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Texas Child Care Deserts

API to create data for any count on child care deserts in Texas

Function and attributes of the Texas Child Care Deserts Package

  1. Create a database of data to be used to create the Texas Child Care Deserts
root <- "F:/Early_Childhood/04_Tarrant_County"
child_care_db(root = root,
              naeyc_pth1 = naeyc_pth1,
              naeyc_pth2 = naeyc_pth2)
  1. Load an child care deserts database or a subset of the database with clean and processed data for use
pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
load_env(pth)
  1. Compute child care distance distributions
pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
load_env(pth)
county <- c("48201", "48439")
calc.distance_decile_table(df = DF_ACF, county_list = county)

pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
load_env(pth)
county <- c("48201", "48439")
calc.distance_density_plot(df = DF_ACF, county_list = county)
  1. Calculate subsidy providers average capacity

Note: The tract_radius (in miles) should be informed by analysis using the above functions.

pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
load_env(pth)

config <- list(`48439` = list(tract_radius = 3),
               `48201` = list(tract_radius = 3))

calc.subsidy_capacity(config = config,
                      xwalk_tracts = XWALK_TRACTS,
                      adj_tracts = ADJ_TRACTS,
                      df_hhsc_ccl = DF_HHSC_CCL,
                      df_acf = DF_ACF)
                      
calc.subsidy_capacity(config = config,
                      xwalk_tracts = XWALK_TRACTS,
                      adj_tracts = ADJ_TRACTS,
                      df_hhsc_ccl = DF_HHSC_CCL,
                      df_acf = DF_ACF,
                      grouping_vars = "center_prvdr")
  1. Subset the database to a specific county to application development

Note: The tract_radius (in miles) and capacity estimates should be informed by analysis using the above functions.

pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
config <- list(`48439` = list(tract_radius = 3,
                              home_prvdr_non_sub_capacity = .85,
                              center_prvdr_non_sub_capacity = .85,
                              home_prvdr_sub_capacity = .75,
                              center_prvdr_sub_capacity = .65),
               `48201` = list(tract_radius = 3,
                              home_prvdr_non_sub_capacity = .85,
                              center_prvdr_non_sub_capacity = .85,
                              home_prvdr_sub_capacity = .84,
                              center_prvdr_sub_capacity = .78))

save_subset_child_care_db(pth = pth,
                          config = config)
  1. Subset the database to a specific county AND 0-3 age range for application development

Note: The tract_radius (in miles) and capacity estimates should be informed by analysis using the above functions.

pth <- "F:/Early_Childhood/04_Tarrant_County/data/processed/child_care_env.RData"
config <- list(`48439` = list(tract_radius = 3),
               `48201` = list(tract_radius = 3))

save_subset_child_care_db_03(pth = pth,
                             config = config)

Project workflow

Clone the analysis and set-up the environment

  1. Open Git Bash
  2. Type git clone https://github.com/Texas-Policy-Lab/texas_child_care_deserts.git
  3. Open the R-project
  4. Type install.packages("renv")
  5. In the console type renv::restore() to create the local R-environment

Create a new branch

  1. Assign a JIRA ticket to yourself
  2. In the console type git checkout -b features/TCCCD-10 or whatever JIRA ticket number you've assigned to yourself
  3. Make the changes to the code
  4. Stage your commit by typing git add file_name and then type `git commit -m "commit message"
  5. To push your changes to the server type git push

Test the code

  1. Make changes to the code according the to ticket you are working on
  2. Load the package devtools::load_all()
  3. Run the child_care_db function
root <- "F:/Early_Childhood/04_Tarrant_County"
child_care_db(root = root)
  1. Update the function documentation devtools::document()
  2. Run all the tests to make sure they are passingdevtools::test()

Ask for review

  1. Ask a team member to review your work by sending a pull request