astro-datalab/notebooks-latest
Jan 2025 – Apr 2026
4 Months active
Languages Used
Jupyter NotebookPythonTextCSSHTMLJavaScriptMarkdownSQL
Technical Skills
AstrophysicsAstropyData AnalysisData VisualizationMatplotlibMetadata Management
Stephanie Juneau
PROFILE
Stephanie Juneau
Over four months, contributed to the astro-datalab/notebooks-latest repository by developing and enhancing Jupyter notebooks for astronomical data analysis and visualization. Delivered features such as the Cosmic Slime Notebook for Coma Cluster research, comprehensive DESI DR1 data exploration tools, and a Stellar Spectra Stacking workflow for SDSS, each emphasizing reproducibility and onboarding efficiency. The work involved Python, SQL, and Matplotlib, with a focus on code organization, metadata management, and documentation improvements. Addressed peer review feedback, standardized project structure, and automated analysis workflows, resulting in user-facing tools that streamline research, support spectral analysis, and improve data discoverability across the project.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
29Total
Bugs
0
Commits
29
Features
5
Lines of code
64,973
Activity Months4
Your Network
26 peopleShared Repositories
10
Benjamin Alan WeaverMember
BrianMolinaMerinoMember
bmerino95Member
David HerreraMember
github-actionsMember
Icuras42Member
Astro-MorganMember
Robert NikuttaMember
rohinsantMember
Work History
April 2026
15 Commits • 1 Features
Apr 1, 2026Month: 2026-04 — Notebooks-Latest (astro-datalab/notebooks-latest) delivered a cohesive Stellar Spectra Stacking notebook workflow for SDSS. The work consolidates data retrieval, visualization, spectral-type counting, and analysis automation into a user-facing feature, with renaming and renumbering clarified for clarity and reuse. nbid.csv and dataset references were updated to reflect the new naming, and galaxies were incorporated to broaden applicability for star- and galaxy-stack analyses. The effort includes comprehensive cleanup and standardization of notebook naming, removal of duplicate copies, and alignment of notebook references across the project.
15 Commits • 1 Features
Apr 1, 2026Month: 2026-04 — Notebooks-Latest (astro-datalab/notebooks-latest) delivered a cohesive Stellar Spectra Stacking notebook workflow for SDSS. The work consolidates data retrieval, visualization, spectral-type counting, and analysis automation into a user-facing feature, with renaming and renumbering clarified for clarity and reuse. nbid.csv and dataset references were updated to reflect the new naming, and galaxies were incorporated to broaden applicability for star- and galaxy-stack analyses. The effort includes comprehensive cleanup and standardization of notebook naming, removal of duplicate copies, and alignment of notebook references across the project.
April 2026
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for astro-datalab/notebooks-latest: Delivered Notebook Documentation and Demo Enhancement. Implemented an updated Jupyter notebook with a new example figure showing a prospect display with a DESI spectrum, expanded the summary section, and elaborated on tool capabilities and data handling. Version bumped to reflect October 2025 release. Change implemented via commit c9c3a1c8d8894849d1bfee6a20346826b54d0f01. No major bugs fixed this month. This work improves onboarding, clarifies capabilities for data exploration, and strengthens reproducibility for notebook users. Technologies demonstrated: Jupyter notebooks, data visualization, documentation, and versioning.
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for astro-datalab/notebooks-latest: Delivered Notebook Documentation and Demo Enhancement. Implemented an updated Jupyter notebook with a new example figure showing a prospect display with a DESI spectrum, expanded the summary section, and elaborated on tool capabilities and data handling. Version bumped to reflect October 2025 release. Change implemented via commit c9c3a1c8d8894849d1bfee6a20346826b54d0f01. No major bugs fixed this month. This work improves onboarding, clarifies capabilities for data exploration, and strengthens reproducibility for notebook users. Technologies demonstrated: Jupyter notebooks, data visualization, documentation, and versioning.
March 2025
9 Commits • 1 Features
Mar 1, 2025March 2025 monthly performance focused on enabling research teams to explore DESI DR1 data efficiently through end-to-end notebooks. Delivered the DESI DR1 Notebooks: Comprehensive Data Exploration and Visualization for astro-datalab/notebooks-latest, providing data access, filtering, spectral-type analysis, redshift visualization, and SPARCL-based spectra plotting, paired with improved documentation and project structure to support DR1 notebook usage. The work enhances reproducibility, accelerates insight generation, and reduces onboarding time for DR1 data exploration.
9 Commits • 1 Features
Mar 1, 2025March 2025 monthly performance focused on enabling research teams to explore DESI DR1 data efficiently through end-to-end notebooks. Delivered the DESI DR1 Notebooks: Comprehensive Data Exploration and Visualization for astro-datalab/notebooks-latest, providing data access, filtering, spectral-type analysis, redshift visualization, and SPARCL-based spectra plotting, paired with improved documentation and project structure to support DR1 notebook usage. The work enhances reproducibility, accelerates insight generation, and reduces onboarding time for DR1 data exploration.
March 2025
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for astro-datalab/notebooks-latest: Delivered a new Cosmic Slime Notebook for Coma Cluster analysis with visualizations of sky coverage and redshift distributions to aid cluster localization. Implemented metadata and documentation improvements, including adding the keyword 'quenching', updated author metadata, and refined wording and table readability. Addressed QA feedback with targeted fixes (typos, code adjustments, and refs) from peer reviews. Result: improved research capability, faster discovery and onboarding, and higher reproducibility through better documentation and quality controls. Technologies/skills demonstrated: Jupyter notebook development, data visualization, metadata management, documentation practices, and collaborative code reviews.
January 2025
4 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for astro-datalab/notebooks-latest: Delivered a new Cosmic Slime Notebook for Coma Cluster analysis with visualizations of sky coverage and redshift distributions to aid cluster localization. Implemented metadata and documentation improvements, including adding the keyword 'quenching', updated author metadata, and refined wording and table readability. Addressed QA feedback with targeted fixes (typos, code adjustments, and refs) from peer reviews. Result: improved research capability, faster discovery and onboarding, and higher reproducibility through better documentation and quality controls. Technologies/skills demonstrated: Jupyter notebook development, data visualization, metadata management, documentation practices, and collaborative code reviews.
Activity
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Quality Metrics
Correctness96.0%
Maintainability94.4%
Architecture93.2%
Performance93.0%
AI Usage22.8%
Skills & Technologies
Programming Languages
CSSCSVHTMLJavaScriptJupyter NotebookMarkdownPythonSQLText
Technical Skills
AstronomyAstrophysicsAstropyCode OrganizationDESIData AnalysisData VisualizationDataLabDatabase QueryingDocumentationFile ManagementJupyterJupyter NotebookJupyter NotebooksMarkdown
Repositories Contributed To
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