BU-Spark/ds-bcc-liz-breadon-accountability
Oct 2024 – Dec 2024
2 Months active
Languages Used
CSVPythonSQL
Technical Skills
Data CleaningData EntryData StandardizationExcel ProcessingPandasData Analysis
haddadzj
PROFILE
Haddadzj
Zachary Haddad worked on the BU-Spark/ds-bcc-liz-breadon-accountability repository, delivering end-to-end property assessment analytics and data standardization over a two-month period. He processed multi-year datasets using Python, Pandas, and Excel, focusing on cleaning and aligning key fields such as ZIP_CODE and OVERALL_COND, mapping categorical data to numeric values, and aggregating statistics by ZIP code. His work included ingesting new property records, computing mean conditions, and generating visualizations with Matplotlib and Seaborn. The resulting processed datasets and Excel exports enabled reliable year-over-year analysis, supported stakeholder reporting, and established a foundation for future dashboards and data-driven policy insights.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
884,913
Activity Months2
Your Network
49 people
Work History
December 2024
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — Delivered ZIP-code level property assessment analytics with visualization capabilities for BU-Spark/ds-bcc-liz-breadon-accountability. Processed 2021-2024 data to analyze owner occupancy, heating systems, and average bedrooms by ZIP code. Implemented data cleaning, aggregation, and mode computation for heating systems (ignoring blanks). Exported results to a new Excel workbook and produced heatmaps and pie charts to illustrate trends over the years. This work establishes a foundation for dashboards and stakeholder reports, enabling data-driven property insights and policy considerations.
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — Delivered ZIP-code level property assessment analytics with visualization capabilities for BU-Spark/ds-bcc-liz-breadon-accountability. Processed 2021-2024 data to analyze owner occupancy, heating systems, and average bedrooms by ZIP code. Implemented data cleaning, aggregation, and mode computation for heating systems (ignoring blanks). Exported results to a new Excel workbook and produced heatmaps and pie charts to illustrate trends over the years. This work establishes a foundation for dashboards and stakeholder reports, enabling data-driven property insights and policy considerations.
December 2024
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 – BU-Spark/ds-bcc-liz-breadon-accountability: Delivered end-to-end data standardization and enrichment for property assessment analytics. Key outcomes include cross-year data cleaning and alignment of ZIP_CODE and OVERALL_COND, numeric mapping of categorical fields, calculation of mean conditions, and ZIP-based classifications. Ingested a large batch of new property assessment records and saved processed data for yearly analysis and Excel visualizations. These changes enable reliable year-over-year analytics, faster reporting, and stronger data governance.
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 – BU-Spark/ds-bcc-liz-breadon-accountability: Delivered end-to-end data standardization and enrichment for property assessment analytics. Key outcomes include cross-year data cleaning and alignment of ZIP_CODE and OVERALL_COND, numeric mapping of categorical fields, calculation of mean conditions, and ZIP-based classifications. Ingested a large batch of new property assessment records and saved processed data for yearly analysis and Excel visualizations. These changes enable reliable year-over-year analytics, faster reporting, and stronger data governance.
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage33.4%
Skills & Technologies
Programming Languages
CSVPythonSQL
Technical Skills
Data AnalysisData CleaningData EntryData StandardizationData VisualizationExcel ProcessingMatplotlibPandasSeaborn
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