Data Visualization

Designing Data Visualizations

Data Visualization

The terms data visualization and information visualization (casually, data viz and infoviz) are useful for referring to any visual representation of data that is:

  • algorithmically drawn (may have custom touches but is largely rendered with the help of computerized methods);
  • easy to regenerate with different data (the same form may be repurposed to rep-resent different datasets with similar dimensions or characteristics);
  • often aesthetically barren (data is not decorated); and
  • relatively data-rich (large volumes of data are welcome and viable, in contrast to infographics).

Encoding for your data type

Figure 4-3

Visual properties grouped by the types of data they can be used to encode.

Figure 4-4

Periodic Table of Elements

Figure 4-10

Healthcare plan

Figure 4-15

healthcare

Quantitative and comparative formats

  • Bar graphs
  • Histograms
  • Line graphs
  • Time series
  • Pie graphs
  • Scatter plots
  • Tables
  • Periodic tables
  • Treemaps
  • Heatmaps
  • Small multiples
  • Marimekko (also known as matrix or mosaic) graphs

Relational formats

  • Data flow diagrams, Entity Relationship Diagrams, etc.
  • Decision maps and flow charts
  • Social network graphs

Spatial formats

  • Geographic map
  • Non-geographic map

Apply Your Encodings Well

  • Color
    The recommended set of 12 colors is shown in below table. It is preferred to use colors from the first half of the list before moving on to the second half.
ID Colors
1 red
2 green
3 yellow
4 blue
5 black
6 white
7 pink
8 cyan
9 gray
10 orange
11 brown
12 purple
  • Size
  • Text and Typography
  • Fonts and Hierarchies
    Serif fonts (fonts with ornamental shapes at the ends of letters, such as Times, Cambria, or Garamond) are better for setting blocks of text, while sans serif fonts (fonts with clean line endings, such as Helvetica, Arial, or Verdana) are better for titles, tags, and labels. Stay away from gothic fonts, fantasy fonts, and script fonts(such as Comic Sans,see this).
    BTW, Tips on fonts.
  • Shape
  • Icons
  • Lines
  • Weight
  • Endings
  • Pattern
  • Path
  • Taper

References

Designing Data Visualizations