{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "# Jupyter Notebooks\n",
    "\n",
    "The [MyST-NB extension](https://github.com/executablebooks/myst-nb) allow notebooks to be seemlessly integrated into a Sphinx website.  This page demonstrates how notebooks are rendered.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Mathematics\n",
    "\n",
    "[MathJax](https://www.mathjax.org) can use used to render mathematical equations. Equations can\n",
    "be rendered either in their own line using double dollar signs \n",
    "\n",
    "$$ y_{it} = \\alpha_i + \\gamma_t + \\beta x_{it} + \\epsilon_{it} $$\n",
    "\n",
    "or inline using single dollar signs ($\\LaTeX$).\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## DataFrames\n",
    "\n",
    "pandas DataFrames are rendered with useful markup."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "df = pd.DataFrame({'ints': [1, 2, 3], \n",
    "                   'floats': [np.pi, np.exp(1), (1+np.sqrt(5))/2],\n",
    "                   'strings': ['aardvark', 'bananarama', 'charcuterie' ]})\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## Plots and Figures\n",
    "\n",
    "matplotlib can be used to produce plots in notebooks\n",
    "\n",
    "This example comes from the [matplotlib gallery](https://matplotlib.org/3.1.1/gallery/ticks_and_spines/colorbar_tick_labelling_demo.html#sphx-glr-gallery-ticks-and-spines-colorbar-tick-labelling-demo-py)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "pycharm": {
     "is_executing": false,
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12,8))\n",
    "\n",
    "data = np.clip(np.random.randn(250, 250), -1, 1)\n",
    "\n",
    "cax = ax.imshow(data, interpolation='nearest', cmap=cm.coolwarm)\n",
    "ax.set_title('Gaussian noise with vertical colorbar', fontsize=16)\n",
    "plt.tick_params(labelsize=16)\n",
    "\n",
    "# Add colorbar, make sure to specify tick locations to match desired ticklabels\n",
    "cbar = fig.colorbar(cax, ticks=[-1, 0, 1])\n",
    "cbar.ax.set_yticklabels(['< -1', '0', '> 1'])  # vertically oriented colorbar\n",
    "cbar.ax.tick_params(labelsize=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STDERR and STDOUT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": [
     "raises-exception"
    ]
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-2920a1c71690>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\", \"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99"
     ]
    }
   ],
   "source": [
    "raise ValueError(\", \".join(str(i) for i in range(100)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "hi\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "print(\"hi\", file=sys.stderr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi, this is stdout\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "hi, this is stderr\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'this is a return value'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"hi, this is stderr\", file=sys.stderr)\n",
    "print(\"hi, this is stdout\", file=sys.stdout)\n",
    "\"this is a return value\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "raises-exception"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi, this is stdout\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "hi, this is stderr\n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "this is an error",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-17771c068de5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"hi, this is stderr\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"hi, this is stdout\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstdout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"this is an error\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m: this is an error"
     ]
    }
   ],
   "source": [
    "print(\"hi, this is stderr\", file=sys.stderr)\n",
    "print(\"hi, this is stdout\", file=sys.stdout)\n",
    "raise ValueError(\"this is an error\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This cell has no output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Alerts\n",
    "\n",
    "Alerts are the Jupyter Notebook version of admonitions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\"> <b>NOTE</b> Use blue boxes for Tips and notes. </div>\n",
    "\n",
    "<div class=\"alert alert-success\"> Use green boxes sparingly, and only for some specific purpose that the other boxes can't cover. For example, if you have a lot of related content to link to, maybe you decide to use green boxes for related links from each section of a notebook. </div>\n",
    "\n",
    "<div class=\"alert alert-warning\"> Use yellow boxes for examples that are not inside code cells, or use for mathematical formulas if needed. </div>\n",
    "\n",
    "<div class=\"alert alert-danger\"> In general, just avoid the red boxes. </div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "celltoolbar": "Tags",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
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  "pycharm": {
   "stem_cell": {
    "cell_type": "raw",
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     "collapsed": false
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