Day 158 of 180 Days of Data Viz Learning #jfdi #dataviz

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.

Three Takeways

Chapter 2 Information Visualization Data Flow

  • Selections and data – think of sequence of load-> Format -> Measure- > Create -> Update p 57
  • “The .insert() function is a sister function to .append(), but .insert() gives you control over where in the DOM you add the new element.  You can also perform an append or insert directly on a selection, which adds one DOM element of the kind you specify for each DOM element in your selection.” p 59
  • “‘Multivariate’ is another way of saying that each data point has multiple data characteristics” p 67

Chapter 6 Network Visualization

  • Degree is degree centrality refers to the total number of links that are connected to a node.  Degree is rough measure of importance of node in a network – weighted degree is the total value of connections to a node p 192
  • “Everytime you start the force() layout, D3 computes the total number of links per node, and updates that node’s weight attribute to reflect that” p 192
  • Eg adding a button that re-sizes nodes based on weight attribute:
      • .on(“click”, sizeByDegree).html(“Degree Size”);
    • function sizeByDegree() {
      • force.stop();
      • d3.selectAll(“circle”)
        • .attr(“r”, function(d) { return d.weight * 2; });
        • };

Reading and Learning Data Visualization Theoretically/Critically:

Edward Tufte Visual Display of Quantitative Information

Chapter One Graphical Excellence
Three Takeaways
  • Think about ability to do parallel series using different visual encodings, eg chart of wheat p 34
  • “The problem with time-series is that the simple passage of time is not a good explanatory variable: descriptive chronology is not casual explanation” p 37
  • “An especially effective device for enhancing the explanatory power of time-series displays is to add spatial dimensions to the design of the graphic, so that the data are moving over space (in two or three dimensions) as well as over time. -> space-time-story graphics as an example with weighted time series lines and descriptors p 41

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