Semi-regular posts of data viz creations. Find the code on Github, follow me on Twitter for updates or check out my website for my portfolio and contact details.
Each day also posted to scroll through below.
Poster created by the app
Data Doodle
Yay, I finally turned my data doodle into an app. So anyone can upload their data and create their own “Strava Wrapped”. The app is made using streamlit, matplotlib, and pyfonts and a few more libraries of course. You can try it out here or check out the full code.
I recently moved house, so I didn’t have time to take part in #30DayMapChallenge in November. Now that I’m getting settled, what better way than using maps to explore my new neighbourhood. So here is Day 1 - Points showing council maintained trees in Abbey Wood, London. 🌳 🗺️ Made in #python #matplotlib. Basemap data from #OpenStreetMap via #OSMnx (finally updated to v2.0). Tree data for London is available in the London Datastore.
Contribution to the #TidyTuesday challenge week 35 using the Kaggle Power Rangers dataset. I didn't even know the Power Rangers Franchise was still going, which is incredible!
I made a stripplot exploring average ratings of episodes + seasons. Looks like the latest ones (2019, 2020) were quite good 😀 Plot made in python using matplotlib + seaborn.
In 2023, 8 cyclists were killed on roads in London, a total of 40 between 2018 and 2022. Most serious and fatal cyclist collisions happen at junctions. The London Cycling Campaign analysed stats19 data for 2018-2022 to rank the most dangerous junctions in London. This small multiples data viz unpicks the top 15 locations and visualises the junction outline and where collisions happened. Note that the layouts are based on the most recent Google Maps satellite views and might have changed over the time period.