Comparing Visualization Types for Your Data

Sep 4, 2018 • 3 Minute Read

Plot Data Over a Continuous Interval

Use: Visualize distribution of data over intervals
Y axis datatype: Frequency of quantitative value per individual interval
X axis datatype : Timescale, series of intervals
Purpose:
- Find the distribution pattern
- Identify unusual values
- Find gaps in value ranges

Use: Compare variable across categories
The columns/bars can be vertical or horizontal
Y axis datatype: Discrete value scale
X axis datatype: Comparison of categories
Purpose
- Answer the questions like "How many in a category/bucket?"
- Compare categories

Use: Compare multiple variables across categories
Points are plotted on a Cartesian coordinate system
Each point represents a category or a label and are generally distringuished by colors
Area (not the radius) of the circle represents third variable
Y axis datatype: One variable
X axis datatype: Second Variable
Radius of bubble: Third variable
Purpose
- Comparison of three or four variables (color can also be used to denote a variable like category )
- Find patterns and correlations
- Get an overview of multi variable data

Use: Plot more than one data series
The point of one data series becomes the starting point for another series, so they stack up
It does not work on negative values
Y axis datatype: Value scale
X axis datatype: Intervals for data series
Purpose
- Compare multiple variables changing over an interval
- Compare the changes of different variables at different point
- Find relations / patterns between variables

Use: Plot multi variable data radially for good visual comparison
Each variable has its own axis which is radial
All axes have center as the common origin
All axes have equal distance and common scale
All points are connected together to form a polygon
Purpose
- Compare multi-variable data
- Find similar variables and outliers
- Find high and low scorers