alexanderquispe/Diplomado_PUCP
Aug 2025 – Oct 2025
3 Months active
Languages Used
Jupyter NotebookPythonHTMLJavaScript
Technical Skills
Data AnalysisData ManipulationDocument GenerationJupyter NotebookPandasPython Scripting
Alexander Quispe
PROFILE
Alexander Quispe
Alexander Quispe developed a suite of data analysis and geospatial workflows in the alexanderquispe/Diplomado_PUCP repository, focusing on reproducible research and automated reporting. He built Jupyter notebooks in Python to preprocess, analyze, and visualize datasets, including district-level COVID-19 heatmaps, historical election data scraping, and precipitation analysis for Peru. Leveraging Pandas, GeoPandas, and Folium, Alexander automated data ingestion, filtering, and export to Word documents, while integrating web scraping with Selenium for dynamic data sources. His work emphasized end-to-end workflows, robust code organization, and clear documentation, enabling repeatable analyses and supporting both statistical and geographic insights without major bug issues.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
5
Lines of code
39,151
Activity Months3
Your Network
41 peopleSame Organization
@pucp.pe1
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Delivered a new Peru District-Level Precipitation Tutorial: an end-to-end raster workflow to analyze monthly precipitation by Peru's districts, including visualization, clipping rasters to district boundaries, computing district-averaged precipitation, and map-based results with basic statistical context. Notebook is prepared for zonal statistics (zonal_stats) and ready for re-execution to support repeatable analyses. Commits to production: 6414bf0c690200b99b73e7933d39a81c0335724b (update raster tutorial); a9fdf21a38acb8f0c779392a61e0186f69756a60 (update code). No major bugs reported this month; minor refinements were applied as part of the feature updates.
2 Commits • 1 Features
Oct 1, 2025Month: 2025-10 — Delivered a new Peru District-Level Precipitation Tutorial: an end-to-end raster workflow to analyze monthly precipitation by Peru's districts, including visualization, clipping rasters to district boundaries, computing district-averaged precipitation, and map-based results with basic statistical context. Notebook is prepared for zonal statistics (zonal_stats) and ready for re-execution to support repeatable analyses. Commits to production: 6414bf0c690200b99b73e7933d39a81c0335724b (update raster tutorial); a9fdf21a38acb8f0c779392a61e0186f69756a60 (update code). No major bugs reported this month; minor refinements were applied as part of the feature updates.
October 2025
September 2025
5 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for alexanderquispe/Diplomado_PUCP: Delivered three primary features with measurable business value across health analytics, election data automation, and geographic visualization. No explicit major bug fixes documented this month; the focus was on feature delivery and code quality improvements to support robust, repeatable analyses. Technologies demonstrated include Python, Folium, Geopandas, Chromedriver-based web scraping, and Jupyter notebooks, reinforcing data science workflow maturity and reproducibility.
September 2025
5 Commits • 3 Features
Sep 1, 2025September 2025 monthly summary for alexanderquispe/Diplomado_PUCP: Delivered three primary features with measurable business value across health analytics, election data automation, and geographic visualization. No explicit major bug fixes documented this month; the focus was on feature delivery and code quality improvements to support robust, repeatable analyses. Technologies demonstrated include Python, Folium, Geopandas, Chromedriver-based web scraping, and Jupyter notebooks, reinforcing data science workflow maturity and reproducibility.
August 2025
2 Commits • 1 Features
Aug 1, 2025Delivered an automated data analysis notebook setup with preprocessing and reporting for the Diplomado_PUCP project. Implemented data loading from CSV, column renaming, filtering to South American countries, sorting, and basic analytics (averages, handling missing values). Added end-to-end export of analysis results to a Word document (.docx) from a pandas DataFrame to support reporting.
2 Commits • 1 Features
Aug 1, 2025Delivered an automated data analysis notebook setup with preprocessing and reporting for the Diplomado_PUCP project. Implemented data loading from CSV, column renaming, filtering to South American countries, sorting, and basic analytics (averages, handling missing values). Added end-to-end export of analysis results to a Word document (.docx) from a pandas DataFrame to support reporting.
August 2025
Activity
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Quality Metrics
Correctness68.8%
Maintainability68.8%
Architecture62.2%
Performance62.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaScriptJupyter NotebookPython
Technical Skills
Data AnalysisData ManipulationData VisualizationDocument GenerationFoliumGeoPandasGeopandasGeospatial AnalysisJupyter NotebookLeaflet.jsMatplotlibPandasPythonPython ScriptingRaster Data Processing
Repositories Contributed To
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