PythonDataScienceHandbook README

The project's README from github.com/jakevdp/PythonDataScienceHandbook. As one markdown file: README.md.

Python Data Science Handbook

Binder Colab

This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.

cover image

How to Use this Book

About

The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.

The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages. Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, A Whirlwind Tour of Python: it's a fast-paced introduction to the Python language aimed at researchers and scientists.

See Index.ipynb for an index of the notebooks available to accompany the text.

Software

The code in the book was tested with Python 3.5, though most (but not all) will also work correctly with Python 2.7 and other older Python versions.

The packages I used to run the code in the book are listed in requirements.txt (Note that some of these exact version numbers may not be available on your platform: you may have to tweak them for your own use). To install the requirements using conda, run the following at the command-line:

$ conda install --file requirements.txt

To create a stand-alone environment named PDSH with Python 3.5 and all the required package versions, run the following:

$ conda create -n PDSH python=3.5 --file requirements.txt

You can read more about using conda environments in the Managing Environments section of the conda documentation.

License

Code

The code in this repository, including all code samples in the notebooks listed above, is released under the MIT license. Read more at the Open Source Initiative.

Text

The text content of the book is released under the CC-BY-NC-ND license. Read more at Creative Commons.

PythonDataScienceHandbook (jakevdp/PythonDataScienceHandbook)

Searching Database…

50.2K ·GitHub
PythonDataScienceHandbook
这是什么？这是《Python Data Science Handbook》的全文，以一组免费的 Jupyter 笔记本形式提供，涵盖 Python 数据科学的核心技术栈。
这是编程库还是书？这是一本书：这些笔记本就是书的各章，把讲解和可运行的代码混在一起，而不是可以安装的软件包。
我该如何阅读或运行这本书？你可以在线完整阅读，直接打开仓库 notebooks 文件夹中的笔记本，也可以立即在 Google Colab 或 Binder 中启动，或者购买 O'Reilly 出版的印刷版。
要自己运行代码，需要先安装什么？你需要 Python（代码以 3.5 编写，大体兼容 2.7），以及 IPython、NumPy、Pandas、Matplotlib 和 Scikit-Learn；requirements.txt 文件列出了确切版本，README 中说明了如何设置 conda 环境。
这些代码在任何 Python 版本上都一定能运行吗？代码在 Python 3.5 上测试过。虽然大部分代码也能在 Python 2.7 和其他版本上运行，但作者提醒，并不能保证全部代码都可以。
我需要先会 Python 吗？需要，默认你已具备基本的 Python 知识；作者建议初学者先阅读他的配套项目《A Whirlwind Tour of Python》。
这本书是怎么组织的？Index.ipynb 列出了所有章节，内容围绕核心库展开：IPython、NumPy、Pandas、Matplotlib 和 Scikit-Learn。
不安装任何东西能试用吗？可以。你可以直接在 Google Colab 中打开任意笔记本，也可以通过仓库中的链接立即启动一个在线 Binder 笔记本服务器，无需任何本地设置。
有付费版本吗？有。同样的内容也以印刷书的形式由 O'Reilly Media 出版销售。
What are similar projects?pydata-book, 100-Days-Of-ML-Code, mlcourse.ai, abu, Virgilio, data-science-ipython-notebooks, Ai-Learn, 100-Days-Of-ML-Code
Which topics is it in?ipython, matplotlib, colab, textbook, scikit-learn, mit-license, pandas, jupyter-notebook, numpy, data-analysis, jupyter notebook, data-science
Creator
jakevdp
Size
42.6 MB
Stars
50.2K
Updated
CommitMay 05
Age
10y
Commits · 90 Days