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DfE data dashboard showing the collated timeseries for Key Stage 5 Attainment and single year entries

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dfe-analytical-services/ks5-timeseries-attainment-and-single-year-entries

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16 to 18 Time series attainment and single year entry dashboard

Introduction | Requirements | How to use | How to contribute | Contact


Introduction

This dashboard allows users to explore time series data for 16 to 18 qualifications in England, with breakdowns by institution type (for average result/grade) and gender (for both A level average result/grade, and A level entries and grades in individual subjects).

It brings together figures compiled from the current and previous versions of the ‘A level and other 16 to 18 results’ statistical release.


Requirements

i. Software requirements (for running locally)

  • Installation of R Studio 2023.12.0+369 or higher

  • Installation of R 4.4.2 or higher

  • Installation of RTools44 or higher

ii. Programming skills required (for editing or troubleshooting)


How to use

Running the app locally

  1. Clone or download the repo.

  2. Open the R project in R Studio.

  3. Run renv::restore() to install dependencies.

  4. Run shiny::runApp() to run the app locally.

Packages

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.

Tests

UI tests have been created using shinytest that check 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.

Deployment

  • 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.

Navigation

In general all .r files will have a usable outline, so make use of that for navigation if in RStudio: Ctrl-Shift-O.

Code styling

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.


How to contribute

Flagging issues

If you spot any issues with the application, please flag it in the "Issues" tab of this repository, and label as a bug.

Merging pull requests

Only members of the 16-18 accountability data and development team can merge pull requests. Add patithomas, cjrace, and rmbielby as a requested reviewers, and the team will review before merging.


Contact

Email [email protected]

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DfE data dashboard showing the collated timeseries for Key Stage 5 Attainment and single year entries

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