{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Global Historical Climatology Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The [Global Historical Climatology Network (GHCN)](http://www.ncdc.noaa.gov/data-access/land-based-station-data/land-based-datasets/global-historical-climatology-network-ghcn) provides access to integrated database of quality reviewed climate data. For these notebooks, we use the [GHCN to access historical records](http://www.ncdc.noaa.gov/) for precipitation at International Falls, MN, [Station KINL](http://forecast.weather.gov/MapClick.php?lat=48.58&lon=-93.38#.VHNxbZPF_Xg) in the NOAA network."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Initialization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Load Python Modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Display graphics inline with the notebook\n",
    "%matplotlib inline\n",
    "\n",
    "# Standard Python modules\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "import datetime\n",
    "import seaborn as sns\n",
    "sns.set_context('talk')\n",
    "\n",
    "# Modules to display images and data tables\n",
    "from IPython.display import Image\n",
    "from IPython.core.display import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Directory where data files are stored\n",
    "dir = \"../data/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Read Precipitation Data Tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRCP</th>\n",
       "      <th>SNWD</th>\n",
       "      <th>SNOW</th>\n",
       "      <th>WESD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1970-01-01</th>\n",
       "      <td>3</td>\n",
       "      <td>356.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>605.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970-01-02</th>\n",
       "      <td>0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>607.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970-01-03</th>\n",
       "      <td>10</td>\n",
       "      <td>356.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>617.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970-01-04</th>\n",
       "      <td>3</td>\n",
       "      <td>356.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1970-01-05</th>\n",
       "      <td>0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>620.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            PRCP   SNWD  SNOW   WESD\n",
       "DATE                                \n",
       "1970-01-01     3  356.0   3.0  605.0\n",
       "1970-01-02     0  356.0   0.0  607.0\n",
       "1970-01-03    10  356.0  10.0  617.0\n",
       "1970-01-04     3  356.0   3.0  620.0\n",
       "1970-01-05     0  356.0   0.0  620.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PRCP</th>\n",
       "      <th>SNWD</th>\n",
       "      <th>SNOW</th>\n",
       "      <th>WESD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-11-16</th>\n",
       "      <td>5</td>\n",
       "      <td>50.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-17</th>\n",
       "      <td>3</td>\n",
       "      <td>80.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-18</th>\n",
       "      <td>5</td>\n",
       "      <td>80.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-19</th>\n",
       "      <td>18</td>\n",
       "      <td>100.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-11-20</th>\n",
       "      <td>0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            PRCP   SNWD  SNOW  WESD\n",
       "DATE                               \n",
       "2014-11-16     5   50.0  18.0   NaN\n",
       "2014-11-17     3   80.0   5.0   NaN\n",
       "2014-11-18     5   80.0  18.0   NaN\n",
       "2014-11-19    18  100.0  51.0   NaN\n",
       "2014-11-20     0  130.0   3.0   NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Read .csv file\n",
    "KINL = pd.read_csv(dir + '434021.csv',index_col=2,parse_dates=True);\n",
    "\n",
    "# Drop unneeded columns\n",
    "KINL.drop('STATION',axis=1,inplace=True)\n",
    "KINL.drop('STATION_NAME',axis=1,inplace=True)\n",
    "KINL.ix[KINL['SNWD']==-9999,'SNWD'] = float('nan')\n",
    "KINL.ix[KINL['SNOW']==-9999,'SNOW'] = float('nan')\n",
    "KINL.ix[KINL['WESD']==-9999,'WESD'] = float('nan')\n",
    "\n",
    "display(KINL.head())\n",
    "display(KINL.tail())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Gij3MXV3BXdOLfZ8r5C776juSOj+3h7I0YZOAx5rnRHltGwsKKwOfcArBcqC1h3lryn0n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\nsj+PIJ6Nsxx9AyGKdAOfPvvE1N4nHE4qP1I4HB6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Rgapmz99atjR0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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115393f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,8))\n",
    "\n",
    "plt.subplot(4,1,1)\n",
    "KINL['PRCP'].plot()\n",
    "plt.title('Precipitation (PRCP)')\n",
    "\n",
    "plt.subplot(4,1,2)\n",
    "KINL['SNWD'].plot()\n",
    "plt.title('Snow Depth (SNWD)')\n",
    "\n",
    "plt.subplot(4,1,3)\n",
    "KINL['SNOW'].plot()\n",
    "plt.title('Snow (SNOW)')\n",
    "\n",
    "plt.subplot(4,1,4)\n",
    "KINL['WESD'].plot()\n",
    "plt.title('Water Equivalent Snow Depth (WESD)')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Pickle KINL Precipitation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "The data series for water equivalent snow depth appears to be incomplete and not useful the present analysis. The data series for precipitation is converted to a Pandas data series and to standard metric units for precipitation, mm of water. The data series is pickled to a file `PRCP.pkl`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x117811c88>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QeO8i4OcB0xUEQRBqmIFcnr7+nHdAwZWV+hAz55dW+kEJovT/GnjK4fks4HXh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\nklbR41548nq/rPelVJkFd3Y2xGLLI6ATFRZOZpS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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1154de748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,6))\n",
    "\n",
    "KINL = pd.Series(KINL['PRCP'])/10.0\n",
    "KINL.name = 'Precipitation at International Falls (KINL)'\n",
    "KINL.to_pickle(dir+'KINL.pkl')\n",
    "\n",
    "KINL.plot(lw=1)\n",
    "plt.title(KINL.name)\n",
    "plt.ylabel('millimeters')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Temperature Data Set for International Falls, MN (KINL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Read .csv file\n",
    "TEMP = pd.read_csv(dir + '528052.csv',index_col=2,parse_dates=True);\n",
    "\n",
    "# Drop unneeded columns\n",
    "TEMP.drop('STATION',axis=1,inplace=True)\n",
    "TEMP.drop('STATION_NAME',axis=1,inplace=True)\n",
    "TEMP.drop('TOBS',axis=1,inplace=True)\n",
    "\n",
    "TEMP.ix[TEMP['TMAX']==-9999,'TMAX'] = float('nan')\n",
    "TEMP.ix[TEMP['TMIN']==-9999,'TMIN'] = float('nan')\n",
    "\n",
    "# Convert to Celcius\n",
    "TEMP = TEMP/10.0   # 32.0 + (9.0*TEMP/50.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tmax 1948-1981</th>\n",
       "      <th>Tmin 1948-1981</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1948-01-01</th>\n",
       "      <td>-8.9</td>\n",
       "      <td>-30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948-01-02</th>\n",
       "      <td>-5.6</td>\n",
       "      <td>-12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948-01-03</th>\n",
       "      <td>-5.0</td>\n",
       "      <td>-10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948-01-04</th>\n",
       "      <td>-4.4</td>\n",
       "      <td>-8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1948-01-05</th>\n",
       "      <td>-0.6</td>\n",
       "      <td>-10.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Tmax 1948-1981  Tmin 1948-1981\n",
       "DATE                                      \n",
       "1948-01-01            -8.9           -30.0\n",
       "1948-01-02            -5.6           -12.2\n",
       "1948-01-03            -5.0           -10.6\n",
       "1948-01-04            -4.4            -8.3\n",
       "1948-01-05            -0.6           -10.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Tmax 1982-2014</th>\n",
       "      <th>Tmin 1982-2014</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1982-01-01</th>\n",
       "      <td>-21.7</td>\n",
       "      <td>-31.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-02</th>\n",
       "      <td>-8.3</td>\n",
       "      <td>-22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-03</th>\n",
       "      <td>-12.2</td>\n",
       "      <td>-28.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-04</th>\n",
       "      <td>-18.3</td>\n",
       "      <td>-26.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-05</th>\n",
       "      <td>-10.0</td>\n",
       "      <td>-26.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Tmax 1982-2014  Tmin 1982-2014\n",
       "DATE                                      \n",
       "1982-01-01           -21.7           -31.1\n",
       "1982-01-02            -8.3           -22.2\n",
       "1982-01-03           -12.2           -28.9\n",
       "1982-01-04           -18.3           -26.7\n",
       "1982-01-05           -10.0           -26.1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9Le4dmtSGsgPmaYqMwzFkONkTTyJx9Chc0TK+a09TVt3I8/M3sml3FXHeeqZX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\ndtkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111d61978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create Comparison Sets\n",
    "Ta = TEMP['1948':'1981']\n",
    "Ta.columns = ['Tmax 1948-1981', 'Tmin 1948-1981']\n",
    "display(Ta.head())\n",
    "\n",
    "Tb = TEMP['1982':'2014']\n",
    "Tb.columns = ['Tmax 1982-2014', 'Tmin 1982-2014']\n",
    "display(Tb.head())\n",
    "\n",
    "# Group by month, plot on same axis\n",
    "plt.figure(figsize=(10,6))\n",
    "ax = Ta['Tmax 1948-1981'].groupby(Ta.index.month).mean().plot()\n",
    "Ta['Tmin 1948-1981'].groupby(Ta.index.month).mean().plot(ax=ax)\n",
    "Tb['Tmax 1982-2014'].groupby(Tb.index.month).mean().plot(ax=ax)\n",
    "Tb['Tmin 1982-2014'].groupby(Tb.index.month).mean().plot(ax=ax)\n",
    "\n",
    "ax.set_xticks(np.arange(1.0,13.0,1.0))\n",
    "ax.set_xticklabels(('Jan','Feb','Mar','Apr','May','Jun',\n",
    "                    'Jul','Aug','Sep','Oct','Nov','Dec'));\n",
    "\n",
    "plt.title('Monthy Means of Min and Max Temperatures at International Falls, MN')\n",
    "plt.ylabel('Temperature [C]');\n",
    "plt.xlabel('Month')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.grid()\n",
    "\n",
    "fname = '../images/KINL_MonthyMeanTemp.png'\n",
    "plt.savefig(fname)\n",
    "!convert $fname -trim $fname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wN+qEcvw28HtMr/9qYIv1++k6D9Oj2+azPb+PqeG/gK46v871b31edRzfg++tX/c9Rr3e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rCaj12Tz9KiRACsxyvp+vvTABjnFZF4/wOic8B5kGWZPdvrAXCEDDFnfhLhOpOfrRJMJULoCgSX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\npC8yAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1114080f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Group by month, plot on same axis\n",
    "plt.figure(figsize=(10,6))\n",
    "ax = Ta['Tmax 1948-1981'].groupby(Ta.index.month).std().plot()\n",
    "Ta['Tmin 1948-1981'].groupby(Ta.index.month).std().plot(ax=ax)\n",
    "Tb['Tmax 1982-2014'].groupby(Tb.index.month).std().plot(ax=ax)\n",
    "Tb['Tmin 1982-2014'].groupby(Tb.index.month).std().plot(ax=ax)\n",
    "\n",
    "ax.set_xticks(np.arange(1.0,13.0,1.0))\n",
    "ax.set_xticklabels(('Jan','Feb','Mar','Apr','May','Jun',\n",
    "                    'Jul','Aug','Sep','Oct','Nov','Dec'));\n",
    "\n",
    "plt.title('Monthly Standard Deviation of Min and Max Temperatures at International Falls, MN')\n",
    "plt.ylabel('Temperature [C]');\n",
    "plt.xlabel('Month')\n",
    "\n",
    "plt.tight_layout()\n",
    "fname = '../images/KINL_MonthyStdTemp.png'\n",
    "plt.savefig(fname)\n",
    "!convert $fname -trim $fname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Cumulative Temperature Distributions, 1948-1981 versus 1981-2014"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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jb7zxGmPGjGDOnAUAfPTRUiZPvpLXX/8nW23VmSFDTmHAgMMAqKioYOrUyTz2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\niEheU8IrIiIiInnt/wMU6OiuFuIfVQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111c15438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = np.arange(-45,10,1)\n",
    "\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.subplot(2,1,1)\n",
    "\n",
    "Ta['Tmin 1948-1981'][Ta.index.month == 1].hist(\n",
    "    cumulative=True,bins=b,color='blue',normed=1,alpha=0.5)\n",
    "Tb['Tmin 1982-2014'][Tb.index.month == 1].hist(\n",
    "    cumulative=True,bins=b,color='gold',normed=1,alpha=0.5)\n",
    "plt.legend(['1948-1981','1982-2014'],loc='best')\n",
    "\n",
    "plt.axis([-45,10,0,1.05])\n",
    "\n",
    "plt.title('Cumulative Distributions of Daily Lows and Highs, January, KINL')\n",
    "plt.ylabel('Fraction Tlow < T')\n",
    "\n",
    "plt.subplot(2,1,2)\n",
    "\n",
    "Ta['Tmax 1948-1981'][Ta.index.month == 1].hist(\n",
    "    cumulative=True,bins=b,color='blue',normed=1,alpha=0.5)\n",
    "Tb['Tmax 1982-2014'][Tb.index.month == 1].hist(\n",
    "    cumulative=True,bins=b,color='gold',normed=1,alpha=0.5)\n",
    "plt.legend(['1948-1981','1982-2014'],loc='best')\n",
    "\n",
    "plt.axis([-45,10,0,1.05])\n",
    "\n",
    "plt.xlabel('Temperature [C]')\n",
    "plt.ylabel('Fraction Thigh < T')\n",
    "\n",
    "plt.tight_layout()\n",
    "fname = '../images/KINL_TempJan.png'\n",
    "plt.savefig(fname)\n",
    "!convert $fname -trim $fname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Distribution of Daily Lows by Month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mostr = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
    "xlo = -45\n",
    "xhi = 25\n",
    "dx = 0.5\n",
    "plt.figure(figsize=(10,8))\n",
    "for mo in range(1,13):\n",
    "    plt.subplot(4,3,mo)\n",
    "    plt.hold(True)\n",
    "    Ta['Tmin 1948-1981'][Ta.index.month == mo].hist(cumulative=True,\n",
    "                                    normed=True,\n",
    "                                    bins=np.arange(xlo,xhi+3*dx,3*dx),\n",
    "                                    color = 'b',\n",
    "                                    alpha = 0.5)\n",
    "    Tb['Tmin 1982-2014'][Tb.index.month == mo].hist(cumulative=True,\n",
    "                                    normed=True,\n",
    "                                    bins=np.arange(xlo,xhi+3*dx,3*dx),\n",
    "                                    color = 'y',\n",
    "                                    alpha = 0.5)\n",
    "    plt.legend(['1970-1999','2000-2012'],loc='upper left')\n",
    "    plt.axis([xlo,xhi,0,1.05])\n",
    "    plt.title(mostr[mo-1])\n",
    "    plt.hold(False)\n",
    "    \n",
    "plt.tight_layout()\n",
    "fname = '../images/KINL_Lows.png'\n",
    "plt.savefig(fname)\n",
    "!convert $fname -trim $fname"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### Distribution of Daily HIghs by Month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mostr = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']\n",
    "xlo = -45\n",
    "xhi = 35\n",
    "dx = 0.5\n",
    "plt.figure(figsize=(10,8))\n",
    "for mo in range(1,13):\n",
    "    plt.subplot(4,3,mo)\n",
    "    plt.hold(True)\n",
    "    Ta['Tmax 1948-1981'][Ta.index.month == mo].hist(cumulative=True,\n",
    "                                    normed=True,\n",
    "                                    bins=np.arange(xlo,xhi+3*dx,3*dx),\n",
    "                                    color = 'b',\n",
    "                                    alpha = 0.5)\n",
    "    Tb['Tmax 1982-2014'][Tb.index.month == mo].hist(cumulative=True,\n",
    "                                    normed=True,\n",
    "                                    bins=np.arange(xlo,xhi+3*dx,3*dx),\n",
    "                                    color = 'y',\n",
    "                                    alpha = 0.5)\n",
    "    plt.legend(['1970-1999','2000-2012'],loc='upper left')\n",
    "    plt.axis([xlo,xhi,0,1.05])\n",
    "    plt.title(mostr[mo-1])\n",
    "    plt.hold(False)\n",
    "    \n",
    "plt.tight_layout()\n",
    "fname = '../images/KINL_Highs.png'\n",
    "plt.savefig(fname)\n",
    "!convert $fname -trim $fname"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}