implications that may come from presenting your data in a specific way.

• Be mindful of the color, font, and font size you use in your graphics
• Accessibility matters when it comes to graphics
• Good starting point for accessible color palettes.

• Data visualizations are meant to give us a relatively quick summary of your results. People should not be trying to decode what your visualization is saying.

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