Embedded Files
Problem
NC State General Assembly members request visual representation of created extension jobs by both NC State House and Senate Districts. This project uses an industrial extension jobs survey combined with spatial data to map new extension job creations by district (for both House and Senate districts separately).
Analysis Procedures
The NC General Assembly provided the tabular results of an industrial extension job survey. Additional data included NC General Assembly House and Senate District boundaries obtained through NC One Map and a Zip Code Point Data file obtained from ESRI. A NC zip code shapefile was created from this last dataset. The created extension jobs were summed in order to facilitate a tabular join to the NC zip code layer. Two separate spatial joins were performed in ArcMap to join the NC zip code layer (following the tabular join) with each district boundary layer. Each map was symbolized for visual display, including job counts as labels in each district.
The extension job spreadsheet, house district boundary, and senate district boundary were added to ArcMap. The extension job table and all attribute tables were reviewed. Additionally, each boundary layer was checked to ensure projection. The zip code point layer was added to ArcMap and its attribute table was reviewed. Using select by attribute, I created a new shapefile containing only the zip code points for North Carolina. In the extension job table, I summarized the zip code field, summing the zip codes by new jobs (EMPLOY_SUM), creating a new table. I then joined the new summed extension job table to the NC zip code point layer, keeping only matching records, and creating a new zip code shapefile. I then performed a spatial join, joining the new zip code shapefile to the house district boundary layer. I then symbolized my map for visual display, adding a count of created jobs per district as a label. Finally, I performed a second spatial join, this time joining the new zip code shapefile to the senate district boundary layer. I then symbolized this map for visual display, adding a count of created jobs per district.
Results
Map displaying number of jobs created by North Carolina House Districts (Click to enlarge)
Map displaying the number of jobs created by North Carolina Senate district (Click to enlarge)
Workflow diagram (Click to enlarge)
Application & Reflection
Data cardinality, as well as tabular and spatial joins, are particularly useful for summarizing numerical attributes for both study and representation. In particular, data cardinality and tabular and spatial joins skills are beneficial for examining farm census data, particularly organic production. For example, perhaps I wanted to know how many farms are producing organic vegetables by county in North Carolina. The USDA offers data on farms at the state level by zip code. I can obtain a data set that includes the number of organic farms producing organic vegetables according to farm size by zip code for North Carolina. I would sum the number of farms (to include all farm sizes) by zip code and perform a tabular join to a NC zip code shapefile (created with select by attribute from ESRI zip code point data). I would then spatially join this to a NC county boundary shapefile available from NC One Map. This would yield counts of organic vegetable producing farms by county in North Carolina.
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