Quantitative data is numerical information that can be measured or counted. It includes discrete values, such as 16 employees, and continuous values, such as a temperature measured as 16.8°C. section 3.1.2
Classify quantitative data before choosing visual encodings or D3 scales:
- Treat whole-number counts as discrete data; treat values that remain meaningful when subdivided as continuous data. section 3.1.2
- Use position, length, area, angle, or continuous color to represent numerical attributes. section 14.2
- Pair quantitative values generally with D3 scales using continuous domains, such as linear scales. section 3.1.2 section 3.4.1
Planning a visualization
List every dataset attribute, label each as quantitative or qualitative, and brainstorm an encoding for the main numerical attributes. A timeline can position paintings, bars can show drawing counts, and an area chart can show letters over time. section 14.2 section 14.0
Figure 14.1 We can group data into two main categories: quantitative (numerical information) and qualitative (nonnumerical information). Quantitative data is discrete or continuous, while qualitative data is nominal or ordinal.
Use the classification diagram to distinguish quantitative data from qualitative data, then separate numerical values into discrete and continuous forms. section 14.2
