PyCon LT 2022

Juan Luis Cano Rodríguez

Juan Luis (he/him/él) is an Aerospace Engineer with a passion for STEM, programming, outreach, and sustainability. He works as Data Scientist Advocate at Orchest, where he empowers data scientists by building an open-source, scalable, easy-to-use workflow orchestrator. He has worked as Developer Advocate at Read the Docs, previously as software engineer in the space, consulting, and banking industries, and as a Python trainer for several private and public entities.

Apart from being a long-time user and contributor to many projects in the scientific Python stack (NumPy, SciPy, Astropy) he has published several open-source packages, the most important one being poliastro, an open-source Python library for Orbital Mechanics used in academia and industry.

Finally, Juan Luis is the founder and former chair of the Python España association, the point of contact for the Spanish Python community, former organizer of PyCon Spain, which attracted more than 800 attendees in its last in-person edition in 2019, and current organizer of the PyData Madrid monthly meetups.


Twitter handle. For example (@handle-name)

@juanluisback

Notable open source projects that you contribute to. Add URLs, one per line.

https://github.com/orchest/orchest
https://github.com/poliastro/poliastro
https://github.com/scipy/scipy
https://github.com/readthedocs/readthedocs.org


Session

05-26
13:30
30min
Beyond pandas: The great Python dataframe showdown
Juan Luis Cano Rodríguez

The pandas library is one of the key factors that enabled the growth of Python in the Data Science industry and continues to help data scientists thrive almost 15 years after its creation. Because of this success, nowadays there are several open-source projects that claim to improve pandas in various ways.

In this talk we will go over some of the most widely used dataframe Python libraries beyond pandas, clarify the relationship between them, compare them in terms of project scope and proximity to the original pandas API, and offer advice on when to use each of them.

PyData
PyData Room