A spatial typology of energy (in)efficiency in the private rental sector in England and Wales using Energy Performance Certificates
Like many countries globally, the private rental sector in England and Wales contains some of the lowest quality, inefficient properties, despite being home to many of the most vulnerable households. In this analysis, we use new property-scale Energy Performance Certificate (EPC) data to analyse detailed energy and housing characteristics for 3.9 million private rentals (~78.8% of total sector), the most comprehensive dataset of its kind. K-means clustering generates a small-area classification of efficiency in the sector at Output Area scale. Demographic datasets allow us to explore wider socio-spatial inequalities, and uncertainties associated with granular, but at-times incomplete, EPC data.
💬 Language: Please note that our project team works across programming languages (R and Python).
🧱 Structure of repository: The analysis is split into three sections.
Clean: How to clean and process the EPC data for analysis
Cluster: How to carry out k-means clustering to derive the final classification
Context: How to contextualise clusters using socio-demographic data
📊 Dataset download: View the final classification mapped for Output Areas in England and Wales here or download it here.
