N-D labeled arrays and datasets in Python

Edit Package python-xarray
http://github.com/pydata/xarray

xarray (formerly xray) is a python-pandas-like and pandas-compatible
toolkit for analytics on multi-dimensional arrays. It provides
N-dimensional variants of the python-pandas labeled data structures,
rather than the tabular data that pandas uses.

The Common Data Model for self-describing scientific data is used.
The dataset is an in-memory representation of a netCDF file.

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Source Files
Filename Size Changed
_multibuild 0000000053 53 Bytes
local_dataset.patch 0000000764 764 Bytes
python-xarray.changes 0000207824 203 KB
python-xarray.spec 0000007024 6.86 KB
xarray-2024.2.0.tar.gz 0003634288 3.47 MB
Revision 46 (latest revision is 48)
Dominique Leuenberger's avatar Dominique Leuenberger (dimstar_suse) accepted request 1154193 from Matej Cepl's avatar Matej Cepl (mcepl) (revision 46)
- Skip Python 3.9. It requires pydap, which is not available any
  more.
- Update to 2024.2.0
  * This release brings size information to the text repr, changes
    to the accepted frequency strings, and various bug fixes.
  ## New Features
  * Added a simple nbytes representation in DataArrays and Dataset
    repr. (GH8690, PR8702). By Etienne Schalk.
  * Allow negative frequency strings (e.g. "-1YE"). These strings
    are for example used in date_range(), and cftime_range()
    (PR8651). By Mathias Hauser.
  * Add NamedArray.expand_dims(), NamedArray.permute_dims() and
    NamedArray.broadcast_to() (PR8380) By Anderson Banihirwe.
  * Xarray now defers to flox’s heuristics to set the default
    method for groupby problems. This only applies to flox>=0.9. By
    Deepak Cherian.
  * All quantile methods (e.g. DataArray.quantile()) now use
    numbagg for the calculation of nanquantiles (i.e., skipna=True)
    if it is installed. This is currently limited to the linear
    interpolation method (method=’linear’). (GH7377, PR8684) By
    Marco Wolsza.
  ## Breaking changes
  * infer_freq() always returns the frequency strings as defined in
    pandas 2.2 (GH8612, PR8627). By Mathias Hauser.
  * Deprecations
  * The dt.weekday_name parameter wasn’t functional on modern
    pandas versions and has been removed. (GH8610, PR8664) By Sam
    Coleman.
  ## Bug fixes
  * Fixed a regression that prevented multi-index level coordinates
    being serialized after resetting or dropping the multi-index
    (GH8628, PR8672). By Benoit Bovy.
  * Fix bug with broadcasting when wrapping array API-compliant
    classes. (GH8665, PR8669) By Tom Nicholas.
  * Ensure DataArray.unstack() works when wrapping array
    API-compliant classes. (GH8666, PR8668) By Tom Nicholas.
  * Fix negative slicing of Zarr arrays without dask installed.
    (GH8252) By Deepak Cherian.
  * Preserve chunks when writing time-like variables to zarr by
    enabling lazy CF encoding of time-like variables (GH7132,
    GH8230, GH8432, PR8575). By Spencer Clark and Mattia Almansi.
  * Preserve chunks when writing time-like variables to zarr by
    enabling their lazy encoding (GH7132, GH8230, GH8432, PR8253,
    PR8575; see also discussion in PR8253). By Spencer Clark and
    Mattia Almansi.
  * Raise an informative error if dtype encoding of time-like
    variables would lead to integer overflow or unsafe conversion
    from floating point to integer values (GH8542, PR8575). By
    Spencer Clark.
  * Raise an error when unstacking a MultiIndex that has duplicates
    as this would lead to silent data loss (GH7104, PR8737). By
    Mathias Hauser.
- Release 2024.1.1
  ## Breaking changes
  * Following pandas, infer_freq() will return "YE", instead of "Y"
    (formerly "A"). This is to be consistent with the deprecation
    of the latter frequency string in pandas 2.2. This is a follow
    up to PR8415 (GH8612, PR8642). By Mathias Hauser.
  ## Deprecations
  * Following pandas, the frequency string "Y" (formerly "A") is
    deprecated in favor of "YE". These strings are used, for
    example, in date_range(), cftime_range(), DataArray.resample(),
    and Dataset.resample() among others (GH8612, PR8629). By
    Mathias Hauser.
- Release 2024.1.0
  * This release brings support for weights in correlation and
    covariance functions, a new DataArray.cumulative aggregation,
    improvements to xr.map_blocks, an update to our minimum
    dependencies, and various bugfixes.
  ## New Features
  * xr.cov() and xr.corr() now support using weights (GH8527,
    PR7392). By Llorenç Lledó.
  * Accept the compression arguments new in netCDF 1.6.0 in the
    netCDF4 backend. See netCDF4 documentation for details. Note
    that some new compression filters needs plugins to be installed
    which may not be available in all netCDF distributions. By
    Markel García-Díez. (GH6929, PR7551)
  * Add DataArray.cumulative() & Dataset.cumulative() to compute
    cumulative aggregations, such as sum, along a dimension — for
    example da.cumulative('time').sum(). This is similar to pandas’
    .expanding, and mostly equivalent to .cumsum methods, or to
    DataArray.rolling() with a window length equal to the dimension
    size. By Maximilian Roos. (PR8512)
  * Decode/Encode netCDF4 enums and store the enum definition in
    dataarrays’ dtype metadata. If multiple variables share the
    same enum in netCDF4, each dataarray will have its own enum
    definition in their respective dtype metadata. By Abel Aoun.
    (GH8144, PR8147)
  ## Deprecations
  * The squeeze kwarg to GroupBy is now deprecated. (GH2157,
    PR8507) By Deepak Cherian.
  ## Bug fixes
  * Support non-string hashable dimensions in xarray.DataArray
    (GH8546, PR8559). By Michael Niklas.
  * Reverse index output of bottleneck’s rolling
    move_argmax/move_argmin functions (GH8541, PR8552). By Kai
    Mühlbauer.
  * Vendor SerializableLock from dask and use as default lock for
    netcdf4 backends (GH8442, PR8571). By Kai Mühlbauer.
  * Add tests and fixes for empty CFTimeIndex, including broken
    html repr (GH7298, PR8600). By Mathias Hauser.
- Create subpackages for the python [extras], test dependencies
  with _multibuild
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