Introduction | Requirements | How to use | How to contribute | Contact
This dashboard provides users an opportunity to investigate the Longitudinal Education Outcomes (LEO) new graduate industry data.
Live version of the dashboard can be accessed at:
The dashboard is split into four themes:
- Interactive Sankey charts that shows the longitudinal journey of the 5 year after graduation (YAG) cohort. This shows the number of graduates working in each industry for the selected subject area at one, three and five years after graduation.
- Regional analysis that compares the number of graduates who studied in and are currently living in each region.
Tables that show proportions and median earnings for combinations of industry, subject, qualification level, sex, prior attainment, current region, ethnicity and FSM status.
- Subject by industry tables, which show for the selected subject, which industries those graduates work in at the selected year after graduation. These tables are also expandable to the 3-digit SIC code level providing more granular breakdowns for each of the industry sections.
- Industry by subject tables, which show for the selected industry, what subjects the graduates working in that industry studied.
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Installation of R Studio 1.2.5033 or higher
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Installation of R 4.1.3 or higher
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Installation of RTools40 or higher
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R at an intermediate level, DfE R training guide
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Particularly R Shiny
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Clone or download the repo.
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Open the R project in R Studio.
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Run
renv::restore()to install dependencies. If it gets stuck on the BH package, manually download the zip from CRAN and unzip into your library folder. -
Run
shiny::runApp()to run the app locally.
Package control is handled using renv. As in the steps above, you will need to run renv::restore() if this is your first time using the project.
UI tests have been created using shinytest that test the app loads, that content appears correctly when different inputs are selected, and that tab content displays as expected. More should be added over time as extra features are added.
GitHub Actions provide CI by running the automated tests and checks for code styling. The yaml files for these workflows can be found in the .github/workflows folder.
The function run_tests_locally() is created in the Rprofile script and is available in the RStudio console at all times to run both the unit and ui tests.
- The app is deployed to the department's shinyapps.io subscription using GitHub actions, to https://department-for-education.shinyapps.io/leo-graduate-industry-dashboard/. The yaml file for this can be found in the .github/workflows folder.
If you have any questions about the shinyapps.io subscription and deployment in DfE please contact the Statistics Development Team at [email protected].
In general all .r files will have a usable outline, so make use of that for navigation if in RStudio: Ctrl-Shift-O.
The function tidy_code() is created in the Rprofile script and therefore is always available in the RStudio console to tidy code according to tidyverse styling using the styler package. This function also helps to test the running of the code and for basic syntax errors such as missing commas and brackets.
Our contributing guidelines can be found at https://github.com/dfe-analytical-services/leo-graduate-industry-dashboard/blob/main/CONTRIBUTING.md.
If you spot any issues with the application, please flag it in the "Issues" tab of this repository, and label as a bug.
Only members of the development team can merge pull requests. Add chfoster, cjrace and rmbielby as requested reviewers, and the team will review before merging.
If you have any questions about the dashboard please contact [email protected].