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01. python tools
01. python tools
 
 
02. python essentials
02. python essentials
 
 
03. numpy
03. numpy
 
 
04. scipy
04. scipy
 
 
05. advanced python
05. advanced python
 
 
06. matplotlib
06. matplotlib
 
 
07. interfacing with other languages
07. interfacing with other languages
 
 
08. object-oriented programming
08. object-oriented programming
 
 
09. theano
09. theano
 
 
10. something interesting
10. something interesting
 
 
11. useful tools
11. useful tools
 
 
12. pandas
12. pandas
 
 
.gitattibutes
.gitattibutes
 
 
.gitignore
.gitignore
 
 
README.md
README.md
 
 
generate index.ipynb
generate index.ipynb
 
 
generate static files.ipynb
generate static files.ipynb
 
 
generate_static_files.py
generate_static_files.py
 
 
index.ipynb
index.ipynb
 
 
index.md
index.md
 
 

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中文 Python 笔记

版本：0.0.1
作者：李金
邮件：lijinwithyou@gmail.com
微信：lijinwithyou

Github 加载 .ipynb 的速度较慢，建议在 Nbviewer 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，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：

$ ipython notebook

来进入 ipython notebook。

基本环境配置

conda update conda
conda update anaconda

参考

目录

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。

  • [01. Python 工具](01. python tools)
    • [01.01 Python 简介](01. python tools/01.01 python overview.ipynb)
    • [01.02 Ipython 解释器](01. python tools/01.02 ipython interpreter.ipynb)
    • [01.03 Ipython notebook](01. python tools/01.03 ipython notebook.ipynb)
    • [01.04 使用 Anaconda](01. python tools/01.04 use anaconda.ipynb)
  • [02. Python 基础](02. python essentials)
    • [02.01 Python 入门演示](02. python essentials/02.01 a tour of python.ipynb)
    • [02.02 Python 数据类型](02. python essentials/02.02 python data types.ipynb)
    • [02.03 数字](02. python essentials/02.03 numbers.ipynb)
    • [02.04 字符串](02. python essentials/02.04 strings.ipynb)
    • [02.05 索引和分片](02. python essentials/02.05 indexing and slicing.ipynb)
    • [02.06 列表](02. python essentials/02.06 lists.ipynb)
    • [02.07 可变和不可变类型](02. python essentials/02.07 mutable and immutable data types.ipynb)
    • [02.08 元组](02. python essentials/02.08 tuples.ipynb)
    • [02.09 列表与元组的速度比较](02. python essentials/02.09 speed comparison between list & tuple.ipynb)
    • [02.10 字典](02. python essentials/02.10 dictionaries.ipynb)
    • [02.11 集合](02. python essentials/02.11 sets.ipynb)
    • [02.12 不可变集合](02. python essentials/02.12 frozen sets.ipynb)
    • [02.13 Python 赋值机制](02. python essentials/02.13 how python assignment works.ipynb)
    • [02.14 判断语句](02. python essentials/02.14 if statement.ipynb)
    • [02.15 循环](02. python essentials/02.15 loops.ipynb)
    • [02.16 列表推导式](02. python essentials/02.16 list comprehension.ipynb)
    • [02.17 函数](02. python essentials/02.17 functions.ipynb)
    • [02.18 模块和包](02. python essentials/02.18 modules and packages.ipynb)
    • [02.19 异常](02. python essentials/02.19 exceptions.ipynb)
    • [02.20 警告](02. python essentials/02.20 warnings.ipynb)
    • [02.21 文件读写](02. python essentials/02.21 file IO.ipynb)
  • [03. Numpy](03. numpy)
    • [03.01 Numpy 简介](03. numpy/03.01 numpy overview.ipynb)
    • [03.02 Matplotlib 基础](03. numpy/03.02 matplotlib basics.ipynb)
    • [03.03 Numpy 数组及其索引](03. numpy/03.03 numpy arrays.ipynb)
    • [03.04 数组类型](03. numpy/03.04 array types.ipynb)
    • [03.05 数组方法](03. numpy/03.05 array calculation method.ipynb)
    • [03.06 数组排序](03. numpy/03.06 sorting numpy arrays.ipynb)
    • [03.07 数组形状](03. numpy/03.07 array shapes.ipynb)
    • [03.08 对角线](03. numpy/03.08 diagonals.ipynb)
    • [03.09 数组与字符串的转换](03. numpy/03.09 data to & from string.ipynb)
    • [03.10 数组属性方法总结](03. numpy/03.10 array attribute & method overview .ipynb)
    • [03.11 生成数组的函数](03. numpy/03.11 array creation functions.ipynb)
    • [03.12 矩阵](03. numpy/03.12 matrix object.ipynb)
    • [03.13 一般函数](03. numpy/03.13 general functions.ipynb)
    • [03.14 向量化函数](03. numpy/03.14 vectorizing functions.ipynb)
    • [03.15 二元运算](03. numpy/03.15 binary operators.ipynb)
    • [03.16 ufunc 对象](03. numpy/03.16 universal functions.ipynb)
    • [03.17 choose 函数实现条件筛选](03. numpy/03.17 choose.ipynb)
    • [03.18 数组广播机制](03. numpy/03.18 array broadcasting.ipynb)
    • [03.19 数组读写](03. numpy/03.19 reading and writing arrays.ipynb)
    • [03.20 结构化数组](03. numpy/03.20 structured arrays.ipynb)
    • [03.21 记录数组](03. numpy/03.21 record arrays.ipynb)
    • [03.22 内存映射](03. numpy/03.22 memory maps.ipynb)
    • [03.23 从 Matlab 到 Numpy](03. numpy/03.23 from matlab to numpy.ipynb)
  • [04. Scipy](04. scipy)
    • [04.01 SCIentific PYthon 简介](04. scipy/04.01 scienticfic python overview.ipynb)
    • [04.02 插值](04. scipy/04.02 interpolation with scipy.ipynb)
    • [04.03 概率统计方法](04. scipy/04.03 statistics with scipy.ipynb)
    • [04.04 曲线拟合](04. scipy/04.04 curve fitting.ipynb)
    • [04.05 最小化函数](04. scipy/04.05 minimization in python.ipynb)
    • [04.06 积分](04. scipy/04.06 integration in python.ipynb)
    • [04.07 解微分方程](04. scipy/04.07 ODEs.ipynb)
    • [04.08 稀疏矩阵](04. scipy/04.08 sparse matrix.ipynb)
    • [04.09 线性代数](04. scipy/04.09 linear algbra.ipynb)
    • [04.10 稀疏矩阵的线性代数](04. scipy/04.10 sparse linear algebra.ipynb)
  • [05. Python 进阶](05. advanced python)
    • [05.01 sys 模块简介](05. advanced python/05.01 overview of the sys module.ipynb)
    • [05.02 与操作系统进行交互：os 模块](05. advanced python/05.02 interacting with the OS - os.ipynb)
    • [05.03 CSV 文件和 csv 模块](05. advanced python/05.03 comma separated values.ipynb)
    • [05.04 正则表达式和 re 模块](05. advanced python/05.04 regular expression.ipynb)
    • [05.05 datetime 模块](05. advanced python/05.05 datetime.ipynb)
    • [05.06 SQL 数据库](05. advanced python/05.06 sql databases.ipynb)
    • [05.07 对象关系映射](05. advanced python/05.07 object-relational mappers.ipynb)
    • [05.08 函数进阶：参数传递，高阶函数，lambda 匿名函数，global 变量，递归](05. advanced python/05.08 functions.ipynb)
    • [05.09 迭代器](05. advanced python/05.09 iterators.ipynb)
    • [05.10 生成器](05. advanced python/05.10 generators.ipynb)
    • [05.11 with 语句和上下文管理器](05. advanced python/05.11 context managers and the with statement.ipynb)
    • [05.12 修饰符](05. advanced python/05.12 decorators.ipynb)
    • [05.13 修饰符的使用](05. advanced python/05.13 decorator usage.ipynb)
    • [05.14 operator, functools, itertools, toolz, fn, funcy 模块](05. advanced python/05.14 the operator functools itertools toolz fn funcy module.ipynb)
    • [05.15 作用域](05. advanced python/05.15 scope.ipynb)
    • [05.16 动态编译](05. advanced python/05.16 dynamic code execution.ipynb)
  • [06. Matplotlib](06. matplotlib)
    • [06.01 Pyplot 教程](06. matplotlib/06.01 pyplot tutorial.ipynb)
    • [06.02 使用 style 来配置 pyplot 风格](06. matplotlib/06.02 customizing plots with style sheets.ipynb)
    • [06.03 处理文本（基础）](06. matplotlib/06.03 working with text - basic.ipynb)
    • [06.04 处理文本（数学表达式）](06. matplotlib/06.04 working with text - math expression.ipynb)
    • [06.05 图像基础](06. matplotlib/06.05 image tutorial.ipynb)
    • [06.06 注释](06. matplotlib/06.06 annotating axes.ipynb)
    • [06.07 标签](06. matplotlib/06.07 legend.ipynb)
    • [06.08 figures, subplots, axes 和 ticks 对象](06. matplotlib/06.08 figures, subplots, axes and ticks.ipynb)
    • [06.09 不要迷信默认设置](06. matplotlib/06.09 do not trust the defaults.ipynb)
    • [06.10 各种绘图实例](06. matplotlib/06.10 different plots.ipynb)
  • [07. 使用其他语言进行扩展](07. interfacing with other languages)
    • [07.01 简介](07. interfacing with other languages/07.01 introduction.ipynb)
    • [07.02 Python 扩展模块](07. interfacing with other languages/07.02 python extension modules.ipynb)
    • [07.03 Cython：Cython 基础，将源代码转换成扩展模块](07. interfacing with other languages/07.03 cython part 1.ipynb)
    • [07.04 Cython：Cython 语法，调用其他C库](07. interfacing with other languages/07.04 cython part 2.ipynb)
    • [07.05 Cython：class 和 cdef class，使用 C++](07. interfacing with other languages/07.05 cython part 3.ipynb)
    • [07.06 Cython：Typed memoryviews](07. interfacing with other languages/07.06 cython part 4.ipynb)
    • [07.07 生成编译注释](07. interfacing with other languages/07.07 profiling with annotations.ipynb)
    • [07.08 ctypes](07. interfacing with other languages/07.08 ctypes.ipynb)
  • [08. 面向对象编程](08. object-oriented programming)
    • [08.01 简介](08. object-oriented programming/08.01 oop introduction.ipynb)
    • [08.02 使用 OOP 对森林火灾建模](08. object-oriented programming/08.02 using oop model a forest fire.ipynb)
    • [08.03 什么是对象？](08. object-oriented programming/08.03 what is a object.ipynb)
    • [08.04 定义 class](08. object-oriented programming/08.04 writing classes.ipynb)
    • [08.05 特殊方法](08. object-oriented programming/08.05 special method.ipynb)
    • [08.06 属性](08. object-oriented programming/08.06 properties.ipynb)
    • [08.07 森林火灾模拟](08. object-oriented programming/08.07 forest fire simulation.ipynb)
    • [08.08 继承](08. object-oriented programming/08.08 inheritance.ipynb)
    • [08.09 super() 函数](08. object-oriented programming/08.09 super.ipynb)
    • [08.10 重定义森林火灾模拟](08. object-oriented programming/08.10 refactoring the forest fire simutation.ipynb)
    • [08.11 接口](08. object-oriented programming/08.11 interfaces.ipynb)
    • [08.12 共有，私有和特殊方法和属性](08. object-oriented programming/08.12 public private special in python.ipynb)
    • [08.13 多重继承](08. object-oriented programming/08.13 multiple inheritance.ipynb)
  • [09. Theano 基础](09. theano)
    • [09.01 Theano 简介及其安装](09. theano/09.01 introduction and installation.ipynb)
    • [09.02 Theano 基础](09. theano/09.02 theano basics.ipynb)
    • [09.03 Theano 在 Windows 上的配置](09. theano/09.03 gpu on windows.ipynb)
    • [09.04 Theano 符号图结构](09. theano/09.04 graph structures.ipynb)
    • [09.05 Theano 配置和编译模式](09. theano/09.05 configuration settings and compiling modes.ipynb)
    • [09.06 Theano 条件语句](09. theano/09.06 conditions in theano.ipynb)
    • [09.07 Theano 循环：scan（详解）](09. theano/09.07 loop with scan.ipynb)
    • [09.08 Theano 实例：线性回归](09. theano/09.08 linear regression.ipynb)
    • [09.09 Theano 实例：Logistic 回归](09. theano/09.09 logistic regression .ipynb)
    • [09.10 Theano 实例：Softmax 回归](09. theano/09.10 softmax on mnist.ipynb)
    • [09.11 Theano 实例：人工神经网络](09. theano/09.11 net on mnist.ipynb)
    • [09.12 Theano 随机数流变量](09. theano/09.12 random streams.ipynb)
    • [09.13 Theano 实例：更复杂的网络](09. theano/09.13 modern net on mnist.ipynb)
    • [09.14 Theano 实例：卷积神经网络](09. theano/09.14 convolutional net on mnist.ipynb)
    • [09.15 Theano tensor 模块：基础](09. theano/09.15 tensor basics.ipynb)
    • [09.16 Theano tensor 模块：索引](09. theano/09.16 tensor indexing.ipynb)
    • [09.17 Theano tensor 模块：操作符和逐元素操作](09. theano/09.17 tensor operator and elementwise operations.ipynb)
    • [09.18 Theano tensor 模块：nnet 子模块](09. theano/09.18 tensor nnet .ipynb)
    • [09.19 Theano tensor 模块：conv 子模块](09. theano/09.19 tensor conv.ipynb)
  • [10. 有趣的第三方模块](10. something interesting)
    • [10.01 使用 basemap 画地图](10. something interesting/10.01 maps using basemap.ipynb)
    • [10.02 使用 cartopy 画地图](10. something interesting/10.02 maps using cartopy.ipynb)
    • [10.03 探索 NBA 数据](10. something interesting/10.03 nba data.ipynb)
    • [10.04 金庸的武侠世界](10. something interesting/10.04 louis cha's kungfu world.ipynb)
  • [11. 有用的工具](11. useful tools)
    • [11.01 pprint 模块：打印 Python 对象](11. useful tools/11.01 pprint.ipynb)
    • [11.02 pickle, cPickle 模块：序列化 Python 对象](11. useful tools/11.02 pickle and cPickle.ipynb)
    • [11.03 json 模块：处理 JSON 数据](11. useful tools/11.03 json.ipynb)
    • [11.04 glob 模块：文件模式匹配](11. useful tools/11.04 glob.ipynb)
    • [11.05 shutil 模块：高级文件操作](11. useful tools/11.05 shutil.ipynb)
    • [11.06 gzip, zipfile, tarfile 模块：处理压缩文件](11. useful tools/11.06 gzip, zipfile, tarfile.ipynb)
    • [11.07 logging 模块：记录日志](11. useful tools/11.07 logging.ipynb)
    • [11.08 string 模块：字符串处理](11. useful tools/11.08 string.ipynb)
    • [11.09 collections 模块：更多数据结构](11. useful tools/11.09 collections.ipynb)
    • [11.10 requests 模块：HTTP for Human](11. useful tools/11.10 requests.ipynb)
  • [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)

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