{"database": "github", "table": "issues", "is_view": false, "human_description_en": "where \"closed_at\" is on date 2015-08-01 and user = 1217238 sorted by updated_at descending", "rows": [[98274024, "MDExOlB1bGxSZXF1ZXN0NDEyODY3ODI=", 504, "ENH: where method for masking xray objects according to some criteria", 1217238, "closed", 0, null, null, 12, "2015-07-30T21:56:00Z", "2015-08-01T20:56:33Z", "2015-08-01T20:56:31Z", "MEMBER", null, 0, "pydata/xarray/pulls/504", "Fixes #503\n\nExample usage:\n\n```\nIn [13]: x = xray.DataArray(np.arange(9).reshape(3, 3), dims=['x', 'y'])\n\nIn [14]: x.where(x > 4)\nOut[14]:\n<xray.DataArray (x: 3, y: 3)>\narray([[ nan,  nan,  nan],\n       [ nan,  nan,   5.],\n       [  6.,   7.,   8.]])\nCoordinates:\n  * y        (y) int64 0 1 2\n  * x        (x) int64 0 1 2\n```\n\nExample from \"What's new\":\n\n```\nIn [4]: ds = xray.Dataset(coords={'x': range(100), 'y': range(100)})\n\nIn [5]: ds['distance'] = np.sqrt(ds.x ** 2 + ds.y ** 2)\n\nIn [6]: ds.distance.where(ds.distance < 100).plot()\nOut[6]: <matplotlib.image.AxesImage at 0x11a819690>\n```\n\n![image](https://cloud.githubusercontent.com/assets/1217238/8996204/156e7dfc-36cb-11e5-8097-fdd1de462a2d.png)\n", "{\"url\": \"https://api.github.com/repos/pydata/xarray/issues/504/reactions\", \"total_count\": 0, \"+1\": 0, \"-1\": 0, \"laugh\": 0, \"hooray\": 0, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", null, null, 13221727, "pull"], [98250388, "MDU6SXNzdWU5ODI1MDM4OA==", 503, "Add \"where\" method copied from pandas", 1217238, "closed", 0, null, null, 0, "2015-07-30T19:57:26Z", "2015-08-01T20:56:31Z", "2015-08-01T20:56:31Z", "MEMBER", null, null, null, "Instead of writing:\n`(ds * (ds > 7)).sum() / (ds > 7).sum()`\n\nIt would be nice to be able to write:\n`ds.where(ds > 7).mean()`\n\nFor more examples, see:\nhttp://pandas.pydata.org/pandas-docs/stable/indexing.html#the-where-method-and-masking\n\nThis came up on the mailing list 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