cudf_pandas_stocks_demo

cudf_pandas_stocks_demo

uDF is a Python GPU DataFrame library (built on the Apache Arrow columnar memory format) for loading, joining, aggregating, filtering, and otherwise manipulating tabular data using a DataFrame style API in the style of pandas.

cuDF includes a pandas accelerator mode (cudf.pandas), enabling you to accelerate your pandas workflows without requiring any code change.

This notebook highlights the impact of GPU-acceleration for common operations and analytical questions analyzing a real-world dataset of stock prices.

For a deeper introduction and insight into how things work under the hood, we encourage you to run the 10 Minutes to RAPIDS cuDF’s pandas accelerator mode Colab notebook or visit https://rapids.ai/cudf-pandas/.

The data we’ll be working with is a subset of the USA 514 Stocks Prices NASDAQ NYSE dataset from Kaggle.

We’ll start by downloading the dataset from NVIDIA’s Public Google Cloud Storage bucket to provide faster download speeds to Colab. This should take under 30 seconds.

https://colab.research.google.com/github/rapidsai-community/showcase/blob/main/getting_started_tutorials/cudf_pandas_stocks_demo.ipynb#scrollTo=WmOguzNUcw4F