Day 54 of 180 Days of Data Viz #jfdi

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.

Knight Journalism Course for the Americas:  Data Visualization and Infographics with D3! 

Code Learning:

Scott Murray From Bar Chart to Scatterplot

Three Takeways:

  • Started getting a thought process down on how to approach building a new visual -> eg starting at x y coordinate and moving to changing variables
  • Look in dev console for missing pieces and change code blocks bit by bit, there’s a tendency with D3 to want to make a lot of changes at once – at least on my end, but don’t forget coding fundamentals when approaching these problems
  • The console is your friend in testing out changes to scales and domains
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Day 53 of 180 Days of Data Viz Learning #jfdi

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.

Knight Journalism Course for the Americas:  Data Visualization and Infographics with D3! 

Reading and Learning Data Visualization Theoretically/Critically:

Alberto Cairo Lecture Insightful Data Viz Module 5

Takeways:

  • John Snow visual review  – > first data viz, bar chart pattern, looking at data points that refute hypothesis
  • Look for exceptions in visuals to verify methodology
  • Symbiosis between words and visuals -> annotations crucial to narratives  -> prevent from people from drawing wrong conclusions
    • Particularly needed for multi-section visuals
    • NYT and Pew do really good job by putting in text and story
    • Sequencing info “The upper layer” to giving a broad view and context to “layering down” and give multiple ways of exploring maps
  • “Splitting-a-sentence” strategy – > write headers as if they were a very long sentence that describes entire process and sequence and find natural breaks and transform each one of portions into headers of each section

Day 52 of 180 Days of Data Viz Learning #jfdi

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.

Reading and Learning Data Visualization Theoretically/Critically:

Knight Journalism Course for the Americas:  Data Visualization and Infographics with D3! 

Alberto Cairo Lecture Part 3 Functional Visualization to End

Takeways

  • If you need to read every single number – the chart is useless
  • Pie charts are not good for comparing changes – > only really good for simple share of total
    • Slope charts the solution
  • It’s difficult to estimate differences in area graphics -> they minimize differences.  People can’t really tell a bubble is 5x as large, for example.
    • Area graphics are more good for general patterns
      •  e.g. general geographic pattern on a map
  • Encode the same dataset in multiple ways -> e.g. bubble graph + table
  • Don’t try to cram too much data into a single chart.  In many cases, a “small multiple” (some call stacked matrix) display is the best solution

Day 51 of 180 Days of Data Viz #jfdi

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.

Visualization Worked On or Created: 

Come to a realization that I’m not understanding some things – particularly formatting, as well as I thought, but I do understanding other topics, such as data munging, a lot better.

Attempt (without axes bc I can’t get them to scale correctly) at looking at Water Usage for the Fiscal 12/13 Year of Hundred Cubic Feet per LA City Zipcode

Code Learning:

Knight Journalism Course for the Americas:  Data Visualization and Infographics with D3! 

Three Takeways from Module 4 Scaling and Axes (covering topics I thought I knew well but apparently do not so just ret-typing for remembering).

  • The proper sequence of methods to use when binding data and creating new elements from data: .selectAll()data()(enter()append()
  • “Dom is current state of memory of a web page that can different from page’s source and CSS”
  • Ordinal Scales have a discrete domain, such as set of names or categories -> values must be coercible to a string, and the stringified version of the domain value uniquely identifies with the corresponding range value
    • + symbol means “take this value and use it as a number” after a return statement

Day 50 of 180 Days of Data Viz Learning #jfdi

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. 

Reading and Learning Data Visualization Theoretically/Critically:

The Best American Infographics 2014 “The Material World” Section p. 137

Three Takeways:

  • Colored maps plotting data points eg race rather than typical geographic barriers and maps in general under a data viz renaissance p 138
  • Map stack as a tool p 135
  • Using colors in bar charts to represent flow of a narrative p 140

Day 49 of 180 Days of Data Viz Learning #jfdi

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. 

Reading and Learning Data Visualization Theoretically/Critically:

The Best American Infographics 2014 “The Material World” Section p. 99-137

Three Takeways:

  • Using a mix of maps and drawn images as a mixed method seems to one of the most effective at creating compelling visuals in the compilation p 106
  • Using line thickenness combined with symbols to add dimension to anotherwise flat linear image (describing tornado strength) p108
  • Somber two tone color visuals are most effective at contrast and understanding (drone attacks info graphic) p. 136

Day 48 of 180 Days of Data Viz Learning #jfdi

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. 

Reading and Learning Data Visualization Theoretically/Critically:

The Best American Infographics 2014 “Us” & “The Material World” Section p. 84-98

Three Takeways:

  • Combining a cultural symbol (in this case a poppy) and using it as a line element in a graph to show war deaths creates emphasis p. 87
  • Using a sunburst and shapes in the sunburst to talk about branching categories (in this case cheese) p. 91
  • Heat maps in shapes – keyboards with color hue encodings to describe music p. 97