#30DayMapChallenge 7 Nov - Accessibility
This map shows the weather stations operated by the Spanish Met Service and regions where there is a lack of stations.
𝗧𝗵𝗲 𝗹𝗮𝗰𝗸 𝗼𝗳 𝘄𝗲𝗮𝘁𝗵𝗲𝗿 𝘀𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗹𝗶𝗺𝗶𝘁𝘀 𝘁𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝗱𝗲𝘁𝗲𝗰𝘁 𝗮𝗻𝗱 𝗮𝗻𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗲 𝗲𝘅𝘁𝗿𝗲𝗺𝗲 𝗲𝘃𝗲𝗻𝘁𝘀.
#aemet #geopandas #cartopy
This map shows the weather stations operated by the Spanish Met Service and regions where there is a lack of stations.
𝗧𝗵𝗲 𝗹𝗮𝗰𝗸 𝗼𝗳 𝘄𝗲𝗮𝘁𝗵𝗲𝗿 𝘀𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗹𝗶𝗺𝗶𝘁𝘀 𝘁𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝗱𝗲𝘁𝗲𝗰𝘁 𝗮𝗻𝗱 𝗮𝗻𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗲 𝗲𝘅𝘁𝗿𝗲𝗺𝗲 𝗲𝘃𝗲𝗻𝘁𝘀.
#aemet #geopandas #cartopy
November 7, 2025 at 8:57 AM
#30DayMapChallenge 7 Nov - Accessibility
This map shows the weather stations operated by the Spanish Met Service and regions where there is a lack of stations.
𝗧𝗵𝗲 𝗹𝗮𝗰𝗸 𝗼𝗳 𝘄𝗲𝗮𝘁𝗵𝗲𝗿 𝘀𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗹𝗶𝗺𝗶𝘁𝘀 𝘁𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝗱𝗲𝘁𝗲𝗰𝘁 𝗮𝗻𝗱 𝗮𝗻𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗲 𝗲𝘅𝘁𝗿𝗲𝗺𝗲 𝗲𝘃𝗲𝗻𝘁𝘀.
#aemet #geopandas #cartopy
This map shows the weather stations operated by the Spanish Met Service and regions where there is a lack of stations.
𝗧𝗵𝗲 𝗹𝗮𝗰𝗸 𝗼𝗳 𝘄𝗲𝗮𝘁𝗵𝗲𝗿 𝘀𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗹𝗶𝗺𝗶𝘁𝘀 𝘁𝗵𝗲 𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝘁𝗼 𝗱𝗲𝘁𝗲𝗰𝘁 𝗮𝗻𝗱 𝗮𝗻𝘁𝗶𝗰𝗶𝗽𝗮𝘁𝗲 𝗲𝘅𝘁𝗿𝗲𝗺𝗲 𝗲𝘃𝗲𝗻𝘁𝘀.
#aemet #geopandas #cartopy
This week's Apache Sedona drop: lazy/selective GeoParquet reads in SedonaDB, @duckdb.org, GDAL, and GeoPandas! This is how querying a GeoParquet file plonked on a web server can be queried locally (and why GeoParquet can be even faster locally!) dewey.dunnington.ca/post/2025/la... #gischat
Lazy GeoParquet reading in SedonaDB, DuckDB, GeoPandas, and GDAL | Dewey Dunnington
I’m an obvious fan of GeoParquet and SedonaDB and it should be no surprise that I worked (still working!) pretty hard making sure SedonaDB could take advantage of all GeoParquet had to offer.
dewey.dunnington.ca
October 16, 2025 at 2:59 PM
This week's Apache Sedona drop: lazy/selective GeoParquet reads in SedonaDB, @duckdb.org, GDAL, and GeoPandas! This is how querying a GeoParquet file plonked on a web server can be queried locally (and why GeoParquet can be even faster locally!) dewey.dunnington.ca/post/2025/la... #gischat
I'm beyond excited for this! Built on Apache DataFusion and Apache Arrow, a composable single-node analytical database with spatial types as first-class citizens. GeoPandas IO, KNN joins, CRS support, R/Python bindings, and top-notch lazy GeoParquet reads.
sedona.apache.org/latest/blog/...
sedona.apache.org/latest/blog/...
Introducing SedonaDB: A single-node analytical database engine with geospatial as a first-class citizen - Apache Sedona
Apache Sedona is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark, Apache Flink, and Snowflake, with a set of...
sedona.apache.org
September 24, 2025 at 7:03 PM
I'm beyond excited for this! Built on Apache DataFusion and Apache Arrow, a composable single-node analytical database with spatial types as first-class citizens. GeoPandas IO, KNN joins, CRS support, R/Python bindings, and top-notch lazy GeoParquet reads.
sedona.apache.org/latest/blog/...
sedona.apache.org/latest/blog/...
🐮 Series: Cattle Density (No. 1/24) - Europe
Europe's cattle density is varied, with high spots in the Netherlands and Italy. It enriches rural culture.
🔧 Tools: Python (Rasterio, Geopandas, Shapely)
Europe's cattle density is varied, with high spots in the Netherlands and Italy. It enriches rural culture.
🔧 Tools: Python (Rasterio, Geopandas, Shapely)
January 5, 2025 at 12:58 PM
🐮 Series: Cattle Density (No. 1/24) - Europe
Europe's cattle density is varied, with high spots in the Netherlands and Italy. It enriches rural culture.
🔧 Tools: Python (Rasterio, Geopandas, Shapely)
Europe's cattle density is varied, with high spots in the Netherlands and Italy. It enriches rural culture.
🔧 Tools: Python (Rasterio, Geopandas, Shapely)
Using GeoPandas can be a great way to enhance your ArcGIS workflow. We take a look at three ways here.
#geospatial #gis #arcgis #geopandas
#geospatial #gis #arcgis #geopandas
Three Ways to Use GeoPandas in Your ArcGIS Workflow
Introduction When combining open-source GIS tools with the ArcGIS ecosystem, there are a handful of challenges one can encounter. The compatibility of data formats, issues with interoperability, tool chain fragmentation, and performance at scale come to mind quickly. However, the use of the open-source Python library GeoPandas can be an effective way of working around these problems. When working with GeoPandas, there’s a simple series of steps to follow - you start with the data in ArcGIS, process it with the GeoPandas library, and import it back into ArcGIS.
cercanasystems.com
February 21, 2025 at 4:10 PM
Using GeoPandas can be a great way to enhance your ArcGIS workflow. We take a look at three ways here.
#geospatial #gis #arcgis #geopandas
#geospatial #gis #arcgis #geopandas
So it turns out that there are two german towns named Aach, but geopandas handles the case rather gracefully.
March 14, 2025 at 4:13 PM
So it turns out that there are two german towns named Aach, but geopandas handles the case rather gracefully.
It takes @xarray.bsky.social and #geopandas inputs, and outputs back to #xarray, #pandas, csv, and more (keeping polygon metadata intact!), so it can plug into many existing workflows.
There are some pretty substantial performance improvements in the pipeline as well, so stay tuned.
There are some pretty substantial performance improvements in the pipeline as well, so stay tuned.
December 31, 2024 at 7:29 PM
It takes @xarray.bsky.social and #geopandas inputs, and outputs back to #xarray, #pandas, csv, and more (keeping polygon metadata intact!), so it can plug into many existing workflows.
There are some pretty substantial performance improvements in the pipeline as well, so stay tuned.
There are some pretty substantial performance improvements in the pipeline as well, so stay tuned.
Exporting Data with GeoPandas in Databricks
Exporting Data with GeoPandas in Databricks
I recently had a project requirement to export the contents of a delta table in Databricks to several formats, including shapefile and file geodatabase, with the output being placed in object stora…
blog.geomusings.com
February 21, 2025 at 9:18 AM
Exporting Data with GeoPandas in Databricks
Writing geoparquet —- a one liner with geopandas github.com/swisstopo/to... reading a few lines github.com/swisstopo/to...
topo-satromo/main_functions/main_extract_warnregions.py at 1d8f14fa1179bd05b438ef2836aec567f302a46f · swisstopo/topo-satromo
Erdbeobachtungs-Satellitendaten fürs Trockenheitsmonitoring (SATROMO) - swisstopo/topo-satromo
github.com
March 4, 2025 at 5:58 AM
Writing geoparquet —- a one liner with geopandas github.com/swisstopo/to... reading a few lines github.com/swisstopo/to...
Are you a #socialscientist who would like to use #Python in your research?
Discover how to get started with Python and how to create maps in Python using #GeoPandas with these great guides from @softwaresaved.bsky.social
Discover how to get started with Python and how to create maps in Python using #GeoPandas with these great guides from @softwaresaved.bsky.social
Software Sustainability Institute (@softwaresaved.bsky.social)
🎓 We are delighted to share two new resources developed as part of the Research Software Practices in the Social Sciences project. Find out more and access the guides at:…
buff.ly
August 11, 2025 at 8:21 AM
Are you a #socialscientist who would like to use #Python in your research?
Discover how to get started with Python and how to create maps in Python using #GeoPandas with these great guides from @softwaresaved.bsky.social
Discover how to get started with Python and how to create maps in Python using #GeoPandas with these great guides from @softwaresaved.bsky.social
🔎 Series: Population Density (No. 1) - South Korea
South Korea’s population density is substantial, with 515.56 people per square kilometer. It contributes to the vibrant urban life that South Korea is known for.
🔧 Tools: Python (Rasterio, Geopandas, Shapely, JenksPy)
~
South Korea’s population density is substantial, with 515.56 people per square kilometer. It contributes to the vibrant urban life that South Korea is known for.
🔧 Tools: Python (Rasterio, Geopandas, Shapely, JenksPy)
~
February 4, 2024 at 12:35 PM
🔎 Series: Population Density (No. 1) - South Korea
South Korea’s population density is substantial, with 515.56 people per square kilometer. It contributes to the vibrant urban life that South Korea is known for.
🔧 Tools: Python (Rasterio, Geopandas, Shapely, JenksPy)
~
South Korea’s population density is substantial, with 515.56 people per square kilometer. It contributes to the vibrant urban life that South Korea is known for.
🔧 Tools: Python (Rasterio, Geopandas, Shapely, JenksPy)
~
Yeah, I suggest building on top of universal-pathlib and fsspec. xarray supports the UPath protocol and I think geopandas does as well.
November 8, 2025 at 3:53 PM
Yeah, I suggest building on top of universal-pathlib and fsspec. xarray supports the UPath protocol and I think geopandas does as well.
#30DayMapChallenge Day20 – Outdoors.
Average number of dogs per household by postcode district in the UK. Lots of dogs in Wales close to beautiful nature. 😊🌿🐶
Made with #python geopandas + matplotlib, final touches in Figma
🔗 github.com/Lisa-Ho/30-d...
Average number of dogs per household by postcode district in the UK. Lots of dogs in Wales close to beautiful nature. 😊🌿🐶
Made with #python geopandas + matplotlib, final touches in Figma
🔗 github.com/Lisa-Ho/30-d...
November 20, 2023 at 8:26 AM
#30DayMapChallenge Day20 – Outdoors.
Average number of dogs per household by postcode district in the UK. Lots of dogs in Wales close to beautiful nature. 😊🌿🐶
Made with #python geopandas + matplotlib, final touches in Figma
🔗 github.com/Lisa-Ho/30-d...
Average number of dogs per household by postcode district in the UK. Lots of dogs in Wales close to beautiful nature. 😊🌿🐶
Made with #python geopandas + matplotlib, final touches in Figma
🔗 github.com/Lisa-Ho/30-d...
🌪️ In Lee Vaughan's new article, learn how to use Python, pygris, GeoPandas, Plotly Express, and part of NOAA’s extensive database to map tornado occurrences, graph their frequencies and magnitudes, and chart the loss of life.
Analyze Tornado Data with Python and GeoPandas
Insights from NOAA’s public domain database
towardsdatascience.com
January 28, 2025 at 10:19 PM
🌪️ In Lee Vaughan's new article, learn how to use Python, pygris, GeoPandas, Plotly Express, and part of NOAA’s extensive database to map tornado occurrences, graph their frequencies and magnitudes, and chart the loss of life.
Been sitting on these #GeoTiffs for a long time, but I’ve finally written and run the script to get all the site data (pixel level, 250m). Thank you #geopandas and #rasterstats.
#Python 🐍 🖥
#Python 🐍 🖥
November 14, 2024 at 4:22 AM
Been sitting on these #GeoTiffs for a long time, but I’ve finally written and run the script to get all the site data (pixel level, 250m). Thank you #geopandas and #rasterstats.
#Python 🐍 🖥
#Python 🐍 🖥
Une carte complètement inutile, donc indispensable.
À quelle latitude le Soleil survole-t-il le plus de terres émergées ? Et à quelles dates ?
#Python #Geopandas
#maps #TeamCarto
À quelle latitude le Soleil survole-t-il le plus de terres émergées ? Et à quelles dates ?
#Python #Geopandas
#maps #TeamCarto
February 10, 2025 at 7:08 PM
Une carte complètement inutile, donc indispensable.
À quelle latitude le Soleil survole-t-il le plus de terres émergées ? Et à quelles dates ?
#Python #Geopandas
#maps #TeamCarto
À quelle latitude le Soleil survole-t-il le plus de terres émergées ? Et à quelles dates ?
#Python #Geopandas
#maps #TeamCarto
🔍 Need to search for species in an area with a buffer? 🔵
Learn how to add a buffer in Python and see how to consider threatened species with obfuscated locations in a new ALA Labs post by Amanda Buyan & me 😀
labs.ala.org.au/posts/2025-0...
🧪🌏 #Python #matplotlib #geopandas #geospatial #quartopub
Learn how to add a buffer in Python and see how to consider threatened species with obfuscated locations in a new ALA Labs post by Amanda Buyan & me 😀
labs.ala.org.au/posts/2025-0...
🧪🌏 #Python #matplotlib #geopandas #geospatial #quartopub
August 27, 2025 at 12:44 AM
🔍 Need to search for species in an area with a buffer? 🔵
Learn how to add a buffer in Python and see how to consider threatened species with obfuscated locations in a new ALA Labs post by Amanda Buyan & me 😀
labs.ala.org.au/posts/2025-0...
🧪🌏 #Python #matplotlib #geopandas #geospatial #quartopub
Learn how to add a buffer in Python and see how to consider threatened species with obfuscated locations in a new ALA Labs post by Amanda Buyan & me 😀
labs.ala.org.au/posts/2025-0...
🧪🌏 #Python #matplotlib #geopandas #geospatial #quartopub
For this year's @bansallab #Halloween costume, we present "Wild about Open-source" & give a huge shout-out to the amazing open-source tools that make our rsch possible! #Anaconda #Spyder #Geopandas #Github @garnierrom1 @ColinJCarlson @casey_zipfel
Happy Halloween y'all!
Happy Halloween y'all!
November 24, 2024 at 7:02 PM
For this year's @bansallab #Halloween costume, we present "Wild about Open-source" & give a huge shout-out to the amazing open-source tools that make our rsch possible! #Anaconda #Spyder #Geopandas #Github @garnierrom1 @ColinJCarlson @casey_zipfel
Happy Halloween y'all!
Happy Halloween y'all!
From there it's a matter of merging with the shapefiles, merging the different datasets with each other and then visualizing.
I use Geopandas for handling the geospatial stuff and it does the visualizations too, using the MatPlotLib under the hood.
I use Geopandas for handling the geospatial stuff and it does the visualizations too, using the MatPlotLib under the hood.
November 29, 2024 at 7:35 PM
From there it's a matter of merging with the shapefiles, merging the different datasets with each other and then visualizing.
I use Geopandas for handling the geospatial stuff and it does the visualizations too, using the MatPlotLib under the hood.
I use Geopandas for handling the geospatial stuff and it does the visualizations too, using the MatPlotLib under the hood.
Just did an inventory of my 8 conda environments:
7 different versions of numpy, pandas, scipy
6 different versions of matplotlib, python, requests
5 different versions of cartopy, tropycal, xarray
4 different versions of metpy, pint, shapely
3 different versions of geopandas, netcdf4
🤣😢
7 different versions of numpy, pandas, scipy
6 different versions of matplotlib, python, requests
5 different versions of cartopy, tropycal, xarray
4 different versions of metpy, pint, shapely
3 different versions of geopandas, netcdf4
🤣😢
May 23, 2024 at 3:37 PM
Just did an inventory of my 8 conda environments:
7 different versions of numpy, pandas, scipy
6 different versions of matplotlib, python, requests
5 different versions of cartopy, tropycal, xarray
4 different versions of metpy, pint, shapely
3 different versions of geopandas, netcdf4
🤣😢
7 different versions of numpy, pandas, scipy
6 different versions of matplotlib, python, requests
5 different versions of cartopy, tropycal, xarray
4 different versions of metpy, pint, shapely
3 different versions of geopandas, netcdf4
🤣😢
Ohhh. I'll check that out.
This is all I'm messing with right now:
geopandas
pandas
matplotlib.pyplot
This is all I'm messing with right now:
geopandas
pandas
matplotlib.pyplot
March 24, 2025 at 8:23 PM
Ohhh. I'll check that out.
This is all I'm messing with right now:
geopandas
pandas
matplotlib.pyplot
This is all I'm messing with right now:
geopandas
pandas
matplotlib.pyplot
☔️ Series: Rainfall (No. 6) - Japan
Japan's rainy season, tsuyu, brings heavy rainfall from June to mid-July.
🔧 Tools: Python (Rasterio, Rioxarray, Geopandas)
Japan's rainy season, tsuyu, brings heavy rainfall from June to mid-July.
🔧 Tools: Python (Rasterio, Rioxarray, Geopandas)
September 28, 2025 at 5:19 PM
☔️ Series: Rainfall (No. 6) - Japan
Japan's rainy season, tsuyu, brings heavy rainfall from June to mid-July.
🔧 Tools: Python (Rasterio, Rioxarray, Geopandas)
Japan's rainy season, tsuyu, brings heavy rainfall from June to mid-July.
🔧 Tools: Python (Rasterio, Rioxarray, Geopandas)
GeoPandas - als Tool zur Basiskartenaktualisierung has been released on media.ccc.de and YouTube #fossgis2025 #Praxisberichte #HS3S1 #fossgis2025deu https://media.ccc.de/v/fossgis2025-58166-geopandas-als-tool-zur-basiskartenaktualisierung
March 26, 2025 at 11:57 AM
GeoPandas - als Tool zur Basiskartenaktualisierung has been released on media.ccc.de and YouTube #fossgis2025 #Praxisberichte #HS3S1 #fossgis2025deu https://media.ccc.de/v/fossgis2025-58166-geopandas-als-tool-zur-basiskartenaktualisierung
Down day due to rain. Working on plotting WPC ERO Forecast with #MetPy and #GeoPandas. Turned out to be quite simple. This is a WIP and needs polishing.
April 29, 2025 at 2:41 PM
Down day due to rain. Working on plotting WPC ERO Forecast with #MetPy and #GeoPandas. Turned out to be quite simple. This is a WIP and needs polishing.
Computing travel time matrices in r⁵py from #geopandas #DataFrame is two lines of code:
(1) create an r5py.TransportNetwork from @openstreetmap.bsky.social and #GTFS data
(2) turn it into an r5py.TravelTimeMatrix()
Try it out in #binder: r5py.readthedocs.io/stable/user-...
(1) create an r5py.TransportNetwork from @openstreetmap.bsky.social and #GTFS data
(2) turn it into an r5py.TravelTimeMatrix()
Try it out in #binder: r5py.readthedocs.io/stable/user-...
April 29, 2025 at 12:55 PM
Computing travel time matrices in r⁵py from #geopandas #DataFrame is two lines of code:
(1) create an r5py.TransportNetwork from @openstreetmap.bsky.social and #GTFS data
(2) turn it into an r5py.TravelTimeMatrix()
Try it out in #binder: r5py.readthedocs.io/stable/user-...
(1) create an r5py.TransportNetwork from @openstreetmap.bsky.social and #GTFS data
(2) turn it into an r5py.TravelTimeMatrix()
Try it out in #binder: r5py.readthedocs.io/stable/user-...