balloon_size_and_cost.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 風船に必要となるヘリウムの値段を計算"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div align=\"center\">\n",
    "<img src=http://www.balloon-pop.com/images/size.jpg width=400>\n",
    "http://www.balloon-pop.com/fs/balloons/c/round_s7?sort=04\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11beecd90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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trFt3NvWsOGluHsW8eS0sWdLKvHkth22yAeX+h1fmvoP77/63N7oJDVPmvhet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\nTjjMzMyscP8fcIW44MZSH3kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11bc9db90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "diameter = np.array([90, 120, 165, 180, 240, 360, 510])\n",
    "volume = np.array([382, 904, 2351, 3052, 7235, 24417, 69421])\n",
    "\n",
    "# ヘリウム400リットル当たり7000円で換算\n",
    "helium_cost = 7000 * volume / 400.0\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(8, 4))\n",
    "ax.plot(volume, helium_cost, 'o')\n",
    "ax.set_xlabel('Volume [Litter]')\n",
    "ax.set_ylabel('Helium cost [Yen]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>diameter</th>\n",
       "      <th>volume</th>\n",
       "      <th>helium_cost</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>90</td>\n",
       "      <td>382</td>\n",
       "      <td>6685.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>120</td>\n",
       "      <td>904</td>\n",
       "      <td>15820.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>165</td>\n",
       "      <td>2351</td>\n",
       "      <td>41142.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>180</td>\n",
       "      <td>3052</td>\n",
       "      <td>53410.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>240</td>\n",
       "      <td>7235</td>\n",
       "      <td>126612.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>360</td>\n",
       "      <td>24417</td>\n",
       "      <td>427297.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>510</td>\n",
       "      <td>69421</td>\n",
       "      <td>1214867.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   diameter  volume  helium_cost\n",
       "0        90     382       6685.0\n",
       "1       120     904      15820.0\n",
       "2       165    2351      41142.5\n",
       "3       180    3052      53410.0\n",
       "4       240    7235     126612.5\n",
       "5       360   24417     427297.5\n",
       "6       510   69421    1214867.5"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(data=np.array([diameter, volume, helium_cost]).T, \n",
    "                  columns=['diameter','volume', 'helium_cost'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 球の直径から体積を計算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def diameter2volume(d):\n",
    "    # Args:\n",
    "    #   d (float): 球の直径 [cm]\n",
    "    # Returns:\n",
    "    #   float: 球の体積\n",
    "    \n",
    "    import numpy as np\n",
    "    \n",
    "    # 球の半径[cm]を計算\n",
    "    r = d / 2.0 \n",
    "   \n",
    "    # 球の体積[cm^3]を計算\n",
    "    volume = (4.0 / 3.0 ) * np.pi * r ** 3\n",
    "    \n",
    "    # 球の体積の単位をcm^3からリットルに変換\n",
    "    volume = volume / 1000.0    \n",
    "    \n",
    "    return volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "球の体積（計算した値）: [   382.    905.   2352.   3054.   7238.  24429.  69456.]\n",
      "球の体積（HPにあった値）: [  382   904  2351  3052  7235 24417 69421]\n"
     ]
    }
   ],
   "source": [
    "computed_volume = diameter2volume(diameter)\n",
    "computed_volume = computed_volume.round()\n",
    "print(\"球の体積（計算した値）: %s\" % computed_volume)\n",
    "print(\"球の体積（HPにあった値）: %s\" % volume)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x106c51350>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jvWnH6HBFEDszXDRsEhzocM7LnkMwxpgKMvXl/dzaY1+1SAa+sLmMjDHGB1qi\nTPwggkn/Lgp0KH5nVwjGGOODL2fuweWCbrfUnMHkkywhGGOMD5ru/Z7xI7MQV/WeyO5sLCEYY0x5\nHT9Oh+OrufmB+EBHUiEsIRhjTHmtXw+JiVCNV0U7F0sIxhhTHqqwejV07hzoSCqMJQRjjCmPPXsg\nPx/atAl0JBXGEoIxxpTDsS+deYuk5g0mn2RPKhtjzHmcOFZIXPMCvl9bQnRC9VsIx55UNsYYP5n9\nf7u5ss3RapkMfGEJwRhjzuPNqUHcd09xoMOocOdNCCISIiIrRGSNiKwXkdFOeYSILBKRzSKyUEQa\nebUZKSJpIrJRRG7yKu8sIutEZIuIjPcqDxaRaU6br0Ukzt8HaowxF2L7t4dZt7Mx/X/XPNChVLjz\nJgRVzQeuU9VOwJVAHxHpAowAFqtqe2AJMBJARJKAgUAHoA8wQcQzCvM6MExV2wHtRORmp3wYcEhV\n2wLjgRf9dYDGGHMx3nolm7tu2k9IaM1YFe1cytVlpKp5zmYI7gnxFOgPTHHKpwADnO1+wDRVLVLV\nHUAa0EVEmgENVfUbp95Urzbe+5oF3HBBR2OMMf5UXEzD7F3c98fwQEdSKcqVEETEJSJrgL3Ap85J\nPUZVswBUdS8Q7VRvCezyap7plLUEMrzKM5yyUm1UtRjIFpHICzoiY4zxl7Q0nrhtK5f2iAh0JJWi\nXNNfq2oJ0ElEwoHZInIp7quEUtX8GFeZt0eNGTPGs52cnExycrIfv60xxnippk8mp6amkpqa6nM7\nn9ZDUNWjIpIK9AayRCRGVbOc7qB9TrVMINarWSunrKxy7za7RaQOEK6qh84Wg3dCMMaYCnP0KOza\nBb/+daAj8dnpH5affvrpcrUrz11GTU/eQSQi9YGfAxuBucBQp9oQYI6zPRdIce4cagMkAiudbqUj\nItLFGWQefFqbIc727bgHqY0xJnDWroWkJAiuWauinUt5rhCaA1NExIU7gUxX1Xki8l9ghojcC6Tj\nvrMIVd0gIjOADUAh8JDX48UPA5OBesA8VV3glE8E3haRNOAgkOKXozPGmAuhCmvWwG23BTqSSmVT\nVxhjzGm+nLGb/3spl/dWJtaIuYts6gpjjLlAb75eyNXdgmtEMvCFXSEYY4yXI3uPE99G2LKxhOjW\noYEOxy/sCsEYYy7AtPF7ubHjgRqTDHxhCcEYY7y8OS2M+x6onafG2nnUxhhzFoc27CWsbgE/H1zz\nJ7I7G0vDWDf4AAAUX0lEQVQIxhjjiPzxW1InbqNO3do1mHySJQRjjAEoLITvv4crrwx0JAFjCcEY\nYwA2bICWLaFRo/PXraEsIRhjDLifTK6GE9n5kyUEY4w5eBD274f27QMdSUDZg2nGmFpp+dy5FGzb\nBsDjL68lpWNHrroRghMS6N6vX4Cj8y97MM0YY84hJiGB2MxM9i9fx+rMRtTJSyM2M5OYhIRAhxYw\nlhCMMbVSQlISaVFR/M+n+SjjmZ62j7SoKBKSkgIdWsBYQjDG1Eoiwvx19Uk7ejcgrNt3N9uCI5Fa\nNqGdN0sIxphaKfXtnUyYtg33ApBwvLAf70z/gdo8TmkJwRhT+2zaRNqcVwgK6s2pJdyF9et788EH\niwIZWUD5tKayMcZUexs2wLx5bIhoRJeu/wX+y9HDhwmPiADgyy8bcNttNwc2xgCx206NMbXHDz/A\n/Plw113QrFmgo6k05b3t1K4QjDG1w/r1sHAh3H03xMQEOpoqya4QjDE13vQX0/nh0938v/8kQHR0\noMOpdHaFYIwxwH+e3cGfX2jKwrkNIToy0OFUaZYQjDE11pSnf2TkK1F8Oq+Iy3pYMjgfSwjGmBpp\n4v/8yOh/NOWzBUV06NY40OFUC+d9DkFEWonIEhH5QUTWi8ijTnmEiCwSkc0islBEGnm1GSkiaSKy\nUURu8irvLCLrRGSLiIz3Kg8WkWlOm69FJM7fB2qMqT0KvlzJ+x/Akk9LLBn4oDwPphUBf1TVS4Fu\nwMMi8hNgBLBYVdsDS4CRACKSBAwEOgB9gAly6lnw14FhqtoOaCciJ2/2HQYcUtW2wHjgRb8cnTGm\n9vnqK4K//Zp5X0XQ7qe1d7GbC3HehKCqe1X1O2c7B9gItAL6A1OcalOAAc52P2Caqhap6g4gDegi\nIs2Ahqr6jVNvqlcb733NAm64mIMyxtRSX34Jq1bB0KHQ2K4MfOXT1BUi0hq4EvgvEKOqWeBOGsDJ\ne7laAru8mmU6ZS2BDK/yDKesVBtVLQayRcRGgIwx5bdsGXz3nTsZ1OJlMC9GuQeVRaQB7k/vj6lq\njoic/kCAPx8QKPN+2TFjxni2k5OTSU5O9uO3NcZUO6rMe2E9vcPW4xo6BBo2DHREAZeamkpqaqrP\n7cr1YJqI1AU+Buar6qtO2UYgWVWznO6gparaQURGAKqqLzj1FgCjgfSTdZzyFKCXqj54so6qrhCR\nOsAeVT3j6RF7MM0YU4oq/++eH3l3QQTLVwTRJL5BoCOqkvy9YtpbwIaTycAxFxjqbA8B5niVpzh3\nDrUBEoGVTrfSERHp4gwyDz6tzRBn+3bcg9TGGFMmLVFG3f0j0xc1JvWrEEsGfnDeKwQR6Q4sA9bj\n7hZS4ElgJTADiMX96X+gqmY7bUbivnOoEHcX0yKn/CpgMlAPmKeqjznlIcDbQCfgIJDiDEifHotd\nIRhj0BLlqTt+5OMvG7H4y/pEtw4NdEhVWnmvEGwuI2NM9aLK3x/cyKR50Xy6PIymsfUDHVGVZwnB\nGFPzqMK8eRxMO4QMvJ3IFvUCHVG1YAnBGFOzqMLHH8O+fe71DEJCAh1RtWGznRpjao6SEvjoIzh0\nyJJBBbKEYIyp0kqKStAP51An5wjceScEBwc6pBrLEoIxpsoqLixh2E07uTQmjsffvgKCggIdUo1m\nYwjGmCqpKL+YoTdmsOdQMHOXNyWssSWDC2VjCMaYaqsov5i7rsvkcE4wH/83ivoN7VRVGeynbIyp\nUgqPFzEoeTfHC+ow56so6jWw01Rl8Wm2U2OMqVBFRRx/530Sm+XywfJmlgwqmY0hGGOqhsJCmD7d\nfUvpr34FdeoEOqIaw8YQjDHVR2EhvPcehIXBrbeCyzovAsESgjEmsAoK4N133Yva9O9vySCA7Cdv\njAmY3EP5PHfHOorCIy0ZVAF2hWCMCYhjB/L5ZfdDJMRGI/2uAtd5u7hNBbN0bIypdEf3naBPt8O0\nb1PImwtjqVPXkkFVYAnBGFOpjuw9zs0/O8IV7fP55yexuOpYMqgq7LZTY0zlycvjoT4/UrdxA16d\nHYdYN1GlsPUQjDFVS24uTJ1KXqt21O97vSWDSmTPIRhjqo6cHJg6FX7yE0Kvuw7EkkFVZAnBGFOx\njh1zJ4NLL4VevSwZVGGWEIwxFWb/9mM0mjOV4Ksuh2uvDXQ45jzsLiNjTIXI3HiUHt2K+Cj3eksG\n1YQlBGOM3+36/gjJ15Zw721Hue1/OgQ6HFNO500IIjJRRLJEZJ1XWYSILBKRzSKyUEQaeX1tpIik\nichGEbnJq7yziKwTkS0iMt6rPFhEpjltvhaROH8eoDGmcqWvO0KvXvDgHdk8MSE+0OEYH5TnCmES\ncPNpZSOAxaraHlgCjAQQkSRgINAB6ANMEPGMIL0ODFPVdkA7ETm5z2HAIVVtC4wHXryI4zHGBNDO\nddkkXwfD78nmj6+2DnQ4xkfnTQiq+iVw+LTi/sAUZ3sKMMDZ7gdMU9UiVd0BpAFdRKQZ0FBVv3Hq\nTfVq472vWcANF3AcxphAO3iQJp9M5eURB3j0b3ZlUB1d6F1G0aqaBaCqe0Uk2ilvCXztVS/TKSsC\nMrzKM5zyk212OfsqFpFsEYlU1UMXGJsxprIdOABTpxLW+zp+1Skh0NGYC+Sv2079+fjwOW9SHjNm\njGc7OTmZ5ORkP35rY4zP9u2Dt9+GG2+Ejh0DHY0BUlNTSU1N9blduaauEJF44CNVvcJ5vxFIVtUs\npztoqap2EJERgKrqC069BcBoIP1kHac8Beilqg+erKOqK0SkDrBHVaPPjMKmrjCmysnKcieDm2+G\nyy8PdDSmDOWduqK8t50KpT+5zwWGOttDgDle5SnOnUNtgERgparuBY6ISBdnkHnwaW2GONu34x6k\nNsZUcWsX72fYLfvQ3n0sGdQQ5+0yEpF3gWSgiYjsxP2J/3lgpojci/vT/0AAVd0gIjOADUAh8JDX\nR/qHgclAPWCeqi5wyicCb4tIGnAQSPHPoRljKsrqhfv5xa9Dee3/NUYuiw10OMZPbLZTY4xPVs3b\nR9/fhPH6s4f51aOtAh2OKQeb7dQY43cr5mbR784G/PvFbPo9aMmgprErBGPMWS2fO5eCbdsA+Pcn\nX3F/t58wdtL13DzgOH/+xy8CHJ3xhV0hGGMuSkxCAixbxnc7D/Lxsqbctu8zJty8B3nwD4EOzVQQ\nm9zOGHMGLVHaRDcjrbCQv322j2OFE3hpXwxb27UlISkp0OGZCmJXCMYYSoqVjV8e5Iv5x/hieR2W\nrY9gXL/l7JVC1h15ABDWHRrKtuB9iC1wU2PZFYIxtVFxMezaBcuX8/q9K4kOP06/24L478o6XH89\nLPm0mF9N+iXvbA7meHE/AI4X9uOd6T9g43g1lw0qG1ML5GUXcOD7PcQVboedOyEzEyIjIT6e9LoJ\nBLVuSYu2YaXazJq1gCFDhLy8U5Mdh4YuYOpU4bbbTp8A2VRlNqhsTC12KCOP5R8d4oulhXzxbSjr\ndkXwQPIxxv2lGK65BmJjoV49AMqal3T58vVcfXUO8BVHDx8mPCICgC+/bGAJoYayKwRjaoIjR9yf\n/NPTWfd1Lj1eHkDXxEP07JJPz5/Xo+svmhDaKCjQUZoAKe8VgiUEY6oZLVHSvjnMqsXZ3JG0FtLT\noaAA4uMhPp6SVnEURzUjKMSGCI2bdRkZU1OUlLBm8QGWzc/ji6/q8MWGSELq1qXn5UH8+oZ4gnv2\nhCZNwLn7x4XdLWIujF0hGFPVFBW5B33T092vjAz6v5dCsxYuevZy0fOXjYi/PDzQUZpqxLqMjKkm\nju47wdcfH+SLzwq4vd1aOgZtgKgodxdQXJz7FRoa6DBNNWZdRsZUVTk5fDVnPzNmCl+sDmNzViOu\nalOHnlcLYT07Q49fQHBwoKM0tZBdIRhzgc6Y/K3vNQAEJyTQvZ/7YS5UITv7VPfPzp2Ql8cHe7ux\n5XgcPW+qz9W9mxISWidQh2FqAesyMqaCbf3hB5g0ie92HuTeOfWZ1P8El8c2YetlA0nfFMUXy13E\nBe/l+b5fnOr+iY+H6GjPALAxlcG6jEyVUK5P0VWUligncorIO1Lofh0rhsJC2sefgMJCEkRYUFTE\n31IPcqxgDvfNfoAi/oeYxkrPK45y442Q3L89XPlTSwCmWrCEYCpUqSmUv4jitsj1dIyLhJtuuqj9\naomSn1tEbnYheUeLyDtWTN7RQqSoiCvb5UFhYalXVha8NiOGvONC3nGcf13ENMzj/+78yl2voMBT\nf/2uxnT8x/0E1xXCgoXQYBehwSVc0SqHmQ9/DkFBSHAw244Use7gMEDIK+nHqCfe5amxDwKN/fLz\nM6YyWUIwFSq2dTtmaAteWrqLYwVvMeqzQfxtSGN6FxXBt996TsD79sHz/4n1nKxzj7vIO+EiKuw4\nU4cuOeOEvXlPI65843eEBjkn7BAIDXHxk+YneO/3X0NQ0KlXcDCuolBC6gkRkRDWQAgNE0LDICo6\nDHpcX7p+UBCX1gmicBzUqVuX0v9NIoAEAFSVd8Z9zfES95VOQckv+WjJH3hS1WYENdWSJQTjkxPH\nCtm/8zj7M/LZv7uQE0fy6d91L+Tmul95eZCbS3pGHTq+MIjcgiDqB7UmJ/8ngLDp0F1sO/AJsnVr\nqRNwUEh9WrbEOVELYQ0gtAFENg2DLn3dd9141f9JUBAn/iGc+SfcFLjkjLijgL/eVv7jLM+DXe+/\nv5D16/sAJ0/+wvr1vfngg0U214+plmxQuZbLyy4odYLPOVzA7d33nHGC35elJD4zhBNFdYkKO05U\n+AmiGxeQ0OIEr/9hi/s++bAw9ys0lOJ6YRwpDKVRTAjde/yRFSvG4T5xKl27/oGvvx5X7T9F/+EP\nL7F6dQ5AqcnfOnduwLhxjwcyNGNKsbuMqgl/DrpqiZJ7uID9u064X3uKOHKgkDt6ZZ5xgs85XEiz\nUfdTVOIiqsFxohqeIKpxIa2iCpj4l81nnOBL6odxrDiU8KgQxFX+E7lNoWxM4FW7u4xEpDcwHvfV\n+kRVfSHAIVWKcw26aoly7EC+++TufII/kFXE0BsykLzSJ/iiY8dp9ORDKC6iGghRDV1ENRZimgiD\nrspFGoS5n351TvBhoWHsGaY0iKyDuBoCDb2ian1GnC6g0QUcn02hbEz1USWuEETEBWwBbgB2A98A\nKaq66bR6uuSVV4CqcdticWEJ+XnFnMgpcv+b6361b52PS4vdc9J4vd79qAG5ucKJ40r+CeXECTh+\nAroGPcfYj3ez4uCf6BrxEqN7hXBz9x5E/vXhU5/gw/OJalxIVEQx/358C0GNQk99inf+zdVQwiKq\n7hOuqampJCcnBzqMClGTjw3s+Kq76naF0AVIU9V0ABGZBvQHNp1e8dDX67kiNpLCa2/k6P588nOL\naNKoCFeJc+ItPnUiXrg0mJxjzsnX6yT8UL8MQlyFpepSVMSwv3fkcE5d8gtcnHBe+YUulj46m4Z1\nj59Rv8nYv5BfXId6dYV6QRBSV6gXJHwzch4Nw0qgbt1Sr9SlV1OiQr16UC9ECAlxr1GyLSSKddl9\ngc9Zd+wBtnXciuv++9j72zrUaxgEnH6SjzvrDzHsrKVVR03+T1eTjw3s+GqLqpIQWgK7vN5n4E4S\nZ7h9ZkOUFwgaDyF1i6gXJGwZ8Q4R4cVQp06pE/Bb/06msKQOIcFKvRAICRbqhShFeQWENHRBSIj7\nE7ZTv09fF1JXqFcf6tVXQkKhXijU7zgA6tU9Y/+H/8fl9KefvvDIsLMe5L9uP7NMVenWLddZt3YN\nx4v6886CP/Dw6HDqVfNBV2NM9VJVEkK51at7Pc8/P5FH//QAcHL+l4fPWnf6kLL20vqspb/u5Fss\n/jhd262LxpiqoqqMIfwMGKOqvZ33IwA9fWBZRAIfrDHGVEPV5rZTEakDbMY9qLwHWAkMUtWNAQ3M\nGGNqkSrRZaSqxSLye2ARp247tWRgjDGVqEpcIRhjjAm8arMWt4j0FpFNIrJFRJ4IdDz+JCITRSRL\nRNYFOhZ/E5FWIrJERH4QkfUi8migY/InEQkRkRUissY5vtGBjqkiiIhLRFaLyNxAx+JvIrJDRNY6\nv8OVgY7Hn0SkkYjMFJGNzv/BruesXx2uEMr74Fp1JSI9gBxgqqpeEeh4/ElEmgHNVPU7EWkAfAv0\nrym/OwARCVXVPGcsbDnwqKrWtBPLH4CrgHBVrdoLWfhIRLYDV6nq4UDH4m8iMhn4XFUniUhdIFRV\nj5ZVv7pcIXgeXFPVQuDkg2s1gqp+CdS4P0YAVd2rqt852znARtzPndQYqprnbIbgHper+p+yfCAi\nrYBfAG8GOpYKIlSfc2G5iUg40FNVJwGoatG5kgFUnx/C2R5cq1EnldpARFoDVwIrAhuJfzndKWuA\nvcCnqvpNoGPys3HA49SwROdFgU9F5BsRuT/QwfhRG+CAiExyuvv+JSL1z9WguiQEU8053UWzgMec\nK4UaQ1VLVLUT0AroKiJJgY7JX0SkL5DlXOUJ/nkes6rprqqdcV8FPex04dYEdYHOwP85x5cHjDhX\ng+qSEDIpPYFPK6fMVANO3+Us4G1VnRPoeCqKczm+FOgd6Fj8qDvQz+lnfw+4TkSmBjgmv1LVPc6/\n+4HZlDFtTjWUAexS1VXO+1m4E0SZqktC+AZIFJF4EQkGUoCadrdDTf30BfAWsEFVXw10IP4mIk1F\npJGzXR/4OWeZlLG6UtUnVTVOVS/B/f9uiaoODnRc/iIioc7VKyISBtwEfB/YqPxDVbOAXSLSzim6\nAdhwrjZV4sG086npD66JyLtAMtBERHYCo08OBFV3ItIduBNY7/SzK/Ckqi4IbGR+0xyY4twJ5wKm\nq+q8AMdkyi8GmO1Mi1MX+I+qLgpwTP70KPAfEQkCtgP3nKtytbjt1BhjTMWrLl1GxhhjKpglBGOM\nMYAlBGOMMQ5LCMYYYwBLCMYYYxyWEIwxxgCWEIwxxjgsIRhjjAHg/wNbMbOsvhLahAAAAABJRU5E\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106c513d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(computed_volume, 'v-r', label='computed', alpha=0.5)\n",
    "plt.plot(volume, '^--', label='values on the webpage')\n",
    "plt.legend()\n",
    "# http://www.balloon-pop.com/fs/balloons/c/round_s7?sort=04"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}