Symbol types, also known as smart mapping, are presented based on the geometry of the feature you are mapping (points, lines, or polygons) and the type of data attributes that you select (numbers, categories, dates, and so on). The symbol type that you select helps you to target specific audiences and provides options to emphasize aspects of your data in a variety of ways.
Learn more about symbol types and smart mapping in the ArcGIS tutorial series Smart Mapping Styles in Map Viewer.
Use the following sections to help determine which symbol type is right for your data. To apply a symbol type to your data, follow the workflow in Change the style settings.
Location
The location symbol type shows how features are distributed on a map—for example, whether features are clustered or dispersed. This style uses one symbol for all features (point, line, or polygon). Location symbols are sized identically across the map.
See Smart Mapping: Location (single symbol) for more information about styling with the location symbol type.
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Heat map
A heat map shows the relative density of points on the map as a continuous color ramp that implies temperature ranging from cool (few points) to hot (many points).
You can use heat maps to map the location of point features only, not lines or polygons. Heat maps are useful when many of the points on a map are close together or overlapping, making it difficult to distinguish between features. They are effective when the data contains many points, or if you have a layer with point-based events. For example, you can use a heat map to show event-based data over time, such as traffic violations.
See the ArcGIS Blog article Reveal patterns with the heat map style for more information about heat maps.
If you have only a few locations, a heat map is less effective; map the actual points.
Tip:
Before you begin, add a numeric Size data attribute to your location data. Heat maps can be used with location data only but work best with numeric size data.
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Size
You can use graduated symbol sizes to represent numeric data or ranked categories, allowing you to visually compare quantities and identify trends.
In maps styled with proportional symbols, larger symbols represent larger numbers. Adjust the size of the symbols to define the data. For example, you can use proportional symbols to show the total population surrounding public library locations in Iowa.
See Smart Mapping: Counts and Amounts (size) for more information about styling with proportional symbols.
Tip:
Before you begin, add a numeric Size data attribute to your location data.
Color
When a map contains numeric data, you can distinguish features using graduated colors to reflect a count or an amount. Different types of color ramps can be used to demonstrate low-to-high data values—for example, a light-to-dark color ramp can show the range of electricity consumption per capita.
See Energy Use by country, 2010 for more information.
Color ramps can be applied to point data, such as business or service locations; lines, such as rivers or highways; and polygons, such as city boundaries or postal codes.
Tip:
Before you begin, add a numeric Color data attribute to your location data.
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Color and size
When the data contains multiple attributes, you can style a map to compare and contrast two of them. This symbol type uses proportional sizes to emphasize the highest and lowest concentrations of the first attribute and complementary colors to emphasize the strongest and weakest distribution of the second attribute.
See Population without Health Insurance for more information.
You can also use color and size to map a single attribute with a median value using different color and proportional symbol pairs to show values above and below the median—for example, where poverty rates are above and below the national average.
Tip:
Before you begin, add two numeric data attributes (one Size and one Color) to your location data.
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Types
You can use the types style to illustrate different types of categorical data in ArcGIS for Excel, not counts or numeric measurements. For example, you can use different colors and shapes to represent different types of road networks or highways.
See Unique types for more information.
Note:
A maximum of 200 unique values can be used, and 10 colors are available. The same color can represent multiple categories. The types map style is most informative when the data contains up to 10 categories—for example, restaurant types, tree species, or political parties.Tip:
Before you begin, add a categorical (non-numeric) Color data attribute to your location data.
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Types and size
Use this style to represent categorical data and a fixed array of numeric data using symbols of proportionate sizes to illustrate areas of greatest variance.
See the ArcGIS Blog article A drawing style designed for categorical data: Types for more information.
Tip:
Before you begin, add a numeric Size data attribute and a categorical (non-numeric) Color data attribute to your location data.
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Charts
Use charts to show the proportions of categorical data associated with a single feature, using either a count or a summary statistic. Pie chart symbols can help answer questions such as what the proportions of categories are for each feature on a map, or comparing counts or other summary statistics between locations.
For example, you are reviewing purchases of insurance policies across the United States to determine where there is market potential for each policy class (automobile, disability, life, and property). You can select each policy class field and map them using the charts style. The data is represented as pie chart symbols showing the proportions of each policy class that are being purchased in each state.
See an example of charts.
Dot density
Use the dot density style to visualize the distribution of one numeric attribute or to compare multiple numeric attributes using different-colored dots. With this style, each dot represents a count of something or someone, such as citizens, sales, or crimes. The dot density style works well for layers with polygon features associated with counts or totals that share a common unit of measurement, such as people, houses, incident reports, total dollars, and more.
For example, you can use this style to show the concentration of unsheltered homeless people compared to sheltered homeless people in a city, or the distribution of population by race across the United States.
See an example of dot density.
Predominant category
This map style is useful if a layer contains multiple related attributes that you want to compare and show which attribute is predominant—that is, has the highest value—and the degree of its predominance compared to the other attributes in the layer.
For example, you can use this style to see the predominant ethnic population in each census tract in Los Angeles, California, and how much higher the predominant population is compared to the others.
See an example of predominance.
Relationship
Using the relationship smart mapping style, you can visualize the relationship between two numeric attributes in point, line, or polygon feature data. For example, you can see whether there is a relationship between the richness and rarity of species in the world and in which areas the relationship is most pronounced. Based on the bivariate choropleth mapping technique, the relationship style applies a distinct graduated color ramp to the classified data in each attribute and combines the color ramps, allowing you to see where the attributes may be related. You can explore the relationship using different focus options.
For example, you can focus on where both richness and rarity of species are high, or change the focus to highlight areas where they are both low. You can also change the classification method and other settings.
See an example of relationship.