issue_comments: 495085021

This data as json

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