I'm doing some data analysis and want to find an easy way to examine all the members of each "group" in a group by function.
Like, 3 agents may be involved in an order. I want to quickly examine the three agents that were 'grouped' in this order for various reasons.
Usually, I would use group_concat for this (easy way to see all grouped strings). However replicating that using a 'group by' appears difficult and unwieldy for now in SQL sever.
Right now, rough-and-dirty, I would max(username) and min(username) to quickly find 2 (and 90% of orders probably have 2 or less people. Is there a way to do mid(username) or 2nd-highest(username), or percentile(50th, username)? That would be a great, quick way to find this relevant data. For some reason, the previous answers I've seen describing group_concat on SQL Server do not sound straightforward to me.
Sample data for instance:
employee purchase_id
bill 1
bob 1
chrissy 1
mike 2
bill 2
bob 3
Currently I have this:
purchase_id, employee_count, complicated metric
1 3 blahblah
2 2 dsflsajf
3 1 98%
I would like to see at a glance:
purchase_id, employees, complicated metric
1 (bill,bob,chrissy) blahblah
However the group_concat seems very confusing to use with a group by statement – or simulating group_concat with SQL Server. So instead, how bout this.
select max(employee), min(employee)
purchase_id, max(employee), min(employee)
1 bill chrissy
in the example you see that bob is omitted, as max/ min will only find the two endpoints. If there was some kind of function to pull the second highest value, or 50th percentile value, on strings, that would be helpful.
Best Answer
Something like this would split the results into multiple columns, but you would need to know in advance the maximum number of employees per purchase_id: