My partners goal for this project is to create an interactive data visualization representing Girl Scout partner potential by comparing current participation to current census data. By using a diverging map the Girl Scouts are able to see where they are reaching more participants than expected and where they are not reaching enough. This map contains all age data from 5-17 years old broken down into three age groups based off of census data. The maps are using percentage of possible partners to create a diverging map using standard deviation to determine what is above average membership and what is below average membership.
Tasks completed:
- Organized Girl Scout data into pivot table representing all age levels
- Combined Girl Scout data with population data
- Calculated potential partner percentage
- Used standard deviation to combine data for Google fusion diverging map
- Created diverging map with all data on one spread sheet
- Created google fusion template
Things to do:
- Work with Google fusion template to combine 5 maps
- Work on issue of only having 3 age levels because of census data
- Add points containing locations of Girl Scouts meeting places
- Finalize design of map
- Work on color scheme for maps to have them match girl scout colors
- Add a key telling you what each color is representing
- Use template to edit view window (show actual percentages, decide what should be seen in each window)
- Tweak template to what partner wants
Hi Stefania,
Your diverging map is telling a great story. I can figure out that green areas represent higher-than-average girl scouts participation, and purple areas represent lower-than-average participation.
When I scroll through different map tabs I can see a change in girl scout participation along with the increasing age of girls. I think it will be excellent if you can incorporate these 4 maps into one single template. That would tell a great story about girl scouts participation.
I guess it will be better to include a legend in your map to clarify where the average point is, and how you determined “above average” or “below average”.
Also here is a small suggestion: is it possible that you include town’s names on the map? As I am not originally from CT, this map cannot give me a sense of which town participate the most in girl scouts on my first glance. I have to click on different towns to get their names. I think it would be much clearer if town’s names are represented on the map.
Stefania, I really like the color scheme you use for this map. The green and purple clearly portray the towns who have higher or lower girl scout participation percentage. I also like the fact that you use the same colors for each map, this makes it easier to compare similarities and differences between the various age groups. These maps are very clear and include a lot of information when you click on a town outline, however I think you should add a legend to these maps. A legend could make the maps even more clear-cut .
As far as combining the maps go, you may want to look at the way Norah combined her maps in her demo. The clickable header in her maps makes it easy to switch between and compare the maps. Here is a link to the post: http://commons.trincoll.edu/dataviz/2016/03/30/demo-in-progress/