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This document is archived and information here might be outdated. Recommended version. |
IDataNormalization Interface (ArcObjects .NET 10.8 SDK)
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This document is archived and information here might be outdated. Recommended version. |
Provides access to members that control the data normalization properties of a renderer.
| Name | Description | |
|---|---|---|
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NormalizationField | Normalization field. |
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NormalizationFieldAlias | Normalization field alias. |
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NormalizationTotal | Total of all values (used when normalizing by percent of total). |
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NormalizationType | Normalization type. |
| Classes | Description |
|---|---|
| BasicTableHistogram | A histogram data structure that is created from table data. Use this to pass data to a classification object. |
| ChartRenderer | A chart renderer used to draw pie, bar, and stacked bar chart symbols. |
| ClassBreaksRenderer | A renderer that can be used to draw graduated color (choropleth) and graduated symbol maps. |
| ProportionalSymbolRenderer | A proportional symbol renderer, used to draw symbols of varying size for each feature, sized in proportion to a field value. |
| TableHistogram (esriCartoUI) | A histogram data structure that is created from table data. Use this to pass data to a classification object. |
Use this interface to symbolize feature data based on normalized attributes using a ClassBreaksRenderer or ProportionalSymbolRenderer, or when preparing a histogram object to classify normalized data using a classification object.
With the exception of log normalization, data normalization creates a ratio by dividing two values. When comparing attribute values between features, normalization is useful to minimize the effect of varying map area or the number of observations. For example, dividing the 18-30 year old population by the area of a polygon feature yields a density value that can be compared for two or more features, regardless of the size of each feature. Also, dividing the 18-30 year old population by the total population of a feature yields a ratio of people between the ages of 18-30 which is again comparable, regardless of the possibly large differences in total population between two features. Log normalization reduces the influence of very large data values and is suitable for some data distributions.
When rendering feature data, to normalize by a field, you can use IProportionalSymbolRenderer::NormField or IClassBreaksRenderer::NormField as an alternative to this interface.