{"action":"created","issue":{"url":"https://api.github.com/repos/numpy/numpy/issues/7742","repository_url":"https://api.github.com/repos/numpy/numpy","labels_url":"https://api.github.com/repos/numpy/numpy/issues/7742/labels{/name}","comments_url":"https://api.github.com/repos/numpy/numpy/issues/7742/comments","events_url":"https://api.github.com/repos/numpy/numpy/issues/7742/events","html_url":"https://github.com/numpy/numpy/pull/7742","id":160229364,"number":7742,"title":"Add `axis` argument to numpy.unique","user":{"login":"martinosorb","id":11293950,"avatar_url":"https://avatars.githubusercontent.com/u/11293950?v=3","gravatar_id":"","url":"https://api.github.com/users/martinosorb","html_url":"https://github.com/martinosorb","followers_url":"https://api.github.com/users/martinosorb/followers","following_url":"https://api.github.com/users/martinosorb/following{/other_user}","gists_url":"https://api.github.com/users/martinosorb/gists{/gist_id}","starred_url":"https://api.github.com/users/martinosorb/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/martinosorb/subscriptions","organizations_url":"https://api.github.com/users/martinosorb/orgs","repos_url":"https://api.github.com/users/martinosorb/repos","events_url":"https://api.github.com/users/martinosorb/events{/privacy}","received_events_url":"https://api.github.com/users/martinosorb/received_events","type":"User","site_admin":false},"labels":[{"id":6359239,"url":"https://api.github.com/repos/numpy/numpy/labels/09%20-%20Enhancement","name":"09 - Enhancement","color":"fef2c0","default":false},{"id":16917082,"url":"https://api.github.com/repos/numpy/numpy/labels/component:%20numpy.lib","name":"component: numpy.lib","color":"009800","default":false}],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":19,"created_at":"2016-06-14T16:44:41Z","updated_at":"2016-11-13T23:58:30Z","closed_at":"2016-11-13T23:58:20Z","pull_request":{"url":"https://api.github.com/repos/numpy/numpy/pulls/7742","html_url":"https://github.com/numpy/numpy/pull/7742","diff_url":"https://github.com/numpy/numpy/pull/7742.diff","patch_url":"https://github.com/numpy/numpy/pull/7742.patch"},"body":"This is an attempt at reviving joferkington's pull request (#3584, I was unable to contact him and his fork is no longer available). It makes use mostly of his code, but updates it to supporting return_counts, which was added later.\n\nThe idea is being able to return the unique rows (or columns) of a 2d array, or the unique (N-1)-dimensional slices of a N-dimensional array. If an N-dimensional array is provided, the function will return an N-dimensional array where the duplicate (N-1)-dimensional arrays found along the provided axis were removed.\n\nFuture work could involve providing more than an axis at once, for example when one wants to find the unique rows of a 10 dimensional array.\n"},"comment":{"url":"https://api.github.com/repos/numpy/numpy/issues/comments/260223156","html_url":"https://github.com/numpy/numpy/pull/7742#issuecomment-260223156","issue_url":"https://api.github.com/repos/numpy/numpy/issues/7742","id":260223156,"user":{"login":"shoyer","id":1217238,"avatar_url":"https://avatars.githubusercontent.com/u/1217238?v=3","gravatar_id":"","url":"https://api.github.com/users/shoyer","html_url":"https://github.com/shoyer","followers_url":"https://api.github.com/users/shoyer/followers","following_url":"https://api.github.com/users/shoyer/following{/other_user}","gists_url":"https://api.github.com/users/shoyer/gists{/gist_id}","starred_url":"https://api.github.com/users/shoyer/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/shoyer/subscriptions","organizations_url":"https://api.github.com/users/shoyer/orgs","repos_url":"https://api.github.com/users/shoyer/repos","events_url":"https://api.github.com/users/shoyer/events{/privacy}","received_events_url":"https://api.github.com/users/shoyer/received_events","type":"User","site_admin":false},"created_at":"2016-11-13T23:58:30Z","updated_at":"2016-11-13T23:58:30Z","body":"Thanks @martinosorb !"}}
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