Clean domestic job placement data - UCSB-MEDS/shiny-dashboard GitHub Wiki

The Career Outcomes tab of the dashboard features a heat map showing initial job placements for both MEDS and MESM alumni. States are shaded based on the number of placements, with darker colors indicating higher counts. Hovering over a state reveals a tooltip displaying the state name and total number of placements.

We've chosen to pre-process the placement counts and geometries, save them to file, and then load them into the dashboard to improve performance -- doing this processing within the app resulted in excessively long load times. Follow these steps to wrangle and save these data:

  1. Download us_state_geoms.rds from Google Drive and add to your local bren-student-data-explorer/data/ directory. us_state_geoms.rds contains US state names / abbreviations and their geometries. These data will not change year-to-year, and can be reused across dashboard updates.

  2. Locate & open the domestic-placement-cleaning.qmd file (inside shiny-dashboard/data-cleaning/). This file includes all necessary wrangling code.

  3. In section 0, update the filter statements to filter for the three most recent years (for mesm_placement and meds_placement objects). E.g.

mesm_placement <- readRDS(here::here("bren-student-data-explorer", "data", "mesm_placement_cleaned.rds")) |> filter(year %in% c(2022:2024))
meds_placement <- readRDS(here::here("bren-student-data-explorer", "data", "meds_placement_cleaned.rds")) |> filter(year %in% c(2022:2024))

  1. Run sections 1 & 2 to join initial job placement data to US state geometries, then count the number of placements per state for both MESM and MEDS.

  2. Run section 3 to write both data frames (mesm_domestic_stats_geoms & meds_domestic_stats_geoms) to file at bren-student-data-explorer/data/ -- they will be named mesm_domestic_placement_data.rds and meds_domestic_placement_data.rds.