Metadata-Version: 2.1
Name: xvec
Version: 0.2.0
Summary: Vector data cubes for Xarray
Author-email: Martin Fleischmann <martin@martinfleischmann.net>, Benoît Bovy <benbovy@gmail.com>
Maintainer: Xvec contributors
License: MIT
Project-URL: Home, https://xvec.readthedocs.io
Project-URL: Repository, https://github.com/xarray-contrib/xvec
Keywords: GIS,cartography,pandas,shapely
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: xarray >=2022.12.0
Requires-Dist: pyproj >=3.0.0
Requires-Dist: shapely >=2.0b1

# Vector data cubes for Xarray

> 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))

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).

## Project status

The project is in the early stage of development and its API may still change.

## Installing

You can install Xvec from PyPI using `pip` or from conda-forge using `mamba` or `conda`:

```sh
pip install xvec
```

Or (recommended):

```sh
mamba install xvec -c conda-forge
```

### Development version

The development version can be installed from GitHub.

```sh
pip install git+https://github.com/xarray-contrib/xvec.git
```

We recommend installing its dependencies using `mamba` or `conda` before.

```sh
mamba install xarray shapely pyproj -c conda-forge
```
