Median Center (Spatial Statistics)
Summary
Identifies the location that minimizes overall Euclidean distance to the features in a dataset.
Illustration
Usage
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While the Mean_Center tool returns a point at the average X and average Y coordinate for all feature centroids, the median center uses an iterative algorithm to find the point that minimizes Euclidean distance to all features in the dataset.
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Both the Mean_Center and Median Center are measures of central tendency. The algorithm for the Median Center tool is less influenced by data outliers.
Calculations based on feature distances require projected data to accurately measure distances.
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For line and polygon features, feature centroids are used in distance computations. For multipoints, polylines, or polygons with multiple parts, the centroid is computed using the weighted mean center of all feature parts. The weighting for point features is 1, for line features is length, and for polygon features is area.
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The Case Field is used to group features for separate median center computations. When a case field is specified, the input features are first grouped according to case field values, and then a median center is calculated for each group. The case field can be of integer, date, or string type, and will appear as an attribute in the Output Feature Class. Records with NULL values for the Case Field will be excluded from analysis.
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The x and y values for the median center feature(s) are attributes in the output feature class. The values are stored in the fields XCOORD and YCOORD.
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The data median will be computed for all fields specified in the Attribute Field parameter.
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Map layers can be used to define the Input Feature Class. When using a layer with a selection, only the selected features are included in the analysis.
When using shapefiles, keep in mind that they cannot store null values. Tools or other procedures that create shapefiles from nonshapefile inputs may store or interpret null values as zero. In some cases, nulls are stored as very large negative values in shapefiles. This can lead to unexpected results. See Geoprocessing considerations for shapefile output for more information.
Syntax
Parameter | Explanation | Data Type |
Input_Feature_Class |
A feature class for which the median center will be calculated. | Feature Layer |
Output_Feature_Class |
A point feature class that will contain the features representing the median centers of the input feature class. | Feature Class |
Weight_Field (Optional) |
The numeric field used to create a weighted median center. | Field |
Case_Field (Optional) |
Field used to group features for separate median center calculations. The case field can be of integer, date, or string type. | Field |
Attribute_Field (Optional) |
Numeric field(s) for which the data median value will be computed. | Field |
Code Sample
The following Python Window script demonstrates how to use the MedianCenter tool.
import arcpy
arcpy.env.workspace = r"C:\data"
arcpy.MedianCenter_stats("coffee_shops.shp", "coffee_MEDIANCENTER.shp", "NUM_EMP", "#", "#")
The following stand-alone Python script demonstrates how to use the MedianCenter tool.
# Measure geographic distribution characteristics of coffee house locations weighted by the number of employees
# Import system modules
import arcpy
# Local variables...
workspace = "C:/data"
input_FC = "coffee_shops.shp"
CF_output = "coffee_CENTRALFEATURE.shp"
MEAN_output = "coffee_MEANCENTER.shp"
MED_output = "coffee_MEDIANCENTER.shp"
weight_field = "NUM_EMP"
try:
# Set the workspace to avoid having to type out full path names
arcpy.env.workspace = workspace
# Process: Central Feature...
arcpy.CentralFeature_stats(input_FC, CF_output, "Euclidean Distance", weight_field, "#", "#")
# Process: Mean Center...
arcpy.MeanCenter_stats(input_FC, MEAN_output, weight_field, "#", "#")
# Process: Median Center...
arcpy.MedianCenter_stats(input_FC, MED_output, weight_field, "#", "#")
except:
# If an error occurred when running the tool, print out the error message.
print arcpy.GetMessages()
Environments
- Output Coordinate System
Feature geometry is projected to the Output Coordinate System prior to analysis. All mathematical computations are based on the Output Coordinate System spatial reference.