ch08-analysis-and-viz.ipynb

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  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "decays_arr = np.loadtxt('data/decays.csv', delimiter=\",\", skiprows=1)\n",
      "decays_arr"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "array([[  0.00000000e+00,   1.00000000e+01],\n",
        "       [  1.00000000e+00,   1.35335283e+00],\n",
        "       [  2.00000000e+00,   1.83156389e-01],\n",
        "       [  3.00000000e+00,   2.47875220e-02],\n",
        "       [  4.00000000e+00,   3.35462600e-03],\n",
        "       [  5.00000000e+00,   4.53999000e-04],\n",
        "       [  6.00000000e+00,   6.14420000e-05],\n",
        "       [  7.00000000e+00,   8.31500000e-06],\n",
        "       [  8.00000000e+00,   1.12600000e-06],\n",
        "       [  9.00000000e+00,   1.52000000e-07]])"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "decays_df = pd.read_csv('data/decays.csv') \n",
      "decays_df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Time (s)</th>\n",
        "      <th>Decays (#)</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>0</td>\n",
        "      <td>1.000000e+01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>1.353353e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>2</td>\n",
        "      <td>1.831564e-01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>3</td>\n",
        "      <td>2.478752e-02</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>4</td>\n",
        "      <td>3.354626e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>5</td>\n",
        "      <td>4.539990e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>6</td>\n",
        "      <td>6.144200e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>7</td>\n",
        "      <td>8.315000e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>8</td>\n",
        "      <td>1.126000e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>9</td>\n",
        "      <td>1.520000e-07</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "   Time (s)    Decays (#)\n",
        "0         0  1.000000e+01\n",
        "1         1  1.353353e+00\n",
        "2         2  1.831564e-01\n",
        "3         3  2.478752e-02\n",
        "4         4  3.354626e-03\n",
        "5         5  4.539990e-04\n",
        "6         6  6.144200e-05\n",
        "7         7  8.315000e-06\n",
        "8         8  1.126000e-06\n",
        "9         9  1.520000e-07"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# can convert to HDF5 format\n",
      "#decays_df.to_hdf('decays.h5', 'experimental')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import blaze as bz\n",
      "csv_data = bz.CSV('data/decays.csv')\n",
      "decays_tb = bz.Table(csv_data)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "decay_df = pd.read_csv(\"data/many_decays.csv\")\n",
      "decay_df.count()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "Time      50\n",
        "Decays    46\n",
        "dtype: int64"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "decay_df.dropna()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Time</th>\n",
        "      <th>Decays</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>2014-11-08T05:19:31.561782</td>\n",
        "      <td>1.000000e+01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2014-11-08T05:19:32.561782</td>\n",
        "      <td>1.353353e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>2014-11-08T05:19:33.561782</td>\n",
        "      <td>1.831564e-01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>2014-11-08T05:19:34.561782</td>\n",
        "      <td>2.478752e-02</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>2014-11-08T05:19:35.561782</td>\n",
        "      <td>3.354626e-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>2014-11-08T05:19:36.561782</td>\n",
        "      <td>4.539993e-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
        "      <td>2014-11-08T05:19:37.561782</td>\n",
        "      <td>6.144212e-05</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
        "      <td>2014-11-08T05:19:38.561782</td>\n",
        "      <td>8.315287e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
        "      <td>2014-11-08T05:19:39.561782</td>\n",
        "      <td>1.125352e-06</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>2014-11-08T05:19:40.561782</td>\n",
        "      <td>1.522998e-07</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>2014-11-08T05:19:41.561782</td>\n",
        "      <td>2.061154e-08</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>2014-11-08T05:19:42.561782</td>\n",
        "      <td>2.789468e-09</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
        "      <td>2014-11-08T05:19:43.561782</td>\n",
        "      <td>3.775135e-10</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
        "      <td>2014-11-08T05:19:44.561782</td>\n",
        "      <td>5.109089e-11</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>14</th>\n",
        "      <td>2014-11-08T05:19:45.561782</td>\n",
        "      <td>6.914400e-12</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>15</th>\n",
        "      <td>2014-11-08T05:19:46.561782</td>\n",
        "      <td>9.357623e-13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>16</th>\n",
        "      <td>2014-11-08T05:19:47.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>17</th>\n",
        "      <td>2014-11-08T05:19:48.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>18</th>\n",
        "      <td>2014-11-08T05:19:49.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>19</th>\n",
        "      <td>2014-11-08T05:19:50.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
        "      <td>2014-11-08T05:19:51.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>21</th>\n",
        "      <td>2014-11-08T05:19:52.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
        "      <td>2014-11-08T05:19:53.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>23</th>\n",
        "      <td>2014-11-08T05:19:54.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>24</th>\n",
        "      <td>2014-11-08T05:19:55.561782</td>\n",
        "      <td>2.000000e+00</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25</th>\n",
        "      <td>2014-11-08T05:19:56.561782</td>\n",
        "      <td>1.928750e-21</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>26</th>\n",
        "      <td>2014-11-08T05:19:57.561782</td>\n",
        "      <td>2.610279e-22</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>27</th>\n",
        "      <td>2014-11-08T05:19:58.561782</td>\n",
        "      <td>3.532629e-23</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>28</th>\n",
        "      <td>2014-11-08T05:19:59.561782</td>\n",
        "      <td>4.780893e-24</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>29</th>\n",
        "      <td>2014-11-08T05:20:00.561782</td>\n",
        "      <td>6.470235e-25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>30</th>\n",
        "      <td>2014-11-08T05:20:01.561782</td>\n",
        "      <td>8.756511e-26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>31</th>\n",
        "      <td>2014-11-08T05:20:02.561782</td>\n",
        "      <td>1.185065e-26</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>32</th>\n",
        "      <td>2014-11-08T05:20:03.561782</td>\n",
        "      <td>1.603811e-27</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>33</th>\n",
        "      <td>2014-11-08T05:20:04.561782</td>\n",
        "      <td>2.170522e-28</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>34</th>\n",
        "      <td>2014-11-08T05:20:05.561782</td>\n",
        "      <td>2.937482e-29</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>35</th>\n",
        "      <td>2014-11-08T05:20:06.561782</td>\n",
        "      <td>3.975450e-30</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>36</th>\n",
        "      <td>2014-11-08T05:20:07.561782</td>\n",
        "      <td>5.380186e-31</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>37</th>\n",
        "      <td>2014-11-08T05:20:08.561782</td>\n",
        "      <td>7.281290e-32</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>38</th>\n",
        "      <td>2014-11-08T05:20:09.561782</td>\n",
        "      <td>9.854155e-33</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>39</th>\n",
        "      <td>2014-11-08T05:20:10.561782</td>\n",
        "      <td>1.333615e-33</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>40</th>\n",
        "      <td>2014-11-08T05:20:11.561782</td>\n",
        "      <td>1.804851e-34</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>45</th>\n",
        "      <td>2014-11-08T05:20:16.561782</td>\n",
        "      <td>8.194013e-39</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>46</th>\n",
        "      <td>2014-11-08T05:20:17.561782</td>\n",
        "      <td>1.108939e-39</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>47</th>\n",
        "      <td>2014-11-08T05:20:18.561782</td>\n",
        "      <td>1.500786e-40</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>48</th>\n",
        "      <td>2014-11-08T05:20:19.561782</td>\n",
        "      <td>2.031093e-41</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>49</th>\n",
        "      <td>2014-11-08T05:20:20.561782</td>\n",
        "      <td>2.748785e-42</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "                          Time        Decays\n",
        "0   2014-11-08T05:19:31.561782  1.000000e+01\n",
        "1   2014-11-08T05:19:32.561782  1.353353e+00\n",
        "2   2014-11-08T05:19:33.561782  1.831564e-01\n",
        "3   2014-11-08T05:19:34.561782  2.478752e-02\n",
        "4   2014-11-08T05:19:35.561782  3.354626e-03\n",
        "5   2014-11-08T05:19:36.561782  4.539993e-04\n",
        "6   2014-11-08T05:19:37.561782  6.144212e-05\n",
        "7   2014-11-08T05:19:38.561782  8.315287e-06\n",
        "8   2014-11-08T05:19:39.561782  1.125352e-06\n",
        "9   2014-11-08T05:19:40.561782  1.522998e-07\n",
        "10  2014-11-08T05:19:41.561782  2.061154e-08\n",
        "11  2014-11-08T05:19:42.561782  2.789468e-09\n",
        "12  2014-11-08T05:19:43.561782  3.775135e-10\n",
        "13  2014-11-08T05:19:44.561782  5.109089e-11\n",
        "14  2014-11-08T05:19:45.561782  6.914400e-12\n",
        "15  2014-11-08T05:19:46.561782  9.357623e-13\n",
        "16  2014-11-08T05:19:47.561782  2.000000e+00\n",
        "17  2014-11-08T05:19:48.561782  2.000000e+00\n",
        "18  2014-11-08T05:19:49.561782  2.000000e+00\n",
        "19  2014-11-08T05:19:50.561782  2.000000e+00\n",
        "20  2014-11-08T05:19:51.561782  2.000000e+00\n",
        "21  2014-11-08T05:19:52.561782  2.000000e+00\n",
        "22  2014-11-08T05:19:53.561782  2.000000e+00\n",
        "23  2014-11-08T05:19:54.561782  2.000000e+00\n",
        "24  2014-11-08T05:19:55.561782  2.000000e+00\n",
        "25  2014-11-08T05:19:56.561782  1.928750e-21\n",
        "26  2014-11-08T05:19:57.561782  2.610279e-22\n",
        "27  2014-11-08T05:19:58.561782  3.532629e-23\n",
        "28  2014-11-08T05:19:59.561782  4.780893e-24\n",
        "29  2014-11-08T05:20:00.561782  6.470235e-25\n",
        "30  2014-11-08T05:20:01.561782  8.756511e-26\n",
        "31  2014-11-08T05:20:02.561782  1.185065e-26\n",
        "32  2014-11-08T05:20:03.561782  1.603811e-27\n",
        "33  2014-11-08T05:20:04.561782  2.170522e-28\n",
        "34  2014-11-08T05:20:05.561782  2.937482e-29\n",
        "35  2014-11-08T05:20:06.561782  3.975450e-30\n",
        "36  2014-11-08T05:20:07.561782  5.380186e-31\n",
        "37  2014-11-08T05:20:08.561782  7.281290e-32\n",
        "38  2014-11-08T05:20:09.561782  9.854155e-33\n",
        "39  2014-11-08T05:20:10.561782  1.333615e-33\n",
        "40  2014-11-08T05:20:11.561782  1.804851e-34\n",
        "45  2014-11-08T05:20:16.561782  8.194013e-39\n",
        "46  2014-11-08T05:20:17.561782  1.108939e-39\n",
        "47  2014-11-08T05:20:18.561782  1.500786e-40\n",
        "48  2014-11-08T05:20:19.561782  2.031093e-41\n",
        "49  2014-11-08T05:20:20.561782  2.748785e-42"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "\n",
      "# as in the previous example, load decays.csv into a NumPy array\n",
      "decaydata = np.loadtxt('data/decays.csv', delimiter=\",\", skiprows=1)\n",
      "\n",
      "# provide handles for the x and y columns\n",
      "time = decaydata[:,0]\n",
      "decays = decaydata[:,1]\n",
      "\n",
      "# import the matplotlib plotting functionality\n",
      "import matplotlib\n",
      "%matplotlib inline\n",
      "import pylab as plt\n",
      "\n",
      "plt.plot(time, decays)\n",
      "\n",
      "plt.xlabel('Time (s)')\n",
      "plt.ylabel('Decays')\n",
      "plt.title('Decays')\n",
      "plt.grid(True)\n",
      "#plt.savefig(\"decays_matplotlib.png\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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LdC1wRsnvcETsTCXZBgHPAqMi52gBlgDD8uVfAadHzvROYD6wVV5D7wb27m39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\noi8i0kBU9EVEGoiKvohIA/n/I0D+cPwPOO8AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f36d2ee4128>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Import various necessary Python and matplotlib packages\n",
      "import numpy as np\n",
      "import matplotlib.cm as cm\n",
      "from matplotlib.pyplot import figure, show, rc\n",
      "from matplotlib.patches import Ellipse\n",
      "\n",
      "# Create a square figure on which to place the plot\n",
      "fig = figure(figsize=(8,8))\n",
      "\n",
      "# Create square axes to hold the circular polar plot\n",
      "ax = fig.add_axes([0.1, 0.1, 0.8, 0.8], polar=True)\n",
      "\n",
      "# Generate 20 colored, angular wedges for the polar plot\n",
      "N = 20\n",
      "theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)\n",
      "radii = 10*np.random.rand(N)\n",
      "width = np.pi/4*np.random.rand(N)\n",
      "bars = ax.bar(theta, radii, width=width, bottom=0.0)\n",
      "for r,bar in zip(radii, bars):\n",
      "    bar.set_facecolor(cm.jet(r/10.))\n",
      "    bar.set_alpha(0.5)\n",
      "\n",
      "# Using dictionaries, create a color scheme for the text boxes\n",
      "bbox_args = dict(boxstyle=\"round, pad=0.9\", fc=\"green\", alpha=0.5)\n",
      "bbox_white = dict(boxstyle=\"round, pad=0.9\", fc=\"1\", alpha=0.9)\n",
      "patch_white = dict(boxstyle=\"round, pad=1\", fc=\"1\", ec=\"1\")\n",
      "\n",
      "# Create various boxes with text annotations in them at specific\n",
      "# x and y coordinates\n",
      "ax.annotate(\" \",\n",
      "    xy=(.5,.93),\n",
      "    xycoords='figure fraction',\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=patch_white)\n",
      "\n",
      "ax.annotate('Matplotlib and the Python Ecosystem for Scientific Computing',\n",
      "    xy=(.5,.95),\n",
      "    xycoords='figure fraction',\n",
      "    xytext=(0, 0), textcoords='offset points',\n",
      "    size=15,\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=bbox_args)\n",
      "\n",
      "ax.annotate('Author and Lead Developer \\n of Matplotlib ',\n",
      "    xy=(.5,.82),\n",
      "    xycoords='figure fraction',\n",
      "    xytext=(0, 0), textcoords='offset points',\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=bbox_args)\n",
      "\n",
      "ax.annotate('John D. Hunter',\n",
      "    xy=(.5,.89),\n",
      "    xycoords='figure fraction',\n",
      "    xytext=(0, 0), textcoords='offset points',\n",
      "    size=15,\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=bbox_white)\n",
      "\n",
      "ax.annotate('Friday November 5th  \\n 2:00 pm \\n1106ME ',\n",
      "    xy=(.5,.25),\n",
      "    xycoords='figure fraction',\n",
      "    xytext=(0, 0), textcoords='offset points',\n",
      "    size=15,\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=bbox_args)\n",
      "\n",
      "ax.annotate('Sponsored by: \\n The Hacker Within, \\n'\n",
      "    'The University Lectures Committee, \\n The Department of '\n",
      "    'Medical Physics\\n and \\n The American Nuclear Society',\n",
      "    xy=(.78,.1),\n",
      "    xycoords='figure fraction',\n",
      "    xytext=(0, 0), textcoords='offset points',\n",
      "    size=9,\n",
      "    ha=\"center\", va=\"center\",\n",
      "    bbox=bbox_args)\n",
      "\n",
      "#fig.savefig(\"plot.pdf\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<matplotlib.text.Annotation at 0x7f36d147cf28>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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vCQ8ul4uSkhJT8eni6NyjuUmLlyzuvvLLlYpqUE8XxxTvcF/sXh+0hotEcj5w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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f36d151f128>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "# import the Bokeh plotting tools\n",
      "from bokeh import plotting as bp\n",
      "\n",
      "# as in the matplotlib example, load decays.csv into a NumPy array\n",
      "decaydata = np.loadtxt('data/decays.csv',delimiter=\",\",skiprows=1)\n",
      "\n",
      "# provide handles for the x and y columns\n",
      "time = decaydata[:,0]\n",
      "decays = decaydata[:,1]\n",
      "\n",
      "# define some output file metadata\n",
      "bp.output_file(\"decays.html\", title=\"Experiment 1 Radioactivity\")\n",
      "\n",
      "# create a figure with fun Internet-friendly features (optional)\n",
      "bp.figure(tools=\"pan,wheel_zoom,box_zoom,reset,previewsave\")\n",
      "\n",
      "# on that figure, create a line plot\n",
      "bp.line(time, decays, x_axis_label=\"Time (s)\", y_axis_label=\"Decays (#)\",\n",
      "     color='#1F78B4', legend='Decays per second')\n",
      "\n",
      "# additional customization to the figure can be specified separately\n",
      "bp.curplot().title = \"Decays\"\n",
      "bp.grid().grid_line_alpha=0.3\n",
      "\n",
      "# open a browser\n",
      "bp.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "AttributeError",
       "evalue": "'module' object has no attribute 'line'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-9-d30fac41d608>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     17\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[1;31m# on that figure, create a line plot\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 19\u001b[1;33m bp.line(time, decays, x_axis_label=\"Time (s)\", y_axis_label=\"Decays (#)\",\n\u001b[0m\u001b[0;32m     20\u001b[0m      color='#1F78B4', legend='Decays per second')\n\u001b[0;32m     21\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mAttributeError\u001b[0m: 'module' object has no attribute 'line'"
       ]
      }
     ],
     "prompt_number": 9
    }
   ],
   "metadata": {}
  }
 ]
}