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Workflows that distribute tabular data manipulation tasks across local or cluster resources for acceleration.
Distinct from Dataframe Processing: Focuses on the parallel distribution of the entire workflow rather than just programmatic manipulation.
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Modin is a distributed dataframe library and parallel data processing engine designed to handle large datasets that exceed system memory. It functions as a distributed computing framework that parallelizes data manipulation tasks across multiple CPU cores or clusters to increase throughput and avoid memory errors. The project mirrors the Pandas API, allowing for the distribution of data workflows without changing core code logic. It utilizes a pluggable backend interface, which enables users to switch between different distributed execution engines to optimize performance based on available h
Accelerates data manipulation tasks by distributing workloads across local or cluster resources without changing core code logic.