Search results for: pandas

Great Expectations For Your Data Pipelines with Abe Gong and James Campbell - Episode 161

Testing is a critical activity in all software projects, but one that is often neglected in data pipelines. The complexities introduced by the inherent statefulness of the problem domain and the interdependencies between systems contribute to make pipeline testing difficult to manage. To make this endeavor more manageable Abe Gong and James Campbell have created Great Expectations. In this episode they discuss how you can use the project to create tests in the exploratory phase of building a pipeline and leverage those to monitor your systems in production. They also discussed how Great Expectations works, the difficulties associated with pipeline testing and managing associated technical debt, and their future plans for the project.

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Jake Vanderplas: Data Science For Academic Research - Episode 140

Jake Vanderplas is an astronomer by training and a prolific contributor to the Python data science ecosystem. His current role is using Python to teach principles of data analysis and data visualization to students and researchers at the University of Washington. In this episode he discusses how he got started with Python, the challenges of teaching best practices for software engineering and reproducible analysis, and how easy to use tools for data visualization can help democratize access to, and understanding of, data.

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Surprise! Recommendation Algorithms with Nicolas Hug - Episode 135

A relevant and timely recommendation can be a pleasant surprise that will delight your users. Unfortunately it can be difficult to build a system that will produce useful suggestions, which is why this week’s guest, Nicolas Hug, built a library to help with developing and testing collaborative recommendation algorithms. He explains how he took the code he wrote for his PhD thesis and cleaned it up to release as an open source library and his plans for future development on it.

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PyTables with Francesc Alted - Episode 97

HDF5 is a file format that supports fast and space efficient analysis of large datasets. PyTables is a project that wraps and expands on the capabilities of HDF5 to make it easy to integrate with the larger Python data ecosystem. Francesc Alted explains how the project got started, how it works, and how it can be used for creating sharable and archivable data sets.

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Python for GIS with Sean Gillies - Episode 80

Location is an increasingly relevant aspect of software systems as we have more internet connected devices with GPS capabilities. GIS (Geographic Information Systems) are used for processing and analyzing this data, and fortunately Python has a suite of libraries to facilitate these endeavors. This week Sean Gillies, an author and contributor of many of these tools, shares the story of his career and contributions, and the work that he is doing at MapBox.

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Test Engineering with Cris Medina - Episode 68

We all know that testing is an important part of software and systems development. The problem is that as our systems and applications grow, the amount of testing necessary increases at an exponential rate. Cris Medina joins us this week to talk about some of the problems and approaches associated with testing these complex systems and some of the ways that Python can help.

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Eric Schles on Fighting Human Trafficking with Python - Episode 12

Listen to past episodes, read about the hosts or donate to the show at podcastinit.com Brief Introduction Date of recording – June 10th, 2015 Hosts Tobias Macey and Chris Patti Follow us on iTunes, Stitcher or TuneIn Give us feedback! (iTunes, Twitter, email, Disqus comments) You can donate (if you want)! Overview – Interview with…

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Mark Baggett on Python for InfoSec - Episode 8

Read all of our show notes and find more information about us at Beautiful Soup Brief Introduction Date of recording – May 28th, 2015 Hosts – Tobias Macey and Chris Patti Overview – Interview with Mark Bagett Follow us on iTunes, Stitcher or TuneIn Give us feedback! (iTunes, Twitter, email, Disqus comments) You can donate…

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