cudf

cuDF - GPU DataFrame Library

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.

Lightweight and extensible compatibility layer between dataframe libraries!

🚚 Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark

GPU accelerated cross filtering with cuDF.

🚕 A spreadsheet-like data preparation web app that works over Optimus (Pandas, Dask, cuDF, Dask-cuDF, Spark and Vaex)

머신러닝/딥러닝(PyTorch, TensorFlow) 전용 도커입니다. 한글 폰트, 한글 자연어처리 패키지(konlpy), 형태소 분석기, Timezone 등의 설정 등을 추가 하였습니다.

Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.

Awesome list of alternative dataframe libraries in Python.

For when your data won't fit in your dataframe

Lightweight, engine-agnostic dataframe validation

Rapidsai_Machine_learnring_on_GPU

Python library to process and classify remote sensing imagery by means of GPUs and ML.

The Incredible RAPIDS: a curated list of tutorials, papers, projects, communities and more relating to RAPIDS.

Unlimited Data-Science Benchmarks for Numeric, Tabular and Graph Workloads

Building NVIDIA's RAPIDS (cuDF, cuML...) in Arch Linux

A simple demo of cuDF which is a RAPIDS GPU-Accelerated Dataframe Library!

jiboia-gpu is a Python package to normalize and optimize DataFrames automatically efficiently using the Nvidia GPU in the RAPIDS ecosystem.

Make AI coding agents write RAPIDS-first GPU Python.