The Value of Visualisation
Why create visualisation
- Answer questions
- Make decisions
- See data in context
- Expand memory
- Support graphical calculation
- Find patterns
Record information. Communicate that information to others and to analyse and support reasoning
Reasoning/Exploration - can answer questions you didn't know to ask
Key applications of IV
- Record Information
- Communications (presentation)
- Reasoning (analysis)
The Visualisation Process
Data Transformation - Create a structural model (schema), mapping raw data into data tables Visual Mapping - Create a visual spatial model, transforming data tables into visual structures View Transformations - Create views of the Visual Structures by specifying graphical parameters such as position, scaling, and clipping
Stages
- Acquire - Obtain the data, whether from a file on a disk or a source over a network
- Parse - Provide some structure to the data, and order it into categories
- Filter - Remove all but the relevant data
- Mine - Apply methods from statistics or data mining as a way to discern patterns or place the data in mathematical context
- Represent - Choose a visual model, such as a bar graph, list, or tree
- Refine - Improve the basic representation to make it clear and more visually engaging
- Interact - Add methods for manipulating the data or controlling what features are visible
R Introduction
- Functional programming language written primarily in C, Fortran
subset - extract subsets meeting some criteria
transform - add or alter column of a data frame
cut - cut a continuous value into groups