Introduction | Requirements | How to use | How to contribute | Contact
The dashboard provides users with an opportunity to investigate the proportion of 16 and 17 year olds not in education, employment or training (NEET) and participation information at a local authority level with national and regional comparisons.
Live version of the dashboard can be accessed at
The dashboard is split across multiple tabs:
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NEET and not known includes information on NEET and not known rates for 16 and 17 year olds with national and regional comparisons and annual changes.
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Vulnerable groups NEET includes information on NEET and not known rates for those 16 and 17 year olds in a vulnerable group, with special educational need or disability (SEND), with special educational needs (SEN) support and no SEN.
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Participation includes information on the proportion of 16 and 17 years old participating in education or training and the proportion of offers made under September Guarantee.
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Contextual - attainment and absence includes information on post-16 attainment, GCSE attainment, absence and population.
The dashboard also includes further information on the data itself on the homepage tab, alongside accessibility and information on where to find further support.
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Installation of R Studio 1.2.5033 or higher
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Installation of R 3.6.2 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. -
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. The yaml file for this can be found in the .github/workflows folder.
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/nccis_localauthority_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 team can merge pull requests. Add AnnekaAlbon as requested reviewers, and the team will review before merging.
If you have any questions about the dashboard please contact [email protected]