CTRP 0821

CTRP 0821 – Digital Mapping | Lab Assignment #5 | October 22nd, 2020

This lab assignment is due by Thursday, October 29th at 3:29pm.

Objective:The objective of this assignment is to develop a deeper understanding of the core concepts introduced during today’s lecture through activities and experiential learning. More specific objectives include:

• Obtaining geographic data from a data portal for the purpose of creating a digital map
• Understand potential sources of error related to a quantitative model
• Implementattribute join operations
• Recognize how the decisions mapmakers make in regard to geographic data (e.g. classification method) affect the outcome
• Conduct analysis based on a quantitative model to understand a real-world problem

Part 1 – Mapping Voter Registration

In this lab, you’ll be making a map of voter registration in Philadelphia by political party affiliation as of the 2016 general election. Now that you have experience using Carto in previous labs, these instructions will be less detailed than before. If you don’t remember how to perform certain tasks in Carto, just ask a classmate or the professor (or revisit instructions from a previous lab).

Important Note: In keeping with the school’s principle of respect for diversity of viewpoints, this lab is not an endorsement of any political party, but is rather an opportunity to understand the spatial configuration of an important attribute of our city.

1. Download the voter registration data from the assignment page in Canvas, then upload it to Carto. This dataset has been edited for you, but you can view the original dataset from the City of Philadelphia at OpenDataPhilly if you’d like.

2. After uploading, take a look at the dataset in Carto. Notice that the enumeration units for the voter registration dataset are “precincts,” which refers to Philadelphia’s election ward divisions.

3. Also notice the data type for the precinct column (shown in gray beneath the column heading). Make sure the data type is set to “string;” if it is set to “number,” click the three dots next to the column head and change the data type.

4. Download the “Political Ward Divisions” dataset from OpenDataPhilly. Be sure to download the correct file format for web maps (see Lecture 3 if you need a reminder). Then upload the dataset to Canvas and make sure that the data type for the precinct column (in this dataset it’s called “division_num”) is set to “string,” which will allow Carto to connect our two datasets by their common attribute.

5. Create a map and add both datasets. The ward division dataset will appear on the map as a polygon feature, while the voter registration dataset will not appear on the map itself because it isn’t geocoded. If your map doesn’t automatically do so, click the three dots next to the political divisions layer, scroll down, and click “center map on layer.”

6. Click into the ward division dataset and add a new analysis to “add columns from 2nd dataset.” Your target should be the voter registration data; the join type should be “append;” your base and target columns should be your enumeration units for each layer (which will have different column names but refer to the same data); for base and target data, choose “select all” to avoid losing any columns you may wish to use later on.

7. You will make a univariate map (showing only one attribute), so now you must choose which attribute to use. Style the layer color by value, and choose whether to display each ward division by voters registered with the Republican Party or the Democratic Party; the dataset also includes voters who are registered with another party or are unaffiliated with a political party, so you can map this on your own if you’d like. Whichever party you choose, be sure to use the right kind of data for use with a choropleth map (see Lecture 5 if you need a reminder). Note: the attribute column names you added in step 6 will now be preceded by “right_” as they have been added to the right of the existing columns in the political divisions dataset.

8. Choose what you believe to be the most appropriate classification method, number of classes, and color scheme. You do not have to use one of Carto’s existing color schemes; if you scroll down past the existing schemes and click “custom color set,” you can control the exact color and opacity/transparency of each color in your scheme. You can also change the thickness and color of the lines around each polygon, which is called the “stroke.”

9. Add a legend and format it appropriately. Hint: add a % symbol in the suffix field to display your legend’s minimum and maximum attribute values as a percent.

10. Edit all titles (including browser tab) and legend text to make the map as clear as possible. There should be no remaining default text, underscores, etc. Remember that your title does not have to be boring! If there’s a message you think your map communicates, you can incorporate it into your title.

11. Choose your favorite basemap (if you haven’t already), ideally one that matches the overall design of the map.

12. Your map is almost complete! But first, we will add another one of the five required map components: metadata. Click the three dots next to the map title and then click “edit metadata.” Add your metadata into the description box, add any tags (i.e. keywords) you wish, and click save. Remember, metadata generally includes the data source (City of Philadelphia), data collection year, cartographer name (you), and any other relevant information.

Paste Map URL here:

Next, answer the questions below:

Which classification choices did you make, and why?

What color choices did you make, and why?

What text choices did you make (title, legend, metadata), and why?

What might a map user learn about Philadelphia from reading your map?