html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,issue,performed_via_github_app
https://github.com/simonw/datasette/issues/485#issuecomment-495085021,https://api.github.com/repos/simonw/datasette/issues/485,495085021,MDEyOklzc3VlQ29tbWVudDQ5NTA4NTAyMQ==,9599,2019-05-23T06:27:57Z,2019-05-26T23:15:51Z,OWNER,"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

```
select 'name' as column, count (distinct name) as count_distinct, avg(length(name)) as avg_length from roadside_attractions
  union
select 'address' as column, count(distinct address) as count_distinct, avg(length(address)) as avg_length from roadside_attractions
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",447469253,
https://github.com/simonw/datasette/issues/485#issuecomment-495083670,https://api.github.com/repos/simonw/datasette/issues/485,495083670,MDEyOklzc3VlQ29tbWVudDQ5NTA4MzY3MA==,9599,2019-05-23T06:21:52Z,2019-05-23T06:22:36Z,OWNER,"If a table has more than two columns we could do a betterl job at guessing the label column. A few potential tricks:


* look for a column called name or title
* look for the first column of type text
* check for the text column with the most diversity in values","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",447469253,