LindaDanalyst14/Nigerian-States-and-LGAs-Population-Analysis-Using-MYSQL

This project focuses on cleaning, transforming, normalizing and analyzing Nigeria's State and Local Government Area (LGA) population dataset using Mysql. # Nigerian-States-and-LGAs-Population-Analysis-Using-MYSQL This project focuses on cleaning, transforming, normalizing and analyzing Nigeria's State and Local Government Area (LGA) population dataset using Mysql. The original dataset contained each state’s LGAs and population in separate columns, making it difficult to perform nationwide analysis. To overcome this, I transformed the data into a normalized structure using SQL and carried out several analytical queries I normalized the dataset using UNION ALL into three columns: STATE | LGA | POPULATION| This transformation made nationwide analysis significantly easier. # SQL Analysis Performed 1️⃣ Displayed all LGAs by population 2️⃣ Found the most populous LGA 3️⃣ Retrieved the Top 10 Most Populous LGAs 4️⃣ Calculated Total Population of Nigeria 5️⃣ Calculated Population for Each State 6️⃣ Retrieved States with Population Greater Than a Threshold 7️⃣ Detected Duplicate Population Values 8️⃣ Identified Duplicate LGA Records 9️⃣ Ranked States by Total Population 🔟 Created a Reusable SQL View # SQL Concepts Demonstrated This project demonstrates practical use of: * SELECT * UNION ALL * CAST() * REPLACE() * SUM() * COUNT() * GROUP BY * HAVING * ORDER BY * LIMIT * CREATE VIEW * Aggregate Functions * Data Cleaning * Data Transformation * Data Normalization # 📈 Key Insights Through this project I was able to: * Transform a denormalized dataset into a structured format suitable for analysis. * Clean numeric data stored as text. * Analyze population distribution across Nigeria. * Rank LGAs by population. * Calculate total population by state. * Detect duplicate records and duplicate population values. * Create reusable SQL views for future analysis. # 🚀 Challenges Faced Throughout the project I encountered and resolved several SQL issues, including: * Syntax errors (Error 1064) * Unknown column errors (Error 1054) * Incorrect use of aliases * Ordering numeric values stored as text * Renaming imported tables * Handling …