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#Geopandas
Thank you to #Kone & Mai and Tor Nessling Foundations for supporting this work. A quantitative work like this would not be possible without a robust suite of FOSS tools. My thanks to the maintainers of #QGIS, #pandas, #geopandas, #duckdb, #dask, #statsmodels, #jupyter and many more!
Seeking recommendations for a #WebMapping tutorial / course?
Slightly at sea on where to start.
- My current JS skill level is _extreme novice_.
- I don't have access to ArcGIS.
- Comfortable with #QGIS [*] and the #python #geospatial ecosystem (#geopandas #xarray #rasterio and plotting with #matplotlib)
Suggestions welcome. TIA. 
* I have looked at the qgis2web plugin, but having some issues associated with my aged laptop (2012 mbp running Ubuntu) and a 'Wayland session'.
Geocomputation with Python copies have arrived 
Somehow, things feel much more real if you can touch them.
Fun fact: the cover was designed in #QGIS. Speaking of going full circle ...
Qiita - 人気の記事 Uberの作った「H3インデックス」とGeoPandasを利用してOverture Mapsの可視化と地理空間解析してみる！
https://qiita.com/nokonoko_1203/items/ce8937489121b69710e5?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items
The development was supported by NumFOCUS (small development grant for the #GeoPandas project). A lot of the credit goes to @jorisvandenbossche and @paleolimbot (through S2Geography). Also many thanks to the new contributors!
https://github.com/benbovy/spherely
Joris is going to give a talk about it next week at the GeoPython conference in Basel. If you go there, don’t miss it!
Une carte complètement inutile, donc indispensable. À quelle latitude le Soleil survole-t-il le plus de terres émergées ?
#Python #Geopandas
#maps #TeamCarto
Number of scholastic buildings per administrative area in Ravenna, 2022
School coverage across the Ravenna province by grade, an analysis to measure how many children live within a 15-minute walking distance of a school.
This post only displays the areas covered by schools due to privacy and safety considerations (GDPR).
This post only displays the areas covered by schools due to privacy and safety considerations in compliance with GDPR regulations.
#dataviz #python #geopandas #matplotlib #qol
Greg Cocks Geospatial Python 
- Full Course for Beginners with GeoPandas 
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https://youtu.be/0mWgVVH_dos?si=KHenBnxdeStppvnH <-- shared video tutorial
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https://moderngis.xyz/courses/geopandas-free-certification/ <-- shared course files
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[sharing of this course should not – necessarily - be considered as an endorsement]
#GIS #spatial #mapping #tutorial #onlinelearning #free #training #python #geopandas #pandas #beginners #video #videotutorial #workflows #automation #spatialanalysis #spatialdata #DuckDB #leafmap #lonboard #certification
"R⁵py is a #Python library for rapid realistic routing on multimodal transport networks (walk, bike, public transport, and car). It provides a simple and friendly interface to R⁵, the Rapid Realistic Routing on Real-world and Reimagined networks, a routing engine developed by Conveyal. #r5py is inspired by r5r, a wrapper for R, and it is designed to interact with #GeoPandas #GeoDataFrames."
https://r5py.readthedocs.io/en/stable/index.html
via @waeiski
Quick glance at the new #Foursquare dataset with 100M places worldwide [1], based on do-me's data upload [2]. See the jupyter notebook here [3].
[1]: https://location.foursquare.com/resources/blog/products/foursquare-open-source-places-a-new-foundational-dataset-for-the-geospatial-community/
[2]: https://huggingface.co/datasets/do-me/foursquare_places_100M
[3]: https://code.ad.ioer.info/wip/snippets/html/2024-11-25_foursquare_parquet.html
#geopandas #geoparquet, #python #datascience #datashader #jupyter
Hungarian Oases.
Bivariate choropleth showing the density of natural (forrás = springs) and unnatural springs (kocsma = pubs) across Hungary.
Data from #OpenStreetMap, hexagons from #h3, plotted using #geopandas & #matplotlib
#30DayMapChallenge Day 4: #hexagons
Cartographic Aotearoa [Ian Reese’s blog]
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https://xycarto.com/2024/08/17/cartographic-aotearoa/ <-- shared blog posts
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https://xycarto.github.io/xyc-wesm-viewer/ <-- USGSPointCloudSurfaceViewer
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https://swa-impactmap.dragonfly.co.nz/ <-- SWAFloodMapping
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https://github.com/xycarto/aerial-index-nz <-- GriddingNZAerial Imagery
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[as I am currently in New Zealand, I thought this was an ‘appropriate’ time to post this]
#GIS #spatial #mapping #xycarto #opensource #blog #cartography #NewZealand #Aotearoa #opendata #global #examples #qgis #gdal #geopandas #python #bash #Colorhexa #Gpick #docker #gischat
Our tutorials and analysis notebooks now come with plenty of usage examples for the new explore() function which provides #folium powered interactive plots
You probably already know and appreciate it from #GeoPandas and now you can also enjoy it in #MovingPandas
Visualisation - Spatial Distribution Of Population Changes With Age In And Around London, UK
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https://www.linkedin.com/feed/update/urn:li:activity:7189190935690293248
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[some beautiful AND enlightening use of animated maps, makes us #spatialgeeks want to get in there and pull the data apart with our bare hands (sic), so many use cases...]
“Earlier this week in a workshop for the Data Science & Analytics team at [UK Ordnance Survey], [they] looked at creating animated maps.
[They] used 2021 Census data reported at MSOA level to look at how the spatial distribution of population changes with age in and around London. The trend between ages 25 to 50 of young people progressively moving away from central London is fun to see..."
#GIS #spatial #mapping #cartography #maps #animated #visualisation #visualisations #census #age #demographics #London #England #UK #Britain #opensource #development #workshop #training #animatedmaps #MSOA #population #change #spatialanalysis #matplotlib #geopandas #imagemagick
@OrdnanceSurvey