DAB-4th/Final-Project
Mar 2025 – Mar 2025
1 Month active
Languages Used
Python
Technical Skills
Data AnalysisData CleaningData VisualizationJupyter NotebookMatplotlibNumPy
InuEast
PROFILE
Inueast
In March 2025, Jae Hong Park developed a Chicago Crime Data Analysis Notebook within the DAB-4th/Final-Project repository, focusing on enabling reproducible, end-to-end workflows for crime data analysis. Using Python, Pandas, and Seaborn, he implemented data loading, preprocessing, analysis, and visualization steps to support data-driven reporting and decision-making. The notebook scaffold was designed for reusability and traceability, streamlining insight generation from complex datasets. During this period, he also addressed an accidental deletion incident, highlighting the importance of backup and recovery processes. The work demonstrated a solid grasp of data engineering fundamentals and practical application of data science tools.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
3,800
Activity Months1
Your Network
1001 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for DAB-4th/Final-Project focusing on business value and technical achievements. Delivered a Chicago Crime Data Analysis Notebook (Final_PJT.ipynb) to enable end-to-end data loading, preprocessing, analysis, and visualization of Chicago crime statistics, supporting data-driven reporting and decision-making. This artifact improves reproducibility and speeds up insight generation from crime data. A notable incident this month involved accidental deletion of the '1팀/박재홍' directory containing Final_PJT.ipynb, which removed the notebook and prior analyses; this underscores the need for backups and recovery controls.
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for DAB-4th/Final-Project focusing on business value and technical achievements. Delivered a Chicago Crime Data Analysis Notebook (Final_PJT.ipynb) to enable end-to-end data loading, preprocessing, analysis, and visualization of Chicago crime statistics, supporting data-driven reporting and decision-making. This artifact improves reproducibility and speeds up insight generation from crime data. A notable incident this month involved accidental deletion of the '1팀/박재홍' directory containing Final_PJT.ipynb, which removed the notebook and prior analyses; this underscores the need for backups and recovery controls.
March 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData CleaningData VisualizationJupyter NotebookMatplotlibNumPyPandasSeaborn
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