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Real-World Data Cleaning with Python & Pandas:
Cleaned a real-world messy dataset (highest-grossing concert tours) using Python and pandas. Handled missing values, removed irrelevant columns, converted currency text to numeric values, and resolved encoding issues like hidden Unicode characters and footnote markers embedded in the raw data.
Tools used: Python, pandas
https://github.com/emanwajid85/concert-tours-data-cleaning
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Short Description
Built a Python workflow that cleans messy customer exports, normalizes fields, detects duplicates, validates rows, and exports clean data, review files, quality reports, and processing logs.
Problem
Business data exports often contain inconsistent emails, phone numbers, countries, dates, revenue fields, duplicate records, and missing values. Manual cleanup is repetitive and creates reporting risk.
Solution
I built a Python cleanup workflow that loads Excel/CSV customer data, maps raw columns to a target schema, normalizes fields, detects duplicates, validates rows, and exports clean and review-ready outputs.
Tools
Python, Pandas, OpenPyXL, YAML configuration, validation rules, CSV/XLSX input, automated reports.
Deliverables
Excel/CSV cleanup pipeline
Clean customer CSV
Duplicate/review output
Data quality report
Processing log
Reusable configuration files
Result
The workflow processed a messy customer export, removed duplicate records, separated clean and review rows, and produced a repeatable data-cleanup process for similar business data tasks.
Customer Segmentation Using SQL CASE Statements
Used SQL conditional logic to segment records into business categories based on numerical thresholds. Implemented CASE WHEN statements to classify entities into low, medium, and high-value groups, enabling easier downstream analysis and reporting.
Skills Demonstrated:
- SQL
- CASE Statements
- Data Transformation
- Data Categorization
- Business Logic Implementation
- Feature Engineering
Business Value:
Converting continuous metrics into categories allows organizations to simplify reporting, improve customer targeting, and support decision-making processes.
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