diff --git a/1_numpy_matplotlib_scipy_sympy/3-ipython_notebook.ipynb b/0_python/0-ipython_notebook.ipynb similarity index 62% rename from 1_numpy_matplotlib_scipy_sympy/3-ipython_notebook.ipynb rename to 0_python/0-ipython_notebook.ipynb index dae7c68..fb7b337 100644 --- a/1_numpy_matplotlib_scipy_sympy/3-ipython_notebook.ipynb +++ b/0_python/0-ipython_notebook.ipynb @@ -4,7 +4,52 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 介绍IPython和Jupyter笔记本" + "# IPython和Jupyter笔记本" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "本在线讲义使用Jupyter Notebook编写，因此首先介绍Jupter Notebook的使用方法。使用Notebook，可以方便的将理论描述、程序、数据可视化等集成在一个多媒体页面，方便大家的学习。\n", + "\n", + "Jupyter notebook 是一种 Web 应用，它能让用户将说明文本、数学方程、代码和可视化内容全部组合到一个易于共享的文档中，非常方便研究和教学，让使用者一目了然。Jupyter notebook特别适合做数据处理，其用途可以包括数据清理和探索、可视化、机器学习和大数据分析。其具有以下一些特点:\n", + "* 编程时具有语法高亮、缩进、tab补全的功能。\n", + "* 可直接通过浏览器运行代码，同时在代码块下方展示运行结果。\n", + "* 以富媒体格式展示计算结果。富媒体格式包括：HTML，LaTeX，PNG，SVG等。\n", + "* 对代码编写说明文档或语句时，支持Markdown语法。\n", + "* 支持使用LaTeX编写数学性说明。\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Jupyter 安装\n", + "安装Jupyter最简单的方法就是使用 Anaconda，其发行版附带了 Jupyter Notebook。在 conda 环境下安装 Jupyter Notebook 可以使用 \n", + "\n", + "```\n", + "conda install jupyter\n", + "```\n", + "\n", + "当然，也可以通过 `pip` 来安装 \n", + "```\n", + "pip install jupyter。\n", + "```\n", + "\n", + "安装后便可在终端中输入以下命令启动：\n", + "```\n", + "# jupyter notebook\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 常用操作\n", + "\n", + "![shortcut](images/jupyter_shortcuts.png)" ] }, { @@ -70,24 +115,20 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1-numpy_tutorial_EN.ipynb\texample.png\r\n", - "1-numpy_tutorial.ipynb\t\tmatplotlib_ani.ipynb\r\n", - "2-matplotlib_tutorial_EN.ipynb\tmatplotlib_full.ipynb\r\n", - "2-matplotlib_tutorial.ipynb\trandom-matrix.csv\r\n", - "3-ipython_notebook_EN.ipynb\trandom-matrix.npy\r\n", - "3-ipython_notebook.ipynb\tREADME.md\r\n", - "4-scipy_tutorial_EN.ipynb\tstockholm_td_adj.dat\r\n", - "4-scipy_tutorial.ipynb\t\tutils_git_advanced.ipynb\r\n", - "5-sympy_tutorial_EN.ipynb\tutils_git.ipynb\r\n", - "5-sympy_tutorial.ipynb\t\tutils_shell.ipynb\r\n", - "bokeh_tutorial.ipynb\r\n" + "0-ipython_notebook_EN.ipynb 3_Data_Structure_1.ipynb\t 7_Class_EN.ipynb\r\n", + "0-ipython_notebook.ipynb 4_Data_Structure_2_EN.ipynb 7_Class.ipynb\r\n", + "1_Basics_EN.ipynb\t 4_Data_Structure_2.ipynb\t images\r\n", + "1_Basics.ipynb\t\t 5_Control_Flow_EN.ipynb\t Python.pdf\r\n", + "2_Print_Statement_EN.ipynb 5_Control_Flow.ipynb\t README_EN.md\r\n", + "2_Print_Statement.ipynb 6_Function_EN.ipynb\t README.md\r\n", + "3_Data_Structure_1_EN.ipynb 6_Function.ipynb\t\t test.txt\r\n" ] } ], @@ -272,7 +313,9 @@ { "cell_type": "code", "execution_count": 4, - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", @@ -301,145 +344,6 @@ "source": [ "%run?" ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "from IPython.display import HTML, SVG, YouTubeVideo" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "podoc": { - "output_text": "" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - "\n", - "\n", - "
0,00,10,20,30,4
1,01,11,21,31,4
2,02,12,22,32,4
3,03,13,23,33,4
4,04,14,24,34,4
\n" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "HTML('''\n", - "\n", - "''' +\n", - " ''.join(['' +\n", - " ''.join([f''\n", - " for col in range(5)]) +\n", - " '' for row in range(5)]) +\n", - " '''\n", - "
{row},{col}
\n", - "''')" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "podoc": { - "output_text": "" - } - }, - "outputs": [ - { - "data": { - "image/svg+xml": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "SVG('''''' +\n", - " ''.join([f'''\n", - " ''' for i in range(10)]) +\n", - " '''''')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "podoc": { - "output_text": "" - } - }, - "outputs": [], - "source": [ - "YouTubeVideo('VQBZ2MqWBZI')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "```json\n", - "{\n", - " \"cells\": [\n", - " {\n", - " \"cell_type\": \"code\",\n", - " \"execution_count\": 1,\n", - " \"metadata\": {},\n", - " \"outputs\": [\n", - " {\n", - " \"name\": \"stdout\",\n", - " \"output_type\": \"stream\",\n", - " \"text\": [\n", - " \"Hello world!\\n\"\n", - " ]\n", - " }\n", - " ],\n", - " \"source\": [\n", - " \"print(\\\"Hello world!\\\")\"\n", - " ]\n", - " }\n", - " ],\n", - " \"metadata\": {},\n", - " \"nbformat\": 4,\n", - " \"nbformat_minor\": 2\n", - "}\n", - "```" - ] } ], "metadata": { @@ -458,7 +362,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/1_numpy_matplotlib_scipy_sympy/3-ipython_notebook_EN.ipynb b/0_python/0-ipython_notebook_EN.ipynb similarity index 100% rename from 1_numpy_matplotlib_scipy_sympy/3-ipython_notebook_EN.ipynb rename to 0_python/0-ipython_notebook_EN.ipynb diff --git a/0_python/1_Basics.ipynb b/0_python/1_Basics.ipynb index 73cde70..8ee281a 100644 --- a/0_python/1_Basics.ipynb +++ b/0_python/1_Basics.ipynb @@ -882,36 +882,6 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**cmp(x,y)**\n", - "\n", - "|x ? y|Output|\n", - "|---|---|\n", - "| x < y | -1 |\n", - "| x == y | 0 |\n", - "| x > y | 1 |" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True\n" - ] - } - ], - "source": [ - "print(1<2)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ "**pow(x,y,z)** 可以被用来找到幂函数$x^y$也可以找到第三个指定数字的mod值，即:($x^y$ % z)。" ] }, @@ -1030,7 +1000,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/0_python/3_Data_Structure_1.ipynb b/0_python/3_Data_Structure_1.ipynb index d01b00e..8059469 100644 --- a/0_python/3_Data_Structure_1.ipynb +++ b/0_python/3_Data_Structure_1.ipynb @@ -578,26 +578,6 @@ ] }, { - "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "False" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "'Rajath' in names" - ] - }, - { "cell_type": "markdown", "metadata": {}, "source": [ @@ -2145,7 +2125,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/0_python/5_Control_Flow.ipynb b/0_python/5_Control_Flow.ipynb index 7723227..7326b44 100644 --- a/0_python/5_Control_Flow.ipynb +++ b/0_python/5_Control_Flow.ipynb @@ -511,7 +511,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "就是这样!只记得用方括号括起来。" + "将表达方式用方括号括起来。" ] }, { @@ -685,7 +685,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/0_python/6_Function.ipynb b/0_python/6_Function.ipynb index dc07c1c..fd0a204 100644 --- a/0_python/6_Function.ipynb +++ b/0_python/6_Function.ipynb @@ -34,7 +34,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "将上面的语法理解为，定义了一个名为“funcname”的函数，它接受“arg1,arg2，…argN”的参数。函数在执行语句后返回一个“值”。" + "将上面的语法理解为，定义了一个名为`funcname`的函数，它接受`arg1,arg2，…argN`的参数。函数在执行语句后返回一个``。" ] }, { @@ -62,16 +62,16 @@ "source": [ "不需要每次都写上面的两个语句，可以通过定义一个函数来替换它，这个函数只需一行就能完成任务。\n", "\n", - "定义一个函数 firstfunc()." + "定义一个函数 `first_func()`." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ - "def firstfunc():\n", + "def first_func():\n", " print(\"Hey Rajath!\")\n", " print(\"Rajath, How do you do?\")" ] @@ -93,8 +93,8 @@ } ], "source": [ - "firstfunc()\n", - "funca=firstfunc\n", + "first_func()\n", + "funca=first_func\n", "funca()" ] }, @@ -102,30 +102,30 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**firstfunc()** 每一次只打印一个人的消息。我们可以让我们的函数 **firstfunc()** 接受参数，该参数将存储名称然后打印相应地接受字符串。为了这样做我们需要像所示的那样在函数内添加一个参数。" + "**first_func()** 每一次只打印一个人的消息。我们可以让我们的函数 **first_func()** 接受参数，该参数将存储名称然后打印相应地接受字符串。为了这样做我们需要像所示的那样在函数内添加一个参数。" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "def firstfunc(username):\n", + "def first_func(username):\n", " print(\"Hey\", username + '!')\n", " print(username + ',' ,\"How do you do?\")" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Please enter your name : Jack\n" + "Please enter your name : hello\n" ] } ], @@ -142,60 +142,50 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Hey Jack!\n", - "Jack, How do you do?\n" + "Hey hello!\n", + "hello, How do you do?\n" ] } ], "source": [ - "firstfunc(name1)" + "first_func(name1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "让我们通过定义另一个函数**secondfunc()** 来进一步简化它，该函数接受名称并将其存储在一个变量中，然后从函数本身内部调用**firstfunc()**。" + "让我们通过定义另一个函数**second_func()** 来进一步简化它，该函数接受名称并将其存储在一个变量中，然后从函数本身内部调用**first_func()**。" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ - "def firstfunc(username):\n", + "def first_func(username):\n", " print(\"Hey\", username + '!')\n", " print(username + ',' ,\"How do you do?\")\n", - "def secondfunc():\n", + "def second_func():\n", " name = input(\"Please enter your name : \")\n", - " firstfunc(name)" + " first_func(name)" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Please enter your name : Tom\n", - "Hey Tom!\n", - "Tom, How do you do?\n" - ] - } - ], + "outputs": [], "source": [ - "secondfunc()" + "second_func()" ] }, { @@ -415,16 +405,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "当一个函数的参数在大多数情况下是常见的或者它是“隐式的”时，使用这个概念。" + "当一个函数的参数在大多数情况下是常见的或者它是`隐式的`时，使用这个概念。" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "def implicitadd(x,addnumber=3):\n", + "def implicitadd(x, addnumber=3):\n", " return x+addnumber" ] }, @@ -1060,7 +1050,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/0_python/7_Class.ipynb b/0_python/7_Class.ipynb index 5d581cb..8f218b7 100644 --- a/0_python/7_Class.ipynb +++ b/0_python/7_Class.ipynb @@ -11,7 +11,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Python中的变量、列表、字典等其实都是对象。不涉及面向对象编程的理论部分，在本教程中对概念进行解释。" + "Python中的变量、列表、字典等其实都是对象。" ] }, { @@ -1275,9 +1275,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "找各个方面的练习题，并独立完成能帮助你掌握Python的窍门，例如给自己一个问题并解决它们，你还可以在任何编程竞赛平台上提交问题求解。你编写的代码越多，你发现的越多，你就越开始欣赏这门语言。强烈建议把[Python作业](https://gitee.com/pi-lab/machinelearning_homework/blob/master/homework_01_python/README.md)完成，并在[其他编程练习](https://gitee.com/pi-lab/machinelearning_homework/blob/master/homework_01_python/README.md#references)里面找一些练习题或者项目做一下。\n", + "找各个方面的练习题，并独立完成能帮助你掌握Python的窍门，例如给自己一个问题并解决它们，你还可以在任何编程竞赛平台上提交问题求解。你编写的代码越多，你发现的越多，你就越开始欣赏这门语言。强烈建议把[《Python作业》](https://gitee.com/pi-lab/machinelearning_homework/blob/master/homework_01_python/README.md)完成，并在[《其他编程练习》](https://gitee.com/pi-lab/machinelearning_homework/blob/master/homework_01_python/README.md#references)里面找一些练习题或者项目做一下。\n", "\n", - "现在已经向你介绍了Python，您可以尝试您感兴趣的领域中的不同Python库。我强烈建议您查看这个Python框架、库和软件列表 http://awesome-python.com\n", + "现在已经介绍了Python，可以尝试感兴趣的领域中的不同Python库。强烈建议查看这个Python框架、库和软件列表 http://awesome-python.com\n", "\n", "\n", "Python 教程:\n", @@ -1286,17 +1286,15 @@ "* [Python官方教程（中文版)](https://docs.python.org/zh-cn/3/tutorial/index.html)\n", "* Python官方文档: https://docs.python.org/3/\n", "* 本教程来源于：https://github.com/rajathkumarmp/Python-Lectures \n", - "\n", - "\n", - "**最后，享受解决问题的快乐！因为生命短暂，你需要Python!**" + "\n" ] }, { - "cell_type": "code", - "execution_count": null, + "cell_type": "markdown", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "**最后，享受解决问题的快乐！因为生命短暂，你需要Python!**" + ] } ], "metadata": { @@ -1315,7 +1313,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.7.9" } }, "nbformat": 4, diff --git a/0_python/README.md b/0_python/README.md index af63ae2..4fd250c 100644 --- a/0_python/README.md +++ b/0_python/README.md @@ -9,22 +9,23 @@ Python 是一门上手简单、功能强大、通用型的脚本编程语言。P ## 内容 0. [Install Python](../references_tips/InstallPython.md) -1. [Basics](1_Basics.ipynb) +1. [IPython & Jupyter Notebook](0-ipython_notebook.ipynb) +2. [Basics](1_Basics.ipynb) - Why Python, Zen of Python - Variables, Operators, Built-in functions -2. [Print statement](2_Print_Statement.ipynb) +3. [Print statement](2_Print_Statement.ipynb) - Tips of print -3. [Data structure - 1](3_Data_Structure_1.ipynb) +4. [Data structure - 1](3_Data_Structure_1.ipynb) - Lists, Tuples, Sets -4. [Data structure - 2](4_Data_Structure_2.ipynb) +5. [Data structure - 2](4_Data_Structure_2.ipynb) - Strings, Dictionaries -5. [Control flow](5_Control_Flow.ipynb) +6. [Control flow](5_Control_Flow.ipynb) - if, else, elif, for, while, break, continue -6. [Functions](6_Function.ipynb) +7. [Functions](6_Function.ipynb) - Function define, return, arguments - Gloabl and local variables - Lambda functions -7. [Class](7_Class.ipynb) +8. [Class](7_Class.ipynb) - Class define - Inheritance diff --git a/0_python/images/jupyter_shortcuts.png b/0_python/images/jupyter_shortcuts.png new file mode 100644 index 0000000..fd054f0 Binary files /dev/null and b/0_python/images/jupyter_shortcuts.png differ diff --git a/1_numpy_matplotlib_scipy_sympy/test.txt b/0_python/test.txt similarity index 100% rename from 1_numpy_matplotlib_scipy_sympy/test.txt rename to 0_python/test.txt