koalas
Koalas allows you to use the familiar pandas API to manipulate and analyze large-scale data on Apache Spark, enabling scalable data processing with a Pythonic interface.
- •When working with big data that exceeds the memory limits of a single machine
- •When needing to perform data analysis and machine learning tasks on distributed data
- •When already familiar with pandas and wanting to leverage its API for large-scale data processing
ks.from_pandas(pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})).groupby('A').sum().to_pandas()Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/koalas && curl -fsSL https://workflowstacks.com/api/skills/koalas/claude-skill -o ~/.claude/skills/koalas/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
Koalas is a large Python project (~36k lines across 57 code files, plus 46 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit 31 months ago, Apache-2.0 license, has a test suite.
- 1README.mdStart here — what it does and how to install it
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Installs with a command or two; your AI agent can do it for you.
mkdir -p ~/.claude/skills/koalas && curl -fsSL https://workflowstacks.com/api/skills/koalas/claude-skill -o ~/.claude/skills/koalas/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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