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Design checklist
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README.md

Data Studio Charting Checklist

You can see a few suggestions at http://designingviz.com/ which may or may not be reasonable. I also really recommend The Wall Street Journal Guide to Information Graphics, a pretty tiny book that is remarkably helpful at helping you not screw things up.

Micro-tutorials for Illustrator can be found at http://jonathansoma.com/lede/data-studio/, including how to open your Python files in Illustrator. Longer, detailed Illustrator tutorials can be found on Lynda.com, accessed for free through the Columbia portal.

Communicating successfully

Story

  • What am I supposed to take away from the graphic?
  • The graphic has a headline
  • The graphic explains what the data is
  • Typically, headline is editorialized and subhead explains what the data is
  • There is a focus to the graphic, for example:
    • Something to obviously pay attention to
    • Something(s) in a highlight color
    • An annotated point on a line
  • List the source of your data (usually in small text, bottom)
  • Be honest mathematically: use per capita when necessary
  • Can your graphic stand alone, outside of the story?

Annotations

  • What should someone be interested in? Mark interesting points, tell us a story.
  • Don't label every point, no one will pay attention
  • But if you have a lot of points or bars or something, you should probably label some of them so people know what to look at
  • Highlight background areas to talk about things that happen over time
  • Use a single line to talk about something that happened at one point in time
  • Do you draw a line to the interesting point? Or an arc? Or just put the text next to it?

Busy-ness

  • Clear hierarchy of what to pay attention to (more important = bigger, more colorful)
  • Do you have too many labels?
  • Do you have too many bars/lines?
  • You can combine smaller categories into an 'other' category if necessary
  • You don't have to show all of your datapoints, subsets or top/bottom is usually fine
  • No one knows what error bars, margin of error, or confidence intervals are. If you're using them, have a good reason
  • Matplotlib likes to put boxes around all of your charts. You probably can open them up.

Visual design

Color

  • Use nice colors! Steal a scheme from somewhere. Colorbrewer2.org is basic but good.
  • Things that aren’t important become grey, things that are important become bright/dark
  • Only using different colors if the colors mean something
  • Are you using the right kind of color scale?
    • Categorical for categories (e.g. different types of crimes)
    • Sequential for ordered numbers or categories (e.g. higher heat is darker red)
    • Diverging for moving away from a middle ground (e.g. voting Republican/Democrat, more/less red/blue)
  • Matching colors between text and elements on the page can look nice if they’re talking about the same thing
  • Legends and keys
    • Instead of using a legend, can you directly label what the points/colors/etc are?
    • Have your color categories be round numbers, not "dark blue is 145.4-156.2"

Axes

  • If years, not every year should be marked
    • if pandas is doing it, try converting year to integer before plotting
  • Ticks and grid lines at round numbers
  • No sideways labels!
  • No labels at all, if it can be avoided
  • Units attached to first/line number on axis
  • Do you really need to label that 0? Do you really need the highest label on the axis?
  • If it's money, you'll need a currency sign somewhere
  • Do you need that axis line? Maybe, maybe not.
    • Sometimes grid lines are better!
  • Don't repeat yourself with labels
  • Is the maximum and minimum reasonable?

Text

  • Pick nice fonts - search online for font combinations you like
  • Only a few sizes of text (e.g. title, subhead, axes, annotations)
  • Large enough and readable
  • Clear hierarchy between text elements - title > subhead > annotations > axes
  • Translate weird phrases or jargon from your dataset into "real people" words
  • Don't put background colors on text elements
  • Commas in thousands
  • Don't repeat yourself with labels

Specific Charts

  • Bars/columns
    • Order them by size
    • Should not have grid lines going in same direction as bars
    • Use labels on the bars instead of an axis if there aren't very many
    • No little tick line at the beginning of the bar (matplotlib and Illustrator both love to do this)
  • Line charts
    • If you're doing lines + dots on measurements, do you really need the dots?
    • Area charts for "stock" and line charts for "flow". Area means “stuff,” basically.
  • Maps
    • Only if there's a geographic trend (e.g. east coast looks different than west coast)
    • If it's the USA: Albers projection, not Mercator
  • Pie chart
    • Are you sure? Maybe do a single stacked bar instead, they look nicer (you can even do it in Illustrator real easy)
    • Four or fewer slices
    • Start with the biggest slice at twelve o’clock, then go in order
  • Small multiples
    • Each multiple is the same size with same axes
    • Each multiple is actually small
    • People can understand the measurements and axes
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