Analysts’ Guide
This website is a guide aimed at anyone working in analysis or statistics in the Department for Education (DfE). It includes tips on best practice and learning resources across a number of areas.
We hope it can prove a useful community driven resource for everyone from the most experienced analyst right through to those just starting out. If you have any feedback, suggested additions, or wish to challenge any of the guidance, feel free to use the GitHub links to suggest changes directly, or contact us at the email you can find at the bottom of the page.
Learning and development
Learning support - Useful learning resources, and support to get you started
SQL - Guidance and tips for accessing data via databases with SQL
R - Guidance and tips for using R
Git - Guidance and tips for version control with Git
Python - Guidance and tips for using Python
Accessibility - Tools and resources for digital accessibility
Statistics production
Routes for publishing - Guidance for how to publish different types of statistics
RAP in statistics - Detailed RAP guidance for statistics publications
Open data standards - Guidance on how to structure data files
Statistics API data standards - Guidance on the standards to meet for API data sets
Explore education statistics (EES) - Tips on using the explore education statistics service
Good examples in EES - Good practice examples in the explore education statistics service
Embedded visualisations in EES - How to embed R Shiny charts in EES publications
Publication scrums - Information on the scrums we run and tips for writing statistical commentary
User engagement - Guidance on understanding and engaging with the users of published statistics
EES analytics - Understanding how users are interacting with your publications
Writing and visualising
Public dashboards - Guidance for publishing public facing statistics dashboards
Publishing an R Shiny based dashboard - Guidance for publishing public facing statistics dashboards using R Shiny
Visualising data - Resources and best practice to guide you when visualising data
Writing about data - Resources and best practice for writing about data
Reproducible Analytical Pipelines (RAP)
RAP in statistics - Detailed RAP guidance for statistics publications
RAP expectations - Guidance for all analysts on expectations of RAP
RAP support - Details on support available for RAP in DfE
RAP FAQs - Frequently asked questions about RAP
Analytical Data Access (ADA) and Databricks
Analytical Data Access (ADA) and Databricks - Guidance for analysts on how to interact with and use data stored in ADA using Databricks
Databricks Fundamental Concepts - Fundamental concepts in DataBricks that will help you navigate and understand the platform
Databricks Notebooks - Guidance on Notebooks in DataBricks
Databricks Workflows - Guidance on Workflows in DataBricks
Setup Databricks SQL Warehouse with RStudio - Guidance for analysts on how to connect to a Databricks SQL Warehouse from RStudio.
Setup Databricks personal cluster Warehouse with RStudio - Guidance for analysts on how to connect to a Databricks personal cluster from RStudio.
Contact us
Our mailbox is always monitored and is available for anyone in DfE to ask questions about statistics, whether that is about RAP, building dashboards, coding support, learning and development or statistics publications.
- statistics.development@education.gov.uk
- 9am-5pm, Monday-Friday, aim to reply within 1-2 days