ERDDAP/ERDDAP_advanced_search_test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using ERDDAP advanced search "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use ERDDAP's RESTful advanced search to find and retrieve all variable data within a specified bounding box and time extent.\n",
    "\n",
    "Rich Signell (rsignell@usgs.gov) and Filipe Fernandes (ocefpaf@gmail.com)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "start = '2016-07-10T00:00:00Z'\n",
    "stop  = '2017-02-10T00:00:00Z'\n",
    "lat_min =  39.\n",
    "lat_max =  41.5\n",
    "lon_min = -72.\n",
    "lon_max = -69.\n",
    "standard_name = 'sea_water_temperature'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Glider Datasets Found = 3\n",
      "https://data.ioos.us/gliders/erddap/search/advanced.csv?page=1&itemsPerPage=1000&searchFor=&protocol=(ANY)&cdm_data_type=(ANY)&institution=(ANY)&ioos_category=(ANY)&keywords=(ANY)&long_name=(ANY)&standard_name=sea_water_temperature&variableName=(ANY)&maxLat=41.5&minLon=-72.0&maxLon=-69.0&minLat=39.0&minTime=2016-07-10T00:00:00Z&maxTime=2017-02-10T00:00:00Z\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Summary</th>\n",
       "      <th>Institution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>U.S. IOOS Mid-Atlantic Regional Association Co...</td>\n",
       "      <td>University of Massachusetts Darmouth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>silbo-20160413T1534</td>\n",
       "      <td>The Silbo Challenger mission is a partnership ...</td>\n",
       "      <td>Teledyne Webb Research Corporation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>Slocum glider dataset gathered as part of the ...</td>\n",
       "      <td>Woods Hole Oceanographic Institution</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Title                                            Summary  \\\n",
       "0      blue-20160818T1448  U.S. IOOS Mid-Atlantic Regional Association Co...   \n",
       "1     silbo-20160413T1534  The Silbo Challenger mission is a partnership ...   \n",
       "2  whoi_406-20160902T1700  Slocum glider dataset gathered as part of the ...   \n",
       "\n",
       "                            Institution  \n",
       "0  University of Massachusetts Darmouth  \n",
       "1    Teledyne Webb Research Corporation  \n",
       "2  Woods Hole Oceanographic Institution  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "base = (\n",
    "    'https://data.ioos.us/gliders/erddap/search/advanced.csv'\n",
    "    '?page=1'\n",
    "    '&itemsPerPage=1000'\n",
    "    '&searchFor='\n",
    "    '&protocol=(ANY)'\n",
    "    '&cdm_data_type=(ANY)'\n",
    "    '&institution=(ANY)'\n",
    "    '&ioos_category=(ANY)'\n",
    "    '&keywords=(ANY)'\n",
    "    '&long_name=(ANY)'\n",
    "    '&standard_name={}'\n",
    "    '&variableName=(ANY)'\n",
    "    '&maxLat={}'\n",
    "    '&minLon={}'\n",
    "    '&maxLon={}'\n",
    "    '&minLat={}'\n",
    "    '&minTime={}'\n",
    "    '&maxTime={}').format\n",
    "\n",
    "url = base(\n",
    "    standard_name,\n",
    "    lat_max,\n",
    "    lon_min,\n",
    "    lon_max,\n",
    "    lat_min,\n",
    "    start,\n",
    "    stop\n",
    ")\n",
    "\n",
    "dft = pd.read_csv(url, usecols=['Title', 'Summary', 'Institution'])  \n",
    "\n",
    "print('Glider Datasets Found = {}'.format(len(dft)))\n",
    "print(url)\n",
    "dft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def download_df(glider_id):\n",
    "    from pandas import DataFrame, read_csv\n",
    "#    from urllib.error import HTTPError\n",
    "    uri = ('https://data.ioos.us/gliders/erddap/tabledap/{}.csv'\n",
    "           '?trajectory,wmo_id,time,latitude,longitude,depth,pressure,temperature'\n",
    "           '&time>={}'\n",
    "           '&time<={}'\n",
    "           '&latitude>={}'\n",
    "           '&latitude<={}'\n",
    "           '&longitude>={}'\n",
    "           '&longitude<={}').format\n",
    "    url = uri(glider_id,start,stop,lat_min,lat_max,lon_min,lon_max)\n",
    "    print(url)\n",
    "    # Not sure if returning an empty df is the best idea.\n",
    "    try:\n",
    "        df = read_csv(url, index_col='time', parse_dates=True, skiprows=[1])\n",
    "    except:\n",
    "        df = pd.DataFrame()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "https://data.ioos.us/gliders/erddap/tabledap/blue-20160818T1448.csv?trajectory,wmo_id,time,latitude,longitude,depth,pressure,temperature&time>=2016-07-10T00:00:00Z&time<=2017-02-10T00:00:00Z&latitude>=39.0&latitude<=41.5&longitude>=-72.0&longitude<=-69.0\n",
      "https://data.ioos.us/gliders/erddap/tabledap/silbo-20160413T1534.csv?trajectory,wmo_id,time,latitude,longitude,depth,pressure,temperature&time>=2016-07-10T00:00:00Z&time<=2017-02-10T00:00:00Z&latitude>=39.0&latitude<=41.5&longitude>=-72.0&longitude<=-69.0\n",
      "https://data.ioos.us/gliders/erddap/tabledap/whoi_406-20160902T1700.csv?trajectory,wmo_id,time,latitude,longitude,depth,pressure,temperature&time>=2016-07-10T00:00:00Z&time<=2017-02-10T00:00:00Z&latitude>=39.0&latitude<=41.5&longitude>=-72.0&longitude<=-69.0\n"
     ]
    }
   ],
   "source": [
    "# We need to add the \"if 'All' not in glider_id\" logic here.\n",
    "    \n",
    "dfs = list(map(download_df, dft['Title'].values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df = pd.concat(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Data Values Found: 87032\n"
     ]
    }
   ],
   "source": [
    "print('Total Data Values Found: {}'.format(len(df)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trajectory</th>\n",
       "      <th>wmo_id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>depth</th>\n",
       "      <th>pressure</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-08-18 14:59:17</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>4801913</td>\n",
       "      <td>41.247997</td>\n",
       "      <td>-70.957159</td>\n",
       "      <td>4.78</td>\n",
       "      <td>4.78</td>\n",
       "      <td>22.6100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-18 14:59:17</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>4801913</td>\n",
       "      <td>41.247997</td>\n",
       "      <td>-70.957159</td>\n",
       "      <td>5.72</td>\n",
       "      <td>5.72</td>\n",
       "      <td>22.5725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-18 14:59:17</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>4801913</td>\n",
       "      <td>41.247997</td>\n",
       "      <td>-70.957159</td>\n",
       "      <td>7.07</td>\n",
       "      <td>7.07</td>\n",
       "      <td>22.0349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-18 14:59:17</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>4801913</td>\n",
       "      <td>41.247997</td>\n",
       "      <td>-70.957159</td>\n",
       "      <td>8.30</td>\n",
       "      <td>8.30</td>\n",
       "      <td>21.0681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-18 14:59:17</th>\n",
       "      <td>blue-20160818T1448</td>\n",
       "      <td>4801913</td>\n",
       "      <td>41.247997</td>\n",
       "      <td>-70.957159</td>\n",
       "      <td>10.14</td>\n",
       "      <td>10.14</td>\n",
       "      <td>17.2991</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             trajectory   wmo_id   latitude  longitude  depth  \\\n",
       "time                                                                            \n",
       "2016-08-18 14:59:17  blue-20160818T1448  4801913  41.247997 -70.957159   4.78   \n",
       "2016-08-18 14:59:17  blue-20160818T1448  4801913  41.247997 -70.957159   5.72   \n",
       "2016-08-18 14:59:17  blue-20160818T1448  4801913  41.247997 -70.957159   7.07   \n",
       "2016-08-18 14:59:17  blue-20160818T1448  4801913  41.247997 -70.957159   8.30   \n",
       "2016-08-18 14:59:17  blue-20160818T1448  4801913  41.247997 -70.957159  10.14   \n",
       "\n",
       "                     pressure  temperature  \n",
       "time                                        \n",
       "2016-08-18 14:59:17      4.78      22.6100  \n",
       "2016-08-18 14:59:17      5.72      22.5725  \n",
       "2016-08-18 14:59:17      7.07      22.0349  \n",
       "2016-08-18 14:59:17      8.30      21.0681  \n",
       "2016-08-18 14:59:17     10.14      17.2991  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trajectory</th>\n",
       "      <th>wmo_id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>depth</th>\n",
       "      <th>pressure</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-09-20 13:32:33</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>4801945</td>\n",
       "      <td>41.048109</td>\n",
       "      <td>-70.928635</td>\n",
       "      <td>5.19</td>\n",
       "      <td>5.19</td>\n",
       "      <td>18.9365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-20 13:32:33</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>4801945</td>\n",
       "      <td>41.048109</td>\n",
       "      <td>-70.928635</td>\n",
       "      <td>4.82</td>\n",
       "      <td>4.82</td>\n",
       "      <td>18.9450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-20 13:32:33</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>4801945</td>\n",
       "      <td>41.048109</td>\n",
       "      <td>-70.928635</td>\n",
       "      <td>4.44</td>\n",
       "      <td>4.44</td>\n",
       "      <td>18.9572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-20 13:32:33</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>4801945</td>\n",
       "      <td>41.048109</td>\n",
       "      <td>-70.928635</td>\n",
       "      <td>4.06</td>\n",
       "      <td>4.06</td>\n",
       "      <td>18.9713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-20 13:32:33</th>\n",
       "      <td>whoi_406-20160902T1700</td>\n",
       "      <td>4801945</td>\n",
       "      <td>41.048109</td>\n",
       "      <td>-70.928635</td>\n",
       "      <td>3.52</td>\n",
       "      <td>3.52</td>\n",
       "      <td>18.9974</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 trajectory   wmo_id   latitude  longitude  \\\n",
       "time                                                                         \n",
       "2016-09-20 13:32:33  whoi_406-20160902T1700  4801945  41.048109 -70.928635   \n",
       "2016-09-20 13:32:33  whoi_406-20160902T1700  4801945  41.048109 -70.928635   \n",
       "2016-09-20 13:32:33  whoi_406-20160902T1700  4801945  41.048109 -70.928635   \n",
       "2016-09-20 13:32:33  whoi_406-20160902T1700  4801945  41.048109 -70.928635   \n",
       "2016-09-20 13:32:33  whoi_406-20160902T1700  4801945  41.048109 -70.928635   \n",
       "\n",
       "                     depth  pressure  temperature  \n",
       "time                                               \n",
       "2016-09-20 13:32:33   5.19      5.19      18.9365  \n",
       "2016-09-20 13:32:33   4.82      4.82      18.9450  \n",
       "2016-09-20 13:32:33   4.44      4.44      18.9572  \n",
       "2016-09-20 13:32:33   4.06      4.06      18.9713  \n",
       "2016-09-20 13:32:33   3.52      3.52      18.9974  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Jy5cvp6FDh3L779+/n/T09CgrK4vKysrIxcWF3N3d66zvxx9/JAMDAyooKKg1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\nAAAQCAAAgAgEAABABAIAACDp/wMBqH0Swyy56AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd614cdef50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "\n",
    "fig, ax = plt.subplots(\n",
    "    figsize=(9, 9),\n",
    "    subplot_kw=dict(projection=ccrs.PlateCarree())\n",
    ")\n",
    "ax.coastlines(resolution='10m')\n",
    "dx = dy = 0.5\n",
    "ax.set_extent([lon_min-dx, lon_max+dx, lat_min-dy, lat_max+dy])\n",
    "\n",
    "g = df.groupby('trajectory')\n",
    "for glider in g.groups:\n",
    "    traj = df[df['trajectory'] == glider]\n",
    "    ax.plot(traj['longitude'], traj['latitude'], label=glider)\n",
    "\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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EQaClS5dW+f8zf/588vf3p8DAQBowYAANGTKkdl4kteyfvKVauQ4PbGCMMXbDdDod9uzZ\nAwDYsGGDUkdVFSLCokWLcPfdd2PkyJF48sknsWPHjhs+DiJCUVFRtR+Xn5+PCxcugIhw4sQJNG3a\nFG3btkWnTp2UWq+qbNmyBc899xzatm2L4OBgXLx4sdylxcLCQhARCgoKIEkSioqKQETQarW4fPky\nPvjgAzz66KMoKSmpsO/KflcT1fmbyGe7ysZQVkpKirLdldLS0iCKIkRRxMqVK5GXl4cjR44gLy8P\nSUlJSvLhdDpRUlKCgoICnDx5Es8//zyaN2+O1q1b49KlSygpKYHBYEBaWpryN9BoKl48lPcnT2VS\nme+++w6XLl3Cbbfdhk2bNqFt27bX/beo6ziJa2DUOKs5wHGrjdrjPn78OIYOHYr+/fvjl19+Ue6/\nfPkykpOTq73fkpIS7N69G8eOHQMApKenIzMzEwCwceNGdO3aFV27dsWHH35YZT1VZmYm+vXrB39/\nf4waNapC/ddXX32FcePGYfHixcjOzsbjjz+O5cuXQ5IkrFu3Dl9++SUGDx6M9evXY+DAgbjjjjuw\nadMmnDhxAllZWVeNa+/evXjwwQcxduxY+Pn5wWKxYMqUKZUmIU6nEwcOHEBSUpLyu61bt8LPzw+N\nGjVC8+bNMW7cOPTo0QNLly6FzWbDqlWrkJubi6effhotW7bE7bffjieeeALbt28HALRr1w4PPvgg\nZs+ejbNnz6K4uLjKBKjsffn5+crvq9re3SMptVpthWTNYDBAEARotVplhOmePXvg7+8Pl8sFu90O\noDRx1Ov1ygS7BQUFZa+WlbNv3z4cOlR+3v68vDzYbDYcOXIE7dq1Uy6rVmb16tUYOHAgRo0apfzf\nulwuTJs2DTt37oTD4cAff/wBT09P9OjRo+Z/kDqGBzYwxlg9ExMTg9GjR8Pf3x8zZ87EqVOn8OOP\nP2Ls2LEQBAH9+/dHREQEDAYD4uPjYbVaq9yX0+nEoEGDcPLkSWRkZKBLly748ccfUVxcjJKSkgpF\n6zabDREREXA4HOjbty8GDRqErVu34sUXX0RSUhKMRiMKCgoQFxeHe+65B1qtFgEBAbj//vsxYMAA\nfPnll8jIyLhqfDabDQEBATh8+DCISJm2ws/PD3l5eTCbzQgLC4PD4UBMTAyWLl2KqKgoHDp0CDqd\nDt7e3jh//jzmzJmDsWPHIiAgABqNBidPnkTXrl1x8eJF5UxT2aRUq9WiuLgYRqMR+fn5kCQJTqcT\n4eHhOHPmTLkExGg0wmKx4Ntvv8WyZctw5swZuFwubNu27boSL41Go5xhkiQJgiDU2lm32iBPhlvZ\n52i7du2U5Fr+G/n6+iIzMxOenp44duwYWrdujbNnzyp/U3mfN/tzWa7Tk59LEAQIgqAM7EhNTcVb\nb71V5SAId6rJwAa3167drAauiVMVjltd1By3y+UijUZD0dHR5OPjQyaTiZ588kmyWCw0a9YsysrK\nIq1WS8OHD6f777//mrVpCxcuVOq0KqvJqkmz2+1KvZK/vz8FBATUWm1XdZuHhweZTKYq67tutPXo\n0YN69OhBM2bMIEmS3BJjbTSNRkP33XcfiaJIwcHBdP/991NQUBD17t2bQkNDSRRF6tu3r7K9KIrU\nu3dv8vPzo9GjRyv/v4IgkN1uJ4PBQJ07d66VYzObzdX+/yv7Wpb/X/z8/Cg+Pp7mzJlza96w1QRw\nTRxjjDVogiDAZDLhyJEjyMnJQV5eHj777DMUFRXhlVdewauvvgqn04ng4GCEhoZi27ZtWLp0Kfz8\n/ODl5YVHH30UxcXFyM/PR3JyMp599lnlTEVtnQmSL8USEZKTk5GUlFSjOrXacPnyZeTl5d20M0AJ\nCQlISEjAokWLrmvqjrrK4XAgIiICgiDAarVi+PDhyMjIQIcOHeB0OiGKIrZs2QKtVgsPDw/odDrY\n7XZIkoQhQ4ZAp9OhRYsWWL9+PbKzszFw4ECcOHECffv2veF52XJzc6v9/1f2tSz/v6SkpGD58uUY\nMGDADR1PXcKXUxljrJ6xWCxwuVxKjREAmEwm5OXlASi9LOjt7Y3k5ORyH36iKMJgMCAkJATHjx9X\nPtz0ej0KCwtvfSCszih7CdnlckEURXTs2BHnz59Ht27dlGWtBEHAd999hyFDhqB9+/ZITExUatWM\nRiMmTZqEJUuWKPuVayMlSVLmtXMXq9UKDw8PvPLKKxg5cqRbj6UyvHYqY4ypQExMDPLz88slaF26\ndIHJZAJQehYiPz8fkZGR5Rb6FkUReXl5OHr0qJLQAeAETuV0Oh2Kiorw6KOPwsPDA127dsWTTz6J\nnTt3Ijk5GTt37oRerwdQena1b9++KCkpwWOPPaYMztBoNMjPz8eSJUtgMBgwaNAgmEwm5ObmIjc3\n1+0JHFC6EkR2dnaVy33VR5zENTC8xqC6cNzqIsdd2Si9LVu2KGfiDAYDLl26pAwMkMmXmIhImd6B\nsaKiIpjNZhw8eBCCIODUqVPo06cPRFHE9OnT8ffff6OoqEiZ4kMURRARRo8eXell8qKiImzcuBF5\neXmQJAkOhwOenp63OqxK5ebmNqjLqZzEMcZYPXP+/PkKvyMiaDQaeHh4ID8/HxaL5ar74HITVlZ2\ndjb27dsHSZIwc+ZMdOrUCQAwf/58+Pv7K6NpJUmCl5eXspC8PBJX/oIg11fKl+rl0c/yCFV3c7lc\niIuLc/vULbWFa+IYY6ye8fLyuuY0HYxVhzxtiDzxcGZmJmJjY3Ho0CEkJSVBr9crl07lNU179OiB\nhIQEZR9XLokl16CdO3fulsdTmcDAQGWi4hEjRmDNmjXlyg3cjWviGGOsgUlPT8fChQuxdOlS5OXl\nweVy3XACd63VFJi66HQ6fPDBB7BYLBg8eDCys7Oxdu1a7N69W6mdLCkpwfjx4yGKonIZfvfu3QBK\nBy+0bt1aSeDk15c8j9yNqq0atgsXLkCr1WLs2LH4/vvv60xyeSP4ndzAqL1WSG047oaBiPDrr7/i\n559/rlDD1qNHDyQmJiIhIQE9evSAKIrw8fG5oefT6XQ3esisgZCXAYuNjUVSUhKaN2+OwsJCDB48\nGLm5ucjKysLs2bPh5eWFNWvWoHPnzpg1axYAKDWYubm5OH78uHJWy+VyKaNST58+fcPHWBtTt0RH\nR0OSJPj7+2PYsGEoKSm56iTY9UXFhcgYY4zdUtOnT8f69etBROjatSs++OADAEBSUhLS0tKwatUq\nFBUVwWQygYhuOAnjAQ3qZjAYlMliXS4XnnrqKXz22WcgIpw9exY6nQ65ubkASufZe/7555WkLCAg\nAM2bNwdQflobebS0PNJVfnxdcejQIUiSpCyftmbNmjoz2OJGcE0cY4y5UXFxMUwmE8xmMzQaDdLT\n07F//374+vri9ddfx4oVKzBq1CgcOHAAycnJSExMhKenJydi7IaJogitVotWrVrh6NGjyMvLUwYg\nWK1WZGdno2vXrti1axecTieef/55PP/88+XOFjscDmRkZECv1yuPrUuDBsou9SUIAh5++GGsWLHC\nzUdVOa6JY4yxeqCkpAS7du3C0aNHcf78eZSUlMDhcMBms0Gj0eD9999Hz549kZWVhW7duuGdd95B\ncnIyfHx8MG7cOGXOLsaqS6fTlVtPtKioCHv37oVGo0FxcbEy/UZWVhYAIDExEXfeeSeGDx+OOXPm\nYMaMGdDpdMro54yMDKUGruxo1bpCTuDkaVH27t3r5iOqXZzENTANrVboenHc6nIr4iYivPTSS2je\nvDmGDRtWa6NBS0pK0LdvX0yYMAFdu3bFnDlzYDAYcOrUKSQnJ8NoNEKj0eDixYtYvnw5Xn31VRQX\nF2Pu3LnQ6/X49NNPcfny5Vo5FqY+8lQgHh4eAEpf506nU3lNCYKg1Fz26tULmZmZOHr0KFauXIms\nrCz897//hb+/P/z9/ZV9ulyuOj9htMvlgt1ux59//unuQ6lVnMQxxlQvPz8fjz32GDp37ow33ngD\nRITNmzdj9erV+PDDD2G32/HMM89Ua5//+7//C7vdjsDAQCxfvhwZGRlYtmwZPDw8sGXLFhw7dgwj\nR47E559/juLiYgQGBiI3Nxc6nQ6jR4+Gl5cXHnvsMcyZMwcajQaTJ09Gbm4utFptnTvbweoPuRau\n7AoKRKRM2rthwwakpaUBKE30+vfvj9OnTyMyMhIOhwP5+fk4c+YMjh8/DqB0YMTEiRPr7Ihnh8Oh\n/JyTk4OgoCA3Hk3t45o4xpjq9e3bF1u3bkXHjh2xe/duvPLKK7DZbNiwYQPWrVuHjz76CB999BG+\n+eYbAKUfeseOHYOHhwcCAgIAlC76vnTpUqSnpyM7OxuffvopPvzwQ0yZMkWpGbpylQR5Xq2mTZsi\nNTUVVqsVLpcLFy9eRElJCbp164Zu3bph37592Lx5M7y8vBAaGoqdO3e65e/E6rfFixejTZs26Nmz\nZ6X32+12GI1GpKamwul0wmazoXXr1ti2bRsCAgIqnWQaqDg/XF0liiK++eYb9O/f392HUqma1MRx\nEscYU4Xdu3fjyy+/RExMDEaNGlVukk+r1Yp77rkHq1evRkREBMLDw7Fu3Tp07twZfn5+OHLkCFav\nXo1+/fqBiDBmzBgkJCQgJycHkydPRuPGjbFgwQK0b98eW7ZsQVFREQoLCyEIAoqKiuByuZRRe/Lz\nEhFEUURISAgyMzNhMBiQlZUFi8WCUaNGoaSkBO+++y5+//13dO3aFU6nE61atcLOnTvLFWszVlsE\nQYBGo4HVakVsbCw2btyI4cOHY8eOHThz5oy7D++GWCwW5OXlYcOGDejXr5+7D6dSPLCBcY2UynDc\n10ZEmDdvHrp3745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eHk49e/YkX19fioyMpPvvv/+695mRkUFjx46l2NhYWrVqFRER9e3b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/H29iYrK8t1naJeU6/XF/jMGo1GAgICSEpKIjw8nHPnzlG1alX++OMPatWqhbe3NwMGDGDUqFEF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\nWK1Watasi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8ugGJTXJA7ySklkZmai1+tdkxr0ej0Wi4X09PSrFodVSp7RaMThcBT4HjRq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\nndD/B5pOV4a/p6JeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd5e6a00650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10,10))\n",
    "plt.scatter(df['temperature'],-df['pressure'],\n",
    "            facecolors='none', edgecolors='black',s=10);\n",
    "plt.ylabel('depth'); plt.xlabel('temperature');\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}