home / github

Menu
  • Search all tables
  • GraphQL API

issues

Table actions
  • GraphQL API for issues

2 rows where type = "issue" and user = 30382331 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date), closed_at (date)

state 2

  • closed 1
  • open 1

type 1

  • issue · 2 ✖

repo 1

  • xarray 2
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
447044177 MDU6SXNzdWU0NDcwNDQxNzc= 2980 Jupyter Notebooks for Tutorials(USER GUIDE) hdsingh 30382331 open 0     3 2019-05-22T10:01:26Z 2022-04-09T02:07:55Z   NONE      

This issue is more of a suggestion.

A small issue that users reading documentation face is unavailability of jupyter notebooks for the tutorial docs User Guide. User constantly has to copy paste code from the documentation or .rst file which results in wastage of time. Having executable notebooks for new users would help them save time and quickly move on to using xarray for their specific tasks.It would ease the learning process for new users which may somehow bring more contributors to xarray community.

Let's take example of pyviz, holoviews, pytorch.

00 Setup — PyViz 0.10.0 documentation

holoviews/examples/user_guide at master · pyviz/holoviews · GitHub

Chatbot Tutorial — PyTorch Tutorials 1.1.0.dev20190507 documentation

All of them provide option to download the tutorial in the form of .ipynb file either in the beginning or end of the notebook.

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/2980/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    xarray 13221727 issue
469117528 MDU6SXNzdWU0NjkxMTc1Mjg= 3137 .sel method gives error with float32 values hdsingh 30382331 closed 0     8 2019-07-17T10:37:29Z 2019-08-10T22:24:27Z 2019-08-10T22:24:27Z NONE      

.sel method gives error when it is used to select float32 values however it works fine for float64 Example: ```python import xarray as xr import numpy as np

a = np.asarray([0. , 0.111, 0.222, 0.333], dtype='float32') ds = xr.Dataset(coords={'a': (['a'],a )}) ds.a.sel({'a': 0.111}) Error Traceback:python KeyError Traceback (most recent call last) ~/anaconda3/envs/check3/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance) 2656 try: -> 2657 return self._engine.get_loc(key) 2658 except KeyError:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

KeyError: 0.111

During handling of the above exception, another exception occurred:

KeyError Traceback (most recent call last) <ipython-input-7-b4190c1d9580> in <module> 4 a = np.asarray([0. , 0.111, 0.222, 0.333], dtype='float32') 5 ds = xr.Dataset(coords={'a': (['a'],a )}) ----> 6 ds.a.sel({'a': 0.111}) 7 ds.a.sel({'a': 0.111}, method= 'nearest')

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, indexers_kwargs) 853 ds = self._to_temp_dataset().sel( 854 indexers=indexers, drop=drop, method=method, tolerance=tolerance, --> 855 indexers_kwargs) 856 return self._from_temp_dataset(ds) 857

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 1729 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, 'sel') 1730 pos_indexers, new_indexes = remap_label_indexers( -> 1731 self, indexers=indexers, method=method, tolerance=tolerance) 1732 result = self.isel(indexers=pos_indexers, drop=drop) 1733 return result._overwrite_indexes(new_indexes)

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs) 315 316 pos_indexers, new_indexes = indexing.remap_label_indexers( --> 317 obj, v_indexers, method=method, tolerance=tolerance 318 ) 319 # attach indexer's coordinate to pos_indexers

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance) 250 else: 251 idxr, new_idx = convert_label_indexer(index, label, --> 252 dim, method, tolerance) 253 pos_indexers[dim] = idxr 254 if new_idx is not None:

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance) 179 indexer, new_index = index.get_loc_level(label.item(), level=0) 180 else: --> 181 indexer = get_loc(index, label.item(), method, tolerance) 182 elif label.dtype.kind == 'b': 183 indexer = label

~/anaconda3/envs/check3/lib/python3.7/site-packages/xarray/core/indexing.py in get_loc(index, label, method, tolerance) 106 def get_loc(index, label, method=None, tolerance=None): 107 kwargs = _index_method_kwargs(method, tolerance) --> 108 return index.get_loc(label, **kwargs) 109 110

~/anaconda3/envs/check3/lib/python3.7/site-packages/pandas/core/indexes/numeric.py in get_loc(self, key, method, tolerance) 434 pass 435 return super(Float64Index, self).get_loc(key, method=method, --> 436 tolerance=tolerance) 437 438 @cache_readonly

~/anaconda3/envs/check3/lib/python3.7/site-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance) 2657 return self._engine.get_loc(key) 2658 except KeyError: -> 2659 return self._engine.get_loc(self._maybe_cast_indexer(key)) 2660 indexer = self.get_indexer([key], method=method, tolerance=tolerance) 2661 if indexer.ndim > 1 or indexer.size > 1:

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.Float64HashTable.get_item()

KeyError: 0.111 ``` xarray version: 0.12.1 numpy version: 1.16.3

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/3137/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
  completed xarray 13221727 issue

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options:

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);
Powered by Datasette · Queries took 21.143ms · About: xarray-datasette