Learning

Helpful resources, such as companion guides for the technologies we use and tutorials demonstrating useful techniques. Choose a companion or tutorial from the following lists. Our tutorials are published on Medium and open in a new window.

Companions

These are recipes to common tasks like retrieving data from Nomis, geocoding addresses, and creating data visualisations like population pyramids. All the R code is provided along with step by step instructions.

We've curated some open datasets relating to climate change to help UK councils that have declared a "climate emergency" and those that haven’t. We have also created a climate emergency slide pack app to help visualise open data relating to climate change.

A guide to creating interactive data visualisations using Vega-Lite. Our accompanying blog post on Medium provides a useful introduction.

This companion provides R code demonstrating how to retrieve and tidy open data from a number of government APIs.

This demonstrates the different types of visualisation that are possible with the ggplot2 package in R, providing code for each of the examples.

Tutorials

This post will show you how to download digital vector boundaries for custom administrative geographies using the Open Geography Portal API.

This is a short introduction to creating choropleth maps in Vega-Lite. We’ll show you how to load geospatial data, customise maps and join attributes.

This tutorial explain step-by-step how to create chart using Vega-Lite that allows users to quickly build visually appealing static and interactive data visualisations in their web browser.

This article details the steps required to request data from Governments and other organisations Web service APIs using R.

This is a short introduction to creating choropleth maps in R. The tutorial will show you how to download Ordnance Survey boundary layers, merge them with 2011 Census data and visualise the results in classed and unclassed choropleth maps.

Using the fingertipsR package the tutorial show you how to download some data from Public Health England’s Fingertips repository and visualise it in R.