CIS API - Workshop 2016.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# CIS as a Python Library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Reading data is really easy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "As a Python package CIS can easily be used in your own scripts:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "from cis import read_data, read_data_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Here we're using it inside an iPython notebook, but this is exactly the same as using it in a script or other Python interpreter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "data_path = \"/Users/watson-parris/Stockholm_workshop/WorkshopData2016/ARCPAC_2008/*.nc\"\n",
    "\n",
    "NC = read_data(data_path, \"NUMBER_CONCENTRATION\")\n",
    "\n",
    "# Note we can also use from cis.data_io.products.AProduct import get_variables to find the variables in a file."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can easily print a summary of the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Identified 1 point(s) which were missing values for some or all coordinates - these points have been removed from the data.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ungridded data: NUMBER_CONCENTRATION / (#/cm3) \n",
      "     Shape = (1268,)\n",
      "\n",
      "     Total number of points = 1268\n",
      "     Number of non-masked points = 981\n",
      "     Long name = \n",
      "     Standard name = None\n",
      "     Units = #/cm3\n",
      "     Missing value = -9999\n",
      "     Range = (17.0, 2191.0)\n",
      "     History = \n",
      "     Coordinates: \n",
      "       time\n",
      "          Long name = \n",
      "          Standard name = time\n",
      "          Units = days since 1600-01-01 00:00:00\n",
      "          Calendar = gregorian\n",
      "          Missing value = -9999\n",
      "          Range = ('2008-04-11 20:01:30.000001', '2008-04-16 03:03:30')\n",
      "          History = \n",
      "       latitude\n",
      "          Long name = \n",
      "          Standard name = latitude\n",
      "          Units = degrees\n",
      "          Missing value = -9999\n",
      "          Range = (63.303199999999997, 75.128600000000006)\n",
      "          History = \n",
      "       longitude\n",
      "          Long name = \n",
      "          Standard name = longitude\n",
      "          Units = degrees\n",
      "          Missing value = -9999\n",
      "          Range = (-165.1241, -139.23159999999999)\n",
      "          History = \n",
      "       altitude\n",
      "          Long name = \n",
      "          Standard name = altitude\n",
      "          Units = m\n",
      "          Missing value = -9999\n",
      "          Range = (77.200000000000003, 6579.6000000000004)\n",
      "          History = \n",
      "       air_pressure\n",
      "          Long name = \n",
      "          Standard name = air_pressure\n",
      "          Units = hPa\n",
      "          Missing value = -9999\n",
      "          Range = (402.13999999999999, 1011.34)\n",
      "          History = \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print NC   # Note the warning below"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Let's take a look at the methods available on the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<cis.data_io.Coord.Coord object at 0x110a99f90>\n"
     ]
    }
   ],
   "source": [
    "print NC.lat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can also access the data directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2191.0 581.0 306.0 ..., 221.0 220.0 187.0]\n",
      "[4800481.0 337561.0 93636.0 ..., 48841.0 48400.0 34969.0]\n"
     ]
    }
   ],
   "source": [
    "print NC.data\n",
    "print NC.data**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "And the coordinates:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time [ 149120.834375    149120.83506944  149120.83576389 ...,  149125.12604167\n",
      "  149125.12673611  149125.12743056]\n",
      "latitude [ 64.8029  64.7594  64.7385 ...,  64.8948  64.8635  64.8336]\n",
      "longitude [-147.8828 -147.9471 -148.0415 ..., -147.7128 -147.7722 -147.8285]\n",
      "altitude [  233.4   652.9  1099.1 ...,   682.1   435.8   203.5]\n",
      "air_pressure [ 989.79  937.43  884.56 ...,  924.03  954.14  983.3 ]\n",
      "days since 1600-01-01 00:00:00\n"
     ]
    }
   ],
   "source": [
    "for c in NC.coords():\n",
    "    print c.name(), c.data\n",
    "print NC.coord('time').units"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "**Note** in the above that one of the calls is to a method, and the other is to a data attribute. See the help output above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can also look at the metadata:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Long name = \n",
      "     Standard name = None\n",
      "     Units = #/cm3\n",
      "     Missing value = -9999\n",
      "     Range = (17.0, 2191.0)\n",
      "     History = \n",
      "\n"
     ]
    }
   ],
   "source": [
    "print NC.metadata"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Or edit it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     Long name = \n",
      "     Standard name = None\n",
      "     Units = #/cm3\n",
      "     Missing value = -9999\n",
      "     Range = (17.0, 2191.0)\n",
      "     History = DWP removed the zero-values\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "NC.metadata.history += 'DWP removed the zero-values\\n'\n",
    "print NC.metadata  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "Note the `\\n` above - this is a line break, and ensures that when we add another line to the history the lines won't run into each other."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Using Pandas with CIS data\n",
    "\n",
    "Now that we have the data in Python we can use any Python library to work with it. \n",
    "\n",
    "We've shown how to access the data in Numpy arrays, but it's also easy to read data into Pandas."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Pandas (http://pandas.pydata.org) is a free, open-source library for data analysis and offers powerful tools similar to R. \n",
    "\n",
    "It's particularly good for working with time series."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can easily convert CIS data into pandas data to take advantage of this time-series functionality:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "df = NC.as_data_frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
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       "  <thead>\n",
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       "      <th>2008-04-11 20:29:30.000000</th>\n",
       "      <td>646.79</td>\n",
       "      <td>3402.5</td>\n",
       "      <td>66.5181</td>\n",
       "      <td>-148.3506</td>\n",
       "      <td>158.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-11 20:30:30.000018</th>\n",
       "      <td>646.75</td>\n",
       "      <td>3403.1</td>\n",
       "      <td>66.5886</td>\n",
       "      <td>-148.3616</td>\n",
       "      <td>151.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:34:30.000003</th>\n",
       "      <td>484.51</td>\n",
       "      <td>5326.5</td>\n",
       "      <td>66.4332</td>\n",
       "      <td>-150.5058</td>\n",
       "      <td>350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:35:30.000000</th>\n",
       "      <td>484.49</td>\n",
       "      <td>5327.2</td>\n",
       "      <td>66.3617</td>\n",
       "      <td>-150.3813</td>\n",
       "      <td>321.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:36:30.000000</th>\n",
       "      <td>484.46</td>\n",
       "      <td>5328.5</td>\n",
       "      <td>66.2913</td>\n",
       "      <td>-150.2537</td>\n",
       "      <td>496.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:37:30.000000</th>\n",
       "      <td>484.47</td>\n",
       "      <td>5330.0</td>\n",
       "      <td>66.2213</td>\n",
       "      <td>-150.1258</td>\n",
       "      <td>403.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:38:30.000000</th>\n",
       "      <td>484.49</td>\n",
       "      <td>5331.2</td>\n",
       "      <td>66.1513</td>\n",
       "      <td>-149.9991</td>\n",
       "      <td>344.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:39:30.000000</th>\n",
       "      <td>484.50</td>\n",
       "      <td>5332.1</td>\n",
       "      <td>66.0805</td>\n",
       "      <td>-149.8781</td>\n",
       "      <td>236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:40:30.000000</th>\n",
       "      <td>484.49</td>\n",
       "      <td>5334.5</td>\n",
       "      <td>66.0091</td>\n",
       "      <td>-149.7616</td>\n",
       "      <td>288.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:41:30.000000</th>\n",
       "      <td>484.50</td>\n",
       "      <td>5337.4</td>\n",
       "      <td>65.9380</td>\n",
       "      <td>-149.6455</td>\n",
       "      <td>544.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:42:30.000000</th>\n",
       "      <td>486.16</td>\n",
       "      <td>5316.7</td>\n",
       "      <td>65.8672</td>\n",
       "      <td>-149.5295</td>\n",
       "      <td>610.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:43:30.000011</th>\n",
       "      <td>507.86</td>\n",
       "      <td>5018.4</td>\n",
       "      <td>65.7983</td>\n",
       "      <td>-149.4151</td>\n",
       "      <td>377.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:44:30.000008</th>\n",
       "      <td>526.33</td>\n",
       "      <td>4771.4</td>\n",
       "      <td>65.7328</td>\n",
       "      <td>-149.3015</td>\n",
       "      <td>303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:45:30.000004</th>\n",
       "      <td>547.05</td>\n",
       "      <td>4504.9</td>\n",
       "      <td>65.6694</td>\n",
       "      <td>-149.1929</td>\n",
       "      <td>231.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:46:30.000001</th>\n",
       "      <td>568.29</td>\n",
       "      <td>4238.8</td>\n",
       "      <td>65.6070</td>\n",
       "      <td>-149.0823</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:47:30.000000</th>\n",
       "      <td>586.90</td>\n",
       "      <td>4013.3</td>\n",
       "      <td>65.5502</td>\n",
       "      <td>-148.9587</td>\n",
       "      <td>302.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:48:30.000000</th>\n",
       "      <td>605.97</td>\n",
       "      <td>3787.6</td>\n",
       "      <td>65.4937</td>\n",
       "      <td>-148.8395</td>\n",
       "      <td>262.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:49:30.000000</th>\n",
       "      <td>627.04</td>\n",
       "      <td>3546.2</td>\n",
       "      <td>65.4354</td>\n",
       "      <td>-148.7259</td>\n",
       "      <td>555.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:50:30.000000</th>\n",
       "      <td>646.55</td>\n",
       "      <td>3328.0</td>\n",
       "      <td>65.3767</td>\n",
       "      <td>-148.6144</td>\n",
       "      <td>546.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:51:30.000000</th>\n",
       "      <td>668.67</td>\n",
       "      <td>3088.1</td>\n",
       "      <td>65.3185</td>\n",
       "      <td>-148.5031</td>\n",
       "      <td>538.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:52:30.000000</th>\n",
       "      <td>702.08</td>\n",
       "      <td>2736.2</td>\n",
       "      <td>65.2592</td>\n",
       "      <td>-148.3931</td>\n",
       "      <td>511.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:53:30.000016</th>\n",
       "      <td>735.12</td>\n",
       "      <td>2400.7</td>\n",
       "      <td>65.2034</td>\n",
       "      <td>-148.2816</td>\n",
       "      <td>187.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:54:30.000012</th>\n",
       "      <td>773.95</td>\n",
       "      <td>2020.8</td>\n",
       "      <td>65.1602</td>\n",
       "      <td>-148.1653</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:55:30.000009</th>\n",
       "      <td>808.48</td>\n",
       "      <td>1694.9</td>\n",
       "      <td>65.1254</td>\n",
       "      <td>-148.0474</td>\n",
       "      <td>222.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:56:30.000005</th>\n",
       "      <td>836.39</td>\n",
       "      <td>1441.9</td>\n",
       "      <td>65.0882</td>\n",
       "      <td>-147.9370</td>\n",
       "      <td>230.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:57:30.000002</th>\n",
       "      <td>860.05</td>\n",
       "      <td>1232.0</td>\n",
       "      <td>65.0506</td>\n",
       "      <td>-147.8268</td>\n",
       "      <td>236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:58:30.000000</th>\n",
       "      <td>863.69</td>\n",
       "      <td>1199.5</td>\n",
       "      <td>65.0156</td>\n",
       "      <td>-147.7097</td>\n",
       "      <td>237.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:59:30.000000</th>\n",
       "      <td>876.09</td>\n",
       "      <td>1091.9</td>\n",
       "      <td>64.9706</td>\n",
       "      <td>-147.6263</td>\n",
       "      <td>226.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 03:00:30.000000</th>\n",
       "      <td>892.80</td>\n",
       "      <td>944.9</td>\n",
       "      <td>64.9277</td>\n",
       "      <td>-147.6486</td>\n",
       "      <td>219.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 03:01:30.000000</th>\n",
       "      <td>924.03</td>\n",
       "      <td>682.1</td>\n",
       "      <td>64.8948</td>\n",
       "      <td>-147.7128</td>\n",
       "      <td>221.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 03:02:30.000000</th>\n",
       "      <td>954.14</td>\n",
       "      <td>435.8</td>\n",
       "      <td>64.8635</td>\n",
       "      <td>-147.7722</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 03:03:30.000000</th>\n",
       "      <td>983.30</td>\n",
       "      <td>203.5</td>\n",
       "      <td>64.8336</td>\n",
       "      <td>-147.8285</td>\n",
       "      <td>187.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1268 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            air_pressure  altitude  latitude  longitude  \\\n",
       "2008-04-11 20:01:30.000001        989.79     233.4   64.8029  -147.8828   \n",
       "2008-04-11 20:02:30.000000        937.43     652.9   64.7594  -147.9471   \n",
       "2008-04-11 20:03:30.000000        884.56    1099.1   64.7385  -148.0415   \n",
       "2008-04-11 20:04:30.000000        839.03    1496.7   64.7820  -148.1129   \n",
       "2008-04-11 20:05:30.000000        797.26    1877.5   64.8434  -148.1207   \n",
       "2008-04-11 20:06:30.000000        758.63    2245.8   64.9073  -148.1275   \n",
       "2008-04-11 20:07:30.000000        719.23    2638.7   64.9720  -148.1360   \n",
       "2008-04-11 20:08:30.000016        683.18    3013.7   65.0354  -148.1538   \n",
       "2008-04-11 20:09:30.000012        658.75    3275.1   65.1007  -148.1691   \n",
       "2008-04-11 20:10:30.000009        646.21    3411.1   65.1700  -148.1806   \n",
       "2008-04-11 20:11:30.000005        646.17    3412.2   65.2419  -148.1874   \n",
       "2008-04-11 20:12:30.000002        646.34    3410.5   65.3126  -148.1910   \n",
       "2008-04-11 20:13:30.000000        646.22    3412.0   65.3824  -148.1974   \n",
       "2008-04-11 20:14:30.000000        646.19    3412.1   65.4528  -148.2055   \n",
       "2008-04-11 20:15:30.000000        646.25    3411.5   65.5235  -148.2154   \n",
       "2008-04-11 20:16:30.000000        646.33    3410.9   65.5938  -148.2256   \n",
       "2008-04-11 20:17:30.000000        646.45    3409.3   65.6636  -148.2357   \n",
       "2008-04-11 20:18:30.000000        646.46    3408.5   65.7332  -148.2463   \n",
       "2008-04-11 20:19:30.000000        646.46    3407.7   65.8034  -148.2568   \n",
       "2008-04-11 20:20:30.000000        646.50    3407.2   65.8740  -148.2664   \n",
       "2008-04-11 20:21:30.000010        646.49    3407.3   65.9449  -148.2756   \n",
       "2008-04-11 20:22:30.000006        646.46    3407.1   66.0160  -148.2849   \n",
       "2008-04-11 20:23:30.000002        646.50    3406.0   66.0875  -148.2942   \n",
       "2008-04-11 20:24:30.000000        646.57    3404.7   66.1592  -148.3032   \n",
       "2008-04-11 20:25:30.000000        646.52    3405.3   66.2312  -148.3120   \n",
       "2008-04-11 20:26:30.000000        646.53    3405.2   66.3033  -148.3210   \n",
       "2008-04-11 20:27:30.000000        646.58    3404.9   66.3755  -148.3303   \n",
       "2008-04-11 20:28:30.000000        646.70    3403.7   66.4471  -148.3402   \n",
       "2008-04-11 20:29:30.000000        646.79    3402.5   66.5181  -148.3506   \n",
       "2008-04-11 20:30:30.000018        646.75    3403.1   66.5886  -148.3616   \n",
       "...                                  ...       ...       ...        ...   \n",
       "2008-04-16 02:34:30.000003        484.51    5326.5   66.4332  -150.5058   \n",
       "2008-04-16 02:35:30.000000        484.49    5327.2   66.3617  -150.3813   \n",
       "2008-04-16 02:36:30.000000        484.46    5328.5   66.2913  -150.2537   \n",
       "2008-04-16 02:37:30.000000        484.47    5330.0   66.2213  -150.1258   \n",
       "2008-04-16 02:38:30.000000        484.49    5331.2   66.1513  -149.9991   \n",
       "2008-04-16 02:39:30.000000        484.50    5332.1   66.0805  -149.8781   \n",
       "2008-04-16 02:40:30.000000        484.49    5334.5   66.0091  -149.7616   \n",
       "2008-04-16 02:41:30.000000        484.50    5337.4   65.9380  -149.6455   \n",
       "2008-04-16 02:42:30.000000        486.16    5316.7   65.8672  -149.5295   \n",
       "2008-04-16 02:43:30.000011        507.86    5018.4   65.7983  -149.4151   \n",
       "2008-04-16 02:44:30.000008        526.33    4771.4   65.7328  -149.3015   \n",
       "2008-04-16 02:45:30.000004        547.05    4504.9   65.6694  -149.1929   \n",
       "2008-04-16 02:46:30.000001        568.29    4238.8   65.6070  -149.0823   \n",
       "2008-04-16 02:47:30.000000        586.90    4013.3   65.5502  -148.9587   \n",
       "2008-04-16 02:48:30.000000        605.97    3787.6   65.4937  -148.8395   \n",
       "2008-04-16 02:49:30.000000        627.04    3546.2   65.4354  -148.7259   \n",
       "2008-04-16 02:50:30.000000        646.55    3328.0   65.3767  -148.6144   \n",
       "2008-04-16 02:51:30.000000        668.67    3088.1   65.3185  -148.5031   \n",
       "2008-04-16 02:52:30.000000        702.08    2736.2   65.2592  -148.3931   \n",
       "2008-04-16 02:53:30.000016        735.12    2400.7   65.2034  -148.2816   \n",
       "2008-04-16 02:54:30.000012        773.95    2020.8   65.1602  -148.1653   \n",
       "2008-04-16 02:55:30.000009        808.48    1694.9   65.1254  -148.0474   \n",
       "2008-04-16 02:56:30.000005        836.39    1441.9   65.0882  -147.9370   \n",
       "2008-04-16 02:57:30.000002        860.05    1232.0   65.0506  -147.8268   \n",
       "2008-04-16 02:58:30.000000        863.69    1199.5   65.0156  -147.7097   \n",
       "2008-04-16 02:59:30.000000        876.09    1091.9   64.9706  -147.6263   \n",
       "2008-04-16 03:00:30.000000        892.80     944.9   64.9277  -147.6486   \n",
       "2008-04-16 03:01:30.000000        924.03     682.1   64.8948  -147.7128   \n",
       "2008-04-16 03:02:30.000000        954.14     435.8   64.8635  -147.7722   \n",
       "2008-04-16 03:03:30.000000        983.30     203.5   64.8336  -147.8285   \n",
       "\n",
       "                            NUMBER_CONCENTRATION  \n",
       "2008-04-11 20:01:30.000001                2191.0  \n",
       "2008-04-11 20:02:30.000000                 581.0  \n",
       "2008-04-11 20:03:30.000000                 306.0  \n",
       "2008-04-11 20:04:30.000000                 281.0  \n",
       "2008-04-11 20:05:30.000000                 246.0  \n",
       "2008-04-11 20:06:30.000000                 230.0  \n",
       "2008-04-11 20:07:30.000000                 241.0  \n",
       "2008-04-11 20:08:30.000016                 197.0  \n",
       "2008-04-11 20:09:30.000012                 209.0  \n",
       "2008-04-11 20:10:30.000009                 194.0  \n",
       "2008-04-11 20:11:30.000005                 185.0  \n",
       "2008-04-11 20:12:30.000002                 184.0  \n",
       "2008-04-11 20:13:30.000000                 190.0  \n",
       "2008-04-11 20:14:30.000000                 173.0  \n",
       "2008-04-11 20:15:30.000000                 170.0  \n",
       "2008-04-11 20:16:30.000000                 175.0  \n",
       "2008-04-11 20:17:30.000000                 169.0  \n",
       "2008-04-11 20:18:30.000000                 162.0  \n",
       "2008-04-11 20:19:30.000000                 177.0  \n",
       "2008-04-11 20:20:30.000000                 194.0  \n",
       "2008-04-11 20:21:30.000010                 236.0  \n",
       "2008-04-11 20:22:30.000006                 360.0  \n",
       "2008-04-11 20:23:30.000002                 333.0  \n",
       "2008-04-11 20:24:30.000000                 307.0  \n",
       "2008-04-11 20:25:30.000000                 277.0  \n",
       "2008-04-11 20:26:30.000000                 268.0  \n",
       "2008-04-11 20:27:30.000000                 255.0  \n",
       "2008-04-11 20:28:30.000000                 252.0  \n",
       "2008-04-11 20:29:30.000000                 158.0  \n",
       "2008-04-11 20:30:30.000018                 151.0  \n",
       "...                                          ...  \n",
       "2008-04-16 02:34:30.000003                 350.0  \n",
       "2008-04-16 02:35:30.000000                 321.0  \n",
       "2008-04-16 02:36:30.000000                 496.0  \n",
       "2008-04-16 02:37:30.000000                 403.0  \n",
       "2008-04-16 02:38:30.000000                 344.0  \n",
       "2008-04-16 02:39:30.000000                 236.0  \n",
       "2008-04-16 02:40:30.000000                 288.0  \n",
       "2008-04-16 02:41:30.000000                 544.0  \n",
       "2008-04-16 02:42:30.000000                 610.0  \n",
       "2008-04-16 02:43:30.000011                 377.0  \n",
       "2008-04-16 02:44:30.000008                 303.0  \n",
       "2008-04-16 02:45:30.000004                 231.0  \n",
       "2008-04-16 02:46:30.000001                 200.0  \n",
       "2008-04-16 02:47:30.000000                 302.0  \n",
       "2008-04-16 02:48:30.000000                 262.0  \n",
       "2008-04-16 02:49:30.000000                 555.0  \n",
       "2008-04-16 02:50:30.000000                 546.0  \n",
       "2008-04-16 02:51:30.000000                 538.0  \n",
       "2008-04-16 02:52:30.000000                 511.0  \n",
       "2008-04-16 02:53:30.000016                 187.0  \n",
       "2008-04-16 02:54:30.000012                 210.0  \n",
       "2008-04-16 02:55:30.000009                 222.0  \n",
       "2008-04-16 02:56:30.000005                 230.0  \n",
       "2008-04-16 02:57:30.000002                 236.0  \n",
       "2008-04-16 02:58:30.000000                 237.0  \n",
       "2008-04-16 02:59:30.000000                 226.0  \n",
       "2008-04-16 03:00:30.000000                 219.0  \n",
       "2008-04-16 03:01:30.000000                 221.0  \n",
       "2008-04-16 03:02:30.000000                 220.0  \n",
       "2008-04-16 03:03:30.000000                 187.0  \n",
       "\n",
       "[1268 rows x 5 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Now we can do cool Pandas stuff!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "air_pressure             729.390544\n",
       "altitude                2671.365300\n",
       "latitude                  68.334602\n",
       "longitude               -151.828151\n",
       "NUMBER_CONCENTRATION     314.305810\n",
       "dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2191.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['NUMBER_CONCENTRATION'].max() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "air_pressure             686.5500\n",
       "altitude                2916.1000\n",
       "latitude                  73.2817\n",
       "longitude               -153.3266\n",
       "NUMBER_CONCENTRATION      17.0000\n",
       "Name: 2008-04-12 23:49:30, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ix[df['NUMBER_CONCENTRATION'].argmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/watson-parris/anaconda/envs/cis_test/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: how in .resample() is deprecated\n",
      "the new syntax is .resample(...).mean()\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
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       "      <td>688.0240</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-11 22:05:00</th>\n",
       "      <td>688.0200</td>\n",
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       "      <td>-148.495080</td>\n",
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       "      <td>688.1380</td>\n",
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       "      <td>68.39114</td>\n",
       "      <td>-148.444920</td>\n",
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       "      <th>2008-04-11 22:15:00</th>\n",
       "      <td>688.0920</td>\n",
       "      <td>2950.600</td>\n",
       "      <td>68.08308</td>\n",
       "      <td>-148.387520</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-11 22:20:00</th>\n",
       "      <td>687.9800</td>\n",
       "      <td>2952.320</td>\n",
       "      <td>67.76916</td>\n",
       "      <td>-148.335040</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-11 22:25:00</th>\n",
       "      <td>685.6160</td>\n",
       "      <td>2979.060</td>\n",
       "      <td>67.45198</td>\n",
       "      <td>-148.282140</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 00:35:00</th>\n",
       "      <td>466.9540</td>\n",
       "      <td>5596.840</td>\n",
       "      <td>71.90058</td>\n",
       "      <td>-161.794960</td>\n",
       "      <td>336.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 00:40:00</th>\n",
       "      <td>423.6320</td>\n",
       "      <td>6243.160</td>\n",
       "      <td>71.86198</td>\n",
       "      <td>-161.742020</td>\n",
       "      <td>201.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 00:45:00</th>\n",
       "      <td>530.3080</td>\n",
       "      <td>4735.020</td>\n",
       "      <td>71.86402</td>\n",
       "      <td>-161.817940</td>\n",
       "      <td>158.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 00:50:00</th>\n",
       "      <td>692.1000</td>\n",
       "      <td>2862.980</td>\n",
       "      <td>71.87168</td>\n",
       "      <td>-161.791360</td>\n",
       "      <td>198.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 00:55:00</th>\n",
       "      <td>905.7960</td>\n",
       "      <td>871.660</td>\n",
       "      <td>71.84994</td>\n",
       "      <td>-161.783800</td>\n",
       "      <td>263.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:00:00</th>\n",
       "      <td>1002.9320</td>\n",
       "      <td>101.400</td>\n",
       "      <td>71.62454</td>\n",
       "      <td>-161.671380</td>\n",
       "      <td>76.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:05:00</th>\n",
       "      <td>1003.1320</td>\n",
       "      <td>101.680</td>\n",
       "      <td>71.36000</td>\n",
       "      <td>-161.370300</td>\n",
       "      <td>63.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:10:00</th>\n",
       "      <td>1003.3440</td>\n",
       "      <td>101.920</td>\n",
       "      <td>71.09450</td>\n",
       "      <td>-161.077060</td>\n",
       "      <td>94.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:15:00</th>\n",
       "      <td>1003.6800</td>\n",
       "      <td>101.760</td>\n",
       "      <td>70.83808</td>\n",
       "      <td>-160.744760</td>\n",
       "      <td>99.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:20:00</th>\n",
       "      <td>997.7360</td>\n",
       "      <td>146.760</td>\n",
       "      <td>70.63746</td>\n",
       "      <td>-160.126080</td>\n",
       "      <td>88.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:25:00</th>\n",
       "      <td>993.7940</td>\n",
       "      <td>175.580</td>\n",
       "      <td>70.42946</td>\n",
       "      <td>-159.496760</td>\n",
       "      <td>71.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:30:00</th>\n",
       "      <td>989.0620</td>\n",
       "      <td>212.600</td>\n",
       "      <td>70.22194</td>\n",
       "      <td>-158.878100</td>\n",
       "      <td>111.200000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 01:35:00</th>\n",
       "      <td>970.1320</td>\n",
       "      <td>357.280</td>\n",
       "      <td>69.99116</td>\n",
       "      <td>-158.264040</td>\n",
       "      <td>135.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 01:40:00</th>\n",
       "      <td>938.5940</td>\n",
       "      <td>609.780</td>\n",
       "      <td>69.75240</td>\n",
       "      <td>-157.591700</td>\n",
       "      <td>142.200000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 01:45:00</th>\n",
       "      <td>736.4300</td>\n",
       "      <td>2416.000</td>\n",
       "      <td>69.49510</td>\n",
       "      <td>-156.964400</td>\n",
       "      <td>123.200000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 01:50:00</th>\n",
       "      <td>567.2580</td>\n",
       "      <td>4264.080</td>\n",
       "      <td>69.23148</td>\n",
       "      <td>-156.304840</td>\n",
       "      <td>153.000000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 01:55:00</th>\n",
       "      <td>517.8180</td>\n",
       "      <td>4890.040</td>\n",
       "      <td>68.93978</td>\n",
       "      <td>-155.606680</td>\n",
       "      <td>164.800000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 02:00:00</th>\n",
       "      <td>514.8580</td>\n",
       "      <td>4929.060</td>\n",
       "      <td>68.62962</td>\n",
       "      <td>-154.884000</td>\n",
       "      <td>129.000000</td>\n",
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       "    <tr>\n",
       "      <th>2008-04-16 02:05:00</th>\n",
       "      <td>505.1460</td>\n",
       "      <td>5059.260</td>\n",
       "      <td>68.30462</td>\n",
       "      <td>-154.159180</td>\n",
       "      <td>124.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:10:00</th>\n",
       "      <td>484.5080</td>\n",
       "      <td>5338.260</td>\n",
       "      <td>67.97726</td>\n",
       "      <td>-153.471540</td>\n",
       "      <td>224.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:15:00</th>\n",
       "      <td>484.5520</td>\n",
       "      <td>5334.240</td>\n",
       "      <td>67.63130</td>\n",
       "      <td>-152.758060</td>\n",
       "      <td>214.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:20:00</th>\n",
       "      <td>484.4540</td>\n",
       "      <td>5329.520</td>\n",
       "      <td>67.28112</td>\n",
       "      <td>-152.079900</td>\n",
       "      <td>154.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:25:00</th>\n",
       "      <td>484.4640</td>\n",
       "      <td>5326.240</td>\n",
       "      <td>66.93080</td>\n",
       "      <td>-151.406660</td>\n",
       "      <td>163.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:30:00</th>\n",
       "      <td>484.4860</td>\n",
       "      <td>5326.120</td>\n",
       "      <td>66.57660</td>\n",
       "      <td>-150.755240</td>\n",
       "      <td>657.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:35:00</th>\n",
       "      <td>484.4820</td>\n",
       "      <td>5329.800</td>\n",
       "      <td>66.22122</td>\n",
       "      <td>-150.127600</td>\n",
       "      <td>360.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:40:00</th>\n",
       "      <td>497.8680</td>\n",
       "      <td>5155.680</td>\n",
       "      <td>65.86908</td>\n",
       "      <td>-149.530640</td>\n",
       "      <td>424.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:45:00</th>\n",
       "      <td>587.0500</td>\n",
       "      <td>4018.160</td>\n",
       "      <td>65.55114</td>\n",
       "      <td>-148.959860</td>\n",
       "      <td>310.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:50:00</th>\n",
       "      <td>705.2740</td>\n",
       "      <td>2714.760</td>\n",
       "      <td>65.26360</td>\n",
       "      <td>-148.391500</td>\n",
       "      <td>398.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 02:55:00</th>\n",
       "      <td>848.9400</td>\n",
       "      <td>1332.040</td>\n",
       "      <td>65.05008</td>\n",
       "      <td>-147.829440</td>\n",
       "      <td>230.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-04-16 03:00:00</th>\n",
       "      <td>938.5675</td>\n",
       "      <td>566.575</td>\n",
       "      <td>64.87990</td>\n",
       "      <td>-147.740525</td>\n",
       "      <td>211.750000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1237 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     air_pressure  altitude  latitude   longitude  \\\n",
       "2008-04-11 20:00:00      912.7025   870.525  64.77070 -147.996075   \n",
       "2008-04-11 20:05:00      723.4100  2610.160  64.97176 -148.141420   \n",
       "2008-04-11 20:10:00      646.2260  3411.580  65.31194 -148.192380   \n",
       "2008-04-11 20:15:00      646.3900  3409.580  65.66350 -148.235960   \n",
       "2008-04-11 20:20:00      646.5040  3406.460  66.01632 -148.284860   \n",
       "2008-04-11 20:25:00      646.6240  3404.320  66.37504 -148.330820   \n",
       "2008-04-11 20:30:00      646.7440  3403.640  66.73098 -148.379880   \n",
       "2008-04-11 20:35:00      646.7860  3402.740  67.09088 -148.422520   \n",
       "2008-04-11 20:40:00      646.8900  3400.620  67.45660 -148.472620   \n",
       "2008-04-11 20:45:00      646.9100  3397.700  67.82766 -148.519480   \n",
       "2008-04-11 20:50:00      646.9740  3397.040  68.20226 -148.570660   \n",
       "2008-04-11 20:55:00      647.1080  3392.420  68.57606 -148.632040   \n",
       "2008-04-11 21:00:00      647.2080  3388.040  68.94462 -148.690500   \n",
       "2008-04-11 21:05:00      647.1900  3385.940  69.31272 -148.745500   \n",
       "2008-04-11 21:10:00      647.1240  3382.820  69.68036 -148.819300   \n",
       "2008-04-11 21:15:00      647.0800  3380.960  70.04538 -148.943500   \n",
       "2008-04-11 21:20:00      690.1840  2926.660  70.40266 -149.060600   \n",
       "2008-04-11 21:25:00      882.1700  1110.420  70.73052 -149.111420   \n",
       "2008-04-11 21:30:00      819.0380  1665.260  70.81190 -148.969740   \n",
       "2008-04-11 21:35:00      705.9140  2751.160  70.53596 -148.903300   \n",
       "2008-04-11 21:40:00      702.9960  2783.040  70.23258 -148.831100   \n",
       "2008-04-11 21:45:00      688.3460  2939.000  69.93050 -148.764420   \n",
       "2008-04-11 21:50:00      687.9320  2943.960  69.62848 -148.704060   \n",
       "2008-04-11 21:55:00      688.0000  2945.160  69.32024 -148.624880   \n",
       "2008-04-11 22:00:00      688.0240  2947.420  69.01042 -148.555620   \n",
       "2008-04-11 22:05:00      688.0200  2948.700  68.70008 -148.495080   \n",
       "2008-04-11 22:10:00      688.1380  2946.580  68.39114 -148.444920   \n",
       "2008-04-11 22:15:00      688.0920  2950.600  68.08308 -148.387520   \n",
       "2008-04-11 22:20:00      687.9800  2952.320  67.76916 -148.335040   \n",
       "2008-04-11 22:25:00      685.6160  2979.060  67.45198 -148.282140   \n",
       "...                           ...       ...       ...         ...   \n",
       "2008-04-16 00:35:00      466.9540  5596.840  71.90058 -161.794960   \n",
       "2008-04-16 00:40:00      423.6320  6243.160  71.86198 -161.742020   \n",
       "2008-04-16 00:45:00      530.3080  4735.020  71.86402 -161.817940   \n",
       "2008-04-16 00:50:00      692.1000  2862.980  71.87168 -161.791360   \n",
       "2008-04-16 00:55:00      905.7960   871.660  71.84994 -161.783800   \n",
       "2008-04-16 01:00:00     1002.9320   101.400  71.62454 -161.671380   \n",
       "2008-04-16 01:05:00     1003.1320   101.680  71.36000 -161.370300   \n",
       "2008-04-16 01:10:00     1003.3440   101.920  71.09450 -161.077060   \n",
       "2008-04-16 01:15:00     1003.6800   101.760  70.83808 -160.744760   \n",
       "2008-04-16 01:20:00      997.7360   146.760  70.63746 -160.126080   \n",
       "2008-04-16 01:25:00      993.7940   175.580  70.42946 -159.496760   \n",
       "2008-04-16 01:30:00      989.0620   212.600  70.22194 -158.878100   \n",
       "2008-04-16 01:35:00      970.1320   357.280  69.99116 -158.264040   \n",
       "2008-04-16 01:40:00      938.5940   609.780  69.75240 -157.591700   \n",
       "2008-04-16 01:45:00      736.4300  2416.000  69.49510 -156.964400   \n",
       "2008-04-16 01:50:00      567.2580  4264.080  69.23148 -156.304840   \n",
       "2008-04-16 01:55:00      517.8180  4890.040  68.93978 -155.606680   \n",
       "2008-04-16 02:00:00      514.8580  4929.060  68.62962 -154.884000   \n",
       "2008-04-16 02:05:00      505.1460  5059.260  68.30462 -154.159180   \n",
       "2008-04-16 02:10:00      484.5080  5338.260  67.97726 -153.471540   \n",
       "2008-04-16 02:15:00      484.5520  5334.240  67.63130 -152.758060   \n",
       "2008-04-16 02:20:00      484.4540  5329.520  67.28112 -152.079900   \n",
       "2008-04-16 02:25:00      484.4640  5326.240  66.93080 -151.406660   \n",
       "2008-04-16 02:30:00      484.4860  5326.120  66.57660 -150.755240   \n",
       "2008-04-16 02:35:00      484.4820  5329.800  66.22122 -150.127600   \n",
       "2008-04-16 02:40:00      497.8680  5155.680  65.86908 -149.530640   \n",
       "2008-04-16 02:45:00      587.0500  4018.160  65.55114 -148.959860   \n",
       "2008-04-16 02:50:00      705.2740  2714.760  65.26360 -148.391500   \n",
       "2008-04-16 02:55:00      848.9400  1332.040  65.05008 -147.829440   \n",
       "2008-04-16 03:00:00      938.5675   566.575  64.87990 -147.740525   \n",
       "\n",
       "                     NUMBER_CONCENTRATION  \n",
       "2008-04-11 20:00:00            839.750000  \n",
       "2008-04-11 20:05:00            224.600000  \n",
       "2008-04-11 20:10:00            185.200000  \n",
       "2008-04-11 20:15:00            170.600000  \n",
       "2008-04-11 20:20:00            286.000000  \n",
       "2008-04-11 20:25:00            242.000000  \n",
       "2008-04-11 20:30:00            148.800000  \n",
       "2008-04-11 20:35:00            151.400000  \n",
       "2008-04-11 20:40:00            173.800000  \n",
       "2008-04-11 20:45:00            169.000000  \n",
       "2008-04-11 20:50:00                   NaN  \n",
       "2008-04-11 20:55:00                   NaN  \n",
       "2008-04-11 21:00:00                   NaN  \n",
       "2008-04-11 21:05:00                   NaN  \n",
       "2008-04-11 21:10:00                   NaN  \n",
       "2008-04-11 21:15:00                   NaN  \n",
       "2008-04-11 21:20:00                   NaN  \n",
       "2008-04-11 21:25:00                   NaN  \n",
       "2008-04-11 21:30:00                   NaN  \n",
       "2008-04-11 21:35:00                   NaN  \n",
       "2008-04-11 21:40:00                   NaN  \n",
       "2008-04-11 21:45:00                   NaN  \n",
       "2008-04-11 21:50:00                   NaN  \n",
       "2008-04-11 21:55:00                   NaN  \n",
       "2008-04-11 22:00:00                   NaN  \n",
       "2008-04-11 22:05:00                   NaN  \n",
       "2008-04-11 22:10:00                   NaN  \n",
       "2008-04-11 22:15:00                   NaN  \n",
       "2008-04-11 22:20:00                   NaN  \n",
       "2008-04-11 22:25:00                   NaN  \n",
       "...                                   ...  \n",
       "2008-04-16 00:35:00            336.500000  \n",
       "2008-04-16 00:40:00            201.666667  \n",
       "2008-04-16 00:45:00            158.000000  \n",
       "2008-04-16 00:50:00            198.200000  \n",
       "2008-04-16 00:55:00            263.800000  \n",
       "2008-04-16 01:00:00             76.800000  \n",
       "2008-04-16 01:05:00             63.600000  \n",
       "2008-04-16 01:10:00             94.400000  \n",
       "2008-04-16 01:15:00             99.400000  \n",
       "2008-04-16 01:20:00             88.200000  \n",
       "2008-04-16 01:25:00             71.600000  \n",
       "2008-04-16 01:30:00            111.200000  \n",
       "2008-04-16 01:35:00            135.600000  \n",
       "2008-04-16 01:40:00            142.200000  \n",
       "2008-04-16 01:45:00            123.200000  \n",
       "2008-04-16 01:50:00            153.000000  \n",
       "2008-04-16 01:55:00            164.800000  \n",
       "2008-04-16 02:00:00            129.000000  \n",
       "2008-04-16 02:05:00            124.800000  \n",
       "2008-04-16 02:10:00            224.000000  \n",
       "2008-04-16 02:15:00            214.200000  \n",
       "2008-04-16 02:20:00            154.200000  \n",
       "2008-04-16 02:25:00            163.800000  \n",
       "2008-04-16 02:30:00            657.000000  \n",
       "2008-04-16 02:35:00            360.000000  \n",
       "2008-04-16 02:40:00            424.400000  \n",
       "2008-04-16 02:45:00            310.000000  \n",
       "2008-04-16 02:50:00            398.400000  \n",
       "2008-04-16 02:55:00            230.200000  \n",
       "2008-04-16 03:00:00            211.750000  \n",
       "\n",
       "[1237 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.resample('5min', how='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# And more plot types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CY3x8+seNhpYWBhXG6iXhdPLeRTt/IEBh63DwEc3sXF9P64LdTqF24AAFZyx0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x111a024d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from pandas.tools.plotting import scatter_matrix\n",
    "m = scatter_matrix(df, alpha=0.2, figsize=(8, 8), diagonal='kde', edgecolors='none')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Accessing CIS functionality - BETA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also use the built in plotting routines (although they need a bit of tidying up):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from cis.plotting.plot import Plotter\n",
    "%matplotlib inline\n",
    "\n",
    "Plotter([NC],x_variable='longitude',y_variable='latitude',plotwidth=18,plotheight=12,cbarscale=0.5,datagroups=[{'itemstyle':'', 'cmap':'jet', 'edgecolor':''}])"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "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"
  },
  "widgets": {
   "state": {},
   "version": "1.1.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}