Pandas 2.0 gets a major performance boost with Apache Arrow backend #python #pandas #pyarrow

Pandas 2.0 has adopted Apache Arrow as a backend. Pyarrow gives Pandas better storage and speed. Pandas 2.0 with the Arrow backend is a significant improvement for the library. Apache Arrow is a columnar memory format that is highly optimized for data analytics workloads. By adopting Apache Arrow as a backend for Pandas, the library can benefit from Arrow's performance optimizations and efficient data transfer between different systems. One of the primary benefits of the Arrow backend is improved performance. Arrow's columnar memory format is highly efficient, especially for analytical workloads that involve large datasets. Pandas 2.0 with the Arrow backend can leverage Arrow's memory format to speed up common operations like filtering, aggregation, and joins, resulting in faster and more efficient data analysis. Another advantage of the Arrow backend is its compatibility with other data processing frameworks. Arrow is an open standard that supports multiple programming languages, including Python, R, Java, and C++. This makes it easier to move data between different systems and tools, enabling better interoperability and reducing data processing bottlenecks. Overall, the adoption of Apache Arrow as a backend for Pandas 2.0 is a significant step forward for the library. It improves performance, increases compatibility with other data processing tools, and enables more efficient data analysis workflows. As a result, users can expect faster and more streamlined data analysis with Pandas 2.0 and the Arrow backend.

▶ Sponsor me on GitHub : https://github.com/sponsors/bhattbhavesh91/
▶ Join this channel to get access to perks: https://bit.ly/BhaveshBhattJoin
▶ Join the Telegram channel for regular updates: https://t.me/bhattbhavesh91
▶ If you like my work, you can buy me a coffee : https://bit.ly/BuyBhaveshCoffee

*I use affiliate links on the products that I recommend. These give me a small portion of the sales price at no cost to you. I appreciate the proceeds and they help me to improve my channel!

▶ Best Book for Python : https://amzn.to/3qYThqu
▶ Best Book for PyTorch & Machine Learning : https://amzn.to/3PyUkdy
▶ Best Book for Statistics : https://amzn.to/3vzvHEn
▶ Best Book for BERT: https://amzn.to/3lpX0fz
▶ Best Book for Machine Learning : https://amzn.to/2P6aZuT
▶ Best Book for Deep Learning : https://amzn.to/30UMTGl
▶ Best Intro Book for MLOps : https://amzn.to/3AoPZmM

Equipments I use for recording the videos:
▶ 1st Laptop I use : https://amzn.to/3AqI8Fp
▶ 2nd Laptop I use : https://amzn.to/3KAiYsB
▶ Microphone : https://amzn.to/3qUPxtz
▶ Camera : https://amzn.to/3rKQsM2
▶ Mobile Phone : https://amzn.to/3nRHP1f
▶ Ring Light : https://amzn.to/33LedM5
▶ RGB Light : https://amzn.to/3KzLgmS
▶ Bag I use : https://amzn.to/3AsM3RZ

If you do have any questions with what we covered in this video then feel free to ask in the comment section below & I'll do my best to answer those.

If you enjoy these tutorials & would like to support them then the easiest way is to simply like the video & give it a thumbs up & also it's a huge help to share these videos with anyone who you think would find them useful.

Please consider clicking the SUBSCRIBE button to be notified for future videos & thank you all for watching.

You can find me on:
▶ Blog - https://bhattbhavesh91.github.io
▶ Twitter - https://twitter.com/_bhaveshbhatt
▶ GitHub - https://github.com/bhattbhavesh91
▶ Medium - https://medium.com/@bhattbhavesh91
▶ About.me - https://about.me/bhattbhavesh91
▶ Linktree - https://linktr.ee/bhattbhavesh91
▶ DEV Community - https://dev.to/bhattbhavesh91
▶ Telegram - https://t.me/bhattbhavesh91

Видео Pandas 2.0 gets a major performance boost with Apache Arrow backend #python #pandas #pyarrow канала Bhavesh Bhatt