This morning I keynoted a conference in Tallahassee. Data visualizers who critique others before critiquing themselves make me gag, so I opened my talk with a trip down memory lane.

Check out this beauty from one of my earliest jobs. I’ve anonymized it but 99.9% of my work from this period had this look and feel, i.e., an overly-labeled graph that I made in Excel and pasted directly into Word without any editing at all.

Redundancies made my graph look more complicated than it really was.

  • The title and the y-axis label were redundant.
  • The numeric labels on each data point and percentages listed down the y-axis scale were redundant.
  • If we’re going to label individual values on the graph, then we no longer need grid lines.
  • The full time period is unnecessary. This graph’s viewers–decisionmakers in a state education agency–would know that ’08-’09 means the 2008-2009 school year.
  • The markers (tiny squares) along with the numeric labels are redundant.
  • The control group’s dotted line and gray color are redundant. I often use dotted lines to represent projections so I removed the dotted lines here.
  • The legend leads to unnecessary zig-zags around the page. Direct labels are faster to read and hold up better in black/white printing scenarios.
  • And so on…

At the time, I adored these graphs because each graph represented hours of data cleaning and good ol’ fashioned hard work. I knew so much about number-crunching but so little about graph-making, and I was probably too tired after all the analysis to even think about the visualization. Plus, this was 2008. Let’s be honest. Everyone’s graphs looked like this in 2008.

Recently, I’ve been showing you one tip at a time, like deciding how far you’ll stretch your scale, whether you’ll use a regular or stacked chart, and whether your chart will be oriented vertically or horizontally. Today, let’s check out how lots of small edits–small deletions, in this case–add up to completely makeover your graph.

Continue scrolling for the play-by-play edits:

Intentional subtraction still blows my mind every time.

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