11-07, 11:40–12:20 (US/Eastern), Winter Garden
The process of data science is inherently iterative, requiring constant inspection and visualization of data. Positron is a new, next generation integrated development environment (IDE) built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. This talk will discuss the motivation behind creating Positron and demonstrate the features that support these iterative data science workflows.
Positron is a next generation IDE that was made public earlier this year. This IDE boosts data science productivity with a range of features for data-focused tasks, such as a dedicated console, variables pane, data explorer, and help pane. This talk will lay out the steps of an end-to-end data science workflow, emphasizing how Positron supports each step. In addition to showcasing these features, this talk will discuss design decisions and considerations that guided how Positron was built.
While particularly relevant for data practitioners, this talk is applicable to all Python developers. By the end, you will understand why Positron was built, what will feel familiar or new coming from other IDEs, and whether it might be a good fit for your own work.
No previous knowledge expected
Isabel is a software engineer at Posit, PBC, where she builds Python-based open source data science tools. She is a current member of the triage team and an Emeritus Editor in Chief at pyOpenSci, an organization that supports scientific Python tools by offering peer reviews of packages. When not thinking about computers, she enjoy reading and training dogs.