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Add Dataset.drop_dims
#2767
Add Dataset.drop_dims
#2767
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I was looking for this functionality and ran across #1949. There was one bit of behavior that was unclear to me. Say I have In [6]: data = xr.Dataset({'A': (['x', 'y'], np.random.randn(2, 3)),
...: 'B': ('x', np.random.randn(2)),
...: 'x': ['a', 'b'], 'z': np.pi})
In [7]: data
Out[7]:
<xarray.Dataset>
Dimensions: (x: 2, y: 3)
Coordinates:
* x (x) <U1 'a' 'b'
Dimensions without coordinates: y
Data variables:
A (x, y) float64 -0.662 -0.705 -0.1866 -0.8655 0.5816 -0.2308
B (x) float64 -0.1002 2.402
z float64 3.142
In [8]: data.drop_dims('x')
Out[8]:
<xarray.Dataset>
Dimensions: ()
Data variables:
z float64 3.142 In this case, I dropped At one point, I implemented this slightly differently, which instead gave In [8]: data.drop_dims('x')
Out[8]:
<xarray.Dataset>
Dimensions: (y: 3)
Dimensions without coordinates: y
Data variables:
z float64 3.142 In some ways, this seems preferable, especially if |
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@shoyer I'm sure you're busy... wondering if you might have time to review this (or direct it to someone else to review)? |
It's OK to use I agree that it makes sense to recompute dimensions from variables. There's not much point in keeping around extra dimensions that don't have corresponding variables, and I'm pretty sure that this is consistent with how |
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Okay, that's what this PR already did (via the call to Rebased on master. From my perspective, this should be good to go. |
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@shoyer I force pushed the requested changes. Please let me know if there is anything else. Thanks! |
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xarray/core/dataset.py
Outdated
coord_names = set(k for k in self._coord_names if k in variables) | ||
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return self._replace_with_new_dims( | ||
variables, coord_names, inplace=inplace) |
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inplace
is now an undefined variable, so your tests are failing
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Whoops! I took that out of the tests, but forgot to take it out of dataset.py
. Should be fixed now.
* Drops full dimensions and any corresponding variables in a Dataset * Fixes GH1949
Rebased to fix the NEWS conflict. |
thanks @kmsquire, especially for your patience here! |
No worries--thanks for merging! |
* upstream/master: Rework whats-new for 0.12 Add whats-new for 0.12.1 Release 0.12.0 enable loading remote hdf5 files (pydata#2782) Push back finalizing deprecations for 0.12 (pydata#2809) Drop failing tests writing multi-dimensional arrays as attributes (pydata#2810) some docs updates (pydata#2746) Add support for cftime.datetime coordinates with coarsen (pydata#2778) Don't use deprecated np.asscalar() (pydata#2800) Improve name concat (pydata#2792) Add `Dataset.drop_dims` (pydata#2767) Quarter offset implemented (base is now latest pydata-master). (pydata#2721) Add use_cftime option to open_dataset (pydata#2759) Bugfix/reduce no axis (pydata#2769) 'standard' now refers to 'gregorian' in cftime_range (pydata#2771)
* ENH: Add Dataset.drop_dims() * Drops full dimensions and any corresponding variables in a Dataset * Fixes GH1949 * DOC: Add Dataset.drop_dims() documentation
* ENH: Add Dataset.drop_dims() * Drops full dimensions and any corresponding variables in a Dataset * Fixes GH1949 * DOC: Add Dataset.drop_dims() documentation
…ns with size>1 (#2757) * Quarter offset implemented (base is now latest pydata-master). (#2721) * Quarter offset implemented (base is now latest pydata-master). * Fixed issues raised in review (#2721 (review)) * Updated whats-new.rst with info on quarter offset support. * Updated whats-new.rst with info on quarter offset support. * Update doc/whats-new.rst Co-Authored-By: jwenfai <jwenfai@gmail.com> * Added support for quarter frequencies when resampling CFTimeIndex. Less redundancy in CFTimeIndex resampling tests. * Removed normalization code (unnecessary for cftime_range) in cftime_offsets.py. Removed redundant lines in whats-new.rst. * Removed invalid option from _get_day_of_month docstring. Added tests back in that raises ValueError when resampling (base=24 when resampling to daily freq, e.g., '8D'). * Minor edits to docstrings/comments * lint * Add `Dataset.drop_dims` (#2767) * ENH: Add Dataset.drop_dims() * Drops full dimensions and any corresponding variables in a Dataset * Fixes GH1949 * DOC: Add Dataset.drop_dims() documentation * Improve name concat (#2792) * Added tests of desired name inferring behaviour * Infers names * updated what's new * Don't use deprecated np.asscalar() (#2800) It got deprecated in numpy 1.16 and throws a ton of warnings due to that. All the function does is returning .item() anyway, which is why it got deprecated. * Add support for cftime.datetime coordinates with coarsen (#2778) * some docs updates (#2746) * Friendlier io title. * Fix lists. * Fix *args, **kwargs "inline emphasis..." * misc * Reference xarray_extras for csv writing. Closes #2289 * Add metpy accessor. Closes #461 * fix transpose docstring. Closes #2576 * Revert "Fix lists." This reverts commit 39983a5. * Revert "Fix *args, **kwargs" This reverts commit 1b9da35. * Add MetPy to related projects. * Add Weather and Climate specific page. * Add hvplot. * Note open_dataset, mfdataset open files as read-only (closes #2345). * Update metpy 1 Co-Authored-By: dcherian <dcherian@users.noreply.github.com> * Update doc/weather-climate.rst Co-Authored-By: dcherian <dcherian@users.noreply.github.com> * Drop failing tests writing multi-dimensional arrays as attributes (#2810) These aren't valid for netCDF files. Fixes GH2803 * Push back finalizing deprecations for 0.12 (#2809) 0.12 will already have a big change in dropping Python 2.7 support. I'd rather wait a bit longer to finalize these deprecations to minimize the impact on users. * enable loading remote hdf5 files (#2782) * attempt at loading remote hdf5 * added a couple tests * rewind bytes after reading header * addressed comments for tests and error message * fixed pep8 formatting * created _get_engine_from_magic_number function, new tests * added description in whats-new * fixed test failure on windows * same error on windows and nix * Release 0.12.0 * Add whats-new for 0.12.1 * Rework whats-new for 0.12 * DOC: Update donation links * DOC: remove outdated warning (#2818) * Allow expand_dims() method to support inserting/broadcasting dimensions with size>1 (#2757) * Make using dim_kwargs for python 3.5 illegal -- a ValueError is thrown * dataset.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * dataarray.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * Add alternative option to passing a dict to the dim argument, which is now an optional kwarg, passing in each new dimension as its own kwarg * Add expand_dims enhancement from issue 2710 to whats-new.rst * Fix test_dataarray.TestDataArray.test_expand_dims_with_greater_dim_size tests to pass in python 3.5 using ordered dicts instead of regular dicts. This was needed because python 3.5 and earlier did not maintain insertion order for dicts * Restrict core logic to use 'dim' as a dict--it will be converted into a dict on entry if it is a str or a sequence of str * Don't cast dim values (coords) as a list since IndexVariable/Variable will internally convert it into a numpy.ndarray. So just use IndexVariable((k,), v) * TypeErrors should be raised for invalid input types, rather than ValueErrors. * Force 'dim' to be OrderedDict for python 3.5 * Allow expand_dims() method to support inserting/broadcasting dimensions with size>1 (#2757) * use .size attribute to determine the size of a dimension, rather than converting to a list, which can be slow for large iterables * Make using dim_kwargs for python 3.5 illegal -- a ValueError is thrown * dataset.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * dataarray.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * Add alternative option to passing a dict to the dim argument, which is now an optional kwarg, passing in each new dimension as its own kwarg * Add expand_dims enhancement from issue 2710 to whats-new.rst * Fix test_dataarray.TestDataArray.test_expand_dims_with_greater_dim_size tests to pass in python 3.5 using ordered dicts instead of regular dicts. This was needed because python 3.5 and earlier did not maintain insertion order for dicts * Restrict core logic to use 'dim' as a dict--it will be converted into a dict on entry if it is a str or a sequence of str * Don't cast dim values (coords) as a list since IndexVariable/Variable will internally convert it into a numpy.ndarray. So just use IndexVariable((k,), v) * TypeErrors should be raised for invalid input types, rather than ValueErrors. * Force 'dim' to be OrderedDict for python 3.5 * Allow expand_dims() method to support inserting/broadcasting dimensions with size>1 (#2757) * Move enhancement description up to 0.12.1 * use .size attribute to determine the size of a dimension, rather than converting to a list, which can be slow for large iterables * Make using dim_kwargs for python 3.5 illegal -- a ValueError is thrown * dataset.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * dataarray.expand_dims() method take dict like object where values represent length of dimensions or coordinates of dimesnsions * Add alternative option to passing a dict to the dim argument, which is now an optional kwarg, passing in each new dimension as its own kwarg * Add expand_dims enhancement from issue 2710 to whats-new.rst * Fix test_dataarray.TestDataArray.test_expand_dims_with_greater_dim_size tests to pass in python 3.5 using ordered dicts instead of regular dicts. This was needed because python 3.5 and earlier did not maintain insertion order for dicts * Restrict core logic to use 'dim' as a dict--it will be converted into a dict on entry if it is a str or a sequence of str * Don't cast dim values (coords) as a list since IndexVariable/Variable will internally convert it into a numpy.ndarray. So just use IndexVariable((k,), v) * TypeErrors should be raised for invalid input types, rather than ValueErrors. * Force 'dim' to be OrderedDict for python 3.5
Is there currently a way to drop unused coordinates, like this? |
I guess |
whats-new.rst
for all changes andapi.rst
for new API