Types of ranged values – Pitney Bowes MapXtreme User Manual

Page 278

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Chapter 14: Using Themes and Legends

RangedTheme

MapXtreme v7.1

285

Developer Guide

Types of Ranged Values

MapXtreme can create ranges automatically using five distribution methods:

Equal count

Equal ranges

Standard Deviation

Natural break

Quantile

Custom

Equal Count

Equal Count has the same number of records in each range. If you want to group 100 records into 4
ranges using Equal Count, MapXtreme computes the ranges so that approximately 25 records fall
into each range, depending on the rounding factor you set.

When using Equal Count (or any other range method), it’s important to watch out for any extreme
data values that might affect your thematic map (in statistics, these values are referred to as
outliers).

Equal Ranges

Equal Ranges divides records across ranges of equal size. For example, you have a field in your
table with data values ranging from 1 to 100. You want to create a thematic map with four equal size
ranges. MapX produces ranges 1–25, 26–50, 51–75, and 76–100. Keep in mind that MapXtreme
may create ranges with no data records, depending on the distribution of your data.

Standard Deviation

When you create ranges using Standard Deviation the middle range breaks at the mean of your
values, and the ranges above and below the middle range are one standard deviation above or
below the mean.

Natural Break

Natural Break is a way to show data that is not evenly distributed. It creates ranges according to an
algorithm that uses the average of each range to distribute the data more evenly across the ranges.
It distributes the values so that the average of each range is as close as possible to each of the
range values in that range. This ensures that the ranges are well-represented by their averages, and
that data values within each of the ranges are fairly close together.

Quantile

Quantile is a second way to show data that is not evenly distributed. Quantiling uses two variables
expressions. For example, use the Quantile distribution method to show the literacy rate as tied to
population.

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