Create a table from another table in SQL Server - sql

Question

I am trying to create the following table in SQL Server:
Id Had_appointment Date Month Year Clinic
1 1 2019-01-03 January 2019 A
1 1 2019-01-05 January 2019 B
5 1 2019-04-03 April 2019 C
From the following:
Id Admin_codes Date Clinic
1 AAA2 2019-01-03 A
1 D22S 2019-01-03 A
1 FFD3 2019-01-05 B
1 E222 2019-01-05 B
5 EEE1 2019-04-03 C
5 P332 2019-04-03 C
5 AA33 2019-04-03 C
5 XC22 2019-04-03 C
6 A000 2019-02-19 C
7 A999 2019-03-11 C
How can I do this? I don't want to include any individuals in my table who 1) did not have appointments & 2) have specific Admin_codes such as 'A000' and 'A999'. Thanks in advance.

Answer 1

We can do this by selecting distinct records for the appointments (treating every admin_code other than 'A000' and 'A999' as an appointment).
SELECT DISTINCT t.Id, '1' AS 'Had_appointment', t.[date], datename(month, [date]) [Month], year([date]) [Year], t.Clinic
FROM #t t
WHERE Admin_codes NOT IN ('A000', 'A999')
Please see demo here.

Answer 2

By "table" I'm assuming you mean query/resultset. In addition to #sacse's Answer, you can also accomplish the same with GROUP BY.
DECLARE #Data TABLE ( id INT, Admin_codes VARCHAR(4), [Date] DATE, Clinic VARCHAR(1) );
INSERT INTO #Data ( id, Admin_codes, [Date], Clinic ) VALUES
( 1, 'AAA2', '2019-01-03', 'A' ),( 1, 'D22S', '2019-01-03', 'A' ),( 1, 'FFD3', '2019-01-05', 'B' ),
( 1, 'E222', '2019-01-05', 'B' ),( 5, 'EEE1', '2019-04-03', 'C' ),( 5, 'P332', '2019-04-03', 'C' ),
( 5, 'AA33', '2019-04-03', 'C' ),( 5, 'XC22', '2019-04-03', 'C' ),( 6, 'A000', '2019-02-19', 'C' ),
( 7, 'A999', '2019-03-11', 'C' );
SELECT
id,
1 AS Had_appointment,
[Date],
DATENAME ( month, [Date] ) AS [Month],
YEAR ( [Date] ) AS [Year],
Clinic
FROM #Data
WHERE
Admin_codes NOT IN ( 'A000', 'A999' )
GROUP BY
id, [Date], Clinic
ORDER BY
id, [Date];
Returns
+----+-----------------+------------+---------+------+--------+
| id | Had_appointment | Date | Month | Year | Clinic |
+----+-----------------+------------+---------+------+--------+
| 1 | 1 | 2019-01-03 | January | 2019 | A |
| 1 | 1 | 2019-01-05 | January | 2019 | B |
| 5 | 1 | 2019-04-03 | April | 2019 | C |
+----+-----------------+------------+---------+------+--------+
Using GROUP BY will come in handy in the event you plan to do any additional aggregating (e.g., SUM, AVG, etc.).