Data gt Memory: 3 Solutions

NVIDIA Developer • May 6, 2025

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Video Description

Squeezing a large data set from a parquet or CSV file into a pandas DataFrame is no fun when your data is too large for memory. This video presents three solutions to getting your data to fit into a pandas DataFrame. Hint: The 3rd solution is the best if you are on Google Colab, Kaggle, or simply using a GPU. 00:00 - Intro 00:16 - Solution 1 00:48 - Solution 2 1:10 - Solution 3 1:24 - Profiling 2:21 - UVM 2:47 - Outro 📝 Learn more about cuDF UVM: https://developer.nvidia.com/blog/unified-virtual-memory-supercharges-pandas-with-rapids-cudf/ ➡️ Join the NVIDIA Developer Program: https://nvda.ws/3OhiXfl ➡️ Read and subscribe to the NVIDIA Technical Blog: https://nvda.ws/3XHae9F #pandas #datascience #gpu #python #nvidia #cudf

Data gt Memory: 3 Solutions

About

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Video Description

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