matplotlib/matplotlib
Feb 2025 – Feb 2025
1 Month active
Languages Used
Python
Technical Skills
Bug FixData Visualization
Raphael Erik Hviding
PROFILE
Raphael Erik Hviding
Raphael Hviding developed a generic DataFrame conversion feature for the astropy/astropy repository, enabling seamless interoperability between Astropy Tables and multiple DataFrame backends such as pandas, polars, and pyarrow using the Narwhals library. He approached this by implementing to_df and from_df methods, accompanied by extensive refactoring and testing to ensure robust integration and data consistency. In the matplotlib/matplotlib repository, Raphael addressed a bug in histogram plotting by normalizing and validating keyword arguments, improving API reliability and user experience. His work demonstrated depth in Python, API design, and data visualization, focusing on maintainability and cross-library compatibility.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
1
Lines of code
2,419
Activity Months2
Your Network
184 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025 – Delivered a key interoperability feature to Astropy Tables by introducing generic DataFrame conversion via Narwhals, enabling seamless to_df and from_df conversions across pandas, polars, and pyarrow. Includes extensive refactoring and testing to ensure robust interoperability with multiple DataFrame backends and sets the stage for broader data ecosystem integration.
1 Commits • 1 Features
Oct 1, 2025October 2025 – Delivered a key interoperability feature to Astropy Tables by introducing generic DataFrame conversion via Narwhals, enabling seamless to_df and from_df conversions across pandas, polars, and pyarrow. Includes extensive refactoring and testing to ensure robust interoperability with multiple DataFrame backends and sets the stage for broader data ecosystem integration.
October 2025
February 2025
2 Commits
Feb 1, 2025February 2025 monthly summary for matplotlib/matplotlib: Focused on robustness of histogram keyword-argument handling. Delivered a targeted bug fix and backport to stabilize histogram APIs, improving correctness and user experience across notebooks and dashboards. Key improvements include normalization and validation of kwargs for histogram/Histogram plotting functions, reduced risk of incorrect argument processing, and strengthened API reliability.
February 2025
2 Commits
Feb 1, 2025February 2025 monthly summary for matplotlib/matplotlib: Focused on robustness of histogram keyword-argument handling. Delivered a targeted bug fix and backport to stabilize histogram APIs, improving correctness and user experience across notebooks and dashboards. Key improvements include normalization and validation of kwargs for histogram/Histogram plotting functions, reduced risk of incorrect argument processing, and strengthened API reliability.
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture70.0%
Performance66.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
API DesignBug FixData VisualizationDataFramesLibrary IntegrationRefactoringTesting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
astropy/astropy
Oct 2025 – Oct 2025
1 Month active
Languages Used
Python
Technical Skills
API DesignDataFramesLibrary IntegrationRefactoringTesting