Torrent details for "Janssens J. Python Polars. The Definitive Guide...2025" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
None
Total Size:
8.4 MB
Info Hash:
1B910FB574FEB4EB543F8F65DD4D4EECBFF74125
Added By:
Added:
April 21, 2026, 1:58 p.m.
Stats:
|
(Last updated: April 21, 2026, 2:03 p.m.)
| File | Size |
|---|---|
| Janssens J. Python Polars. The Definitive Guide...2025.pdf | 8.4 MB |
Name
DL
Uploader
Size
S/L
Added
-
135.1 MB
[1
/
0]
2023-07-01
| Uploaded by indexFroggy | Size 135.1 MB | Health [ 1 /0 ] | Added 2023-07-01 |
-
376.7 MB
[50
/
38]
2025-06-14
| Uploaded by TheExecutive | Size 376.7 MB | Health [ 50 /38 ] | Added 2025-06-14 |
-
503.1 MB
[1
/
1]
2024-05-04
| Uploaded by nomdeguerre | Size 503.1 MB | Health [ 1 /1 ] | Added 2024-05-04 |
NOTE
SOURCE: Janssens J. Python Polars. The Definitive Guide...2025
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
Textbook in PDF format Want to speed up your data analysis and work with larger-than-memory datasets? Python Polars offers a blazingly fast, multithreaded, and elegant API for data loading, manipulation, and processing. With this hands-on guide, you'll walk through every aspect of Polars and learn how to tackle practical use cases using real-world datasets. Jeroen Janssens and Thijs Nieuwdorp from Xomnia in Amsterdam show you how this superfast DataFrame library is perfect for efficient data wrangling, ETL pipelines, and so much more. This book helps you quickly learn the syntax and understand Polars' underlying concepts. You don't need to have experience with pandas or Spark, but if you do, this book will help you make a smooth transition. With this definitive guide at your side, you'll be able to: Process larger-than-memory datasets at record speed Apply the eager, lazy, and streaming APIs of Polars and decide when to use them Transition smoothly from pandas or Spark to Polars Integrate Polars into your existing code base Work with Arrow and Parquet to efficiently read and write data Translate complex ETL tasks into efficient and elegant queries
×