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# Python 数据分析中文笔记
> 版本0.0.1
>
> 作者:李金
>
> 邮件:[[email protected]](/cdn-cgi/l/email-protection)
>
> 微信lijinwithyou
`Github` 加载 `.ipynb` 的速度较慢,建议在 [Nbviewer](http://nbviewer.ipython.org/github/lijin-THU/notes-python/blob/master/index.ipynb) 中查看该项目。
* * *
## 简介
大部分内容来自网络。
默认安装了 `Python 2.7`,以及相关的第三方包 `ipython` `numpy` `scipy``pandas`
> life is short. use python.
推荐使用 [Anaconda](http://www.continuum.io/downloads)这个IDE集成了大部分常用的包。
笔记内容使用 `ipython notebook` 来展示。
安装好 `Python` 和相应的包之后,可以在命令行下输入:
```py
$ ipython notebook
```
来进入 `ipython notebook`
* * *
## 基本环境配置
* 安装 [Anaconda](http://www.continuum.io/downloads) 或者 [Miniconda](http://conda.pydata.org/miniconda.html)
* 更新环境
```py
conda update conda
conda update anaconda
```
* * *
## 参考
* [Enthought Training on Demand](https://training.enthought.com/)
* [Computational Statistics in Python](http://people.duke.edu/~ccc14/sta-663/index.html#rd)
* [Scipy.org](http://scipy.org/)
* [Deep Learning Tutorials](http://deeplearning.net/tutorial/)
* [High Performance Scientific Computing](http://faculty.washington.edu/rjl/uwhpsc-coursera/index.html)
* [Scipy Lectures](http://www.scipy-lectures.org/)
* [Pandas.org](http://pandas.pydata.org/pandas-docs/stable/index.html)