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www.peterbaumgartner.com | ||
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xcorr.net
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| | | | | As a scientist, interacting with data allows you to gain new insight into the phenomena you're studying. If you read the New York Times, the D3 docs or you browse distill, you'll see impressive browser-based visualizations - interactive storytelling that not only accurately represent data but bring your attention to surprising aspects of it. Making... | |
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accessibleai.dev
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| | | | | Let's see how Anaconda helps you get a standardized Python data science environment up and running on your machine in minutes. | |
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tomaugspurger.net
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| | | | | Today I released stitch into the wild. If you haven't yet, check out the examples page to see an example of what stitch does, and the Github repo for how to install. I'm using this post to explain why I wrote stitch, and some issues it tries to solve. Why knitr / knitpy / stitch / RMarkdown? Each of these tools or formats have the same high-level goal: produce reproducible, dynamic (to changes in the data) reports. They take some source document (typically markdown) that's a mixture of text and code and convert it to a destination output (HTML, PDF, docx, etc.). | |
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pythonspeed.com
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| | | How to activate a Python virtualenv in a Dockerfile without repeating yourself-plus, you'll learn what activating a virtualenv actually does. | ||
