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#osmnx

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I recently moved house, so I didn’t have time to take part in #30DayMapChallenge in November. Now that I’m getting settled, I want to start exploring my new neighbourhood and get back to mapping.

So here is Day 1 - Points showing council maintained trees in Abbey Wood, southeast 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.

🔗 Code: github.com/Lisa-Ho/30-day-map-

Croissant Distribution🥐 📊

or, where am I most likely to have my next croissant, assuming (something something) independence from my previous croissant. 🥐^k * e^(-🥐) / k!
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2d kernel density estimation of the location of bakeries (blue) and farms (red) across France.

Locations taken from OpenStreetMap (considered paying attention to the size of the farm, but didn't), with #osmnx & plotted with #matplotlib & #seaborn. font: Borel, by Rosalie Wagner.

#30DayMapChallenge Day 2: Lines

Despite my recent absolute failure with #LazyMaston, here we go again:

Dear toot-pals, where can I find wholesome learning materials on #matplotlib and/or #maps /#cartography / #geodataviz in #Python?

I've been playing with #OpenStreetMaps via #osmnx, which is awesome , but I struggle with simple stuff like adding a bunch of places as markers. Everything looks a bit like the owl drawing meme, either showing something too easy and useless, or something too advanced and also useless or beyond my comprehension. Maybe some other Python tools?
(I know about Marcelo's fabulous PrettyMaps but it is not exactly a viz tool)

For those interested in such things, here is a map of "European" current rail-electrification based on @openstreetmap tagged data

Electrified track is red, all other track in black

Developed in @python using #OSMnx to wrangle the data and visualised in @qgis

Update this is an OLE map

For true connoisseurs of the art please note, this makes a distinction between voltage, frequency, and type (OLE/third-rail/fourth-rail)