Lab 2: Downloading and Displaying GIS Data

Goals:

The purpose of this lab assignment was to teach us students how to access, download, use, and manipulate mat data frames which include demographics data taken from an online source. In this particular assignment, 2010 SF1 100% demographics data was obtained from the American Factfinder website of the U.S. Census Bureau. The data we were tasked with obtaining and working with was Wisconsin county demographics, in this particular case population, and a variable of individual choosing. Anything was a viable choice, so long as it was available in the 2010 SF1 100% data format, although we were advised to steer away from race demographics, do to the complexity of race data, as individuals can list themselves of on of up to eight races. Afterwards, we were tasked with publishing the population demographics data as a pop-up style map and sharing it with the ArcGIS UWEC Geography and Anthropology organization.

Methods:

I began with visiting the American Factfinder website of the U.S. Census Bureau. Using the search made available by the website, I located and downloaded a 2010 SF1 data set under the title TOTAL POPULATION. I extracted the files into the work folder I specifically designated for this lab. I opened and viewed both the tabular data and metadata CSV files in Microsoft Excel, and after determining that this rather simple data set required no major changes to make it compatible with ArcMap, saved the tabular data as an Excel file. I opened the file into ArcMap and checked the attribute table for errors that may have been created in the transfer process, finding none. I returned to the American Factfinder website and downloaded a Wisconsin counties shapefile.zip file and extracted its contents into the lab folder holding the data retrieved earlier. I created a blank map document in ArcMap and added both the Excel and shapefile to the map. I opened the attribute tables of both the shapefile and the tabular excel data and proceeded to construct a table join between the two, using the GEO_ID and GEO#id data columns as the basis of the join. After verifying the join, I created a new field in the shapefile attribute table with the field type of Double. Using the field calculator tool, I set the new field to equal that of the D001 field, which held the county population data. I did this because the original D001 filed was of the string field type, which could not be mapped as a graduated colors map, like the new D001 double field. I proceeded to map the new D001 field as such with seven population classes.

I then returned once again to the American Factfinder website and obtained data for a variable of my choosing for mapping and comparison. In my particular case, I chose to search for data containing population demographics of different individual age groups. I wished to know the population percent of individuals between the ages of 20 and 24 in various counties, the same age category I fall within. After I found the data I was looking for in the 2010 SF1 format, I downloaded and unzipped it into its own sub-folder within the larger lab folder I set up specifically for this lab assignment. I opened and viewed both the tabular data and metadata CSV files of the age demographics data. Within the tabular data CSV file, I discovered and removed an extra field descriptor row that would have prevented proper viewing in ArcGIS before converting it to and Excel file. Within ArcGIS, I created a second data frame for the viewing of the age demographics data and added both the age demographics Excel table and the shapefile from before into the new data frame. Using a similar join which also utilized the GEO ID fields, I joined the attribute tables of the age demographics data and the county shapefile. I converted the field total population of the age group I sought to analyze (ages 20 to 24) to a double field using the same method as before, by creating a new field of the double type and using the field calculator to set the data of the new field. Once this was completed I created a graduated colors map of the percent population of individuals between the ages of 20 and 24 by using the newly created field and normalizing with the total population field already present in the shapefile attribute table. Once both of these maps were constructed, I created a special layout displaying both data frames along with corresponding titles, legends, north and scale markers, the proper state level coordinate systems, and citations with each data frame displayed against a topography basemap for reference. I organized all of this using proper map construction rules that I have learned previously.

Afterwards, I created a feature service of the population demographics map shared it as a service to the ArcGIS online account I was given and had properly signed up for earlier by the University of Wisconsin, Eau Claire Geography department. From my ArcGIS online account, I constructed a pop-up map that would display both the county name and population as each county was clicked on. As per instructed, I shared this map privately with the UW-Eau Claire – Geography and Anthropology organization.

Results:

From this lab assignment, I learned the fundamentals of downloading and utilizing demographic data from credited sources. I learned how to properly set up and convert the data I had retrieved into a usable format that could be opened within ArcGIS programs. I also learned how to join the fields from two attribute tables together and what form the fields need to be in so the data could be manipulated into maps that revealed important information and patterns. This data could then be exported to external locations for viewing by others, like my population demographics map.

As to the data's results, my population data frame map showed a population concentration around city centers and to the east and south-east portions of the state. In addition, the age demographics map revealed surprising results. At first, it seemed to favor city centers but with less focus than the population map. However, certain counties showing a high percentage of of individuals between 20 and 24 years of age when compared to the counties immediately neighboring them. This seemingly random pattern stumped me at first, until the pattern suddenly hit me as I was viewing my current home county. This pattern was displaying counties which held college or university campuses within their borders.

Sources:

Hupy, C. (2016). Lab 2: Downloading GIS Data. Eau Claire, Wisconsin.

In American Fact Finder. Retrieved April 8, 2016, from United States Census Bureau.