Today we will explore Polars - the fastest data science library in Python!! 🐻❄️🐻❄️🐻❄️
The best part is, as of earlier this month, it even got faster with a brand new release of a GPU engine! 🤩
We will learn about Queries, Lazy Frames, Engines, and use them in real life settings, analyzing and visualizing a free dataset with over 260 million rows (and 22GB in size!!! way bigger than what programs like Excel or Sheets can process).
So not only will we learn how to load, compress and process so much data all at once, but we will also plot it with millions of data nodes on the same graph!! 😱
If you think it might be challenging for Polars - prepare to be surprised!!! because that's exactly where it shines, especially when the new GPU engine is involved!
⭐ More about Polars GPU on GitHub: https://nvda.ws/gpu-polars-xr
⭐ Official GPU Polars Colab Notebook: https://nvda.ws/gpu-polars-xt
💻Tutorial GitHub Repository 💻
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https://github.com/MariyaSha/GPU_Polars.git
🎥 Video Commands and Links 🎥
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⭐ Install Polars GPU:
!pip install polars[gpu] --extra-index-url=https://pypi.nvidia.com
⭐ Mount Google Drive
from google.colab import drive
drive.mount('/content/drive')
⭐ Download Compressed Parquet Dataset (4GB):
For Google Colab:
!wget https://storage.googleapis.com/rapidsai/polars-demo/transactions-t4-20.parquet -O transactions.parquet
For PC:
!wget https://storage.googleapis.com/rapidsai/polars-demo/transactions.parquet -O transactions.parquet
📺 Related Videos 📺
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⭐ Anaconda for beginners:
https://youtu.be/MUZtVEDKXsk
⭐ Basic Guide to Pandas:
https://youtu.be/zN2Hua6oII0
⏰ TIMESTAMPS ⏰
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00:00 - intro
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⭐ QUICKSTART
00:48 - Polars in Google Colab
01:01 - Lazy Frame
02:36 - Querying
03:29 - GPU Engine
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⭐ WORKFLOW
04:51 - Simulated Transactions Dataset
05:25 - Install Polars and GPU Engine locally
06:33 - Read CSV File with Polars
07:07 - Compress CSV to Parquet
07:54 - Read Parquet File with Polars
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⭐ QUERYING
08:38 - Select Statement
09:09 - Filter Statement
10:05 - Column Data Types
10:37 - Multiple Filters
11:15 - Group By Statement
12:32 - GPU Versus CPU
13:06 - Multiple Aggregations
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⭐ DATA VISUALIZATION
15:40 - Bar Chart
16:15 - Scatter Plot
16:58 - Chart Width
17:17 - Chart Z Axis with Colors
17:38 - Mark Styling
18:09 - Chart Title
18:29 - Tooltip Customization
19:10 - Solve Max Rows Error
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20:33 - Thanks for Watching
🤝 Connect with me 🤝
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🔗 Github:
https://github.com/mariyasha
🔗 X:
https://x.com/MariyaSha888
🔗 LinkedIn:
https://ca.linkedin.com/in/mariyasha888
🔗 Blog:
https://www.pythonsimplified.org
🔗 Discord:
https://discord.com/invite/wgTTmsWmXA
💳 Credits 💳
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⭐ Beautiful titles, transitions, sound FX:
mixkit.co
⭐ Thumbnail:
flaticon.com
freepik.com
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