Coding Projects

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🧪 Real-world SQL Scenarios & Challenges Let’s dive into the types of real-world problems you’ll encounter as a data analyst, data scientist , data engineer, or developer. 1. Finding Duplicates SELECT name, COUNT(*) FROM employees GROUP BY name HAVING COUNT(*) > 1; Perfect for data cleaning and validation tasks. 2. Get the Second Highest Salary SELECT MAX(salary) AS second_highest FROM employees WHERE salary < ( SELECT MAX(salary) FROM employees ); 3. Running Totals SELECT name, salary, SUM(salary) OVER (ORDER BY id) AS running_total FROM employees; Essential in dashboards and financial reports. 4. Customers with No Orders SELECT c.customer_id, c.name FROM customers c LEFT JOIN orders o ON c.customer_id = o.customer_id WHERE o.order_id IS NULL; Very common in e-commerce or CRM platforms. 5. Monthly Aggregates SELECT DATE_TRUNC('month', order_date) AS month, COUNT(*) AS total_orders FROM orders GROUP BY month ORDER BY month; Great for trends and time-based reporting. 6. Pivot-like Output (Using CASE) SELECT department, COUNT(CASE WHEN gender = 'Male' THEN 1 END) AS male_count, COUNT(CASE WHEN gender = 'Female' THEN 1 END) AS female_count FROM employees GROUP BY department; Super useful for dashboards and insights. 7. Recursive Queries (Org Hierarchy or Tree) WITH RECURSIVE employee_tree AS ( SELECT id, name, manager_id FROM employees WHERE manager_id IS NULL UNION ALL SELECT e.id, e.name, e.manager_id FROM employees e INNER JOIN employee_tree et ON e.manager_id = et.id ) SELECT * FROM employee_tree; Used in advanced data modeling and tree structures. You don’t just need to know how SQL works — you need to know when to use it smartly! React with ❤️ if you’d like me to explain more data analytics topics Share with credits: https://t.me/sqlspecialist SQL Roadmap: https://t.me/sqlspecialist/1340 Hope it helps :)

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How to create Frontend development Portfolio

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Must-know Pandas Functions for Data Analysis

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Beginner’s Roadmap to Learn Data Structures & Algorithms 1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation. 2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently. 3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation. 4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data. 5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving. 6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation. 7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems. 8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding. 9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges. 10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio. Best DSA RESOURCES: https://topmate.io/coding/886874 All the best 👍👍

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AI & ML Project Ideas

JavaScript Array Methods Visualised

⌨️ QR code generation in Python