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Add SQL conditional examples documentation
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‎.gitignore

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# Database files
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*.mdf
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*.ldf
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*.ndf
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# IDE specific files
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.vscode/
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.idea/
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*.swp
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*.swo
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.DS_Store
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# Backup files
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*.bak
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*.backup
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*.tmp
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# Environment specific
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.env
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.env.local
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*.config

‎CONTRIBUTING.md

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# Contributing to SQL Conditional Examples
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We love your input! We want to make contributing to SQL Conditional Examples as easy and transparent as possible, whether it's:
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- Reporting a bug
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- Discussing the current state of the code
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- Submitting a fix
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- Proposing new features
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- Becoming a maintainer
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## We Develop with Github
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We use Github to host code, to track issues and feature requests, as well as accept pull requests.
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## We Use [Github Flow](https://guides.github.com/introduction/flow/index.html)
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Pull requests are the best way to propose changes to the codebase. We actively welcome your pull requests:
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1. Fork the repo and create your branch from `main`.
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2. If you've added code that should be tested, add tests.
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3. If you've changed APIs, update the documentation.
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4. Ensure the test suite passes.
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5. Make sure your code follows our coding standards.
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6. Issue that pull request!
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## Any contributions you make will be under the MIT Software License
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In short, when you submit code changes, your submissions are understood to be under the same [MIT License](http://choosealicense.com/licenses/mit/) that covers the project. Feel free to contact the maintainers if that's a concern.
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## Report bugs using Github's [issue tracker](https://github.com/yourusername/sql-examples/issues)
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We use GitHub issues to track public bugs. Report a bug by [opening a new issue](https://github.com/yourusername/sql-examples/issues/new); it's that easy!
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## Write bug reports with detail, background, and sample code
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**Great Bug Reports** tend to have:
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- A quick summary and/or background
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- Steps to reproduce
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- Be specific!
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- Give sample code if you can.
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- What you expected would happen
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- What actually happens
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- Notes (possibly including why you think this might be happening, or stuff you tried that didn't work)
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## License
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By contributing, you agree that your contributions will be licensed under its MIT License.

‎LICENSE

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MIT License
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Copyright (c) 2024 SQL Examples
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md

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# SQL Conditional Expressions and Examples
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This repository contains comprehensive examples of SQL conditional expressions, functions, and their practical applications. The examples cover various SQL flavors including SQL Server, Oracle, MySQL, and PostgreSQL.
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## Contents
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1. [Basic Conditional Expressions](comprehensive_conditional_examples.sql)
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- CASE Statements
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- IIF Functions
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- NULL Handling
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- Conditional Aggregates
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2. [Case Statement Examples](case_statement_examples.sql)
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- Simple CASE
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- Searched CASE
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- CASE in UPDATE statements
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- CASE with GROUP BY
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3. [IF Statement Alternatives](if_statement_examples.sql)
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- IIF usage
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- CASE alternatives
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- Complex conditions
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4. [Conditional Column Examples](conditional_column_examples.sql)
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- Dynamic columns
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- Calculated fields
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- Date-based conditions
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## Database Compatibility
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- **SQL Server Specific**:
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- IIF()
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- ISNULL()
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- TRY_CONVERT()
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- CHOOSE()
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- **Oracle Specific**:
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- NVL()
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- DECODE()
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- **Universal Functions**:
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- CASE
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- COALESCE
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- NULLIF
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## Common Use Cases
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1. **Data Categorization**
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- Price ranges
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- Age groups
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- Performance tiers
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2. **NULL Handling**
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- Default values
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- Data cleaning
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- Conditional aggregation
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3. **Business Logic**
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- Discount calculations
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- Commission structures
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- Status updates
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4. **Reporting**
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- KPI calculations
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- Performance metrics
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- Dynamic grouping
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## Best Practices
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1. Always include an ELSE clause in CASE statements
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2. Use appropriate NULL handling functions
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3. Consider performance implications with complex conditions
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4. Keep conditions mutually exclusive
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5. Use comments to explain complex logic
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## Performance Considerations
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- CASE statements are generally more performant than multiple IF conditions
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- Use appropriate indexes for columns used in conditions
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- Avoid unnecessary CASE expressions in WHERE clauses
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- Consider materialized views for complex conditional calculations
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## Examples
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Check the SQL files for detailed examples and implementations.

‎advanced_conditional_examples.sql

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/*
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Advanced SQL Conditional Examples
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-------------------------------
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This file contains advanced examples of SQL conditional expressions and their applications
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in real-world scenarios. Each section demonstrates different aspects of conditional logic
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in SQL.
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*/
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-- 1. Advanced Data Classification
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-- Example: Customer Segmentation based on multiple factors
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SELECT
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customer_id,
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customer_name,
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total_purchases,
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avg_order_value,
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CASE
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WHEN total_purchases > 100 AND avg_order_value > 1000 THEN 'Platinum'
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WHEN total_purchases > 50 AND avg_order_value > 500 THEN 'Gold'
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WHEN total_purchases > 20 OR avg_order_value > 250 THEN 'Silver'
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ELSE 'Bronze'
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END as customer_tier,
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-- Loyalty Score Calculation
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CASE
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WHEN months_active > 24 THEN 3
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WHEN months_active > 12 THEN 2
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ELSE 1
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END *
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CASE
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WHEN return_rate < 0.05 THEN 3
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WHEN return_rate < 0.10 THEN 2
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ELSE 1
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END as loyalty_score;
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-- 2. Dynamic Date Handling
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SELECT
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event_date,
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event_name,
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-- Fiscal Quarter Calculation
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CASE
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WHEN MONTH(event_date) BETWEEN 1 AND 3 THEN 'Q1'
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WHEN MONTH(event_date) BETWEEN 4 AND 6 THEN 'Q2'
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WHEN MONTH(event_date) BETWEEN 7 AND 9 THEN 'Q3'
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ELSE 'Q4'
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END + '-' + CAST(YEAR(event_date) AS VARCHAR) as fiscal_quarter,
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-- Season Classification
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CASE
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WHEN MONTH(event_date) IN (12, 1, 2) THEN 'Winter'
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WHEN MONTH(event_date) IN (3, 4, 5) THEN 'Spring'
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WHEN MONTH(event_date) IN (6, 7, 8) THEN 'Summer'
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ELSE 'Fall'
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END as season;
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-- 3. Advanced Statistical Calculations
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SELECT
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department,
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AVG(salary) as avg_salary,
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-- Salary Variance Categories
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CASE
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WHEN STDEV(salary) > 10000 THEN 'High Variance'
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WHEN STDEV(salary) > 5000 THEN 'Medium Variance'
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ELSE 'Low Variance'
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END as salary_variance,
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-- Percentile-based Categories
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CASE
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WHEN salary > PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY salary)
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OVER (PARTITION BY department) THEN 'Top 25%'
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WHEN salary > PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY salary)
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OVER (PARTITION BY department) THEN 'Top 50%'
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ELSE 'Bottom 50%'
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END as salary_percentile;
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-- 4. Complex Business Rules
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-- Example: Insurance Premium Calculation
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SELECT
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policy_id,
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customer_age,
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coverage_amount,
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-- Base Premium Calculation
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CASE
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WHEN customer_age < 25 THEN coverage_amount * 0.05
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WHEN customer_age < 35 THEN coverage_amount * 0.04
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WHEN customer_age < 45 THEN coverage_amount * 0.035
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WHEN customer_age < 55 THEN coverage_amount * 0.045
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ELSE coverage_amount * 0.055
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END +
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-- Risk Adjustment
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CASE risk_factor
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WHEN 'Low' THEN -500
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WHEN 'Medium' THEN 0
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WHEN 'High' THEN 1000
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ELSE 0
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END as calculated_premium;
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-- 5. Advanced String Manipulation
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SELECT
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email,
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-- Email Provider Classification
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CASE
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WHEN LOWER(email) LIKE '%@gmail.com' THEN 'Google'
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WHEN LOWER(email) LIKE '%@outlook.com' OR
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LOWER(email) LIKE '%@hotmail.com' OR
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LOWER(email) LIKE '%@live.com' THEN 'Microsoft'
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WHEN LOWER(email) LIKE '%@yahoo.com' THEN 'Yahoo'
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ELSE 'Other'
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END as email_provider,
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-- Phone Number Formatting
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CASE
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WHEN LEN(phone) = 10 THEN
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'(' + SUBSTRING(phone, 1, 3) + ') ' +
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SUBSTRING(phone, 4, 3) + '-' +
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SUBSTRING(phone, 7, 4)
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ELSE phone
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END as formatted_phone;
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-- 6. Hierarchical Data Processing
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WITH EmployeeHierarchy AS (
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SELECT
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employee_id,
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manager_id,
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salary,
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1 as level
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FROM employees
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WHERE manager_id IS NULL
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UNION ALL
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SELECT
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e.employee_id,
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e.manager_id,
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e.salary,
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eh.level + 1
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FROM employees e
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INNER JOIN EmployeeHierarchy eh
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ON e.manager_id = eh.employee_id
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)
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SELECT
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employee_id,
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level,
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CASE
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WHEN level = 1 THEN 'CEO'
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WHEN level = 2 THEN 'VP'
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WHEN level = 3 THEN 'Director'
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WHEN level = 4 THEN 'Manager'
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ELSE 'Staff'
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END as position_level;
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-- 7. Dynamic Pivot Tables
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DECLARE @columns NVARCHAR(MAX);
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DECLARE @sql NVARCHAR(MAX);
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SELECT @columns = STRING_AGG(
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QUOTENAME(category),
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',')
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FROM (SELECT DISTINCT category FROM products) as categories;
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SET @sql = N'
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SELECT *
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FROM (
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SELECT
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department,
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category,
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CASE
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WHEN units_sold > 1000 THEN ''High''
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WHEN units_sold > 500 THEN ''Medium''
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ELSE ''Low''
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END as sales_volume
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FROM sales
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) as SourceTable
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PIVOT (
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COUNT(sales_volume)
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FOR category IN (' + @columns + ')
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) as PivotTable;
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';
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EXEC sp_executesql @sql;
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-- 8. Geographic Data Processing
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SELECT
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location_id,
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latitude,
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longitude,
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-- Hemisphere Classification
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CASE
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WHEN latitude > 0 AND longitude > 0 THEN 'Northeast'
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WHEN latitude > 0 AND longitude < 0 THEN 'Northwest'
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WHEN latitude < 0 AND longitude > 0 THEN 'Southeast'
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ELSE 'Southwest'
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END as hemisphere,
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-- Time Zone Approximation
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CASE
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WHEN longitude BETWEEN -180 AND -135 THEN 'GMT-10'
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WHEN longitude BETWEEN -134 AND -90 THEN 'GMT-8'
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WHEN longitude BETWEEN -89 AND -45 THEN 'GMT-5'
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WHEN longitude BETWEEN -44 AND 0 THEN 'GMT'
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WHEN longitude BETWEEN 1 AND 45 THEN 'GMT+2'
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WHEN longitude BETWEEN 46 AND 90 THEN 'GMT+5'
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WHEN longitude BETWEEN 91 AND 135 THEN 'GMT+8'
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ELSE 'GMT+10'
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END as approximate_timezone;

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