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27 changes: 7 additions & 20 deletions README.md
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[![Analytics](https://ga-beacon.appspot.com/UA-80121379-2/notes-python)](https://github.com/lijin-thu/notes-python)

# 中文 Python 笔记
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`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。

基于本笔记的实体书:《自学Python——编程基础、科学计算及数据分析》已经出版,京东自营链接:
基于本笔记的实体书:《自学Python——编程基础、科学计算及数据分析》已经出版

京东自营链接:
https://item.jd.com/12328920.html

天猫:

https://detail.tmall.com/item.htm?id=566648749647

![](book.jpg)
天猫、亚马逊、当当均有销售。

---

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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。
笔记内容使用 `jupyter notebook` 来展示。

安装好 `Python` 和相应的包之后,可以在命令行下输入:

```
$ ipython notebook
$ jupyter notebook
```
来进入 `ipython notebook`
来进入 `jupyter notebook`

----

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- [12. **Pandas**](12-pandas)
- [12.01 十分钟上手 Pandas](12-pandas/12.01-ten-minutes-to-pandas.ipynb)
- [12.02 一维数据结构:Series](12-pandas/12.02-series-in-pandas.ipynb)
- [12.03 二维数据结构:DataFrame](12-pandas/12.03-dataframe-in-pandas.ipynb)

觉得有用打赏一下?

![](payment.jpeg)


打个广告:

- 基于本笔记第一二节录制的视频:[Python小白入门课视频教学](http://www.softlinkonline.cn/zhibo.html?id=43)
- [12.03 二维数据结构:DataFrame](12-pandas/12.03-dataframe-in-pandas.ipynb)
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"cell_type": "markdown",
"metadata": {},
"source": [
"[![Analytics](https://ga-beacon.appspot.com/UA-80121379-2/notes-python)](https://github.com/lijin-thu/notes-python)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 中文 Python 笔记"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[![Analytics](https://ga-beacon.appspot.com/UA-80121379-2/notes-python)](https://github.com/lijin-thu/notes-python)\n",
"\n",
"# 中文 Python 笔记\n",
"\n",
"> 版本:0.0.1<br>\n",
"> 作者:李金<br>\n",
"> 邮件:[email protected]<br>\n",
Expand All @@ -28,20 +18,13 @@
"\n",
"`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。\n",
"\n",
"基于本笔记的实体书:《自学Python——编程基础、科学计算及数据分析》已经出版,京东自营链接:\n",
"基于本笔记的实体书:《自学Python——编程基础、科学计算及数据分析》已经出版\n",
"\n",
"京东自营链接:\n",
"https://item.jd.com/12328920.html\n",
"天猫:\n",
"\n",
"https://detail.tmall.com/item.htm?id=566648749647\n",
"天猫、亚马逊、当当均有销售。\n",
"\n",
"![](book.jpg)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"\n",
"## 简介\n",
Expand All @@ -54,20 +37,15 @@
"\n",
"推荐使用 [Anaconda](http://www.continuum.io/downloads),这个IDE集成了大部分常用的包。\n",
"\n",
"笔记内容使用 `ipython notebook` 来展示。\n",
"笔记内容使用 `jupyter notebook` 来展示。\n",
"\n",
"安装好 `Python` 和相应的包之后,可以在命令行下输入:\n",
"\n",
"```\n",
"$ ipython notebook\n",
"$ jupyter notebook\n",
"```\n",
"来进入 `ipython notebook`。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"来进入 `jupyter notebook`。\n",
"\n",
"----\n",
"\n",
"## 基本环境配置\n",
Expand All @@ -78,13 +56,8 @@
"``` \n",
"conda update conda\n",
"conda update anaconda\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```\n",
"\n",
"---\n",
"\n",
"## 参考\n",
Expand All @@ -95,31 +68,16 @@
"- [Deep Learning Tutorials](http://deeplearning.net/tutorial/)\n",
"- [High Performance Scientific Computing](http://faculty.washington.edu/rjl/uwhpsc-coursera/index.html)\n",
"- [Scipy Lectures](http://www.scipy-lectures.org/)\n",
"- [Pandas.org](http://pandas.pydata.org/pandas-docs/stable/index.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- [Pandas.org](http://pandas.pydata.org/pandas-docs/stable/index.html)\n",
"\n",
"----\n",
"\n",
"## 目录"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 目录\n",
"\n",
"可以在 Notebook 中打开 `generate static files.ipynb`,或者命令行中运行代码 `generate_static_files.py` 来生成静态的 HTML 文件。\n",
"\n",
"---"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"\n",
"- [01. **Python 工具**](01-python-tools)\n",
"\t - [01.01 Python 简介](01-python-tools/01.01-python-overview.ipynb)\n",
"\t - [01.02 Ipython 解释器](01-python-tools/01.02-ipython-interpreter.ipynb)\n",
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"\t - [12.02 一维数据结构:Series](12-pandas/12.02-series-in-pandas.ipynb)\n",
"\t - [12.03 二维数据结构:DataFrame](12-pandas/12.03-dataframe-in-pandas.ipynb)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"觉得有用打赏一下?\n",
"\n",
"![](payment.jpeg)\n",
"\n",
"打个广告:\n",
"\n",
"- 基于本笔记第一二节录制的视频:[Python小白入门课视频教学](http://www.softlinkonline.cn/zhibo.html?id=43)"
]
}
],
"metadata": {
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.14"
"version": "2.7.15"
}
},
"nbformat": 4,
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