Customizing Cutpoints

This short guide will help you:

1. Understand what cutpoints are
2. Why they are important
3. How to use them

Social Explorer uses choropleth maps – a special type of map that uses color to represent statistical data, and not geographic features such as elevation. However, reading maps can be quite a challenge, as the colors displayed rarely have an inherent meaning. This is where a map legend comes in handy. Just like your house key opens your front door, a map legend offers the key to understanding a map.

There are multiple ways to customize the look and feel of your map on Social Explorer. We’ve included a wealth of predefined color palettes, but you can also create your own custom palette and decide which color or shade should represent a particular data range. In addition to playing with colors, Social Explorer allows you to tweak the data ranges as well.

What are cutpoints?
Cutpoints are used to cluster a set of values into classes in such a way that the values in the same group are more similar to each other than to the ones in other groups. If we’re talking about values ranging from 0 to 100 percent, we wouldn’t normally represent each value with a different shade or color. Instead, we would cluster the values and represent all the values ranging from 0 to 10 percent with one shade or color, turning them into a single data class. Values ranging from 11 to 20 percent would be another class, represented by a different shade and so on. Of course, you can always set different classes that work better with your data.

Why are cutpoints important?
Let’s say we want to check out the percentage of the population over 16 years working in the armed forces.

1. In the Change data menu, click Change data.
2. In the Categories tab, select 2018.
3. Select Labor Force.
4. In the Employment Status for Total Population 16 Years and Over section, click In Armed Forces.

As you can see, the displayed map is rather bland. This is because data value for each state is less than 1 percent. A state that has 0.99 percent of the population over 16 years working in the armed forces is represented with the same color as a state that has 0.01 percent of the population over 16 years working in the armed forces. But if we divide the legend in a slightly different way, we can make the differences appear clearly.

Customizing cutpoints

Note: Right in the popup, there’s a master detail slider that allows you to zoom in on a particular range. Simply drag the handles on the left and right side to mark the range you want to zoom in on and fine-tune the cutpoints.

Additional settings
In addition to tweaking the default cutpoints, you can change the number of classes. The default (and maximum) number of classes is 11, but you can use fewer classes. Simply enter the number of classes at the top of the popup, or use the up and down arrows to set the number.

We have included 5 premade classification methods, but you can create your own custom method. The default method is Category – a method devised by our data scientists for each table individually to ensure cutpoints match the visualized variable. From the method dropdown, you can also select Equal interval, Arithmetic progression, Quantile, and Natural breaks. To create a custom method, follow these steps.

1. From the classification method dropdown, select Custom.
2. In the legend preview portion, click on any of the cutpoints indicated.
3. Enter the cutpoint value in the value field, or drag the cutpoint that you have selected left and right.
4. Click Done when you have customized all your cutpoints.

Apart from the default Category method, Social Explorer allows you to choose from four other data classification methods while customizing cutpoints, namely Equal interval, Arithmetic progression, Quantile, and Natural breaks.

• Equal interval: This classification method divides the data into equal-size classes and works best with data spread across the entire range.
• Arithmetic progression: this type of classification scheme creates class breaks based on class intervals that have an arithmetic series, which means the difference between consecutive intervals is constant.
• Quantile: this type of classification method distributes data as equal-sized segments of a dataset.
• Natural breaks (Jenks): this type of classification scheme divides the data based on natural groupings inherent in the data. Named after George Frederick Jenks, the Jenks natural breaks classification method minimizes variation within each range, so that areas within a particular range are closer in value to each other. This type of classification works best with data that is unevenly distributed.

Upload custom cutpoints

1. Click the icon for styling the visualization in the map legend.
2. Select Cutpoints.
3. To upload custom cutpoints, click Upload at the top of the popup window.
4. Locate the file on your hard drive and select it.
5. Click Open.

Download custom cutpoints

1. Click the icon for styling the visualization in the map legend
2. Select Cutpoints.
3. To download the current cutpoints, click on the icon at the top of the popup window.
4. Depending on your browser settings, you might need to select the folder where you want to save the file and click Save in the dialog box.

Using the Interactive Legend

Since the colors displayed on a map rarely have an inherent meaning, reading a map can be quite a challenge. This is where a map legend comes in handy. Just like your house key opens your front door, a map key or legend opens up a map. However, we wanted to take our legend to the next level and make sure it allows you to dig even deeper into your maps. We were successful in doing so by introducing the element of interactivity.

Click on a data color in the legend to spotlight the areas on the map which fall within that data range. This allows you to quickly focus on the states with the highest income or lowest population density without getting distracted by other groupings on the map.