1. Mapping Child Care Availability in Denver Ann Wacker

2. About this project
Part of the Butler Institute for Families’ Denver Preschool Program (DPP) evaluation
Also my RMS PhD practicum project
The Denver Preschool Program…
Offers tuition credits to help families afford preschool
Works with preschools to improve their quality

3. Study Design
Purpose: Conduct a neighborhood analysis of early care and education (ECE) availability in Denver
Evaluation question: What is the distribution of ECE and preschool programs across Denver neighborhoods?
Implications:
Provide DPP with information they can use to better reach out to preschools and families
Add to previous analyses of child care in Denver

4. Data Sources Licensed child care facilities Neighborhood demographics
CSV spreadsheet (CDHS Office of Early Childhood, 2018)
Neighborhood demographics
File type: CSV spreadsheet (Piton Foundation, n.d)
Denver statistical neighborhood boundaries
GIS “Shapefile” (City and County of Denver, Community Planning and Development, 2018)

5. Measures Density of ECE slots per square mile Average quality rating
Type of program (% centers)
Ratio of ECE slots to children
If < .33, this indicates a “child care desert” (Malik & Hamm, 2017)

6. Working with Spatial Data in RStudio
Reading data files into the R environment

7. Working with Spatial Data in RStudio
Basic plot of the child care centers:

8. Working with Spatial Data in RStudio
Basic plot of Denver neighborhoods

9. Working with Spatial Data in RStudio
Plotting child care centers and neighborhood boundaries together
These files needed a common Coordinate Reference System (CRS)!
Child care data did not have a CRS.
Neighborhood file used the CRS called “WGS84”

10. Working with Spatial Data in RStudio
Plotting child care centers and neighborhood boundaries together

11. Working with Spatial Data in RStudio
Which ECE programs are in each neighborhood?
I needed a variable to indicate which child care programs were in which neighborhoods
The “sp” vignette helped me figure this out (Pebesma & Bivand, 2005).

12. Working with Spatial Data in RStudio
Computing aggregated variables of interest by neighborhood
Many lines of R script!
Used data on the area of each polygon (a.k.a., neighborhood) to determine the density of child care centers per square mile.
Most computations not specific to geographic analyses (recoding from string to numeric, collapsing/deleting categories, averaging ratings by neighborhood)

13. Creating Maps using Leaflet
Create a map widget:
Add Polygons (a.k.a., my neighborhood boundaries)
Add Circles (plots of the ECE programs)
Specify the formatting to make it look nicer

14. Creating Maps using Leaflet
Map using all default settings: Formatted map:

15. Creating Maps using Leaflet
Choropleths: shading of maps based on attributes
Need to specify:
Bins: categories for the variable
Palette: which colors to use
Then in the Leaflet script, tell R to use this to shade the neighborhoods accordingly
Note: order of cases in data file by neighborhood matters!

17. Development of Shiny web-based app
So far, these maps live in the R environment
But DPP probably doesn’t want to learn R… 
Shiny makes it possible to publish maps and other content on the web so your audience can interact with it without R!

18. Development of Shiny web-based app
Shiny app script
Server: generates the content that you want to display & includes…
Script to create the maps
“Layers” of the map that can display different characteristics
A drop-down list of programs by neighborhood
UI: specifies what to display on the web
Pulls up the maps, displays the drop-down box, provides a title and other text

19. Development of Shiny web-based app
Shiny apps can be published to the web
Create an account at:
Errors/challenges:
Publishing to the web while on VPN and/or my DU drive  save all files in a desktop folder (with nothing else)
Tip for de-bugging while publishing to the web:
options(shiny.sanitize.errors = FALSE)

20. Walk-through of ECE availability app

21. Results Development of web-based app to visualize ECE availability
Key finding:
Neighborhoods with low-income residents tend to have higher quality ratings, but are geographically isolated and do not have enough ECE slots

22. Practicum Reflections
I think this was a successful practicum because …
I was interested in this topic and in mapping
I had access to the necessary data
The project had a well-defined scope
It was both work-related and a new learning experience!
What
When
Estimated Hours
Project Planning
November - January
10 hours
Analysis & Mapping
January
40 hours
Development of Web App.
February
35 hours
Reporting
March 30

23. Thank you!
Questions? Comments?

24. References
City and County of Denver, Community Planning and Development. (2018). Statistical Neighborhoods – Shapefile [Data file]. Retrieved from statistical-neighborhoods
Colorado Department of Human Services - Office of Early Childhood (2018). Colorado Licensed Child Care Facilities Report [Data file]. Retrieved from Facilities-Report/a9rr-k8mu
Malik, R., & Hamm, K. (2017) Mapping America’s Child Care Deserts. Center for American Progress. Retrieved from childhood/reports/2017/08/30/437988/mapping-americas-child-care- deserts/#.Wii13gKyLhg.
Pebesma, E.J., & Bivand, R.S. (2005). Classes and methods for spatial data in R. R News 5 (2), Retrieved from project.org/doc/Rnews/Rnews_ pdf
The Piton Foundation. (n.d.c) Report Builder. Retrieved from