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Day2️⃣1️⃣of 21 Day SQL Challenge by
@indiandataclub & @dpdzero
Topics: WITH clause, CTEs, recursive CTEs
CTEs create temporary named result sets that exist only during query execution. They make complex queries more readable and maintainable.
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Day2️⃣0️⃣of 21 Day SQL Challenge by
@indiandataclub & @dpdzero
Topics: SUM() OVER, AVG() OVER, running totals, moving averages
Aggregate window functions calculate running totals, moving averages, and cumulative statistics without collapsing rows.
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Day1️⃣9️⃣of 21 Day SQL Challenge by
@indiandataclub & @dpdzero
Topics: ROW_NUMBER(), RANK(), DENSE_RANK(), OVER clause Window functions perform calculations across rows related to the current row, without collapsing results like GROUP BY.
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Day1️⃣8️⃣ of 21 Day SQL Challenge by
@indiandataclub & @dpdzero
Topics: UNION, UNION ALL, combining result sets,
UNION combines results from multiple SELECT statements into a single result set.
#SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic
Day1️⃣7️⃣ of 21 Day SQL Challenge by
@indiandataclub & @dpdzero
Topics: Subqueries in SELECT, derived tables, and inline views. Used subqueries with SELECT and FROM to get calculated columns and drive tables from data.
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Day1️⃣6️⃣ of 21 Day SQL Challenge by @indiandataclub & @dpdzero
Topics: Subqueries in WHERE, nested queries, filtering with subqueries
Subqueries are queries nested inside other queries.
#SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic #Joins
total patients admitted that week, total patients refused, average patient satisfaction, count of staff assigned to service, and count of staff present that week. Order by patients admitted descending.
#SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic
Day 1️⃣4️⃣/21 Day SQL Challenge by @indiandataclub Sponsored by @dpdzero
Getting back on track.
Revised JOINS, focusing on LEFT JOIN and RIGHT JOIN
Observation:
- Nurses and nurse assistants are present more than doctors; all 5 staff members
#SQL #SQLWithIDC #21DaysOfSQL
Day 1️⃣2️⃣ & 1️⃣3️⃣ of 21 Day SQL Challenge by @indiandataclub
Sponsored by @DPDzero
[Couldn't post yesterday]
Day 12 focused on NULL handling in MySQL and understanding how missing values can completely change analysis results. Practiced using IS NULL, IS NOT NULL, and +
🔍 Observation:
- ICU is the most staffed service (48 staff)
- Emergency follows with 29 staff
- All services meet the staffing threshold (>5)
#SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL #LearningInPublic #NULLHandling #INNERJOIN
Day 11 of #21DaysOfSQL by @indiandataclub sponsored by @dpdzero.
Practiced DISTINCT, handling duplicates, and counting unique service–event combinations.
Found flu as the most common event across services, with general medicine leading.
#SQLWithIDC #21DaysOfSQL #DataAnalytics
Day 🔟/ #21DaysOfSQL with @indiandataclub & @dpdzero
Used CASE + GROUP BY to build a service performance report.
All services scored 77–82, landing in the “Good” category. Solid performance, with scope to push toward “Excellent.”
#SQLWithIDC #21DaysOfSQL #DataAnalytics #MYSQL
Day 9️⃣ of #21DaysOfSQL with @IndianDataClub & @dpdzero
Practiced DATE functions & date arithmetic 📅
Built a query to find services with avg hospital stay > 7 days.
Surgery stays longest, Emergency sees highest patient count.
#SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL
Day 8️⃣ of #21DaysOfSQL by @IndianDataClub (sponsored by #DPDzero)
Practiced string functions like UPPER, LOWER, LENGTH & CONCAT. Built a patient summary using CASE for age categories and filters on name length. Learning by doing!
#SQL #SQLWithIDC #DataAnalytics
Day 7⃣ of 21 SQL Challenge by @indiandataclub
and @dpdzero
Not feeling great, but showed up. Practiced HAVING—used after GROUP BY to filter aggregates (not rows like WHERE).
Found Emergency & Surgery with >100 refusals and avg satisfaction <80.
#SQLWithIDC #21DaysOfSQL #MySQL
Day 6️⃣ of 21 SQL Challenge by @indiandataclub and @dpdzero
Past midnight but still learning
Revised GROUP BY in MySQL for hospital data.
ICU had the highest admission rate (82.13%), Emergency had the lowest (19.13%).
#SQL #SQLWithIDC #21DaysOfSQL #DataAnalytics #MySQL
Day 5️⃣ | 21-Day SQL Challenge
Practiced on aggregate functions & data summarization in MySQL.
🔹 Practiced:
COUNT(), AVG(), MIN(), MAX(), SUM(), ROUND()
🔹 Daily Challenge:
Total patients admitted, total refused & avg satisfaction (2 decimals)
#SQL #SQLWithIDC #21DaysOfSQL
Day 4️⃣ of 21 Days of SQL by @indiandataclub (sponsored by @dpdzero ) 🚀
Focused on OFFSET & LIMIT for sorting, ranking, and top-N analysis.
Challenge: Retrieved the top 5 weeks with the highest patient refusals across services 📊
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Day 3️⃣ of 21 Day SQL Challenge by @indiandataclub
sponsored by @dpdzero
Focus: ORDER BY & LIMIT
* Sorted data using ORDER BY (single & multi-column)
* Used LIMIT for top-N analysis
* Learned how sorting supports ranking & performance insights
#SQL #SQLWithIDC #21DaysOfSQL
- Applied LIMIT to fetch the top 10 records from the services_weekly table
Challenge for DAY 1:
List all unique hospital services available in the hospital.
" SELECT DISTINCT (service) FROM services_weekly; "
#SQL #SQLWithIDC #21DaysOfSQL
The dataset includes patient details, weekly hospital services, and staff schedules in CSV format. For practice, I:
- Used SELECT with " * " to retrieve all records from the patients table,
- Selected specific columns using column names,
#SQL #SQLWithIDC #21DaysOfSQL
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