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Lecture 7

Charts

DATA 8

Fall 2023

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Announcements

  • HW 3 has been released and is due Wednesday (9/13)
    • Submit by Tuesday at 11pm for extra credit
  • Lab 3 is due tonight at 11pm

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Weekly Goals

  • Wednesday
    • Table review
    • Working with Census data
  • Today
    • Visualizing data
    • Distributions

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Attribute Types

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Types of Attributes

All values in a column of a table should be both the same type and be comparable to each other in some way

  • Numerical — Each value is from a numerical scale
    • Numerical measurements are ordered
    • Differences are meaningful
  • Categorical — Each value is from a fixed inventory
    • May or may not have an ordering
      • Examples of ordered categorical values?
    • Categories are the same or different

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“Numerical” Attributes

Just because the values are numbers, doesn’t mean the attribute is numerical

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  • Census example has numerical SEX code (0, 1, and 2)

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  • It doesn’t make sense to perform arithmetic on these “numbers”, e.g. (0+1+2)/3 is meaningless

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  • The attribute SEX is still categorical, even though numbers were used for the categories

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Numerical Data

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Plotting Two Numerical Variables

Line plot: plot

Scatter plot : scatter

(Demo)

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https://en.wikipedia.org/wiki/C-3PO

Anthony Daniels,

actor

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Line vs Scatter Plot

  • Use line plots for sequential quantitative data: if...
    • ...your x-axis has an order
    • ...sequential differences in y values are meaningful
    • ...there’s only one y-value for each x-value
    • Often: x-axis is time or distance
  • Use scatter plots for non-sequential quantitative data
    • If you are looking for associations

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  • t.plot(x_label, y_label)
  • t.scatter(x_label, y_label)

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Categorical and Numerical Variables

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Highest Grossing Movies as of 2017

(Demo)

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How Do You Generate This Chart?

Top 10 highest grossing movies

Number of years since release

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Visualization Fundamentals

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Don’t Do This

Source: Washington Post

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Do This Instead

Source: Ross Ihaka

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Good Practices

  • Less can be more
    • Minimize decoration
    • Choose colors carefully
      • Minimize the number of different colors
  • If data are numerical, preserve their relative values and distances between them

See Edward Tufte’s “The Visual Display of Quantitative Information”

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Importance of the Y-Axis