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Found 104 Skills
Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Parallel/distributed computing. Scale pandas/NumPy beyond memory, parallel DataFrames/Arrays, multi-file processing, task graphs, for larger-than-RAM datasets and parallel workflows.
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
A Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Great for exploring relationships between variables and visualizing distributions. Use for statistical data visualization, exploratory data analysis (EDA), relationship plots, distribution plots, categorical comparisons, regression visualization, heatmaps, cluster maps, and creating publication-quality statistical graphics from Pandas DataFrames.
Use when "Dask", "parallel computing", "distributed computing", "larger than memory", or asking about "parallel pandas", "parallel numpy", "out-of-core", "multi-file processing", "cluster computing", "lazy evaluation dataframe"
Smart Excel/CSV file parsing with intelligent routing based on file complexity analysis. Analyzes file structure (merged cells, row count, table layout) using lightweight metadata scanning, then recommends optimal processing strategy - either high-speed Pandas mode for standard tables or semantic HTML mode for complex reports. Use when processing Excel/CSV files with unknown or varying structure where optimization between speed and accuracy is needed.
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
Geospatial Analysis provides workflows for satellite imagery processing, GIS operations with GeoPandas, spatial statistics, and Earth observation data analysis.
Best practices for doing quick exploratory data analysis with minimal code and a Pandas .plot like API using HoloViews hvPlot.
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified. Originally from OpenAI's curated skills catalog.
Python data analysis with pandas, numpy, and analytics libraries
Use when tasks involve creating, editing, analyzing, or formatting spreadsheets (`.xlsx`, `.csv`, `.tsv`) using Python (`openpyxl`, `pandas`), especially when formulas, references, and formatting need to be preserved and verified.