Read here for more generic information about georeferencing in mySidewalk.
Goal of this Example
In this article we are going to walk through an example of how to use the georeference tool. The goal will be to upload the voter turnout data for the US, Arkansas, Kansas and Missouri then show it on a map and in a callout with the following steps:
1. Get and Clean the Data
We can use the data publicly available here at the electproject.org. Once you have the data in a spreadsheet form, we will narrow it down to only what we need and adjust the formatting a bit.
First, we can remove all of the rows that we do not want to upload
We need to keep the first column as a 'geography' column as it will not upload as data values, only labels.
Finally, we need to ensure that there is only one header column row (access file in the cleaned format here)
Save the cleaned file as a .csv
2. Upload and Assign the geographies
We will now take the cleaned file and upload it into mySidewalk.
Click Upload -> Upload and Georeference
Upload the file we created
At this point, you will see a sample of the file.
Select the “Multiple Geographies” button
Using the dropdowns, assign “United States of America” and the state names (Arkansas, Kansas, Missouri) to the corresponding rows. You must select a corresponding geography for each line.
You can also change the name of your file by updating the “Layer File name” at the top of the page
Click “Submit” to upload the layer with the geographies assigned
A successful layer upload will look like the above image.
Things to note:
The column headers that contained numbers say “number” in the Type column and not “text”. This means that the format can be changed within mySidewalk (to percent, for example, and used in calculations such as normalization)
All the column headers load into the “Name” list. We want to ensure that the data we need is the data we are getting. You can confirm the data values by choosing the different geographies and watching the data values change to match the spreadsheet.
The geographies are outlined on the map image. This confirms that you agree with our representation of the geography.
Things to Do:
Choose a label for your layer with the radio buttons in the “Use as Label?” column (typically the name of the geographic region). In this example, choose the row name “label”. The label is basically the name of the geographic region that will appear when you aren’t using a map (see callout example).
Change the aliases if desired.
3. Use the layer in a Map
To start using this layer, you will need to navigate to a report. You can choose “New Report” at the top of the page or select “Reports” from the blue quick start menu button on the left.
Create the Map
Hover to view then select the add content blue “+” button on the page and select “Map”
Select “Add My Layer” since you are adding a layer you uploaded and not a layer created by mySidewalk.
Select the layer you just uploaded
Filter out the USA data point
Select the layer and select the “Filters” tab
Select “Add a Filter” then select “Change Data”
Choose a column that makes sense to filter – for this example, we will choose “State Abv”
On this menu under “Condition 1” and “Operator,” use the dropdown to choose a criteria to use as a filter. For this example, we will choose “Has Any Value.” Since the column has the values (blank), AR, KS, and MO, the (blank) column will be filtered out, which leaves us with only the states as values.
Style by Data - Show the prison voter eligible population by state
Select the layer
Select “Style by Data”
Select “Change Data”
Choose the desired variable (Prison)
Because the separation is so small, we need to choose “Equal Interval” for the “Break methodology” and change the “# of Bins” to 3
Normalize Style by Data for Voting-Eligible Population
Underneath “Change Data,” find the selection for “Normalize By”
Choose the desired variable (Voting-Eligible Population)
Change the format to “Ratio as Percent”
What does this map tell me?
This map clearly shows a few things. We can gather that the percent of prison eligible voters that actually voted is smallest in Kansas and largest in Arkansas. (Remember that we normalized the data by the total number of eligible voters.) Based on the legend, we can also see that while Kansas is the smallest percentage, the numbers are actually very close (between 0.47% and 0.8%). We can do this same thing to make comparisons for various other subsets within the eligible voter population.
4. Use the layer in a callout
We can also use this layer in a callout which will help highlight how each state compared to the United States as a whole. Let’s explore that a bit.
Create the Callout
Hover to view then select the add content blue “+” button on the page and select “Callout” and “Your Data”
Choose the layer you uploaded earlier
Add Additional Geographies
On the Geography tab, click “Manage Geographies”
Choose the desired outlines from the map (all in this example)
Click “Finish Editing”
Select the Data tab
Click “Add Variables”
Choose the desired variables (Total Ballots Counted and Vote for Highest Office)
Click “Complete Column Selection”
Remove the unwanted “Feature Class ID” variable
Normalize Data and Edit Labels
Select the Data tab
Add your normalizer FIRST – click “Normalize by” and choose a denominator (Voter-Eligible Population)
Change labels as desired (Voter-Eligible Turnout Rate)
Change Format (Ratio as Percent) to accurately reflect that this is the rate at which voters that turned out to vote in that region
Repeat for additional variables as desired
What does this tell me?
The callout information that was created from this layer shows quite clearly that, when taking voter-eligible population into account, Kansas, Missouri and Arkansas turned out to vote at a higher rate than the United States population as a whole. It shows both the turnout generally and the turnout specifically for the presidential election. We can compare the individual states as well as the United States. The additional information in the layer can be leveraged similarly to compare turnout for various population subsets (e.g. prison population eligible voters, like we did earlier in this exercise).