Posts

We communicate by telling stories. In our professional world, we often use data to support our stories. But how do we tell compelling stories with data? This post explores, very briefly, the art and science of data storytelling, providing insights and techniques to help you craft narratives that resonate with your audience.

Introduction This post was last updated on 2025-08-07 Large Language Models (LLMs) represent a class of artificial intelligence systems that have fundamentally transformed natural language processing and generation. These neural networks, trained on vast corpora of text data, demonstrate remarkable capabilities in mimicking the understanding context, generating coherent(ish) responses, and performing complex reasoning tasks across diverse domains.

Introduction In this post, I am going to show how one might go about analysing the Bikeshare use in New York city.

Introduction Understanding the reach and effectiveness of public transit is important to understand how urban environments are accessible for different groups of people.

Introduction Some transportation networks are intuitive to understand as networks. We can easily visualize intersections as nodes and roadways as edges in a road network.

Introduction In other posts, I have shown how to use external servers (google, craigslist etc.) to access information. You can also query a local (on your computer) server and your R session acts like a client (e.

Some exploratory graphics using air pollution data in the US.

Intersection Density is often used as an indicator of urban form in travel behaviour and urban design. In this post, I detail a way to calculate this indicator by leveraging OpenStreetMap data. I also focus on how to link R & QGIS as an illustration.

Free form text is ubiquitous in planning, including plans, regulations, meeting minutes, and transcripts, etc. This is a short introduction to analysing such text quantitatively.