Part-to-whole charts show how partial elements add up to a total.

Use cases include:

Consolidated revenue of product categories
Budgets

Part-to-whole

Distribution charts show how often each values occur in a dataset.

Use cases include:

Population distribution
Income distribution

Distribution

Multiple types of charts can be suitable for depicting data. The guidelines below provide insight into how to choose one chart over another.
- Showing Change Over Time
- Bar and Pie Charts
- Area Charts

Selecting Charts

Relationship charts show how multiple items relate to one another.

Use cases include:

- Social networks
- Word charts
- Types of Relationship Charts

Relationship Charts

Flow charts show the movement of data between multiple states.

Use cases include:

- Fund transfers
- Vote counts 
- Election results

Flow Charts

Change over time charts show data over a period of time, such as trends or comparisons across multiple categories.

Common use cases include:

- Stock price performance
- Health statistics
- Chronologies

Change Over Time Charts

Category comparison charts compare data between multiple distinct categories.

Use cases include:

- Income across different countries
- Popular venue times
- Team allocations

Category Comparison Charts 

Ranking charts show an item’s position in an ordered list.

Use cases include:

- Election results
- Performance statistics

Ranking Charts

Correlation charts show correlation between two or more variables.

Use cases include:

Income and life expectancy

Correlation Charts

- Change over time
- Category comparison
- Ranking
- Part-to-whole
- Correlation
- Distribution
- Flow
- Relationship

Arizona State University

University of Michigan - Ann Arbor

- Data visualization can be expressed in different forms.
- Charts are a common way of expressing data, as they depict different data varieties and allow data comparison.
- The type of chart you use depends primarily on two things:
- The data you want to communicate
- What you want to convey about that data
- These guidelines provide descriptions of various different types of charts and their use cases

Types of Data Visualization 

Data visualizations use custom styles and shapes to make data easier to understand at a glance, in ways that suit the user’s needs and context.

Charts can benefit from customizing the following:

- Graphical elements
- Typography
- Iconography
- Axes and labels
- Legends and annotations

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