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alterlab-dask

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Scale pandas/NumPy with distributed Dask.

Data & Analytics#pandas#numpy#parallel-processing#big-data#distributed-computing#dask
AuthorAlterLab-IEU
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Dask enables large-scale, parallel computing for data workflows that exceed memory limits by distributing work across cores or clusters, letting you process datasets that don’t fit in a single machine.

Core Features & Use Cases

  • Parallel DataFrames and NumPy arrays with lazy execution and task graphs
  • Unstructured data processing with Bags, futures-based dynamic workflows, and integration with XArray and Dask-ML
  • Domain-wide use cases for large-scale analytics, ETL, and scientific computing

Quick Start

Run a quick test by reading a few CSV files with dd.read_csv and computing the mean.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: alterlab-dask
Download link: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/archive/main.zip#alterlab-dask

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