Data visualization tools are required to translate the findings of data scientists into charts, graphs, and pictures. Understanding how to utilize these tools and display data is necessary for a data scientist to communicate with people in other domains. In this episode, Srini Kadamati hosts a discussion with Jake VanderPlas about the Python ecosystem for data science and the different attempts at creating a data visualization library.

Jake VanderPlas is the Director of Research for Physical Sciences at the University of Washington’s eScience institute, where he also received his PhD in Astronomy. In addition to contributing to many Python data science libraries like scikit-learn, scipy, numpy, and matplotlib, he’s written multiple books that have been published by O’Reilly and has given many talks on data science tools and techniques. He’s also the co-creator of the Altair project, which is a declarative data visualization library for Python built on the Vega-Lite visualization grammar.

Sponsors

Dice.com helps you manage your career in tech.  Dice.com has a huge index of tech job opportunities that it has developed from 20 years in the business of connecting tech professionals with job opportunities. To check out Dice and support Software Engineering Daily, go to dice.com/sedaily.

Saagie is an end-to-end data platform that lets you focus on deriving business value from data. Saagie helps you take control of your wide variety of data sources, and gets them in one place. Check it out at Saagie.com

SnapCI is a continuous integration tool built by Thoughtworks. Go to snap.ci/softwareengineeringdaily to check it out.