{"action":"created","issue":{"url":"https://api.github.com/repos/pydata/pandas/issues/1623","repository_url":"https://api.github.com/repos/pydata/pandas","labels_url":"https://api.github.com/repos/pydata/pandas/issues/1623/labels{/name}","comments_url":"https://api.github.com/repos/pydata/pandas/issues/1623/comments","events_url":"https://api.github.com/repos/pydata/pandas/issues/1623/events","html_url":"https://github.com/pydata/pandas/issues/1623","id":5627471,"number":1623,"title":"Add aggregate method to DataFrame","user":{"login":"wesm","id":329591,"avatar_url":"https://avatars.githubusercontent.com/u/329591?v=3","gravatar_id":"","url":"https://api.github.com/users/wesm","html_url":"https://github.com/wesm","followers_url":"https://api.github.com/users/wesm/followers","following_url":"https://api.github.com/users/wesm/following{/other_user}","gists_url":"https://api.github.com/users/wesm/gists{/gist_id}","starred_url":"https://api.github.com/users/wesm/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wesm/subscriptions","organizations_url":"https://api.github.com/users/wesm/orgs","repos_url":"https://api.github.com/users/wesm/repos","events_url":"https://api.github.com/users/wesm/events{/privacy}","received_events_url":"https://api.github.com/users/wesm/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/pydata/pandas/labels/Algos","name":"Algos","color":"eb6420"},{"url":"https://api.github.com/repos/pydata/pandas/labels/API%20Design","name":"API Design","color":"AD7FA8"},{"url":"https://api.github.com/repos/pydata/pandas/labels/Difficulty%20Intermediate","name":"Difficulty Intermediate","color":"fbca04"},{"url":"https://api.github.com/repos/pydata/pandas/labels/Effort%20Medium","name":"Effort Medium","color":"006b75"},{"url":"https://api.github.com/repos/pydata/pandas/labels/Enhancement","name":"Enhancement","color":"4E9A06"},{"url":"https://api.github.com/repos/pydata/pandas/labels/Groupby","name":"Groupby","color":"729FCF"},{"url":"https://api.github.com/repos/pydata/pandas/labels/Prio-high","name":"Prio-high","color":"FF5050"}],"state":"open","locked":false,"assignee":null,"milestone":{"url":"https://api.github.com/repos/pydata/pandas/milestones/38","html_url":"https://github.com/pydata/pandas/milestones/0.18.1","labels_url":"https://api.github.com/repos/pydata/pandas/milestones/38/labels","id":1570594,"number":38,"title":"0.18.1","description":"after 0.18.0 of course!","creator":{"login":"jreback","id":953992,"avatar_url":"https://avatars.githubusercontent.com/u/953992?v=3","gravatar_id":"","url":"https://api.github.com/users/jreback","html_url":"https://github.com/jreback","followers_url":"https://api.github.com/users/jreback/followers","following_url":"https://api.github.com/users/jreback/following{/other_user}","gists_url":"https://api.github.com/users/jreback/gists{/gist_id}","starred_url":"https://api.github.com/users/jreback/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jreback/subscriptions","organizations_url":"https://api.github.com/users/jreback/orgs","repos_url":"https://api.github.com/users/jreback/repos","events_url":"https://api.github.com/users/jreback/events{/privacy}","received_events_url":"https://api.github.com/users/jreback/received_events","type":"User","site_admin":false},"open_issues":140,"closed_issues":11,"state":"open","created_at":"2016-02-08T15:29:59Z","updated_at":"2016-03-13T17:17:52Z","due_on":"2016-04-26T04:00:00Z","closed_at":null},"comments":4,"created_at":"2012-07-15T15:20:05Z","updated_at":"2016-03-13T21:16:43Z","closed_at":null,"body":"a la groupby-aggregate"},"comment":{"url":"https://api.github.com/repos/pydata/pandas/issues/comments/196055424","html_url":"https://github.com/pydata/pandas/issues/1623#issuecomment-196055424","issue_url":"https://api.github.com/repos/pydata/pandas/issues/1623","id":196055424,"user":{"login":"jreback","id":953992,"avatar_url":"https://avatars.githubusercontent.com/u/953992?v=3","gravatar_id":"","url":"https://api.github.com/users/jreback","html_url":"https://github.com/jreback","followers_url":"https://api.github.com/users/jreback/followers","following_url":"https://api.github.com/users/jreback/following{/other_user}","gists_url":"https://api.github.com/users/jreback/gists{/gist_id}","starred_url":"https://api.github.com/users/jreback/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jreback/subscriptions","organizations_url":"https://api.github.com/users/jreback/orgs","repos_url":"https://api.github.com/users/jreback/repos","events_url":"https://api.github.com/users/jreback/events{/privacy}","received_events_url":"https://api.github.com/users/jreback/received_events","type":"User","site_admin":false},"created_at":"2016-03-13T21:16:43Z","updated_at":"2016-03-13T21:16:43Z","body":"this would *work* like ``.groupby(...).agg(np.sum)`` in the sense that the aggregations will take the same form. But this is an aggregation on the frame itself.\r\n\r\ne.g. imagine\r\n\r\n``df.agg(['sum', 'count'])``\r\n``df.agg({'A' : 'sum', 'B' : 'count'})``\r\n``df.agg({'A' : ['sum','count'], 'B' : ['sum','mean']})``"}}