This week I took to DataWrapper to test three different data map options and see which fit best for my data.
- Locator Map- A map that uses markers to show specific locations
- Choropleth Map- A map widely used to show regional patterns or local data
- Symbol Map- A map best used to show data for specific geometric locations (DataWrapper 2020)
Locator map– Wineries in Connecticut
For my locator map, I chose to chart the top 33 wineries in Connecticut. Latitude and Longitude marks were provided by https://www.latlong.net/ and the list of wineries provided were from Tripadvisor.
While I found the map to be successful overall, I did realize that my data was building up quickly making it difficult to read the names of wineries. Perhaps I should have picked a smaller dataset. After all, Connecticut is quite a small state!
Because of large amount of markers, I hoped I could zoom in a little tighter to focus strictly on the state; however, the map would zoom in too much and I would lose some of the markers on the outer perimeter.
Therefore, in order to separate the data and add a little flair to my markers, I was able to add the little wine markers and highlight the points in red to create separation from the name of the winery.
One of the questions I asked myself while building this dataset was which county had the most wineries. Luckily, Datawrapper gave me an option to highlight certain regions and I could highlight New London County as the county with the most top rated wineries. Using this feature allowed me to tell a somewhat deeper visual story if I were to use that dataset in the future.
Choropleth Map– Drug Deaths in the Northeastern United States
According to Datawrapper, chorolopleth maps are best for showing regional patterns in data (Datawrapper 2020). With data collected from the United Heath Foundation I created a Choropleth map depicting the number of drug related deaths in the US. I was particularly interesting in displaying which states had the highest number of drug related deaths. These deaths could be categorized by unintentional death, suicide, homicide or undetermined (United Health Foundation 2020).
To demonstrate high contrast, I chose to use a diverging color scale to show the darkest states as having the highest number of drug related deaths.
To take it a step further I wanted to create a more condensed map. I decided to input my data to represent just drug related deaths in the Northeastern United States. Immediately the scale and colors in the key changed from the highly contrasted map that represented the whole country. Therefore, I decided changed my color key to a sequential color scale to depict more of a relationship between states with lower rates of drug deaths and higher rates (Datawrapper 2020).
All in all, of all the maps I tested in Datawrapper, this type of map was the easiest to use. It was easy to cut and paste my values from the excel sheet I created.
I again had a difficult time playing with the ability to zoom in and could not find an option to make my final map of just the Northeastern United States.
Symbol Map– Top Wineries in CT According to Google Reviews
Creating my symbol map was undoubtedly my most frustrating experience and I had to visit Datawrapper’s Symbol Map resource multiple times.
Initially, I had the idea of showing which park in Disney World had the highest rated restaurants. My first instinct was to download my own map of Disney World, but could not upload with the proper setting. Unable to continue I tried to use the map of zip codes in Florida, hoping that the map would change with the more coordinates I put in. As you can see, it did not.
Switching gears, I decided to adjust to my next dataset to include Top Rated Wineries in Connecticut according to the average Google Rating from 0-5. This map allowed me to give a clear visual of which wineries are the most popular by again using a diverging color scale. I included an option to view the ratings of each of the wineries.
The final map is presented below. I wish I could have made the winery markers into bigger shapes depending on the rating, but I suppose that I would have been able to if I was creating a symbol map to represent population instead. I also should have provided a more clear indicator in the scale that the values were on a scale of 0-5 stars.
As I continue using Datawrapper and using datasets to create visuals, I will need to be more specific with my datasets to create more clear and detailed representations. This will employ better use of sizing scales to depict low to high populations (or ratings in the case of my last map.) Luckily, throughout testing three different kinds of maps, I have found how important the use of color choices is in depicting data and I can now be conscious of the color sets I am using.
Hopefully in the future, I will be able to use my Disney Restaurant Ratings dataset to tell a visually interesting map!
References
Datawrapper. (2020, July 22). How to create a symbol map. Retrieved August 02, 2020, from https://academy.datawrapper.de/article/114-how-to-create-a-symbol-map-in-datawrapper
Datawrapper. (2020, January 31). What to consider when creating choropleth maps. Retrieved August 02, 2020, from https://academy.datawrapper.de/article/134-what-to-consider-when-creating-choropleth-maps
TripAdvisor. (2020). THE 10 BEST Connecticut Wineries & Vineyards (with Photos) https://www.tripadvisor.com/Attractions-g28928-Activities-c36-t132-Connecticut.html
United Health Foundation (2019). Drug Use and Death Heat Map [Data set]. https://www.americashealthrankings.org/health-topics/subtag-7/heat-map?topics=category-1,tag-3
dananalyze.com 