Mean Center (Spatial Statistics)—ArcGIS Pro

Summary

Identifies the geographic center (or the center of concentration) for a set of features.

Illustration

Usage

The mean center is a point constructed from the average x, y and if available, z values for the input feature centroids.
This tool requires projected data to accurately measure distances.
The x, y and z values for the mean center point features are attributes in the Output Feature Class. The values are stored in the fields XCOORD, YCOORD and ZCOORD.
The Case Field is used to group features for separate mean center computations. When a Case Field is specified, the input features are first grouped according to case field values, and then a mean center is calculated for each group. The case field can be of integer, date, or string type. Records with NULL values for the Case Field will be excluded from analysis.
The Dimension Field is any numeric field in the input feature class. The Mean Center tool will compute the average for all values in that field and include the result in the output feature class.
This tool honors the 3D nature of your point data and will use x, y and z values in its calculations if z values are available. Since these results are 3D in nature, they will need to be visualized in a Scene. Be sure that you are running the analysis in a Scene or copy the result layer into a Scene for correct visualization of your analysis results.
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.
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.

Caution:

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.

Parameters

Label	Explanation	Data Type
Input Feature Class	A feature class for which the mean center will be calculated.	Feature Layer
Output Feature Class	A point feature class that will contain the features representing the mean centers of the input feature class.	Feature Class
Weight Field (Optional)	The numeric field used to create a weighted mean center.	Field
Case Field (Optional)	Field used to group features for separate mean center calculations. The case field can be of integer, date, or string type.	Field
Dimension Field (Optional)	A numeric field containing attribute values from which an average value will be calculated.	Field

arcpy.stats.MeanCenter(Input_Feature_Class, Output_Feature_Class, {Weight_Field}, {Case_Field}, {Dimension_Field})

Name	Explanation	Data Type
Input_Feature_Class	A feature class for which the mean center will be calculated.	Feature Layer
Output_Feature_Class	A point feature class that will contain the features representing the mean centers of the input feature class.	Feature Class
Weight_Field (Optional)	The numeric field used to create a weighted mean center.	Field
Case_Field (Optional)	Field used to group features for separate mean center calculations. The case field can be of integer, date, or string type.	Field
Dimension_Field (Optional)	A numeric field containing attribute values from which an average value will be calculated.	Field

Code sample

MeanCenter example 1 (Python window)

The following Python window script demonstrates how to use the MeanCenter function.

import arcpy
arcpy.env.workspace = r"C:\data"
arcpy.stats.MeanCenter("coffee_shops.shp", "coffee_MEANCENTER.shp", "NUM_EMP")

MeanCenter example (stand-alone script)

The following stand-alone Python script demonstrates how to use the MeanCenter function.


# 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.stats.CentralFeature(input_FC, CF_output, "Euclidean Distance", 
                               weight_field)
 
    # Process: Mean Center...
    arcpy.stats.MeanCenter(input_FC, MEAN_output, weight_field)

    # Process: Median Center...
    arcpy.stats.MedianCenter(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, Geographic Transformations, Current Workspace, Scratch Workspace, Qualified Field Names, Output has M values, M Resolution, M Tolerance, Output has Z values, Default Output Z Value, Z Resolution, Z Tolerance, XY Resolution, XY Tolerance

Special cases

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.

Licensing information

Basic: Yes
Standard: Yes
Advanced: Yes