File Details

Title GCE ArcGIS Python Scripts
Archive All Files / Other Files / Software / GIS Scripts
Description

Eight Python scripts (version 2.5) were developed to dynamically generate ESRI shapefiles. The scripts use input data from a database or csv file, and the output is saved as a zipfile. Each script has two variants: 1) a prompt interface, which allows the user to pass in variables from the command line, and 2) hard coded variables, which allows the script to be utilized in an integrated information system. The scripts are organized into two main categories. The first category receives input data from a database. Six scripts receive input data from a database, and are further categorized according to their output. These are: 1) One point shapefile that contains one or more points, 2) One polygon shapefile that contains two or more polygons, and 3) One polygon shapefile that contains one polygon per shapefile. The SQL and ArcGIS attribute table fields are dynamically generated based on variables that are either passed in or hard coded in the script. The other main category, a total of two scripts, receives input data from a csv file. For every csv file in a directory, one point shapefile is generated for every row in the csv file. The ArcGIS attribute field names are dynamically generated based on the first row in the csv file. The code is thoroughly commented.

Contributor Travis Douce
Citation

Travis Douce. 2010. GCE ArcGIS Python Scripts. Georgia Coastal Ecosystems LTER File Archive, University of Georgia, Athens, Georgia. (http://gce-lter.marsci.uga.edu/public/app/resource_details.asp?id=432)

Key Words CSV, Database, GIS, Python, Shapefiles
File Date Dec 14, 2010 (version 1)
Web Link Zip archive
view/download Zip archive
(82 kb)
LTER
NSF

This material is based upon work supported by the National Science Foundation under grants OCE-9982133, OCE-0620959 and OCE-1237140. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.