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Exploring pandas 2.0 & Targets for Apache Arrow

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Manage episode 373272815 series 2637014
Contenuto fornito da Real Python. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Real Python o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

What are the new ways to describe your data in pandas 2.0? Will the addition of Apache Arrow to the data back end foster the growth of data interoperability? This week on the show, we talk with pandas core developer Marc Garcia about the release of pandas 2.0.

Marc shares his background and work on pandas. We discuss the history of data representation in pandas and the need to move beyond NumPy. We also talk about how Apache Arrow only solves some of the issues.

We dig into the potential of an Apache Arrow back end and how it could offer interoperability between data platforms. We also cover the moderate adoption and backward-compatibility concerns. Marc also shares his thoughts on making pandas more extensible.

Course Spotlight: The pandas DataFrame: Working With Data Efficiently

In this course, you’ll get started with pandas DataFrames, which are powerful and widely used two-dimensional data structures. You’ll learn how to perform basic operations with data, handle missing values, work with time-series data, and visualize data from a pandas DataFrame.

Topics:

  • 00:00:00 – Introduction
  • 00:02:07 – Getting involved with the pandas project
  • 00:03:48 – Continued growth of the platform
  • 00:06:49 – Parallel branch development
  • 00:09:19 – The introduction of Apache Arrow
  • 00:18:53 – Working with NumPy data in pandas
  • 00:30:18 – Arrow data types and strings
  • 00:41:23 – Video Course Spotlight
  • 00:42:37 – Interoperability of Arrow data back end
  • 00:50:36 – Could pandas be more extensible?
  • 01:00:49 – Python DataFrame Summit 2023
  • 01:08:12 – What are you excited about in the world of Python?
  • 01:11:13 – What do you want to learn next?
  • 01:12:12 – How can people follow your work online?
  • 01:13:46 – Thanks and Goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

211 episodi

Artwork
iconCondividi
 
Manage episode 373272815 series 2637014
Contenuto fornito da Real Python. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Real Python o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

What are the new ways to describe your data in pandas 2.0? Will the addition of Apache Arrow to the data back end foster the growth of data interoperability? This week on the show, we talk with pandas core developer Marc Garcia about the release of pandas 2.0.

Marc shares his background and work on pandas. We discuss the history of data representation in pandas and the need to move beyond NumPy. We also talk about how Apache Arrow only solves some of the issues.

We dig into the potential of an Apache Arrow back end and how it could offer interoperability between data platforms. We also cover the moderate adoption and backward-compatibility concerns. Marc also shares his thoughts on making pandas more extensible.

Course Spotlight: The pandas DataFrame: Working With Data Efficiently

In this course, you’ll get started with pandas DataFrames, which are powerful and widely used two-dimensional data structures. You’ll learn how to perform basic operations with data, handle missing values, work with time-series data, and visualize data from a pandas DataFrame.

Topics:

  • 00:00:00 – Introduction
  • 00:02:07 – Getting involved with the pandas project
  • 00:03:48 – Continued growth of the platform
  • 00:06:49 – Parallel branch development
  • 00:09:19 – The introduction of Apache Arrow
  • 00:18:53 – Working with NumPy data in pandas
  • 00:30:18 – Arrow data types and strings
  • 00:41:23 – Video Course Spotlight
  • 00:42:37 – Interoperability of Arrow data back end
  • 00:50:36 – Could pandas be more extensible?
  • 01:00:49 – Python DataFrame Summit 2023
  • 01:08:12 – What are you excited about in the world of Python?
  • 01:11:13 – What do you want to learn next?
  • 01:12:12 – How can people follow your work online?
  • 01:13:46 – Thanks and Goodbye

Show Links:

Level up your Python skills with our expert-led courses:

Support the podcast & join our community of Pythonistas

  continue reading

211 episodi

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