Understanding Heat Maps

In this module, we’re exploring heat maps - a visualization that uses color intensity or patterns to show relationships between two categorical variables.

A heat map is like a grid or table where:

• Rows represent one category
• Columns represent another category
• Each cell shows a value through color intensity or pattern
• Higher values typically have stronger intensity
• Lower values typically have lighter intensity

Think of it like a temperature grid of a room, where each square represents how warm or cool that spot is.

Structure of a Heat Map

1. Grid Layout:
   • Rows and columns form a matrix
   • Each cell represents an intersection
   • Labels on both axes identify categories
2. Values Representation:
   • Numerical values in each cell
   • Color intensity shows magnitude
   • Patterns can replace colors for accessibility

Example: Weekly Activity Schedule

Let’s explore a student’s weekly activity levels across different times:

• Days (Rows):
  • Monday through Friday
• Time Slots (Columns):
  • Morning (8-12)
  • Afternoon (12-4)
  • Evening (4-8)
• Activity Levels (Cell Values):
  • High: 8-10 hours (intense)
  • Medium: 4-7 hours (moderate)
  • Low: 0-3 hours (light)

Common Applications

1. Time-Based Patterns:
   • Weekly schedules
   • Monthly activities
   • Seasonal variations
2. Correlation Matrices:
   • Relationship strength between variables
   • Pattern identification
   • Cluster analysis
3. Geographic Data:
   • Population density
   • Weather patterns
   • Economic indicators

Common Patterns to Listen For

1. Clusters:
   • Groups of similar values
   • Hot spots (high values)
   • Cold spots (low values)
2. Gradients:
   • Smooth transitions
   • Value progression
   • Directional changes
3. Outliers:
   • Unexpected high values
   • Unexpected low values
   • Irregular patterns

Reflection and Exploration

Think about data that could be shown in a heat map:

• Your daily schedule
• Monthly expenses by category
• Activity levels throughout the day