|
4 | 4 | "cell_type": "markdown", |
5 | 5 | "metadata": {}, |
6 | 6 | "source": [ |
7 | | - "[](https://github.com/lijin-thu/notes-python)" |
8 | | - ] |
9 | | - }, |
10 | | - { |
11 | | - "cell_type": "markdown", |
12 | | - "metadata": {}, |
13 | | - "source": [ |
14 | | - "# 中文 Python 笔记" |
15 | | - ] |
16 | | - }, |
17 | | - { |
18 | | - "cell_type": "markdown", |
19 | | - "metadata": {}, |
20 | | - "source": [ |
| 7 | + "[](https://github.com/lijin-thu/notes-python)\n", |
| 8 | + "\n", |
| 9 | + "# 中文 Python 笔记\n", |
| 10 | + "\n", |
21 | 11 | "> 版本:0.0.1<br>\n", |
22 | 12 | "> 作者:李金<br>\n", |
23 | 13 | |
|
28 | 18 | "\n", |
29 | 19 | "`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", |
30 | 20 | "\n", |
31 | | - "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", |
| 21 | + "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", |
32 | 22 | "\n", |
| 23 | + "京东自营链接:\n", |
33 | 24 | "https://item.jd.com/12328920.html\n", |
34 | | - "天猫:\n", |
35 | 25 | "\n", |
36 | | - "https://detail.tmall.com/item.htm?id=566648749647\n", |
| 26 | + "天猫、亚马逊、当当均有销售。\n", |
37 | 27 | "\n", |
38 | | - "" |
39 | | - ] |
40 | | - }, |
41 | | - { |
42 | | - "cell_type": "markdown", |
43 | | - "metadata": {}, |
44 | | - "source": [ |
45 | 28 | "---\n", |
46 | 29 | "\n", |
47 | 30 | "## 简介\n", |
|
54 | 37 | "\n", |
55 | 38 | "推荐使用 [Anaconda](http://www.continuum.io/downloads),这个IDE集成了大部分常用的包。\n", |
56 | 39 | "\n", |
57 | | - "笔记内容使用 `ipython notebook` 来展示。\n", |
| 40 | + "笔记内容使用 `jupyter notebook` 来展示。\n", |
58 | 41 | "\n", |
59 | 42 | "安装好 `Python` 和相应的包之后,可以在命令行下输入:\n", |
60 | 43 | "\n", |
61 | 44 | "```\n", |
62 | | - "$ ipython notebook\n", |
| 45 | + "$ jupyter notebook\n", |
63 | 46 | "```\n", |
64 | | - "来进入 `ipython notebook`。" |
65 | | - ] |
66 | | - }, |
67 | | - { |
68 | | - "cell_type": "markdown", |
69 | | - "metadata": {}, |
70 | | - "source": [ |
| 47 | + "来进入 `jupyter notebook`。\n", |
| 48 | + "\n", |
71 | 49 | "----\n", |
72 | 50 | "\n", |
73 | 51 | "## 基本环境配置\n", |
|
78 | 56 | "``` \n", |
79 | 57 | "conda update conda\n", |
80 | 58 | "conda update anaconda\n", |
81 | | - "```" |
82 | | - ] |
83 | | - }, |
84 | | - { |
85 | | - "cell_type": "markdown", |
86 | | - "metadata": {}, |
87 | | - "source": [ |
| 59 | + "```\n", |
| 60 | + "\n", |
88 | 61 | "---\n", |
89 | 62 | "\n", |
90 | 63 | "## 参考\n", |
|
95 | 68 | "- [Deep Learning Tutorials](http://deeplearning.net/tutorial/)\n", |
96 | 69 | "- [High Performance Scientific Computing](http://faculty.washington.edu/rjl/uwhpsc-coursera/index.html)\n", |
97 | 70 | "- [Scipy Lectures](http://www.scipy-lectures.org/)\n", |
98 | | - "- [Pandas.org](http://pandas.pydata.org/pandas-docs/stable/index.html)" |
99 | | - ] |
100 | | - }, |
101 | | - { |
102 | | - "cell_type": "markdown", |
103 | | - "metadata": {}, |
104 | | - "source": [ |
| 71 | + "- [Pandas.org](http://pandas.pydata.org/pandas-docs/stable/index.html)\n", |
| 72 | + "\n", |
105 | 73 | "----\n", |
106 | 74 | "\n", |
107 | | - "## 目录" |
108 | | - ] |
109 | | - }, |
110 | | - { |
111 | | - "cell_type": "markdown", |
112 | | - "metadata": {}, |
113 | | - "source": [ |
| 75 | + "## 目录\n", |
| 76 | + "\n", |
114 | 77 | "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", |
115 | 78 | "\n", |
116 | | - "---" |
117 | | - ] |
118 | | - }, |
119 | | - { |
120 | | - "cell_type": "markdown", |
121 | | - "metadata": {}, |
122 | | - "source": [ |
| 79 | + "---\n", |
| 80 | + "\n", |
123 | 81 | "- [01. **Python 工具**](01-python-tools)\n", |
124 | 82 | "\t - [01.01 Python 简介](01-python-tools/01.01-python-overview.ipynb)\n", |
125 | 83 | "\t - [01.02 Ipython 解释器](01-python-tools/01.02-ipython-interpreter.ipynb)\n", |
|
274 | 232 | "\t - [12.02 一维数据结构:Series](12-pandas/12.02-series-in-pandas.ipynb)\n", |
275 | 233 | "\t - [12.03 二维数据结构:DataFrame](12-pandas/12.03-dataframe-in-pandas.ipynb)" |
276 | 234 | ] |
277 | | - }, |
278 | | - { |
279 | | - "cell_type": "markdown", |
280 | | - "metadata": {}, |
281 | | - "source": [ |
282 | | - "觉得有用打赏一下?\n", |
283 | | - "\n", |
284 | | - "\n", |
285 | | - "\n", |
286 | | - "打个广告:\n", |
287 | | - "\n", |
288 | | - "- 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)" |
289 | | - ] |
290 | 235 | } |
291 | 236 | ], |
292 | 237 | "metadata": { |
|
305 | 250 | "name": "python", |
306 | 251 | "nbconvert_exporter": "python", |
307 | 252 | "pygments_lexer": "ipython2", |
308 | | - "version": "2.7.14" |
| 253 | + "version": "2.7.15" |
309 | 254 | } |
310 | 255 | }, |
311 | 256 | "nbformat": 4, |
|
0 commit comments