Patrick Hoefler

PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people. pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the tutorial. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html .

PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people. pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the workshop. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html . ❓Any other requirements ❓ 1. Bring your own laptop 2. Have Github account: https://github.com 3. Have git installed: https://git-scm.com/book/en/v2/Getting-Started-Installing-Gitf • Format for the session: First 15 minutes : an introduction - what you can contribute, how to contribute, and how to set up your development environment or use gitpod; The rest : "office hours", during which you'll be mentored through setting up a development environment and making a contribution to pandas. • Preparation (optional) For those who are more keen on using the workshop to work on their contribution to pandas, you may want to start setting up your development environment in advance. This w​​ay, by the time you arrive you are ready to get started on picking issues, and starting to contribute. Please be aware that it could take longer to set up a development on ​​a computer running a Windows operating system compared to MacOS or Unix. We will guide you through the steps, and they are useful to learn for many open source projects. We also offer a development environment on gitpod. It can take some minutes to load, but provides you an instant and fresh development environment for each new task directly from your browser, using VScode. Documentation is in the works and will be provided before the workshop. To get the most out of the session, it's encouraged (but not required) that you have a look at the contributing guide beforehand: https://pandas.pydata.org/pandas-docs/dev/development/contributing.html. Particularly, the development environment instructions: https://pandas.pydata.org/docs/dev/development/contributing_environment.html • Audience level Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. It is useful to have some pandas, git, and python and experience. If you don't have much experience with them, you might expect to spend time "learning by doing".

Other people: Noa Tamir

PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people. pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the tutorial. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html .

PyData Berlin are excited to bring you this open source workshop dedicated to contributing to pandas. This tutorial is 3 hours. We will have a break and continue with the same group of people. pandas is a data wrangling platform for Python widely adopted in the scientific computing community. In this session, you will be guided on how you can make your own contributions to the project, no prior experience contributing required! Not only will this teach you new skills and boost your CV, you'll also likely get a nice adrenaline rush when your contribution is accepted! If you don’t finish your contribution during the event, we hope you will continue to work on it after the workshop. pandas offers regular new contributor meetings and has a slack space to provide ongoing support for new contributors. For more details, see our contributor community page: http://pandas.pydata.org/docs/dev/development/community.html . ❓Any other requirements ❓ 1. Bring your own laptop 2. Have Github account: https://github.com 3. Have git installed: https://git-scm.com/book/en/v2/Getting-Started-Installing-Gitf • Format for the session: First 15 minutes : an introduction - what you can contribute, how to contribute, and how to set up your development environment or use gitpod; The rest : "office hours", during which you'll be mentored through setting up a development environment and making a contribution to pandas. • Preparation (optional) For those who are more keen on using the workshop to work on their contribution to pandas, you may want to start setting up your development environment in advance. This w​​ay, by the time you arrive you are ready to get started on picking issues, and starting to contribute. Please be aware that it could take longer to set up a development on ​​a computer running a Windows operating system compared to MacOS or Unix. We will guide you through the steps, and they are useful to learn for many open source projects. We also offer a development environment on gitpod. It can take some minutes to load, but provides you an instant and fresh development environment for each new task directly from your browser, using VScode. Documentation is in the works and will be provided before the workshop. To get the most out of the session, it's encouraged (but not required) that you have a look at the contributing guide beforehand: https://pandas.pydata.org/pandas-docs/dev/development/contributing.html. Particularly, the development environment instructions: https://pandas.pydata.org/docs/dev/development/contributing_environment.html • Audience level Everyone is welcome to attend this session! If you've never contributed to open source software before, then you will learn how to, and if you have experience contributing, then you can either help mentor other attendees or you can work on more challenging contributions. It is useful to have some pandas, git, and python and experience. If you don't have much experience with them, you might expect to spend time "learning by doing".

Other people: Noa Tamir

Pandas has reached a 2.0 milestone in 2023. But what does that mean? And what is coming after 2.0? This talk will give an overview of what happened in the latest releases of pandas and highlight some topics and major new features the pandas project is working on.

The pandas 2.0 release is targeted for the first quarter of 2023. This is a major milestone for the pandas project, and this talk will start with an overview of this release. Pandas 2.0 includes some new (experimental) features, but mostly means enforcing deprecations that have been accumulated in the 1.x series, along with some necessary breaking changes. But that doesn’t mean there are no interesting features to talk about! The main part of the presentation will showcase some new features, both already released as opt-in features or to come in future releases. Support for non-nanosecond resolution datetimes, allowing time spans ranging over a billion of years. Improved support for nullable data types, including easy opt-in options for I/O functions. Experimental integration with pyarrow to back columns of a DataFrame (beyond the string dtype). A major change that is under way is a change to the copy and view semantics of operations in pandas (related to the well-known (or hated) SettingWithCopyWarning). This is already available as an experimental opt-in to test and use the new behaviour, and will probably be a highlight of pandas 3.0.

Other people: Joris Van den Bossche