Introduction

Data visualization tells a story and sometimes these stories don't require an axis. The components making up the chart are used to represent scale in their own dimension. This helps to find more relationships and patterns in a dataset. In this guide, we will explore few charts which are used for comparing dataset and don't use scale of an axis.

For more information on Comparing Visualization Types for Your Data check out my previous guide.

- Use: Display proportions and percentages by dividing a circle
- The arc length of a pie represents the proportion
- The full circle represents the total sum
- If the number of proportions are very high, then it this is not a good choice for visualizing your data
- Purpose: To get a quick idea of the proportional distribution of the data

- Use: Display flow and data quantities in proportion to one another
- The width of the lines represent the magnitude of the quantity, so the thicker the line the higher it's magnitude
- Each category is represented by a line-set and the proportions of that category are represented by the relative thickness of lines in one line-set
- Purpose:
- Compare the flow of different quantities in one category
- Represent flow of many to many cases or many to one cases
- Display flow of resources across projects

- Use: Display variance across multiple variables
- All rows are one category and all columns are one category
- All rows and columns are divided into subcategories
- Each cell contains color-coded categorical data
- Each heatmap has a legend
- Purpose:
- Find similarity in variables
- Find correlation between data-sets
- If one row or columns is a time interval, then changes occur across time
- Generalized view of the numerical data
- Not a very accurate view because it is difficult to tell the exact difference in color shades

- Use: Compare relationships or similarities between datasets or different groups of data
- The connections between entities are used to display any relation or something in common
- Along the arc of the circle, the different variables are represented and relationships between them are represented using arcs or Bézier curves
- The size or thickness of each arc represents the value of each connection
- To group relationships between different categories, colors are used to code the arcs
- Purpose:
- Visualise inter-relationships between entities
- Find similarities between datasets

- Use: Display quantities for each category area, while also visualizing the hierarchical structure of the data
- The categories are represented by rectangles and the rectangles are nested under other rectangles to represent categories and subcategories
- The size of the area of the parent category is the total of the subcategories
- The area of a category is represented relative to the parent category and to the other categories grouped together with it
- Initially it was developed to visualize size of files on the computer
- Purpose:
- Space efficient option to display hierarchies
- Gives a quick overview of the structure of the data