#Xarray

Laurent CourtyLaurentCourty
2025-06-05

I am excited to announce xarray-grass, a new free software Python library designed to bridge two open source data science heavy weights: @grassgis and (xarray.dev/).

Although xarray-grass is in its nascent phase, I encourage you to check out the repository on GitHub (github.com/lrntct/xarray-grass) and experiment with it. Your insights and contributions will play a significant role in the project's future.

#geo #RemoteSensing #earthobservation people! Has anyone got an example of using the #Copernicus #DataSpace -> documentation.dataspace.copern to go from searching using #pystac to getting a working #xarray dataset for #Sentinel2 reflectances? #python #geopython

Yann Bรผchau :nixos:nobodyinperson@fosstodon.org
2025-04-15

I am really looking forward to a time when scientific data analysis is less of a constant fuckaround and fight with technical bullshit. I'd *really* like

- #netCDF natively supporting complex numbers
- #Python #xarray and #pandas to natively support physical units (#pint is great on its own but the integrations leave a LOT to be desired)
- #Jupyter notebooks to suck less (crashes, glitches, widget plots not saved statically, an effing BUILTIN formatter, etc.)
- proper data pipeline systems
...

2025-03-20

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. ๐Ÿ‘

* I have looked at the qgis2web plugin, but having some issues associated with my aged laptop (2012 mbp running Ubuntu) and a 'Wayland session'.

#Leaflet #OpenLayers #MapBox #PrototoMaps #MapLibre #d3js #OpenStreetMap #GIS

2025-02-28

๐—š๐—ฒ๐—ผ๐˜€๐—ฝ๐—ฎ๐˜๐—ถ๐—ฎ๐—น ๐—ฃ๐˜†๐˜๐—ต๐—ผ๐—ป ๐—ง๐˜‚๐˜๐—ผ๐—ฟ๐—ถ๐—ฎ๐—น๐˜€
SpatialThoughts provides tutorials which cover a broad range of geospatial topics and technologies, e.g., #GeoPandas, #XArray, #dask, and more. Each technology is described in a notebook with step-by-step explanation. Check it out.
geopythontutorials.com

๐Ÿ’ง๐ŸŒ Greg CocksGregCocks@techhub.social
2025-01-31
Conceptual diagram of GSPy workflow. Data from a variety of formats and types are read into GSPy, along with required metadata files. Through the GSPy software, data are converted into a standardized NetCDF file containing the dataset and metadata appropriate for archiving and sharing.GS data convention. (A) Datasets are structured into three fundamental group types based on content and data geometry. The Survey group contains general metadata about the dataset. Unstructured datasets, such as from CSV or TXT files, form Tabular groups, whereas structured (gridded) datasets are categorized under the Raster group. Metadata is attached to all groups, with various required attributes (green text) that expands on the CF-1.8 convention. (B) Groups follow a strict hierarchy in the NetCDF file, with a single Survey group at the top to which all data groups are attached. Datasets are indexed within their respective group type. (C) Tabular and Raster data groups must contain clearly defined dimensions, such as index or x, y, z, as well as coordinate variables. Raster groups are distinct in that dimensions are also coordinates, whereas Tabular datasets are assigned spatial coordinates that align with the index dimension. Lastly, the coordinate variable โ€œspatial_refโ€ is required for all data groups, which expands on the โ€œcoordinate_informationโ€ variable required in the Survey metadata.photo - rigs preparing to do a seismic survey, Middle EastGSPy code base - Writing and plotting examples. Once all groups have been attached to a Survey, the โ€œwrite_netcdfโ€ and โ€œwrite_ncmlโ€ methods will write the GS NetCDF and NcML files, respectively. GSPy also provides methods to generate scatter and pcolor plots for variables.
2024-12-05

Justus made a great intro on using #DGGS through #xarray #xdggs at the #Pangeo showcase talk. Xdggs is now in a stage where you can use it fairly robustly with #HEALPIX and #H3. Other integrations like for #DGGRID are developed as separate plugins.

youtube.com/watch?v=bAMGFKsxsj

2024-09-30

... while I find ChatGPT increasingly useful for technical things like telling me how to manipulate #xarray datasets in #python, or how to add a docstring to my python routine.

Virgile AndreaniArmavica@fosstodon.org
2024-09-18

I am moving all my computing libraries to #xarray, no regrets. It is a natural way to manipulate datasets of rectangular arrays, with named coordinates and dimensions: xarray.dev/
There are several possible backends, including #dask which allows lazy data loading.
I had the pleasure of meeting some of the devs last week, who showed me a preview of the upcoming `DataTree` structure which is going to make this library even more versatile!

#Python #numpy #ScientificComputing

2024-09-06

๐ŸŒ๐Ÿ“Š Want to work with NetCDF files in Python? My tutorial series covers everything from opening and plotting NetCDF data to creating CF-compliant files for FAIR data publication.

Whether you're new to NetCDF or looking to enhance your skills, I've got you covered! ๐Ÿš€ Check it out: lhmarsden.github.io/NetCDF_in_

Topics include:
๐Ÿ”ธExtracting data ๐Ÿ“
๐Ÿ”ธPlotting ๐Ÿ“ˆ
๐Ÿ”ธCreating CF-compliant files ๐ŸŒ
๐Ÿ”ธGranularity ๐Ÿ–ฅ๏ธ
๐Ÿ”ธCF & ACDD ๐Ÿ–ฅ๏ธ

Suggestions? Let me know! #Python #DataScience #NetCDF #xarray #FAIRData #ClimateData

Michael Sumnermdsumner@rstats.me
2024-08-19

I dreamt that #xarray kerchunk/VirtualiZarr was being used to stream music

Michael Sumnermdsumner@rstats.me
2024-08-19

xarray.open_mfdataset() is worth all the effort of learning #python and #xarray
every single time I use it makes me laugh

"just open this mf dataset(s), please and thank you"

Michael Sumnermdsumner@rstats.me
2024-07-22

Can we serialize a lazy #xarray to json? Lining up 10000 URLs takes a minute, can we save it out?

I figure that's what #kerchunk is, but it doesn't seem like it's used that way ๐Ÿ™

Donald Hoberndhobern@scicomm.xyz
2024-06-11

My mental picture of image files has always been of pixels covering a surface as tiles each like a tiny rectangular shapefile.

Investigating #Python #xarray has made me see the elegance of handling images as a grid of equally spaced dimensionless sensor readings. Upscaling/downscaling and interpolation become more meaningful and lossless, and image data is functionally identical to (although denser than) other point-based sensor data (e.g. weather stations).

The data science becomes so clean.

Juan Nunez-Iglesiasjni@fosstodon.org
2024-06-01

Excellent #OpenSource #OpenScience job opportunity: #xarray community developer at Earthmover PBC:

github.com/pydata/xarray/discu

US-only ๐Ÿ˜ž, but remote available ๐Ÿ˜Š. And the Earthmover folks are awesome!

#GetFediHired

2024-05-29

๐ŸŽ‰ ๐ŸŽ‰ I released gsw-xarray v0.4.0 ๐ŸŽ‰ ๐ŸŽ‰

pypi.org/project/gsw-xarray/0.

this release brings a new accessor for xarray, which may be a game changer for clarity and ease:
`ds.gsw[["sigma0", "alpha"]]`

#xarray #oceanography

2024-05-23

v0.3.0 of yt_xarray is out!

This includes the initial release of the embedded transformation framework -- the main perk being how it simplifies the process of using yt's volume rendering methods with non-cartesian data (which is common in geophysical datasets)!

Full release notes at github.com/data-exp-lab/yt_xar

Figure uses relative humidity from a MERRA-2, see chrishavlin.github.io/NASASoft for an overview.

#yt #geophysics #xarray #python #DataVisualization #geodata

An overview of the yt_xarray embedded transformation framework. Proceeding clockwise from the top left in 3 panels is (1) a map-projection of relative humidity from a MERRA-2 sample. (2) this data is wrapped in a variable resolution yt cartesian data set, allowing access to yt's methods that require cartesian datasets like (3) volume rendering.
Olivier D'Hondt ๐Ÿ›ฐ๏ธ๐ŸŒ๐ŸŒฑtyldurd@framapiaf.org
2024-04-18

I am deepening my knowledge of #xarray by actually using it to store intermediate data for the interferometric processing of Sentinel-1. I found that learning by doing is much more efficient for me than just reading about a topic.

#datascience #remotesensing #python

Michael Sumnermdsumner@rstats.me
2024-04-11

Join this cool #Pangeo presentation (or watch it afterwards) about scalable #Zarr with #Dask and #Xarray

discourse.pangeo.io/t/webinar-

A possible hook for # RStats folks, dask is like {targets} become toolkit, inside Xarray and all automatic

ๅ‰ๅ‰weiji14@mastodon.nz
2024-03-28

@pokateo

Checking in from New Zealand! I'm developing a library to decode #GeoTIFF files in #rustlang (without using GDAL ๐Ÿ˜‚). Currently trying to add an #xarray backend (in Python) at github.com/weiji14/cog3pio/pul.

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