cuDF GPU DataFrames (NVIDIA)
3,484 starsNVIDIA-authored guidance for cuDF GPU DataFrames: pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics and multi-GPU DataFrame workloads.
- First published：2026-02-25
- data as of：
- 2026-09-30
- Licence：
- Apache-2.0
When to use it
When accelerating pandas/DataFrame workloads on GPUs for large-scale data.
Caution
Requires NVIDIA GPUs and a RAPIDS environment; the repo description names Claude Code, Codex and similar coding agents as install targets.
Install prompt
請幫我安裝「cuDF GPU DataFrames (NVIDIA)」技能：從 https://github.com/NVIDIA/skills/tree/main/skills/accelerated-computing-cudf（技能路徑：skills/accelerated-computing-cudf/） 取得完整的技能目錄，放進我的 Agent 的技能目錄（例如專案內的 skills/ 資料夾，或該 Agent 文件指明的全域技能位置），確認裡面的 SKILL.md 存在、frontmatter 的 name 與 description 完整，然後列出這個技能宣告的腳本、外部工具與 API 需求，先不要執行任何腳本。Paste this to your agent. It deliberately contains no tool subcommands — check the tool's official docs for commands.
Compatible with