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Polars: Fast DataFrame Library for Data Science
polars
sickn33/antigravity-awesome-skills
324
Polars is a lightning-fast DataFrame library designed for efficient, memory-efficient data processing in Python and Rust. Built upon Apache Arrow, it supports lazy evaluation and parallel execution, making it ideal for ETL pipelines, large-scale data transformations, and scenarios where standard Pandas performance is insufficient. It excels at handling datasets up to 100GB that fit within available RAM.
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Seaborn Statistical Visualization Library
seaborn
sickn33/antigravity-awesome-skills
171
Seaborn is a high-level Python visualization library designed for creating publication-quality statistical graphics. It facilitates dataset-oriented plotting, multivariate analysis, and complex statistical visualizations (like KDEs, distributions, and relationships) directly from Pandas DataFrames with minimal code. It builds upon Matplotlib to provide semantic mapping and statistical awareness.
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Azure Monitor Query SDK
azure-monitor-query-py
sickn33/agentic-awesome-skills
182
Python SDK for querying Azure Monitor logs and Log Analytics workspaces, with authentication, batch queries, DataFrames, and metrics examples.
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