matplotlib/matplotlib
Oct 2024 – Feb 2026
2 Months active
Languages Used
Python
Technical Skills
Data VisualizationMatplotlibPandasPythongraphics programmingunit testing
Aman Nijjar
PROFILE
Aman Nijjar
Contributed to the matplotlib/matplotlib repository by enabling direct Pandas DataFrame support in ax.table, allowing users to pass DataFrames and automatically use their indices and columns as default row and column labels. This enhancement, implemented in Python with Pandas and Matplotlib, streamlines data visualization workflows by reducing manual label specification and improving integration for dashboards and reports. Additionally, addressed a rendering issue in SimpleLineShadow by replacing a deprecated method with get_rgb in GraphicsContextBase and introduced a regression unit test to ensure reliable path effects rendering. The work demonstrated attention to both feature development and robust, test-driven maintenance practices.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
94
Activity Months2
Your Network
157 peopleShared Repositories
157
Work History
February 2026
1 Commits
Feb 1, 2026February 2026 monthly summary for matplotlib/matplotlib focusing on rendering reliability and test coverage. Delivered a critical bug fix to SimpleLineShadow rendering by replacing get_foreground with get_rgb and added a regression unit test to validate the path.
1 Commits
Feb 1, 2026February 2026 monthly summary for matplotlib/matplotlib focusing on rendering reliability and test coverage. Delivered a critical bug fix to SimpleLineShadow rendering by replacing get_foreground with get_rgb and added a regression unit test to validate the path.
February 2026
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024: Delivered Pandas DataFrame support for Matplotlib's ax.table in matplotlib/matplotlib. The feature allows passing a DataFrame directly to table.table and automatically uses the DataFrame's indices and columns as row/column labels when explicit labels are not provided. This reduces boilerplate in dashboards and data exploration, improving integration with Pandas workflows. The change is anchored by commit 8e6d6b6bb27b518b9bd45b3aa6ff5842b9efd81a, demonstrating solid toolchain integration between Pandas and Matplotlib. No major bug fixes were recorded for this feature in October 2024.
October 2024
1 Commits • 1 Features
Oct 1, 2024October 2024: Delivered Pandas DataFrame support for Matplotlib's ax.table in matplotlib/matplotlib. The feature allows passing a DataFrame directly to table.table and automatically uses the DataFrame's indices and columns as row/column labels when explicit labels are not provided. This reduces boilerplate in dashboards and data exploration, improving integration with Pandas workflows. The change is anchored by commit 8e6d6b6bb27b518b9bd45b3aa6ff5842b9efd81a, demonstrating solid toolchain integration between Pandas and Matplotlib. No major bug fixes were recorded for this feature in October 2024.
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Data VisualizationMatplotlibPandasPythongraphics programmingunit testing
Repositories Contributed To
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