
命令行中的数据科学
Data Science at the Command Line
Jeroen Janssens · 初版 2014 年
8人推荐
15位读者提及
24次提及
为什么值得读
- 把单行命令转化为可扩展的Shell脚本
- 结合Drake与GNU Parallel构建数据流
- 免费在线阅读且深入讨论清洗与可视化思路
Data Science at the Command Line 展示了 command line 的灵活性如何帮助你成为更高效、多产的 data scientist。你将学会如何组合微小但功能强大的 command-line 工具,以快速获取、清洗、探索和建模你的数据。
Hacker News 上怎么说
正在加载完整评论……
我之前看过这篇文章,现在依然觉得很有参考价值,尤其是对临时的一次性任务(one-offs)。另一个类似且很有价值的资源是 Jeronen Janssens 写的《命令行中的数据科学》(Data Science at the Command Line,https://datascienceatthecommandline.com/)。可以通过链接免费阅读。
I've seen this article before and still consider it valid, especially for one-offs. Another similar and valuable resource is "https://datascienceatthecommandline.com/" Data Science at the Command Line, by Jeronen Janssens. Free to read at the link.
另见 Jeroen Janssens 的《命令行中的数据科学》(Data Science at the Command Line):https://datascienceatthecommandline.com/2e/
See also Jeroen Janssens' Data Science at the Command Line: https://datascienceatthecommandline.com/2e/
……更具可维护性/可支持性的解决方案。比如 drake(https://github.com/Factual/drake),一个用于数据的“Make”,它自带依赖项检查,可以让 pipeline 能够合情合理地断点重启。O'Reilly 的《命令行中的数据科学》(Data Science at the Command Line)一书(评论区别处有链接)在这个话题上讲得很透彻:如何把单行命令变成可扩展的 shell 脚本、如何使用 drake、如何使用 Gnu Parallel。
…maintainable / supportable solution. For instance drake (https://github.com/Factual/drake) a 'Make for data' which does dependency checking would allow for sensible restarts of the pipeline. The O'Reilly Data Science at the Command Line book (linked elsewhere in the comments) has a good deal to say on the subject: turning one liners into extensible shell scripts, using drake, using Gnu Parallel.
我从《命令行中的数据科学》(Data Science at the Command Line)这本书中学到了很多,现在已经免费在线开放阅读了:https://www.datascienceatthecommandline.com/
I learnt a lot from the book Data Science at the Command Line, now free and online at https://www.datascienceatthecommandline.com/
……数据科学和分析 pipeline。我学东西很快,也喜欢学习使用新工具,去理解它们的设计哲学以及它们擅长什么(或者不擅长什么!)。在工作中我通常遵循《命令行中的数据科学》(Data Science at the Command Line)那一套思路,而且我喜欢从底层构建 Web 系统来分享我的工作成果(偏好 d3.js,而不是 Observable、Tableau 这种全家桶系统)。
…the data science and analysis pipeline. I'm quick to learn, and I love learning how to use new tools, understanding their philosophy and what they're good for (or not good for!) I generally follow the "Data Science at the Command Line" approach to my work, and I like to build web systems for sharing my work from the lower level (d3.js over full-fat systems like observable, tableau, etc).
O'Reilly 有本类似的书叫《命令行中的数据科学》(Data Science at the Command Line),我也很推荐:https://datascienceatthecommandline.com/ Buffalo 那本书很棒,我在生物信息学职业生涯中一般都会推荐它,不过它确实深入到了一些特定的细分领域(尤其是……
There's a similar O'Reilly book, Data Science at the Command Line, which I can also recommend: https://datascienceatthecommandline.com/ Buffalo's book is great and I generally recommend it in my bioinformatics career, but it does go into some speciifc niches (especially…