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using-pandas

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Write idiomatic, fast pandas code.

Data & Analytics#performance#pandas#data-analysis#vectorization#groupby#copy-on-write#tidy-data
Authorindiosmo
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This guide helps data practitioners write idiomatic and high-performance pandas code, reducing technical debt and enabling clearer analytics by emphasizing modern API usage, vectorized operations, and robust data handling.

Core Features & Use Cases

  • Modern API usage (loc/iloc, method chaining, pipe) to improve readability and maintainability.
  • Performance optimization through vectorization, explicit dtypes, and avoidance of DataFrame.apply where possible.
  • Proper data reshaping and time-series handling (tidy data, melt/pivot, Copy-on-Write semantics, categoricals) to enable scalable analytics.
  • Real-world example: Refactor a slow, apply-based transformation into vectorized operations for large datasets.

Quick Start

Analyze a pandas script and rewrite it to use idiomatic APIs, vectorization, and robust data handling for performance.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: using-pandas
Download link: https://github.com/indiosmo/skills/archive/main.zip#using-pandas

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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