Identify overlap percent of IDs between 2 dates in same table - sql

Question

I have a table of names with two different dates. I want to know the count of names that are occurring between the two dates and the overlap percentage.
This is the output format that is desired. I am not looking for dates in between. I am looking for records that are in July 05 and also in August 10. Overlap percentage for each id would be - count of records in July 5 and also August 10/count of records on July 5.(Actual table has dates in date datatype).
Overlap % will always be less than or equal to 100 since count of records existing on July 5 as well as August 10 will always be <=count of records on July 5.
id
Count on July 05
Count of IDs from July 05 included in August 10
% overlap
ABC
BCD
CDE
DEF
EFG
Rough version of the input table
id
type
Group
date
ABC
Mobile
1
July 5
BCD
Mobile
1
July 5
ABC
Desktop
1
August 10
CDE
Mobile
2
July 5
BCD
Mobile
2
August 10

Answer 1

As I understood from your comments, the overlap will be the minimum count value of the two dates, i.e. for ABC if we have 6 in July and 2 in August the overlap will be 2, and if we have 3 in July and 5 in August the overlap will be 3.
If that is the case then you may use the following query tested on MS SQL Server 2019:
SELECT t.id, t.[Count on July 05],
CASE
WHEN t.[Count on July 05]<= t.[Count of August 10] THEN t.[Count on July 05]
WHEN t.[Count on July 05]> t.[Count of August 10] THEN t.[Count of August 10]
END AS [Count of IDs from July 05 included in August 10],
CASE
WHEN t.[Count on July 05]<= t.[Count of August 10] THEN CAST(t.[Count on July 05]*1.00/t.[Count on July 05] * 100 AS DECIMAL(18, 2))
WHEN t.[Count on July 05]> t.[Count of August 10] THEN CAST(t.[Count of August 10]*1.00/t.[Count on July 05] * 100 AS DECIMAL(18, 2))
END AS [% overlap]
FROM(
SELECT id,
COUNT(CASE WHEN [tdate] IN ('July 5') THEN 1 END) as [Count on July 05],
COUNT(CASE WHEN [tdate] IN ('August 10') THEN 1 END) as [Count of August 10]
FROM [Tbl]
GROUP BY id) t
I hope that is what you are looking for.