2025-11-23 –, Plenary Space
Crow Advisory chose python for their spatial forecast analysis of the Wellington housing development response to Wellington's 2024 District Plan, which greatly increased allowable building capacity across the city. We'll talk through the tools we used, the design approach, and what we learned about doing spatial data science in python.
Tools used include
poetryfor dependency management,hydra(viahydra-zen) withdataclassesfor config management, CLI setup, and keeping a record of config inputs vs model outputsDVCfor data version control, preprocessing management, efficient pipeline runs, and more tracking of inputs vs outputslogurufor logging and terminal outputspandas,numpy, andgeopandasfor data wranglingosmnxandnetworkxfor street and public transport network analysis- 'statsmodels',
scikit-learn,econML,scipy, andpulpfor modelling and prediction matplotlibandpyDeckfor visualisation- Github for source control
