cudf.pandas ----------- cuDF pandas accelerator mode (``cudf.pandas``) is built on cuDF and **accelerates pandas code** on the GPU. It supports **100% of the Pandas API**, using the GPU for supported operations, and automatically **falling back to pandas** for other operations. .. code-block:: python %load_ext cudf.pandas # pandas API is now GPU accelerated import pandas as pd df = pd.read_csv("filepath") # uses the GPU! df.groupby("col").mean() # uses the GPU! df.rolling(window=3).sum() # uses the GPU! df.apply(set, axis=1) # uses the CPU (fallback) .. figure:: ../_static/colab.png :width: 200px :target: https://nvda.ws/rapids-cudf Try it on Google Colab! +---------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ | **Zero Code Change Acceleration** | **Third-Party Library Compatible** | | | | | Just ``%load_ext cudf.pandas`` in Jupyter, or pass ``-m cudf.pandas`` on the command line. | ``cudf.pandas`` is compatible with most third-party libraries that use pandas. | +---------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ | **Run the same code on CPU or GPU** | **100% of the Pandas API** | | | | | Nothing changes, not even your `import` statements, when going from CPU to GPU. | Combines the full flexibility of Pandas with blazing fast performance of cuDF | +---------------------------------------------------------------------------------------------+---------------------------------------------------------------------------------------------------------------------+ Starting with the version 23.10.01 release ``cudf.pandas`` is available in Open Beta, as part of the ``cudf`` package . See `RAPIDS Quick Start `_ to get up-and-running with ``cudf``. .. toctree:: :maxdepth: 1 :caption: Contents: usage benchmarks how-it-works faq