{"html_url": "https://github.com/simonw/datasette/issues/485#issuecomment-495085021", "issue_url": "https://api.github.com/repos/simonw/datasette/issues/485", "id": 495085021, "node_id": "MDEyOklzc3VlQ29tbWVudDQ5NTA4NTAyMQ==", "user": {"value": 9599, "label": "simonw"}, "created_at": "2019-05-23T06:27:57Z", "updated_at": "2019-05-26T23:15:51Z", "author_association": "OWNER", "body": "I could attempt to calculate the statistics needed for this in a time limited SQL query something like this one: https://latest.datasette.io/fixtures?sql=select+%27name%27+as+column%2C+count+%28distinct+name%29+as+count_distinct%2C+avg%28length%28name%29%29+as+avg_length+from+roadside_attractions%0D%0A++union%0D%0Aselect+%27address%27+as+column%2C+count%28distinct+address%29+as+count_distinct%2C+avg%28length%28address%29%29+as+avg_length+from+roadside_attractions\r\n\r\n```\r\nselect 'name' as column, count (distinct name) as count_distinct, avg(length(name)) as avg_length from roadside_attractions\r\n  union\r\nselect 'address' as column, count(distinct address) as count_distinct, avg(length(address)) as avg_length from roadside_attractions\r\n```", "reactions": "{\"total_count\": 0, \"+1\": 0, \"-1\": 0, \"laugh\": 0, \"hooray\": 0, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", "issue": {"value": 447469253, "label": "Improvements to table label detection "}, "performed_via_github_app": null}