An exploration of fuel poverty in the private rental housing market
- Tuesday 20 October 2020
- 10:00 - 12:00 (BST)
- Online (via Zoom) GET DIRECTIONS
The recording of this webinar and related resources are available on our Interactive Data Dives page.
Many homeowners and tenants are at risk of fuel poverty in the UK. Those on low incomes are also experiencing “double deprivation” due to the low energy efficiency of their houses or rental properties. These poor thermal conditions may cause chronic health problems and threaten lives. Properties in the private rented sector are known to have particularly significant problems with energy efficiency while the proportion of low-income households in private renting is rising rapidly.
In this webinar, led by UBDC's Dr Qunshan Zhao, we will explore whether low-income neighbourhoods experience worse energy efficiency in the private rental market. We will examine if a lack of energy efficiency also increases the fuel poverty level and how we can help those on low incomes. Results from research like this can serve as guidance for the Scottish Government to identify low energy efficiency areas in the private rental market.
In this session, we will use Glasgow as an example and attempt to accurately identify the fuel poverty area within the city. To achieve this goal, we will use Zoopla data hosted by UBDC, Scottish Index of Multiple Deprivation (SIMD data), Scottish Census data, and the Scottish EPC data.
The first session from 10:00-10:45 am will be a lecture-style overview to explain the research questions and data. Following a 15-minute break, the second session from 11:00-12:00 will be a hands-on practical demonstration and Q&A session with Python in the Jupyter notebook environment.
What you will learn
- Understand the challenges of fuel poverty in Scotland
- How to use open source programming languages to clean, manage, analyse, and visualize urban big data
- Gain hands-on coding experience through GitHub and Jupyter Notebook
- How the UBDC data service can help with your research
Data and software requirements
The following data will be used in this webinar:
- Scottish EPC dataset (Postcode sector)
- Scottish Index of Deprivation dataset (Datazone)
- Scottish Census data (Datazone)
- Local Level Average Household Income Estimates 2014 (Datazone)
For this session, we will be working in Python and you can download Anaconda for Python distribution. Packages that we will use in this webinar include pandas, NumPy, Matplotlib, PySAL, and scikit-learn.
Who should attend
University students, academic researchers, housing researchers and anyone interested in urban data science and urban analytics should attend.
About the Data Dives series
This series of free online interactive tutorials taking place throughout October 2020, will enable you to dive confidently into urban data science with the help of UBDC researchers and our data collections.
These online courses are delivered by members of our research staff, who want to share their knowledge and advice on working with novel forms of data with you.