# Multivariate data visualization

Weather stations styled with a simple renderer and visual variables to display wind speed, direction, and air temperature

## What is multivariate data visualization?

Multivariate data visualization involves visualizing more than one data value in a single renderer. This is done for many reasons, including to:

1. View the relationship between two or more variables
2. Compare or contrast the difference between two variables
3. View spatial patterns that may not be related among several variables at one time.

## How multivariate data visualizations work

Multivariate visualizations can be done by adding more than one visual variable to a simple renderer. Common combinations include the following:

1. Color and size
2. Size and rotation
3. Size, rotation, and color

You can create multivariate visualizations using many other combinations of visual variables as well, including opacity.

## Examples

### Color and size

Color and size are typically used to show the relationship between two variables or to show a rate with a color variable, and the magnitude of a variable using a size variable.

The following example visualizes how humidity influences the heat index, or the "feels like" temperature using color and size.

• color is used to visualize relative humidity
• size is used to visualize the difference between the heat index (feels like temperature) and the measured air temperature at a weather station.
ArcGIS JS API
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``````          visualVariables: [
{
type: "size",
valueExpression: "\$feature.HEAT_INDEX - \$feature.TEMP",
valueExpressionTitle: "Difference in 'feels like' temperature from air temperature",
minDataValue: 0,
maxDataValue: 30,
minSize: 4,
maxSize: 24
}, {
type: "color",
field: "R_HUMIDITY",
stops: [
{ value: 20, color: "#ffefdc" },
{ value: 35, color: "#edac90" },
{ value: 50, color: "#da6843" },
{ value: 65, color: "#a03523" },
{ value: 80, color: "#660202" }
]
}
]
``````
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### Size and rotation

Size variables are good for visualization total counts or magnitudes. Rotation and size are commonly paired together to map weather data, such as wind. Rotation indicates the direction of flow, while size indicates the wind speed.

ArcGIS JS API
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``````          visualVariables: [
{
type: "size",
field: "WIND_SPEED",
minDataValue: 5,
maxDataValue: 60,
minSize: 4,
maxSize: 24
}, {
type: "rotation",
field: "WIND_DIRECT",
rotationType: "geographic"
}
]
``````
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### Size, rotation, and color

In rare cases, you can effectively use three visual variables together. In the example below, we add a color variable to the wind visualization to represent air temperature. This visualization allows the end user to view patterns of wind and temperature together in one visual.

• Size - wind speed
• Rotation - wind direction
• Color - air temperature
ArcGIS JS API
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``````          visualVariables: [
{
type: "rotation",
field: "WIND_DIRECT",
rotationType: "geographic"
},
{
type: "size",
field: "WIND_SPEED",
minDataValue: 5,
maxDataValue: 60,
minSize: {
type: "size",
valueExpression: "\$view.scale",
// adjust the min size by scale
stops: [
{ value: referenceScale, size: 8 },
{ value: referenceScale*2, size: 6 },
{ value: referenceScale*4, size: 4 },
{ value: referenceScale*8, size: 2 }
]
},
maxSize: {
type: "size",
valueExpression: "\$view.scale",
// adjust the max size by scale
stops: [
{ value: referenceScale, size: 40 },
{ value: referenceScale*2, size: 30 },
{ value: referenceScale*4, size: 20 },
{ value: referenceScale*8, size: 10 }
]
}
},
{
type: "color",
field: "TEMP",
stops: [
{ value: 20, color: "#2b83ba" },
{ value: 35, color: "#abdda4" },
{ value: 50, color: "#ffffbf" },
{ value: 65, color: "#fdae61" },
{ value: 80, color: "#d7191c" }
]
}
]
``````
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## Best practices

Using more than one visual variable adds complexity to the visualization. This makes it more difficult for the end user to understand the message. You should always carefully consider whether using multiple variables in one view is preferable to displaying separate views of the data.

## Other multivariate styles

You don't need visual variables to create multivariate visualizations. The following guide pages demonstrate how to create multivariate visualizations with other renderer types.

### Predominance

A predominance visualization colors features based on the predominant value among a set of competing or similar numeric attributes.

### Dot density

Learn how to use dot density to measure the density of a numeric attribute or set of comparable variables.

### Charts

Learn how to use charts to visualize the distribution of multiple numeric variables in a layer.

### Relationship

Learn how to use a relationship renderer to explore the relationship between two numeric data attributes.