  A desire to understand the decision of the UK to leave the European Union,
Brexit, in the referendum of June 2016 has continued to occupy academics, the
media and politicians. Using topological data analysis ball mapper we extract
information from multi-dimensional datasets gathered on Brexit voting and
regional socio-economic characteristics. While we find broad patterns
consistent with extant empirical work, we also evidence that support for Leave
drew from a far more homogenous demographic than Remain. Obtaining votes from
this concise set was more straightforward for Leave campaigners than was
Remain's task of mobilising a diverse group to oppose Brexit.
