0-jupyter-notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Jupyter Notebook \n",
    "\n",
    "It is a **```web application```** that allows you to create and share documents that contain \n",
    "- live code\n",
    "- equations\n",
    "- visualizations\n",
    "- explanatory text\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Jupyter-Notebook\" data-toc-modified-id=\"Jupyter-Notebook-1\">Jupyter Notebook</a></span><ul class=\"toc-item\"><li><span><a href=\"#Copy-and-Paste-images\" data-toc-modified-id=\"Copy-and-Paste-images-1.1\">Copy and Paste images</a></span></li><li><span><a href=\"#Set-the-layout-of-figures\" data-toc-modified-id=\"Set-the-layout-of-figures-1.2\">Set the layout of figures</a></span></li><li><span><a href=\"#Publish-on-Github-Pages\" data-toc-modified-id=\"Publish-on-Github-Pages-1.3\">Publish on Github Pages</a></span></li><li><span><a href=\"#Workflow\" data-toc-modified-id=\"Workflow-1.4\">Workflow</a></span></li><li><span><a href=\"#引用\" data-toc-modified-id=\"引用-1.5\">引用</a></span><ul class=\"toc-item\"><li><span><a href=\"#搜狗输入法表情和符号\" data-toc-modified-id=\"搜狗输入法表情和符号-1.5.1\">搜狗输入法表情和符号</a></span></li></ul></li><li><span><a href=\"#运行C代码\" data-toc-modified-id=\"运行C代码-1.6\">运行C代码</a></span></li><li><span><a href=\"#Jupyter-魔术命令\" data-toc-modified-id=\"Jupyter-魔术命令-1.7\">Jupyter 魔术命令</a></span></li><li><span><a href=\"#References\" data-toc-modified-id=\"References-1.8\">References</a></span></li></ul></li></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Copy and Paste images\n",
    "\n",
    "    ![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Set the layout of figures\n",
    "\n",
    "- first copy and paste a figure into notebook, and you will get this line of script: \n",
    "\n",
    "```\n",
    "![image.png](attachment:image.png)\n",
    "```\n",
    "\n",
    "- Second, replace it with the following script:\n",
    "\n",
    "```        \n",
    "<div>\n",
    "<img src=\"attachment:image.png\"\n",
    "     align=\"right\" width = \"200px\"/>\n",
    "</div>\n",
    "```\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "```\n",
    "<div>\n",
    "<img src=\"attachment:image.png\" align=\"right\" width = \"200px\"/>\n",
    "</div>\n",
    "```\n",
    "> “Know thyself.” ― Socrates\n",
    "\n",
    "> “The unexamined life is not worth living.” ― Socrates \n",
    "\n",
    "> “Wonder is the beginning of wisdom.” ― Socrates\n",
    "\n",
    ">  “True wisdom comes to each of us when we realize how little we understand about life, ourselves, and the world around us.” \n",
    "― Socrates\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    },
    "tags": [
     "popout"
    ]
   },
   "source": [
    "## Publish on Github Pages\n",
    "\n",
    "1. Confirm that your book's HTML is built in the **_site** folder.\n",
    "2. Install the ghp-import tool.\n",
    "\n",
    "```bash\n",
    "pip install ghp-import\n",
    "```\n",
    "\n",
    "3. Use ghp-import to push your book's HTML onto the gh-pages branch of your repository.\n",
    "\n",
    "```bash\n",
    "ghp-import -n -p -f _site\n",
    "```\n",
    "\n",
    "https://jupyterbook.org/guide/publish/github-pages.html\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Workflow\n",
    "\n",
    "```bash\n",
    "#!/bin/bash\n",
    "# open github master branch\n",
    "# open atom master branch\n",
    "cd ..\n",
    "jupyter-book build ccbook/\n",
    "cd ccbook\n",
    "make serve\n",
    "\n",
    "# Publish your book's HTML manually to GitHub-pages\n",
    "# publish the _site folder of master \n",
    "# branch to gh-pages branch\n",
    "\n",
    "ghp-import -n -p -f _site\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-10-08T07:47:38.249629Z",
     "start_time": "2023-10-08T07:47:38.240007Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world!\n",
      "I am Cheng-Jun Wang.\n"
     ]
    }
   ],
   "source": [
    "# my first python script\n",
    "print(\"Hello world!\\nI am Cheng-Jun Wang.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2016-10-21T19:12:33.661328",
     "start_time": "2016-10-21T19:12:33.656067"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Uses include: \n",
    "- data cleaning and transformation, \n",
    "- numerical simulation, \n",
    "- statistical modeling, \n",
    "- machine learning \n",
    "- and much more.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-10-08T07:47:51.137192Z",
     "start_time": "2023-10-08T07:47:51.133860Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello world\n"
     ]
    }
   ],
   "source": [
    "print('hello world')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-10-08T07:47:52.912993Z",
     "start_time": "2023-10-08T07:47:52.900256Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 + 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$E = MC^2$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2016-10-24T22:38:25.581356",
     "start_time": "2016-10-24T22:38:25.576650"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "\\begin{align}\n",
    "\\dot{x} & = \\sigma(y-x) \\\\\n",
    "\\dot{y} & = \\rho x - y - xz \\\\\n",
    "\\dot{z} & = -\\beta z + xy\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 引用\n",
    "\n",
    "Because jupyter-book is built on top of Jekyll, we can use the excellent `jekyll-scholar` plugin to include citations and a bibliography with your book.\n",
    "\n",
    "Note: It only works if you're building your book HTML locally and hosting the HTML files online somewhere. \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "{% cite holdgraf_evidence_2014 %}\n",
    "\n",
    "For example, this text: {% cite holdgraf_evidence_2014 %} generates this citation:\n",
    "\n",
    "\n",
    "https://jupyterbook.org/features/citations.html\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "```\n",
    "# 一级标题\n",
    "## 二级标题\n",
    "\n",
    "[南京大学](http://www.fdu.edu.cn)是一个*非常棒*的大学！\n",
    "\n",
    "1. point 1\n",
    "1. point 2\n",
    "1. point 3\n",
    "```\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "blockquote"
    ]
   },
   "source": [
    "> Here's an example of an epigraph quote. Note that in this case, the quote itself is a bit larger and italicized. You probably shouldn't make this too long so that they don't stand out too much. - Jo the Jovyan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-10-12T01:15:39.993593Z",
     "start_time": "2019-10-12T01:15:39.989621Z"
    },
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [
     "popout"
    ]
   },
   "source": [
    "\n",
    "For example, here's some popout content! It was created by adding the popout tag to a cell in the notebook. Jupyter Book automatically converts these cells into helpful side content.\n",
    "\n",
    "To enable the cell tag editor, go click View -> Cell Toolbar -> Tags. This will enable the tags UI. Here's what the menu looks like."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-10-11T17:20:03.906713Z",
     "start_time": "2019-10-11T17:20:03.900878Z"
    },
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### 搜狗输入法表情和符号\n",
    "\n",
    "- ∫ ∑ ※ ➕➖✖️➗ ❎ √ ×\n",
    "- 😪😠😡😎☺️😁📚🌲\n",
    "- 👌👍👎👂👃👀✋❌💰🌂\n",
    "- 0️⃣1️⃣2️⃣3️⃣4️⃣5️⃣6️⃣7️⃣8️⃣9️⃣②🔟 \n",
    "- 🐶🐱🐔🐷🐖🐴🐎🐂🐑🐯🐧🐺🐒🐵🐻🐦🐲\n",
    "- 💻 🌈🌎☁️❄️🏃♀👩👱✨\n",
    "- 🆚🔥🌹✈️🌉🎄\n",
    "\n",
    "(✿◡‿◡)害羞 ⁄(⁄ ⁄•⁄ω⁄•⁄ ⁄)⁄ d=====(￣▽￣*)b厉害 \n",
    "\n",
    "我是我，不一样花火。～(￣▽￣～)(～￣▽￣)～ 矜持 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-10-08T07:49:04.617438Z",
     "start_time": "2023-10-08T07:48:56.247494Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "xi = [1, 2, 3, 4, 5]\n",
    "y = [3, 5, 9, 13, 16]\n",
    "\n",
    "plt.plot(xi, y, 'g-s')\n",
    "plt.xlabel('$x_i$', fontsize = 20)\n",
    "plt.ylabel('$y$', fontsize = 20)\n",
    "plt.title('$Scatter\\,Plot$', fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-05-14T03:05:04.880685Z",
     "start_time": "2021-05-14T03:04:59.164441Z"
    },
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": [
     "popout",
     "hide_input"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot') \n",
    "xi = [1, 2, 3, 4, 5]\n",
    "y = [3, 5, 9, 13, 16]\n",
    "plt.plot(xi, y, 'g-s')\n",
    "plt.xlabel('$x_i$', fontsize = 20)\n",
    "plt.ylabel('$y$', fontsize = 20)\n",
    "plt.title('$Scatter\\,Plot$', fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 运行C代码\n",
    "\n",
    "C functions are typically split into header files (.h) where things are declared but not defined, and implementation files (.c) where they are defined. http://people.duke.edu/~ccc14/sta-663/CrashCourseInC.html#a-tutorial-example-coding-a-fibonacci-function-in-c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-07T06:26:11.397052Z",
     "start_time": "2019-06-07T06:26:11.391964Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting hello.c\n"
     ]
    }
   ],
   "source": [
    "%%file hello.c\n",
    "#include <stdio.h>\n",
    "\n",
    "int main() {\n",
    "    printf(\"Hello, world!\");\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-07T06:26:29.912376Z",
     "start_time": "2019-06-07T06:26:29.789505Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xcrun: error: invalid active developer path (/Library/Developer/CommandLineTools), missing xcrun at: /Library/Developer/CommandLineTools/usr/bin/xcrun\r\n"
     ]
    }
   ],
   "source": [
    "! gcc hello.c -o hello # 编译"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-04-27T05:54:12.626044Z",
     "start_time": "2018-04-27T05:54:12.511042Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, world!"
     ]
    }
   ],
   "source": [
    "! ./hello # 执行"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Jupyter 魔术命令 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2018-04-19T10:29:30.618186Z",
     "start_time": "2018-04-19T10:29:30.612065Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/json": {
       "cell": {
        "!": "OSMagics",
        "HTML": "Other",
        "SVG": "Other",
        "bash": "Other",
        "capture": "ExecutionMagics",
        "debug": "ExecutionMagics",
        "file": "Other",
        "html": "DisplayMagics",
        "javascript": "DisplayMagics",
        "js": "DisplayMagics",
        "latex": "DisplayMagics",
        "markdown": "DisplayMagics",
        "perl": "Other",
        "prun": "ExecutionMagics",
        "pypy": "Other",
        "python": "Other",
        "python2": "Other",
        "python3": "Other",
        "ruby": "Other",
        "script": "ScriptMagics",
        "sh": "Other",
        "svg": "DisplayMagics",
        "sx": "OSMagics",
        "system": "OSMagics",
        "time": "ExecutionMagics",
        "timeit": "ExecutionMagics",
        "writefile": "OSMagics"
       },
       "line": {
        "alias": "OSMagics",
        "alias_magic": "BasicMagics",
        "autocall": "AutoMagics",
        "automagic": "AutoMagics",
        "autosave": "KernelMagics",
        "bookmark": "OSMagics",
        "cat": "Other",
        "cd": "OSMagics",
        "clear": "KernelMagics",
        "colors": "BasicMagics",
        "config": "ConfigMagics",
        "connect_info": "KernelMagics",
        "cp": "Other",
        "debug": "ExecutionMagics",
        "dhist": "OSMagics",
        "dirs": "OSMagics",
        "doctest_mode": "BasicMagics",
        "ed": "Other",
        "edit": "KernelMagics",
        "env": "OSMagics",
        "gui": "BasicMagics",
        "hist": "Other",
        "history": "HistoryMagics",
        "killbgscripts": "ScriptMagics",
        "ldir": "Other",
        "less": "KernelMagics",
        "lf": "Other",
        "lk": "Other",
        "ll": "Other",
        "load": "CodeMagics",
        "load_ext": "ExtensionMagics",
        "loadpy": "CodeMagics",
        "logoff": "LoggingMagics",
        "logon": "LoggingMagics",
        "logstart": "LoggingMagics",
        "logstate": "LoggingMagics",
        "logstop": "LoggingMagics",
        "ls": "Other",
        "lsmagic": "BasicMagics",
        "lx": "Other",
        "macro": "ExecutionMagics",
        "magic": "BasicMagics",
        "man": "KernelMagics",
        "matplotlib": "PylabMagics",
        "mkdir": "Other",
        "more": "KernelMagics",
        "mv": "Other",
        "notebook": "BasicMagics",
        "page": "BasicMagics",
        "pastebin": "CodeMagics",
        "pdb": "ExecutionMagics",
        "pdef": "NamespaceMagics",
        "pdoc": "NamespaceMagics",
        "pfile": "NamespaceMagics",
        "pinfo": "NamespaceMagics",
        "pinfo2": "NamespaceMagics",
        "pip": "BasicMagics",
        "popd": "OSMagics",
        "pprint": "BasicMagics",
        "precision": "BasicMagics",
        "profile": "BasicMagics",
        "prun": "ExecutionMagics",
        "psearch": "NamespaceMagics",
        "psource": "NamespaceMagics",
        "pushd": "OSMagics",
        "pwd": "OSMagics",
        "pycat": "OSMagics",
        "pylab": "PylabMagics",
        "qtconsole": "KernelMagics",
        "quickref": "BasicMagics",
        "recall": "HistoryMagics",
        "rehashx": "OSMagics",
        "reload_ext": "ExtensionMagics",
        "rep": "Other",
        "rerun": "HistoryMagics",
        "reset": "NamespaceMagics",
        "reset_selective": "NamespaceMagics",
        "rm": "Other",
        "rmdir": "Other",
        "run": "ExecutionMagics",
        "save": "CodeMagics",
        "sc": "OSMagics",
        "set_env": "OSMagics",
        "store": "StoreMagics",
        "sx": "OSMagics",
        "system": "OSMagics",
        "tb": "ExecutionMagics",
        "time": "ExecutionMagics",
        "timeit": "ExecutionMagics",
        "unalias": "OSMagics",
        "unload_ext": "ExtensionMagics",
        "who": "NamespaceMagics",
        "who_ls": "NamespaceMagics",
        "whos": "NamespaceMagics",
        "xdel": "NamespaceMagics",
        "xmode": "BasicMagics"
       }
      },
      "text/plain": [
       "Available line magics:\n",
       "%alias  %alias_magic  %autocall  %automagic  %autosave  %bookmark  %cat  %cd  %clear  %colors  %config  %connect_info  %cp  %debug  %dhist  %dirs  %doctest_mode  %ed  %edit  %env  %gui  %hist  %history  %killbgscripts  %ldir  %less  %lf  %lk  %ll  %load  %load_ext  %loadpy  %logoff  %logon  %logstart  %logstate  %logstop  %ls  %lsmagic  %lx  %macro  %magic  %man  %matplotlib  %mkdir  %more  %mv  %notebook  %page  %pastebin  %pdb  %pdef  %pdoc  %pfile  %pinfo  %pinfo2  %popd  %pprint  %precision  %profile  %prun  %psearch  %psource  %pushd  %pwd  %pycat  %pylab  %qtconsole  %quickref  %recall  %rehashx  %reload_ext  %rep  %rerun  %reset  %reset_selective  %rm  %rmdir  %run  %save  %sc  %set_env  %store  %sx  %system  %tb  %time  %timeit  %unalias  %unload_ext  %who  %who_ls  %whos  %xdel  %xmode\n",
       "\n",
       "Available cell magics:\n",
       "%%!  %%HTML  %%SVG  %%bash  %%capture  %%debug  %%file  %%html  %%javascript  %%js  %%latex  %%markdown  %%perl  %%prun  %%pypy  %%python  %%python2  %%python3  %%ruby  %%script  %%sh  %%svg  %%sx  %%system  %%time  %%timeit  %%writefile\n",
       "\n",
       "Automagic is ON, % prefix IS NOT needed for line magics."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%lsmagic "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    ">  pip install version_information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-07T06:28:42.462467Z",
     "start_time": "2019-06-07T06:28:39.036474Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: version_information in /Users/datalab/Applications/anaconda/lib/python3.5/site-packages (1.0.3)\n",
      "\u001b[33mYou are using pip version 19.0.3, however version 19.1.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install version_information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-06-07T06:29:42.785175Z",
     "start_time": "2019-06-07T06:29:41.429103Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/json": {
       "Software versions": [
        {
         "module": "Python",
         "version": "3.5.4 64bit [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]"
        },
        {
         "module": "IPython",
         "version": "6.2.1"
        },
        {
         "module": "OS",
         "version": "Darwin 18.6.0 x86_64 i386 64bit"
        },
        {
         "module": "numpy",
         "version": "1.16.3"
        },
        {
         "module": "matplotlib",
         "version": "3.0.1"
        },
        {
         "module": "pandas",
         "version": "0.23.4"
        },
        {
         "module": "scipy",
         "version": "1.1.0"
        },
        {
         "module": "statsmodels",
         "version": "0.9.0"
        }
       ]
      },
      "text/html": [
       "<table><tr><th>Software</th><th>Version</th></tr><tr><td>Python</td><td>3.5.4 64bit [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]</td></tr><tr><td>IPython</td><td>6.2.1</td></tr><tr><td>OS</td><td>Darwin 18.6.0 x86_64 i386 64bit</td></tr><tr><td>numpy</td><td>1.16.3</td></tr><tr><td>matplotlib</td><td>3.0.1</td></tr><tr><td>pandas</td><td>0.23.4</td></tr><tr><td>scipy</td><td>1.1.0</td></tr><tr><td>statsmodels</td><td>0.9.0</td></tr><tr><td colspan='2'>Fri Jun 07 14:29:42 2019 CST</td></tr></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{|l|l|}\\hline\n",
       "{\\bf Software} & {\\bf Version} \\\\ \\hline\\hline\n",
       "Python & 3.5.4 64bit [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE\\_401/final)] \\\\ \\hline\n",
       "IPython & 6.2.1 \\\\ \\hline\n",
       "OS & Darwin 18.6.0 x86\\_64 i386 64bit \\\\ \\hline\n",
       "numpy & 1.16.3 \\\\ \\hline\n",
       "matplotlib & 3.0.1 \\\\ \\hline\n",
       "pandas & 0.23.4 \\\\ \\hline\n",
       "scipy & 1.1.0 \\\\ \\hline\n",
       "statsmodels & 0.9.0 \\\\ \\hline\n",
       "\\hline \\multicolumn{2}{|l|}{Fri Jun 07 14:29:42 2019 CST} \\\\ \\hline\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "Software versions\n",
       "Python 3.5.4 64bit [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]\n",
       "IPython 6.2.1\n",
       "OS Darwin 18.6.0 x86_64 i386 64bit\n",
       "numpy 1.16.3\n",
       "matplotlib 3.0.1\n",
       "pandas 0.23.4\n",
       "scipy 1.1.0\n",
       "statsmodels 0.9.0\n",
       "Fri Jun 07 14:29:42 2019 CST"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# install version_information in the terminal first.\n",
    "%reload_ext version_information\n",
    "%version_information numpy, matplotlib, pandas, scipy, statsmodels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## References\n",
    "\n",
    "{% bibliography %}\n",
    "\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  },
  "latex_envs": {
   "LaTeX_envs_menu_present": true,
   "autoclose": false,
   "autocomplete": true,
   "bibliofile": "references.bib",
   "cite_by": "number",
   "current_citInitial": 1,
   "eqLabelWithNumbers": true,
   "eqNumInitial": 0,
   "hotkeys": {
    "equation": "Ctrl-E",
    "itemize": "Ctrl-I"
   },
   "labels_anchors": false,
   "latex_user_defs": false,
   "report_style_numbering": false,
   "user_envs_cfg": false
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": true,
   "toc_position": {
    "height": "355.747px",
    "left": "1213.97px",
    "top": "112.778px",
    "width": "212.969px"
   },
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}