Pandas Code Is Now 50x Faster On Google Colab With cuDF

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Table Of Contents

• Introduction
• What Is cuDF?
• Pandas Code Is Now 50x Faster On Google Colab With cuDF
• Summary
• References

Introduction

In the world of data analysis and manipulation, speed is often paramount. With the exponential growth of data volumes, efficient processing becomes crucial for timely insights and decision-making.Pandas Code Is Now 50x Faster On Google Colab With cuDF.

Pandas, a popular Python library for data manipulation, has long been a staple tool for data scientists and analysts. However, as datasets continue to expand, traditional Pandas workflows can struggle to keep pace.

What Is cuDF?

cuDF (pronounced “KOO-dee-eff”) is a Python GPU DataFrame library (built on the Apache Arrow columnar memory format) for loading, joining, aggregating, filtering, and otherwise manipulating data.

cuDF also provides a pandas-like API that will be familiar to data engineers & data scientists, so they can use it to easily accelerate their workflows without going into the details of CUDA programming.

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.

Pandas Code Is Now 50x Faster On Google Colab With cuDF

It now comes with native integration for RAPIDS cuDF, which powers GPU acceleration for pandas.

To boost your pandas code, use this single command at the top of your NVIDIA GPU-enabled Colab notebook:

%load_ext cudf.pandas

Zero Code Change Acceleration

• Just %load_ext cudf.pandas in Jupyter, or pass -m cudf.pandas on the command line.

Third-Party Library Compatible

• cudf.pandas is compatible with most third-party libraries that use pandas.

Run the same code on CPU or GPU

• Nothing changes, not even your import statements, when going from CPU to GPU.

100% of the Pandas API

• Combines the full flexibility of Pandas with blazing fast performance of cuDF

Here is the quick demo of cuDF and pandas with Google Colab notebook:

• https://colab.research.google.com/github/rapidsai-community/showcase/blob/main/getting_started_tutorials/cudf_pandas_colab_demo.ipynb

Summary

You can learn more about cuDF with pandas in the below documentation:

• https://docs.rapids.ai/api/cudf/stable/cudf_pandas/

• https://galaxyofai.com/category/python/

References

• https://docs.rapids.ai/api/cudf/stable/user_guide/

Happy Learning And Keep Learning

Thank You..