N-D labeled arrays and datasets in Python
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.
- Developed at devel:languages:python:numeric
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Source Files
Filename | Size | Changed |
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_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 50)
Dominique Leuenberger (dimstar_suse)
accepted
request 1154193
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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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