Our task in this lab was to take data from The American Fact Finder site and illustrate it in a cartographically pleasing way in ArcMap. In the process of making these maps we were able to learn more about this site as a source for data, the ArcGIS program, and the integration from one to the other.
Objective I
This Lab Started by downloading data from our online source. We used The American Fact Finder site at factfinder2.census.gov and locating the data to be used later in the exercise. We were able to simply select data and download them as zip files. The zip files were then extracted and converted to a file type useable in ArcMap ( from .csv, Comma Separated Values, to .xlsx Excel workbook format).
We then took a look at the data that was downloaded as well as the metadata that came with it. Metadata acts as a means of understanding the data table that it coordinates with, allowing for a more streamlined table that can still be interpreted. Using these we located our data of interest.
Objective II
Next, we downloaded the shape files for the Wisconsin census data. Without them we would have been able to move our data into the ArcMap program, but it would still simply be tabular data. We needed a visual representation to attach this data to, and fortunately the A.F.F. site provides us with the appropriate shape files for our data at the county level. This data was downloaded and extracted in the same manner as before.
Objective III
Next came joining of the data. Now that both the data and the counties shape file were in ArcMap, we needed a way of connecting the data to the map in order to change visual representations according to the data. To do this we used a table join, which takes a category that both sets of data share and uses it to combine them into one table. both the both the shape file and the table we loaded shared a category called Geo ID, which identifies each county in Wisconsin the same way between different tables and files.
Objective IV
The task in this objective was to map the data onto the shape file. This was complicated by the fact that the files we downloaded needed to display data in a certain format. When we downloaded the files, all values were in text format. This means that the computer takes every symbol for its symbol value, essentially treating them all, including numbers, as text. In order for the program to display the data numerically the format had to be changed. The method I used to achieve this was to go to the joined table, make a new field (column) that was formatted for "short integers", and use the field calculator tool to set those numerical values to the same as the symbol values of the field of interest (the one we want to represent visually). Now the numbers are actually numbers! (Fig.2)
After all this we were able to simply go to layer properties and display the data in a graduated color scheme.
Objective V
We were now tasked with using all the same steps to find our own data from A.F.F. I chose to simply represent housing data in a manner that was similar to the population data. I was also careful to make sure that the data was from 2010, just like the population data, in order to keep the data itself and any comparison between the two relevant and up to date. It turns out that the distribution the quantity of houses per county matches the population distribution per county fairly well. This makes sense as a place with more people should have more houses.
The metadata was important in finding my data of interest. The A.F.F. website fortunately gives previews of what data are enclosed in the files available, but metadata also needs to be examined to see if the variable if interest should be normalized or to see what field title matches your actual variable.
Objective VI
The final task was to take our maps and give them a pleasing layout and representation. I chose to change the projection of the layers to something that would more accurately represent the smaller area of the state of Wisconsin. In layout view the maps were framed with the appropriate titles and legends added. Credit was given to the cartographer and data source for this project. (Fig. 1)
Results
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| Figure 1. Final maps indicating Total Household Distribution and Total Population Distribution per county |
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| Figure 2. The process of adding a column in a numerical format and copying the data from our field of interest involved the use of the field calculator in ArcMap. This was not a part of the program we had used before so I included an image showing what it looked like when I was able to get it to work (after much trial and error). I also tried using excel itself to format the values as numerical but they would simply revert when being loaded into ArcMap. |
U.S. Census Bureau, 2010 Census; American FactFinder; <http://factfinder2.census.gov>; (26 October, 2014).
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