Day 19/21 days sql challenge
#SQLwithIDC
with @indiandataclub and @dpdzero
SELECT SERVICE,
SUM(PATIENTS_ADMITTED) AS TOTAL_PATIENTS_ADMITTED,
RANK() OVER (ORDER BY SUM(PATIENTS_ADMITTED) DESC) AS ADMISSION_RANK
FROM SERVICES_WEEKLY
GROUP BY SERVICE;
Day 14 โ of #21DaysSQLChallenge by @IndianDataClub x @DPDzero
Explored LEFT & RIGHT JOIN to handle unmatched records. Built a staff utilization report showing all staff their weeks present.
Takeaway: JOINs COALESCE = clean, complete insights.
#SQLWithIDC#SQL
๐๐ฎ๐ 14 of #21DaysSQLChallenge ๐
Todayโs focus: LEFT & RIGHT JOIN โ include unmatched records for a complete view.
๐ก Key Takeaways:
โ LEFT JOIN โ all left rows matches
โ RIGHT JOIN โ all right rows matches
โ Use COALESCE to handle NULLs
#SQLWithIDC
๐๐ฎ๐ 13 of #21DaysSQLChallenge ๐
INNER JOIN โ connect tables, get only matching rows.
๐ก Tips:
โ Use aliases & qualify columns
โ Chain joins for insights
โ Filter with WHERE after join
#SQLWithIDC
Day 11 of #21DaysSQLChallenge with @indiandataclub!
Today's topic: DISTINCT keyword โ the simplest way to handle duplicatesโจ
โ COUNT(DISTINCT col) for unique counts
โ GROUP BY for aggregates, DISTINCT for quick de-duplication
โ NULL values count as one
#SQLWithIDC#SQL