Census Data

10/09/14

Problem:

Human Resource divisions at every level of government frequently need information about the populations they serve. For example, the Office of Human Resources for the State of Wyoming may wish to produce maps about the number of jobs for residents 16 years or older and the categories into which those jobs fall for every county subdivision in the state. To explore this process, data will be examined from the Total Civilian Employed Population 16 years and over, field name HC01_EST_VC01, as described in the table file ACS_12_5YR_S2405_with_ann.csv, pulled from 2010 Census data. The demographic data used for these analyses were acquired from the American Fact Finder site at http://factfinder2.census.gov and sub-county divisions were available from the U.S. Census Bureau US Census TIGER/Line® Shapefiles site at: http://www.census.gov/cgi-bin/geo/ shapefiles2010/main. The data were acquired as GCS_North_ American_1983, datum D_North_American_1983 in decimal degrees, then projected to NAD_1983_State Plane_Wyoming_East_Central_ FIPS_4902 (meters).

Analysis Procedure:

Depending on the question(s) of interest, a series of filters can be applied to the census websites to narrow the data search window. After acquisition, the data can be formatted appropriately in a spreadsheet software that can output a .xls format as appears to be required by ArcMap. It may be appropriate to project the shapefile into the standard coordinates specific to the geographic location of interest in ArcCatalog upon the shapefile itself and in the ArcMap document prior to loading the files. The tabular data associated with the shapefile should be formatted using the Field Calculator function, then the census tabular data and the shapefile tabular data can be joined. Once the data is joined, the census map(s) can be generated.

Figure 1. Workflow diagram for the acquisition and processing of census data

Results:

Data acquired from the census websites and processed according to the described methods produced a table containing demographic information separated by sub-county (Figure 2). For this assessment, the information presented in the column labeled HC01_EST_VC01 were used and pertained to the number of total civilian employees aged 16 years and over. From these data, a map was generated that showed the level of employment at the sub-county level (Figure 3). These data suggest that the vast majority of the State of Wyoming have fewer than 3600 employed, civilian individuals 16 years or older.

Figure 2. Example of the tabular data produced from the table join action described in Methods.

Figure 3. Map showing the number of employees 16 years or older by sub-county in the State of Wyoming, 2010

Application and Reflection:

There are an abundance of data that pertain to the socio-economic characteristics of our country, and we can search them to address questions to guide our decision making processes. For instance, Wyoming may be interested in encouraging companies to relocate their operations to the state. They might contact the state of Wyoming A&I Human Resources Division to identify areas where such opportunities might be attractive. From the perspective of residents within the state, it might appear that a huge majority of the counties have insufficient opportunities for folks who live there or who may wish to relocate there. Concurrently, however, the vast majority of the counties in the state of Wyoming might also have exceedingly low population densities, so the proportion of employed civilians might be in alignment with other areas, and the infrastructure necessary to support businesses may be limited. In addition, the types of industries the state might try to attract would likely need to be in alignment with the education, training, and skills types of the areas targeted for relocation. With these considerations in mind, the data required for the state of Wyoming to address a marketing campaign to attract businesses might include information about current employment levels, current training and skills of the residents, available infrastructure and supporting resources, and population densities at the sub-county level. I would initially employ a data acquisition and analysis strategy that follows the procedures outlined in this segment, specifically focused on identifying the scores of each of these characteristics at the sub-county level. With these information, another search could be initiated that identifies potential industries that would benefit from the available resources and from which business could be relocated.