Day 173 of 180 Days of Data Viz Learning #jfdi #dataviz #doneisbetterthanperfect

I’m doing some form of data visualization learning for 180 days because I need to #JFDI.

See post explaining how and why I’m doing this.

Eljiah Meeks D3.js in Action

Chapter 4 General Charting Principles 

Three Takeways Today

  • Elements of an axis created from d3.svg.axis are:
    1) <path.domain> with a size equal to size of axis
    2) <g.tick.major> contains <line> and <text> for each major tick
    3) <line.tick.minor> for each minor tick
    g element is called when these elemnets are created
    p 113
  • Use d3.scale.quartile() to create a box plot p 117
  • “It’s a good rule to always use the <g> elements for your charts, because they allow you to apply labels or other important information to your grpahicl representations. But that means yo’ull need to use the tranform attribute, which is how <g> elements are position on the canvas. Elements appened to a <g> base their coorindates off of the coordinates of their parent. When applying x and y attributes to child elmenet,s you need to set them relative to the parent <g>.” p 119

Reading and Learning Data Visualization Theoretically/Critically:

Chapter 2 Simple Statistics to Get You Started
Three Takeaways Today
  • Quantitative stories include two types of data: 1) Quantitative 2) Categorical p. 20
  • “If more than two values appear more than once with the same high degree of frequency, the set is multimodal.  Modes are rarely useful for most data presentation purposes” p 24
  • Frequency polygon uses a line to map the frequency of instances that occur for each value from lowest to highest p 28
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