SpikyCherry/DSA3101_group9
Apr 2025 – Apr 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
ClusteringData AnalysisData PreprocessingData VisualizationExploratory Data Analysis
SpikyCherry
PROFILE
Spikycherry
Sherry contributed to the SpikyCherry/DSA3101_group9 repository by enhancing data analysis and preparation workflows over a one-month period. She updated the exploratory data analysis notebook to provide more detailed insights into data distributions and correlations, improving the clarity and depth of analysis. Her work extended preprocessing steps to incorporate numpy, integrating these enhancements with existing data processing and clustering notebooks. Using Python and Jupyter Notebook, Sherry focused on reproducibility and streamlined analytics pipelines, enabling more efficient downstream clustering. The changes addressed the need for better data preparation and analysis, resulting in a more robust and maintainable workflow for the project.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
594
Activity Months1
Your Network
8 people
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 – SpikyCherry/DSA3101_group9: Key feature delivered: Enhanced Data Analysis and Preparation Workflows. Updated EDA notebook with detailed distributions and correlations, and updated preprocessing to include numpy with integration to data processing and clustering notebooks. Commit 9a73f1e26729f711182dd10e86ba2dd2c73112f9. Major bugs fixed: None reported. Overall impact: Strengthened data analysis throughput and reproducibility; improved preprocessing integration to streamline analytics pipelines and downstream clustering. Technologies demonstrated: Python, numpy, Jupyter notebooks, data preprocessing and exploratory data analysis, and version-controlled workflows (git).
1 Commits • 1 Features
Apr 1, 2025April 2025 – SpikyCherry/DSA3101_group9: Key feature delivered: Enhanced Data Analysis and Preparation Workflows. Updated EDA notebook with detailed distributions and correlations, and updated preprocessing to include numpy with integration to data processing and clustering notebooks. Commit 9a73f1e26729f711182dd10e86ba2dd2c73112f9. Major bugs fixed: None reported. Overall impact: Strengthened data analysis throughput and reproducibility; improved preprocessing integration to streamline analytics pipelines and downstream clustering. Technologies demonstrated: Python, numpy, Jupyter notebooks, data preprocessing and exploratory data analysis, and version-controlled workflows (git).
April 2025
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
ClusteringData AnalysisData PreprocessingData VisualizationExploratory Data Analysis
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