The goal of this lab was to become familiar with the
different data within the United States Census Bureau. The state of Wisconsin
was the selected area of study for this assignment. The total population of
Wisconsin was the assigned map. The assignment called for another map to be
made based on my own interests, and the data from the two maps were then to be analyzed
for different spatial patterns and trends.
Methods:
The first step in being able to complete this assignment was
to become comfortable using the data provided by the United States Census
Bureau. Once at the site, the data dealing with total population was needed. By
clicking on the topics tab on the left hand side of the page, this allowed for
different categories of data to be displayed. When the topics were displayed,
the category “people” was selected, followed by “basic count/estimate”. By
choosing these categories, it allowed for accessing the necessary data dealing
with the total population for the state of Wisconsin.
Once the data was located, it was necessary to choose the
SF1 set of data. The reason for this is the assignment called for the basic
census data. It did not require ACS, or American Community Survey data. After
the SF1 data for total population was selected, it needed to be downloaded to
the folder dealing with the data pertaining to this particular assignment.
When the data was downloaded to the desired location, it
then needed to be unzipped so the data was easier to access. After being
unzipped, the different comma separated values, CSV, files needed to be
identified to see which file contained the metadata and the actual tabular
data. Once the actual tabular data was located, that file was then saved into a
MS excel file. Since this information only contained the different tabular
data, it was necessary to go back to the United States Census website to
download the information containing the spatial representations for the different
Wisconsin counties.
The next task was to download the shapefile for the
Wisconsin census data. By going back to the United States Census website, they
had the information we needed. The first step was to click on the geographies
tab on the left hand side of the screen. Instead of keeping the window on the
list tab, the map tab needed to be selected. Once the selection was made, it
showed the selected area of all the counties for the state of Wisconsin. After
all the needed data was selected, it needed to be downloaded. By clicking on
the download icon, it brought up a window with different options as to how the
data would be stored. For the purpose of the assignment, the shapefiles
selection was the necessary output of our data. The data was then downloaded to
the desired location and unzipped, like was done with the previous data that
was downloaded.
After all the data was downloaded and organized, ArcMap was
needed to show the different data that was acquired. The shapefile for the
Wisconsin counties was the first thing added to the map. After the shapefile,
the table dealing with the total population was then added to the map. Since
these two data sets had separate attribute tables, it was necessary to join the
two tables by a common attribute. The common attribute in this case was GEO#id,
so that is how the tables were linked together. Once they were linked, the data
could then be viewed as one table, rather than two separated tables.
As of now, all the data has been added to the table, but it
does not show any thing because of how it is currently mapped. It was necessary to change the properties for
the shapefile to make an understandable map. The assignment called for a
graduated colors map to be made so the population distribution throughout Wisconsin
could be easily recognized. Since there was only one variable to map, it was
not necessary to normalize this data set.
The last task for the assignment was to create another map
for a data set of my choosing. That data set I chose pertained to the occupancy
percentage of houses, and that was divided into owner occupancy or renter
occupancy.
As outlined above, the first step was to go to the United
States Census website to access the information. SF1 data was then selected
again in order to have all the necessary information for the different
counties. I chose a data set that looked interesting and fulfilled all the
necessary expectations. Once the data was chosen, it was then downloaded to the
desired location and unzipped into that folder. Since this was going to a new
map, the first thing I did was create a new data frame in ArcMap to keep the
data separated from the first map. Then the tabular data then needed to be saved
into an MS excel file. Once it was converted into an MS excel file, it could
then be added to the new data from in ArcMap. Since the shapefile for the
Wisconsin counties was already made, it was not necessary to repeat that step
again, rather just add it to the map with the household occupancy data.
Once both data sets were added to the map, the attribute
tables then needed to be joined based on a common attribute. Once again, the
common attribute was GEO#id. Once the tables were joined, a variable needed to
be chosen in order to map the data. The data I chose to map showed the owner
occupancy of households for the state of Wisconsin. Since there were three
different variables to choose from, it was necessary to look back at the metadata
table to see what variable was being mapped.
After both maps were made, the data frames needed to be
changed to be more local over the state of Wisconsin. It was not necessary to
use the project tool in this case; all that was needed was to change the
projection for each individual data frame.
Results:
 |
| Figure 2.1 These are the two maps of population. The map on the left shows the number of housing units occupied by the owner. The map on the right shows the total population of each county in Wisconsin. |
The graphic above shows the two different maps made of the
state of Wisconsin. The pattern between a higher population and higher amount
of home owner occupancy are almost directly related. The counties that have a
larger population typically also have a higher amount of homeowners that occupy
their own home.
Sources:
United States Census Bureau. (2014, March 6). Retrieved http://factfinder2.census.gov/faces/nav/jsf/pages/searchresults.xhtml?refresh=t
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