Innocent Watsala
Data cleaning & visualization with Python and Excel.
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A cleaned and structured HR/CRM employee dataset covering 20 employees across 11 countries and 10 departments. Prepared for analytics, reporting, and data pipeline projects.
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HR Dataset — Data Cleaning & Analysis
Cleaned a raw HR dataset of 1,470 employee records using Python (Pandas) and Excel. Removed 214 duplicate and null rows, standardized formatting, and built an interactive dashboard showing salary distribution by department and employee attrition rates by age group. Tools used: Python, Pandas, Excel, Power BI.
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A cleaned and structured HR/CRM employee dataset covering 20 employees across 11 countries and 10 departments. Prepared for analytics, reporting, and data pipeline projects. From Region Countries East Africa Kenya (6), Uganda (3) West Africa Nigeria (2), Ghana (1) Southern Africa Zimbabwe (1) Middle East UAE (2), Egypt (1) Asia China (1) Europe Spain (1), UK (1) North America USA (1)
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A full end-to-end data analysis project on San Francisco International Airport (SFO) air cargo traffic from 1999 to 2025 — covering data cleaning, exploratory analysis, and stakeholder-ready reporting. 1,756 rows where Operating ≠ Published airline. Unit (conversion-LBS) MT had tiny rounding errors (~1.56e-5) — perfectly acceptable
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Built an end-to-end Excel Price Intelligence Dashboard analyzing 1,100 food price records across multiple cities. Applied statistical techniques (Standard Deviation, Z-Score, Median vs Mean comparison) to measure price volatility, detect outliers, and evaluate city performance. Designed executive dashboard with KPI tracking and structured backend .
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