RAPIDS cuDF Cheat Sheet
RAPIDS cuDF is an open-source Python library for GPU accelerated DataFrames. Grab this handy reference now and accelerate your data science!
RAPIDS cuDF is an open-source Python library for GPU accelerated DataFrames. cuDF provides a Pandas-like API that allows data engineers, analysts, and data engineers can use perform data manipulation and analysis tasks on large datasets and time series data using the power of NVIDIA GPUs allowing for faster data processing and analysis.
Getting started with cuDF is straightforward, especially if you have experience using Python and libraries like Pandas. While both cuDF and Pandas offer similar APIs for data manipulation, there are specific types of problems in which cuDF can provide significant performance improvements over Pandas, including large scale datasets, data preprocessing and engineering, real-time analytics, and, of course, parallel processing. The bigger the dataset, the greater the performance benefits.
For more on using cuDF for data science, check out our latest cheat sheet.
This cheat sheet covers the following aspects of RAPIDS cuDF:
- Reading data
- Writing data
- Selecting data
- Handling missing data
- Applying functions
- Processing data
- and more
Check out the RAPIDS cuDF Cheat Sheet now, and check back soon for more.