{"database": "github", "table": "issues", "is_view": false, "human_description_en": "where state_reason = \"completed\", \"updated_at\" is on date 2019-09-16 and user = 35968931 sorted by updated_at descending", "rows": [[324350248, "MDU6SXNzdWUzMjQzNTAyNDg=", 2159, "Concatenate across multiple dimensions with open_mfdataset", 35968931, "closed", 0, null, null, 27, "2018-05-18T10:10:49Z", "2019-09-16T18:54:39Z", "2019-06-25T15:50:33Z", "MEMBER", null, null, null, "#### Code Sample\r\n\r\n```python\r\n# Create 4 datasets containing sections of contiguous (x,y) data\r\nfor i, x in enumerate([1, 3]):\r\n    for j, y in enumerate([10, 40]):\r\n        ds = xr.Dataset({'foo': (('x', 'y'), np.ones((2, 3)))},\r\n                         coords={'x': [x, x+1],\r\n                                 'y': [y, y+10, y+20]})\r\n\r\n        ds.to_netcdf('ds.' + str(i) + str(j) + '.nc')\r\n\r\n# Try to open them all in one go\r\nds_read = xr.open_mfdataset('ds.*.nc')\r\nprint(ds_read)\r\n```\r\n#### Problem description\r\n\r\nCurrently ``xr.open_mfdataset`` will detect a single common dimension and concatenate DataSets along that dimension. However a common use case is a set of NetCDF files which have two or more common dimensions that need to be concatenated along simultaneously (for example collecting the output of any large-scale simulation which parallelizes in more than one dimension simultaneously). For the behaviour of ``xr.open_mfdataset`` to be n-dimensional it should automatically recognise and concatenate along all common dimensions.\r\n\r\n#### Expected Output\r\n```\r\n<xarray.Dataset>\r\nDimensions:  (x: 4, y: 6)\r\nCoordinates:\r\n  * x        (x) int64 1 2 3 4\r\n  * y        (y) int64 10 20 30 40 50 60\r\nData variables:\r\n    foo      (x, y) float64 dask.array<shape=(4, 6), chunksize=(2, 3)>\r\n```\r\n\r\n#### Current output of ``xr.open_mfdataset()``\r\n```\r\n<xarray.Dataset>\r\nDimensions:  (x: 4, y: 12)\r\nCoordinates:\r\n  * x        (x) int64 1 2 3 4\r\n  * y        (y) int64 10 20 30 40 50 60 10 20 30 40 50 60\r\nData variables:\r\n    foo      (x, y) float64 dask.array<shape=(4, 12), chunksize=(4, 3)>\r\n```\r\n", "{\"url\": \"https://api.github.com/repos/pydata/xarray/issues/2159/reactions\", \"total_count\": 4, \"+1\": 4, \"-1\": 0, \"laugh\": 0, \"hooray\": 0, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", null, "completed", 13221727, "issue"]], "truncated": false, "filtered_table_rows_count": 1, "expanded_columns": [], "expandable_columns": [[{"column": "repo", "other_table": "repos", "other_column": "id"}, "name"], [{"column": "milestone", "other_table": "milestones", "other_column": "id"}, "title"], [{"column": "assignee", "other_table": "users", "other_column": "id"}, "login"], [{"column": "user", "other_table": "users", "other_column": "id"}, "login"]], "columns": ["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"], "primary_keys": ["id"], "units": {}, "query": {"sql": "select 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 from issues where \"state_reason\" = :p0 and date(\"updated_at\") = :p1 and \"user\" = :p2 order by updated_at desc limit 101", "params": {"p0": "completed", "p1": "2019-09-16", "p2": "35968931"}}, "facet_results": {"state": {"name": "state", "type": "column", "hideable": false, "toggle_url": "/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931", "results": [{"value": "closed", "label": "closed", "count": 1, "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&state=closed", "selected": false}], "truncated": false}, "repo": {"name": "repo", "type": "column", "hideable": false, "toggle_url": "/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931", "results": [{"value": 13221727, "label": "xarray", "count": 1, "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&repo=13221727", "selected": false}], "truncated": false}, "type": {"name": "type", "type": "column", "hideable": false, "toggle_url": "/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931", "results": [{"value": "issue", "label": "issue", "count": 1, "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&type=issue", "selected": false}], "truncated": false}}, "suggested_facets": [{"name": "created_at", "type": "date", "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&_facet_date=created_at"}, {"name": "updated_at", "type": "date", "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&_facet_date=updated_at"}, {"name": "closed_at", "type": "date", "toggle_url": "http://xarray-datasette.fly.dev/github/issues.json?state_reason=completed&updated_at__date=2019-09-16&user=35968931&_facet_date=closed_at"}], "next": null, "next_url": null, "private": false, "allow_execute_sql": true, "query_ms": 36.33161447942257}