用开源工具做数据分析

Hacker News 上怎么说

• samuel · 2022 年

  1. 《Data Analysis with Open Source Tools》。这本书教会了我如何分析“小”数据集，对我的职业生涯帮助极大。从技术的角度来看已经非常过时了，但里面的概念依然适用。我觉得很难找到能…

  1. Data Analysis with Open Source Tools This learnt me how to analyze "small" datasets which have helped me incredibly in my career. Technology wise is very out of date, but the concepts are still valid. I think it's hard to get more with…

• joeclark77 · 2016 年

  …它开箱即用的东西包括 iPython（一个更好用的 Python shell）、Spyder（RStudio 的 Python 版）以及 Jupyter Notebook。学习的话，我建议找类似 Janert 的《Data Analysis with Open Source Tools》这样的书，一章一章地照着做，试着用 Python 把各种分析实现一遍。特别是那本书，每一章的教程练习用的技术都不一样，…

  …things it gives you right out of the box are iPython (a better Python shell), Spyder (the Python version of RStudio), and Jupyter Notebooks. For learning, I'd recommend taking something like Janert's "Data Analysis with Open Source Tools" and go through chapter-by-chapter trying to figure out how to implement the various analyses in Python. That book in particular uses a different technology every chapter for its tutorial exercises,…

• anigbrowl · 2021 年

  …仓库。正因为太普遍了，你真应该学点基础统计学，这样才能更好地结合上下文理解数据，即便你最后决定用外部工具或库来做统计也一样。我觉得 Philipp Janert 写的《Data Analysis with Open Source Tools》（O'Reilly 出版）是个很棒的资源：它不绑定特定语言，立足于实际应用，并且假定你希望用统计学（以及其他数学分析工具）来解决问题…

  …repository. Because it's so common, you should learn some basic statistics in order to be able to better read things in context, even if you decide to use external tools or libraries to do statistics. I found 'Data Analysis with Open Source Tools' by Philipp Janert (O'Reilly) a great resource: it's language-agnostic, grounded in real-world practices, and assumes you want to solve problems using statistics (and other mathematical analysis tools)…

• larrykubin · 2012 年

  …想学一门跟你平时用惯了的语言有点不一样的全新语言，顺便重温一下数学，我强烈推荐去玩一阵子 R。另一本值得一读的书是 O'Reilly 出版的《Data Analysis with Open Source Tools》，里面有关于 R 和 NumPy 的章节。

  …to learn a new language that is a bit different than what you might be used to and want to brush up on some math, I highly recommend playing with R for a while. Another book to checkout is O'Reilly's Data Analysis with Open Source Tools, which has sections on R and NumPy.

• Homunculiheaded · 2012 年

  …受到质疑，但你想跟这帮人交流，这就是共通的语言。《到底什么是 p 值？》——一本非常轻量、不涉及繁重数学的读物，教你如何避免经典统计学中的玄学思维。《Data Analysis with Open Source Tools》——我特别喜欢这本书，因为它完全跳出了“统计学入门 101”的框框，给出了大量极佳的实战建议，并涉及了许多能帮你理解数据的数学工具。它…

  …questioned, but this is the common language you'll want talking to any of these people. "What is a p-value anyway?" -A very quick, non-math heavy read on avoiding magical thinking in classical statistics. "Data Analysis with Open Source Tools" -I really love this book because it steps way out of "stats 101" land and gives a lot of really great real world advice and touches on many mathematical tools that can help you understand data. The…

• jclos · 2012 年

  …《Programming Collective Intelligence》和《Machine Learning for Hackers》，这两本大同小异，只不过前一本用的是 Python，后一本用的是 R（而且难度稍高一点）；或者是《Data Analysis with Open Source Tools》，它更偏向统计学，而且比《Think Stats》更深入。如果你真想深入学习 R，那些 R 相关的书挺有意思的，因为我觉得它们从统计学角度讲得并没有那么细…

  …"Programming Collective Intelligence" and "Machine Learning for Hackers", which are more or less the same thing, except the first one is in Python and the second one in R (and slightly more advanced), or "Data Analysis with open source tools", which is more statistics oriented and more advanced than "Think Stats". The R books are interesting if you want to really get into R because I don't think they go into much details from a stats point…

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