{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>vehicle</th> <th>year</th> <th>msrp</th> <th>acceleration</th> <th>mpg</th> <th>class</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Prius (1st Gen)</td> <td>1997</td> <td>24509.7</td> <td>7.46        </td> <td>41.26</td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Tino           </td> <td>2000</td> <td>35355  </td> <td>8.2         </td> <td>54.1 </td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Prius (2nd Gen)</td> <td>2000</td> <td>26832.2</td> <td>7.97        </td> <td>45.23</td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Civic (1st Gen)</td> <td>2001</td> <td>25833.4</td> <td>7.04        </td> <td>47.04</td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Alphard        </td> <td>2003</td> <td>38084.8</td> <td>8.33        </td> <td>40.46</td> <td>Minivan</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Civic          </td> <td>2003</td> <td>14071.9</td> <td>8.62        </td> <td>41   </td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Escape         </td> <td>2004</td> <td>36676.1</td> <td>10.32       </td> <td>31.99</td> <td>SUV    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Lexus RX400h   </td> <td>2005</td> <td>58521.1</td> <td>12.76       </td> <td>28.23</td> <td>SUV    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Civic (2nd Gen)</td> <td>2005</td> <td>26354.4</td> <td>7.63        </td> <td>39.99</td> <td>Compact</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Highlander     </td> <td>2005</td> <td>29186.2</td> <td>12.76       </td> <td>29.4 </td> <td>SUV    </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>\n",
       "<p>... (65 rows omitted)</p>"
      ],
      "text/plain": [
       "vehicle         | year | msrp    | acceleration | mpg   | class\n",
       "Prius (1st Gen) | 1997 | 24509.7 | 7.46         | 41.26 | Compact\n",
       "Tino            | 2000 | 35355   | 8.2          | 54.1  | Compact\n",
       "Prius (2nd Gen) | 2000 | 26832.2 | 7.97         | 45.23 | Compact\n",
       "Civic (1st Gen) | 2001 | 25833.4 | 7.04         | 47.04 | Compact\n",
       "Alphard         | 2003 | 38084.8 | 8.33         | 40.46 | Minivan\n",
       "Civic           | 2003 | 14071.9 | 8.62         | 41    | Compact\n",
       "Escape          | 2004 | 36676.1 | 10.32        | 31.99 | SUV\n",
       "Lexus RX400h    | 2005 | 58521.1 | 12.76        | 28.23 | SUV\n",
       "Civic (2nd Gen) | 2005 | 26354.4 | 7.63         | 39.99 | Compact\n",
       "Highlander      | 2005 | 29186.2 | 12.76        | 29.4  | SUV\n",
       "... (65 rows omitted)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datascience import *\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plots\n",
    "plots.style.use('fivethirtyeight')\n",
    "\n",
    "cars = Table.read_table('hybrid.csv')\n",
    "\n",
    "cars = cars.where('class', are.contained_in(\"Compact SUV Minivan\"))\n",
    "cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "metadata": {},
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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "from IPython.display import display\n",
    "\n",
    "# Taken from https://stackoverflow.com/questions/31517194/how-to-hide-one-specific-cell-input-or-output-in-ipython-notebook\n",
    "tag = HTML('''<script>\n",
    "code_show=true; \n",
    "function code_toggle() {\n",
    "    if (code_show){\n",
    "        $('div.cell.code_cell.rendered.selected div.input').hide();\n",
    "    } else {\n",
    "        $('div.cell.code_cell.rendered.selected div.input').show();\n",
    "    }\n",
    "    code_show = !code_show\n",
    "} \n",
    "$( document ).ready(code_toggle);\n",
    "</script>\n",
    "To show/hide this cell's raw code input, click <a href=\"javascript:code_toggle()\">here</a>.''')\n",
    "display(tag)\n",
    "\n",
    "############### Write code below ##################\n",
    "\n",
    "cars.scatter('msrp','mpg')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>\n",
       "code_show=false; \n",
       "function code_toggle() {\n",
       "    if (code_show){\n",
       "        $('div.cell.code_cell.rendered.selected div.input').hide();\n",
       "    } else {\n",
       "        $('div.cell.code_cell.rendered.selected div.input').show();\n",
       "    }\n",
       "    code_show = !code_show\n",
       "} \n",
       "$( document ).ready(code_toggle);\n",
       "</script>\n",
       "To show/hide this cell's raw code input, click <a href=\"javascript:code_toggle()\">here</a>."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "from IPython.display import display\n",
    "\n",
    "# Taken from https://stackoverflow.com/questions/31517194/how-to-hide-one-specific-cell-input-or-output-in-ipython-notebook\n",
    "tag = HTML('''<script>\n",
    "code_show=false; \n",
    "function code_toggle() {\n",
    "    if (code_show){\n",
    "        $('div.cell.code_cell.rendered.selected div.input').hide();\n",
    "    } else {\n",
    "        $('div.cell.code_cell.rendered.selected div.input').show();\n",
    "    }\n",
    "    code_show = !code_show\n",
    "} \n",
    "$( document ).ready(code_toggle);\n",
    "</script>\n",
    "To show/hide this cell's raw code input, click <a href=\"javascript:code_toggle()\">here</a>.''')\n",
    "display(tag)\n",
    "\n",
    "\n",
    "\n",
    "############### Write code below ##################\n",
    "\n",
    "cars.scatter('msrp','mpg')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <script>\n",
       "    function code_toggle() {\n",
       "        if ($('div.cell.code_cell.rendered.selected div.input').css('display')!='none'){\n",
       "            $('div.cell.code_cell.rendered.selected div.input').hide();\n",
       "        } else {\n",
       "            $('div.cell.code_cell.rendered.selected div.input').show();\n",
       "        }\n",
       "    }\n",
       "    </script>\n",
       "\n",
       "\n",
       "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Show Sloution\"></form>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "toggle_code_str = '''\n",
    "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Show Sloution\"></form>\n",
    "'''\n",
    "\n",
    "toggle_code_prepare_str = '''\n",
    "    <script>\n",
    "    function code_toggle() {\n",
    "        if ($('div.cell.code_cell.rendered.selected div.input').css('display')!='none'){\n",
    "            $('div.cell.code_cell.rendered.selected div.input').hide();\n",
    "        } else {\n",
    "            $('div.cell.code_cell.rendered.selected div.input').show();\n",
    "        }\n",
    "    }\n",
    "    </script>\n",
    "\n",
    "'''\n",
    "\n",
    "def toggle_code():\n",
    "    display(HTML(toggle_code_str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Show Sloution\"></form>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cars.scatter('msrp','mpg')\n",
    "\n",
    "toggle_code()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <script>\n",
       "    function code_toggle() {\n",
       "        if ($('div.cell.code_cell.rendered.selected div.input').css('display')!='none'){\n",
       "            $('div.cell.code_cell.rendered.selected div.input').hide();\n",
       "        } else {\n",
       "            $('div.cell.code_cell.rendered.selected div.input').show();\n",
       "        }\n",
       "    }\n",
       "    </script>\n",
       "\n",
       "\n",
       "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Click Here to Hide Code Above\n",
       " (Too Advanced for Us)\"></form>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.core.display import display, HTML\n",
    "toggle_code_str = '''\n",
    "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Click Here to Hide Code Above\n",
    " (Too Advanced for Us)\"></form>\n",
    "'''\n",
    "\n",
    "toggle_code_prepare_str = '''\n",
    "    <script>\n",
    "    function code_toggle() {\n",
    "        if ($('div.cell.code_cell.rendered.selected div.input').css('display')!='none'){\n",
    "            $('div.cell.code_cell.rendered.selected div.input').hide();\n",
    "        } else {\n",
    "            $('div.cell.code_cell.rendered.selected div.input').show();\n",
    "        }\n",
    "    }\n",
    "    </script>\n",
    "\n",
    "'''\n",
    "\n",
    "display(HTML(toggle_code_prepare_str + toggle_code_str))\n",
    "\n",
    "def hide_code():\n",
    "    display(HTML(toggle_code_str))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<form action=\"javascript:code_toggle()\"><input type=\"submit\" id=\"toggleButton\" value=\"Click Here to Hide Code Above\n",
       " (Too Advanced for Us)\"></form>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hide_code()\n",
    "\n",
    "cars.scatter('msrp','mpg')\n",
    "plots.title(\"Hide Code\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Occasionally we'll see something like this in the code:\n",
    "\n",
    "\n",
    "\n",
    "<input type=\"submit\"  id=\"toggleButton\" value=\"Click Here to Hide Code Above\n",
    " (Too Advanced for Us)\">\n",
    "\n",
    "That means that a bunch of Python code was used to create something, usually a graphic, whose REAL purpose is to demonstrate something statistical or mathematical, AND the code to create it is either more advanced than we're supposed to worry with, or just really long.  Either way, just click the button to hide the code, forget about it, then focus on the thing the code is demonstrating.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}