Data Visualization Practical Guide

Data Considerations

  1. Does your data have categorical values present like type of program, user or funding source?
  2. Does your data have multiple quantitative values like amount spent, number of minutes?
  3. Does your data have a date field allowing you track measures over time?
  4. Do you have a target value for any measure?
  5. Do you need to benchmark your measures against peers?

Do you know what questions you expect your data to answer?

  • Who is the data primarily for?
  • What message do you hope to share?

Pie Charts

Purpose: Show proportion of values for handful of categories
Examples: Park Usage by Type of Person (Teams, Renters, Visitors, Participants)
Requirements: Categorical Measure + 1 Numeric Measure

Bar Charts

Purpose: Show values across some dimension
Examples: What is the trail usage by pedestrian and bicyclists?
Requirements: 1 Dimension + 1 Numeric Measure

Grouped Bar Charts

Purpose:  Show proportion of values for lots of categories
Examples: Park Usage by Recreation Program (Ballfields, Facility Rentals, Tennis Courts, etc.)
Requirements: 1 Dimension + 1 Categorical Measure + 1 Numeric Measure

Stacked Bar Charts

Purpose: Show value for some dimension across a categorical value
Examples: Road Condition over Time
Requirements: 1 Dimension + 1 Categorical Measure + 1 Numeric Measure

Timeline Chart

Purpose: Show how values change over time
Examples: Median Income, Rent over Time, Unemployment Rate
Requirements: Date + Numeric Measure

Combo Charts

Purpose: Show 2 measures at the same time that share same dimension like date with a bar chart + timeline chart
Examples: Compare quantity by dollar amount, compare target with measure
Requirements: Common dimension for x-axis, 2 numeric values for dual y-axes

Choropleths

Purpose: Show values for some dimension across geographies
Examples: Median Income, Rent, Commute Time for Washington Counties or County Tracts
Requirements: 1 Numeric Measure + 1 Spatial Value + Boundary File (spatial lens)

Data Visualization Suitability Report

Review all datasets to see whether data types support a visualization type.

Datasets without a Number or Date

These datasets may have an incorrect data type set for a field or has not been published yet.

Datasets without a Priority Area

Metadata check to ensure that all datasets supporting a priority area are easily discoverable.

Additional Resources

Visualization & Exploration

Articles


Publish and Visualize Data