The Right Chart for your Data
Preset is capable of producing a wide variety of different visualizations based on how you want to convey your data. Some charts may be more appropriate based on what you want to show.
Here is a breakdown of the 5 categories of charts featured in Preset:
- Time Series Charts: These kinds of charts display data over time and are best used to discover trends and patterns. Examples of Time Series Charts include line charts, time series bar charts, and time series tables.
- Composition Charts: These kinds of charts show how data is distributed across a specific field and are best used to highlight volumetric trends, such as 'The Most...', 'The Least...', and 'Top 10' type charts. Examples of Composition Charts include bar charts, pie charts, and treemaps.
- Distribution Charts: These kinds of charts show how data is distributed across one or more fields and are best used to highlight data with multiple dimensionsal attributes. Examples of Distributions Charts include histograms, box plots, and horizon charts.
- Relationship Charts: These kinds of charts show the relationship between two or more variables and are often used to convey commonality, uncommonality, or cause & effect type relationships. Examples of Relationship Charts include pivot tables, heat maps, and bubble charts.
- Geospatial Charts: These kinds of charts show data on a geographical basis. Preset offers a wide variety of deck.gl based geospatial charts for large datasets, such as scatterplots, arcs, grids, and polygons.
How Do I Know What to Use?
Start by giving careful thought to the goals of your visualization. A good chart is able to answer your questions in a simple and efficient manner.
Have a look at the your data and use the following general guidelines to help you to determine an appropriate category starting point:
- Use Time Series Charts when you want to show how data changes over time (e.g., change in product sales last quarter).
- Use Composition Charts when your data is focused on a single factor (e.g., number of bankruptcies, number of graduates, most popular city, etc.).
- Use Distribution Charts when your data is allotted across different categories (e.g., breakdown of tree height, IQ scores across a pool of applicants, etc.).
- Use Relationship Charts when you are making a comparison between two or more values (e.g., rise in sea level rise compared to temperature changes).
- Use Geospatial Charts when your data is reliant on geography (e.g., population density in a city, air traffic routes, etc.).