Given the recent storms and floods it seemed a good time to try something slightly new in python, calling an API. Specifically, I want to be able to call the Environment Agency flood warning API then map all areas with a flood warning and then extract a list of postcodes within those flood areas. Code …
In a previous post I used NetworkX functions to convert a shapefile into a graph network for use in spatial smoothing. But there is a problem! Rivers and seas were un-crossable voids. I don’t really want to swim across the rivers, particularly the Thames, but luckily for us there are bridges across rivers and ferries …
My previous post, network analysis and spatial smoothing, I investigated how to use NetworkX functions in python for potential use in spatial smoothing. In this post I’ll actually go over an example of the code being used to smooth average house price data across London. The code for this investigation is here The area being …
Read more “Spatial Smoothing using Network Analysis – Implementation”
In my last post I introduced the concept of using network analysis for use on Road data. In another post I looked at using pygeos to spatially smooth data. This time I’ll be combining network analysis and spatial smoothing. The Problem Using distance related spatial smoothing, whether this is using kernel density or count/average within …
Maps are all well and good, but do you know what’s better. Graphs! I’m not talking about pie charts or even bar charts I mean the ones with edges and vertices (also known as networks). In this post, and this code, I’m going to convert a geodataframe of A-roads around St Pauls into a graph …
How to use python to map uk open data. Including land registry, ONS, OS and post office data.