halley1116/2025_DA_study
Jan 2025 – Feb 2025
2 Months active
Languages Used
Python
Technical Skills
Data AnalysisJupyter NotebookPandasData PreprocessingData VisualizationFastText
hyeonu12
PROFILE
Hyeonu12
During a two-month period, Halley Lee developed two Jupyter Notebooks for the halley1116/2025_DA_study repository, focusing on data analysis and natural language processing. In January, Halley built an exploratory data analysis notebook for insurance data, implementing data loading, descriptive statistics, and analysis of relationships between medical and lifestyle factors using Python and pandas. In February, Halley delivered a sentiment analysis workflow that included data preprocessing, visualization with word clouds, and integration of FastText and logistic regression models. The work emphasized reproducibility and extensibility, providing a solid foundation for future analytics and model experimentation without reported bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
3,031
Activity Months2
Your Network
1074 peopleSame Organization
@naver.com1065
Work History
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for halley1116/2025_DA_study: Delivered a Sentiment Analysis Notebook enabling end-to-end sentiment analysis workflow with data loading, preprocessing, visualization, and NLP model integration (FastText + Logistic Regression). The work enhances data science experimentation, reproducibility, and actionable insights from customer feedback. This aligns with business goals by enabling faster sentiment analytics and better product feedback loops.
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for halley1116/2025_DA_study: Delivered a Sentiment Analysis Notebook enabling end-to-end sentiment analysis workflow with data loading, preprocessing, visualization, and NLP model integration (FastText + Logistic Regression). The work enhances data science experimentation, reproducibility, and actionable insights from customer feedback. This aligns with business goals by enabling faster sentiment analytics and better product feedback loops.
February 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for halley1116/2025_DA_study. Delivered the Insurance Data Analysis Notebook (JHW_3.ipynb), enabling self-service exploratory data analysis on an insurance dataset using pandas. Implemented data loading, descriptive statistics, and exploration of relationships between medical and lifestyle factors. This work positions the project for data-driven underwriting insights and analytics automation. Major bugs fixed: none reported this month.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for halley1116/2025_DA_study. Delivered the Insurance Data Analysis Notebook (JHW_3.ipynb), enabling self-service exploratory data analysis on an insurance dataset using pandas. Implemented data loading, descriptive statistics, and exploration of relationships between medical and lifestyle factors. This work positions the project for data-driven underwriting insights and analytics automation. Major bugs fixed: none reported this month.
Activity
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Quality Metrics
Correctness66.6%
Maintainability66.6%
Architecture60.0%
Performance60.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data AnalysisData PreprocessingData VisualizationFastTextJupyter NotebookLogistic RegressionMatplotlibNLPPandasSeabornWordCloud
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