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DOC: User guide (#29)
* delete notebooks folder * wip guide * update env * the rest of pages * lint * proofread * switch the order of geopandas and io
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.gitignore

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# ruff
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doc/source/cube.joblib.compressed
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doc/source/cube.pickle

Readme.md

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> Where raster data cubes refer to data cubes with raster (x- and y-, or lon- and lat-) dimensions, vector data cubes are n-D arrays that have (at least) a single spatial dimension that maps to a set of (2-D) vector geometries. ([Edzer Pebesma](https://r-spatial.org/r/2022/09/12/vdc.html))
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Xvec combines [Xarray](http://xarray.pydata.org) n-D arrays and [shapely 2.0](https://shapely.readthedocs.io/en/latest/) planar vector geometries to create a support for vector data cubes in Python. See [this post](https://r-spatial.org/r/2022/09/12/vdc.html) by Edzer Pebesma on an introduction of the concept.
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Xvec combines [Xarray](http://xarray.pydata.org) n-D arrays and [shapely 2](https://shapely.readthedocs.io/en/latest/) planar vector geometries to create a support for vector data cubes in Python. See [this post](https://r-spatial.org/r/2022/09/12/vdc.html) by Edzer Pebesma on an introduction of the concept or the introduction of their implementation in Xvec in our [documentation](https://xvec.readthedocs.io/en/latest/intro.html).
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Xvec is in an early stage of development and we do not advise to use it yet as the API will likely change.
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## Installing
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## Resources
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Xvec is not released yet and can be installed from GitHub.
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- <https://github.com/corteva/rioxarray/issues/588>
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- <https://github.com/dcherian/crsindex/blob/main/crsindex.ipynb>
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- <https://hackmd.io/Zxw_zCa7Rbynx_iJu6Y3LA?view>
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```sh
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pip install git+https://github.com/martinfleis/xvec.git
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```
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We recommend installing its dependencies using `mamba` or `conda` before.
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```sh
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mamba install xarray shapely pyproj -c conda-forge
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```

doc/source/conf.py

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html_theme_options = {
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"github_url": "https://github.com/martinfleis/xvec",
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"use_sidenotes": True,
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}
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nb_execution_mode = "off"
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autodoc_typehints = "none"

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