Parsing and Plotting StratiJSON in Python

ipython_stratigy_parsing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing stratigraphic data from Stratigy in Python\n",
    "\n",
    "This is a short tutorial on what you can do with data from Stratigy\n",
    "\n",
    "At first, we get us some Python libraries. simplejson is for parsing JSON formatted data, pandas is for dataframes, urllib2 talks HTTP and matplotlib does the plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import simplejson as json\n",
    "import pandas as pd\n",
    "import urllib2\n",
    "%pylab inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we define where to get the data from. We specify the side id and the API Endpoint. Use localhost with port number if you have Stratigy running locally in development mode or `http://stratigy.danielkerkow.de/data/` if you want to get data from the demo server."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "site_id = '44'\n",
    "api_endpoint = 'http://localhost:5000/data/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we construct the URL with the site id and API endpoint and get the data from the server. We also load the JSON response into a native python dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "url = api_endpoint + site_id\n",
    "response_json = urllib2.urlopen(url)\n",
    "site_data = json.load(response_json)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's have a look inside:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'geometry': {'coordinates': [13, 43], 'type': 'Point'},\n",
       " 'properties': {'description': 'Description Placeholder',\n",
       "  'marker-size': 'large',\n",
       "  'strat_units': {'78': {'depth': 1,\n",
       "    'loi': 0.8925787,\n",
       "    'lower_boundary': 1,\n",
       "    'upper_boundary': 1},\n",
       "   '79': {'depth': 2,\n",
       "    'loi': 0.10485864,\n",
       "    'lower_boundary': 2,\n",
       "    'upper_boundary': 2},\n",
       "   '80': {'depth': 3,\n",
       "    'loi': 0.05788331,\n",
       "    'lower_boundary': 3,\n",
       "    'upper_boundary': 3},\n",
       "   '81': {'depth': 4,\n",
       "    'loi': 0.72363725,\n",
       "    'lower_boundary': 4,\n",
       "    'upper_boundary': 4},\n",
       "   '82': {'depth': 5,\n",
       "    'loi': 0.87343967,\n",
       "    'lower_boundary': 5,\n",
       "    'upper_boundary': 5},\n",
       "   '83': {'depth': 6,\n",
       "    'loi': 0.02176066,\n",
       "    'lower_boundary': 6,\n",
       "    'upper_boundary': 6},\n",
       "   '84': {'depth': 7,\n",
       "    'loi': 0.39986422,\n",
       "    'lower_boundary': 7,\n",
       "    'upper_boundary': 7},\n",
       "   '85': {'depth': 8,\n",
       "    'loi': 0.34846959,\n",
       "    'lower_boundary': 8,\n",
       "    'upper_boundary': 8},\n",
       "   '86': {'depth': 9,\n",
       "    'loi': 0.90826686,\n",
       "    'lower_boundary': 9,\n",
       "    'upper_boundary': 9},\n",
       "   '87': {'depth': 10,\n",
       "    'loi': 0.80576194,\n",
       "    'lower_boundary': 10,\n",
       "    'upper_boundary': 10}},\n",
       "  'title': 'Site Name'},\n",
       " 'type': 'Feature'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "site_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that the response is a valid geojson. But for the moment, we are interested in the stratigraphic data nested inside the geojson. We can simply strip it out of the dictionary by selecting the `strat_units` key inside the `properties` dictionary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'78': {'depth': 1,\n",
       "  'loi': 0.8925787,\n",
       "  'lower_boundary': 1,\n",
       "  'upper_boundary': 1},\n",
       " '79': {'depth': 2,\n",
       "  'loi': 0.10485864,\n",
       "  'lower_boundary': 2,\n",
       "  'upper_boundary': 2},\n",
       " '80': {'depth': 3,\n",
       "  'loi': 0.05788331,\n",
       "  'lower_boundary': 3,\n",
       "  'upper_boundary': 3},\n",
       " '81': {'depth': 4,\n",
       "  'loi': 0.72363725,\n",
       "  'lower_boundary': 4,\n",
       "  'upper_boundary': 4},\n",
       " '82': {'depth': 5,\n",
       "  'loi': 0.87343967,\n",
       "  'lower_boundary': 5,\n",
       "  'upper_boundary': 5},\n",
       " '83': {'depth': 6,\n",
       "  'loi': 0.02176066,\n",
       "  'lower_boundary': 6,\n",
       "  'upper_boundary': 6},\n",
       " '84': {'depth': 7,\n",
       "  'loi': 0.39986422,\n",
       "  'lower_boundary': 7,\n",
       "  'upper_boundary': 7},\n",
       " '85': {'depth': 8,\n",
       "  'loi': 0.34846959,\n",
       "  'lower_boundary': 8,\n",
       "  'upper_boundary': 8},\n",
       " '86': {'depth': 9,\n",
       "  'loi': 0.90826686,\n",
       "  'lower_boundary': 9,\n",
       "  'upper_boundary': 9},\n",
       " '87': {'depth': 10,\n",
       "  'loi': 0.80576194,\n",
       "  'lower_boundary': 10,\n",
       "  'upper_boundary': 10}}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_data = site_data['properties']['strat_units']\n",
    "strat_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we now have a dictionary containing only records and its properties. We can get a list of the record ids by taking the dictionaries keys:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['86', '84', '82', '83', '80', '81', '85', '87', '79', '78']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_data.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we want to get an overview of the stratigraphic data itself. For further analysis and plotting it is better to have that in a table. So we construct a DataFrame from it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>depth</th>\n",
       "      <th>loi</th>\n",
       "      <th>lower_boundary</th>\n",
       "      <th>upper_boundary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>  1</td>\n",
       "      <td> 0.892579</td>\n",
       "      <td>  1</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>  2</td>\n",
       "      <td> 0.104859</td>\n",
       "      <td>  2</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>  3</td>\n",
       "      <td> 0.057883</td>\n",
       "      <td>  3</td>\n",
       "      <td>  3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>  4</td>\n",
       "      <td> 0.723637</td>\n",
       "      <td>  4</td>\n",
       "      <td>  4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>  5</td>\n",
       "      <td> 0.873440</td>\n",
       "      <td>  5</td>\n",
       "      <td>  5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>  6</td>\n",
       "      <td> 0.021761</td>\n",
       "      <td>  6</td>\n",
       "      <td>  6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>  7</td>\n",
       "      <td> 0.399864</td>\n",
       "      <td>  7</td>\n",
       "      <td>  7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>  8</td>\n",
       "      <td> 0.348470</td>\n",
       "      <td>  8</td>\n",
       "      <td>  8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>  9</td>\n",
       "      <td> 0.908267</td>\n",
       "      <td>  9</td>\n",
       "      <td>  9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td> 10</td>\n",
       "      <td> 0.805762</td>\n",
       "      <td> 10</td>\n",
       "      <td> 10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    depth       loi  lower_boundary  upper_boundary\n",
       "78      1  0.892579               1               1\n",
       "79      2  0.104859               2               2\n",
       "80      3  0.057883               3               3\n",
       "81      4  0.723637               4               4\n",
       "82      5  0.873440               5               5\n",
       "83      6  0.021761               6               6\n",
       "84      7  0.399864               7               7\n",
       "85      8  0.348470               8               8\n",
       "86      9  0.908267               9               9\n",
       "87     10  0.805762              10              10"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame.from_dict(strat_data, orient='index')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could now go further with analysis of the table data, but I won't cover this here for now. Let's go ahead and plot the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting\n",
    "\n",
    "When working with stratigraphic data, it is very common to plot measured data against the depth on the inverted y-axis, so you look on the plot like you would look on an outcrop, measuring depth from the top to the bottom. With this kind of plot you can visualize measurement curves, categorial layer segments or parallel comparisons. \n",
    "\n",
    "For now, I just want to plot the loss on ignition measurement agains the depth. Therefore we create a figure with a size of (2,6) and select the data. Here we just select `df['loi']` for the x-axis and `df['depth']` for the y-axis. The y-axis is inverted with `plt.gca().invert_yaxis()` and the rest is just a little bit of cosmetics.\n",
    "\n",
    "Now we have a nice little plot for data retrieved from the Stratigy database!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": [
       "iVBORw0KGgoAAAANSUhEUgAAAKIAAAGJCAYAAAAJ7uhaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
       "AAALEgAACxIB0t1+/AAAIABJREFUeJztnXe4VNXVh9+foAIKYq8QIljQq6J+NtR4jZUbW2yJLSYK\n",
       "MVGxxcSS5zNFjSZGo+hnYrCS2GLXiAgoWFFjQUEsWIhoLDEGxK6wvj/2udxhuHfmzMypc/b7PPNw\n",
       "58yZtde9Z7H3b7e1ZWZ4PGmzRNoOeDzgA9GTEXwgejKBD0RPJvCB6MkEPhA9mcAHYspIOkfS8THY\n",
       "XVXSDElLRW07DnwgApI+kjQveC2Q9EnJ+4OCezaQdKekOZI+lHS/pG3K7Cwl6ZeSXg5svi7pCklf\n",
       "66LclYHDgD8F71slze7iXkn6aWD7E0n/lPSb0kCTdLWkMwHM7F1gEvDDKP5GceMDETCzZc2st5n1\n",
       "Bv4J7NH+3syulzQQeAR4FhgArA7cBoyXtHWJqZuBPYCDgD7AJsCTwE5dFP194G4z+zyEm6OAEbjA\n",
       "XRYYFtj9W+mvErzauRY4KoTt9DEz/yp5Aa8D3yy79hfg753ceynwQPDzzsAnwJo1lHUfcHDJ+1Zg\n",
       "dif3rQN8BfxP2fW1gM+A1uD9VcCZJZ93Bz4G+qX9d6328jViOHYGburk+k3AtpJ6BPc8bmZv1WB3\n",
       "I+ClEPfthAvQJ0svmtmbwGPArp19ycy+Al4BhtTgUyr4QAzHSsDbnVx/G/c3XAFYEXinRrt9gXkh\n",
       "y+/K9ttB2V0xD1iuRr8SxwdiON4H1ujk+urAAuC/wH+C97XwX6B3yPK7sr1G8HlX9Abm1OhX4vhA\n",
       "DMdE4IBOrh8IPGpmnwb3bClpzRrsPgesF+K++4B+krYovSipH7BV8PliSOoODMJ1sjKND8Rw/AoY\n",
       "KuksSctL6i1pJK4HewqAmU0EJgC3SdpMUvfgvh9J+kEXdscCO5RflLS0pB7tLzObiRviuVbSVpK6\n",
       "SdoQuAWYYGb3t3+1zNSWwCwz63RIKEv4QAyBmb0CbIcbjpkF/Av4NrCrmU0puXV/XHDdiGsOpwGb\n",
       "4QK0M8YAbUFnB9zQy5rAp7ge+CfAx5LWBo4FLgf+itN99wD3A/uVusqiwzeHAH+s+RdOAQXd/GQL\n",
       "la4EvgW8Z2YbJe5AhpB0Nu7vcFHEdlcBJgNDzOyLKG3HQVqBuD3wETCm6IHocaTSNJvZQ7geo8cD\n",
       "eI3oyQg+ED2ZoHvaDnSGJL+1MOeYWflQUkUyWyOamaJ+Ab+Kw26cthOzC0sbHGIwxeCN4fBy+1hQ\n",
       "6WsYjAthu2ZSCURJ1wOPAutKml1hwDdqBuTQdrx2pTWQfoVb/nYE8Dtg4BQ4cYRbMLGQ4fDqG3Bx\n",
       "HM6k0jSb2UFplOsJcCt1V0G6Ebdy5zpgJ8xmtN8yHca2SLTByGWh50fw6Rtw8XSzsbG4lMY4YjUk\n",
       "Wb1VfBW7rWY2OWq7cdqO1K7UCzgYOHYcrLg7nAdcg9ncSOwvLKb251eoQCwsborwx8APgCm45nUi\n",
       "ZgviKa7255fZzkocSGrNm+267UpLIO2KdCfwRHB1S8z2xGy84BtR+RgFmRy+8TSA1Ac4HLdI4jNc\n",
       "7fddzD5J1a8q+Ka5WZAG44LvINxqn0uAh0nhAdfz/HyNmGekbsCeuABsAf4MbERt+2YygdeIGbfd\n",
       "qV1pJaRTgNdwC3OvAr6G2RlhgzDOv0U9+BoxT0ib4Wq/bwN3APtRtrMvr3iNmHVcJof9cQG4Fm4v\n",
       "9RWY/TtVvyrgNWIzIa2By9LwQ2AGbvD5Ltxe5abDa8Qs2ZaEtB3SDcDzwMoHwmmY7YTZbVEGYdY0\n",
       "YqECMbNIvZCOBJ4GrsTNfgzA7Oib3GatpsdrxDSRvg4cTcfU2yXAhLim3pLCT/HlgUWn3v6B24u8\n",
       "VTD1dm/eg7BeChWIqWpEqQ9uU/4M4PfAXUB/zE7G7NW67dZJ1jSi7zXHjZt6Owa3/GoiLsdhKlNv\n",
       "WcZrxDhwU297ACPpmHq7LI9Tb/XgxxHTRloRGI5b+/c2rvNxM+EywhYarxGjMbzZddJY3B6PwcD+\n",
       "mG2D2bWNBqHXiJ7KuKm3/XBTb/3mwDhg3SxPvWUZrxFrxU29/RA3/fYCbuFp00691YPXiHEhCRiK\n",
       "63zsBlwP7IzZ86n61UR4jVj5C6VTb1fhZj++jtnR5UGYNy3nNWIecFNv7bveHgdOA8YXddYjCbxG\n",
       "LCkUd0TFSGBb4Grg0kqzHp7O8RqxHjp2vR0DfIHrfByE2cep+lUwiqsRpcFIl+CWWW2P6wlvgtno\n",
       "eoIwb1rOa8QU6QFLIO2NG/vbCBgNbIw7wcmTIolrxOBskDHAKrhMZ382s1Fl90SrEd3U25G4tX/v\n",
       "4KbebvJTb/GQi9w3klYDVjOzqZKWBZ4C9jGzF0ruiSYQpU1xnY99cbveLsHsHw3b9VQkFwtjzewd\n",
       "M5sa/PwRbnais+PFqtIitQ2Txh0oTR4mjWuR2pCWQjoI6RHgTtz87zqYHS5YJrJfpIy8aTmvEUuQ\n",
       "NADYFDdWVxMtUts2cNFod8QXACfCFvcBO7kjv84H7vRTb/kgtXHEoFmeDJxlZreXfVa1ah8mjbvH\n",
       "TbctwgHw8E1m20fqrKcmcjOOKGlJ3Dlyfy0PwpJ7rqZjB9scYGp7wkpJrUNhtfZ7Jwf/tgKC+e3N\n",
       "Tun9/n2s70/AnQk9i3qx5E+IF67X/IcK91g1O7vDOAMrfw2DeyrYbY3x94rFdt7shn1+5a80BrS3\n",
       "BQ4FdpT0TPDavVYjs2HUUS4J0ULiTDbuiZdczzUfL41cGs6eBU/HnWzcE55cjCOGIfQvIh0IfAez\n",
       "/are60mMXIwjRswgys4CqUTmc980gd16KVQgerJL3pvmB4FfYDYpfq88YSli07wOvkZsCvIbiG5m\n",
       "ZjkgdPYErxHjt1sv+Q1EGAi8ht9H0hTkVyNK+wGHYbZPMl55wlI0jeh7zE1EoQLRa8T47dZLoQLR\n",
       "k13yrBFnA9tjNisRpzyhKY5GlHoCKwOz03bFEw35DERYG5iF2fxavuQ1Yvx26yWvgej1YZORT40o\n",
       "/QRYC7MTk/PKE5biaERfIzYdhQpErxHjt1sveQ1Ev+qmycifRpSWBj4ElsFvns8kRdGIXwfe8EHY\n",
       "XOQxEOvuqHiNGL/deilUIHqySx414iXATMwuStYrT1iKohF9jdiE5DUQZ9bzRa8R47dbL/kKRJdF\n",
       "bC0ayTrlyST50ojSINzBO2sn75UnLEXQiF4fNimJB6KkHpIelzRV0gxJ59Tw9YYC0WvE+O3WS+IZ\n",
       "Y83sM0k7mtknkroDD0vazswervS9FqntG3Cy4KvXpHGzYZRPQdc8pJK62Mw+CX5cCugGfFDp/vbE\n",
       "7ZfC14JLA0fAwBaJWoLRglS7cRCX7bzZrZdUNKKkJSRNBd4FJpnZjEr394PjSk8PABgNg/q7M1Q8\n",
       "TUBaNeICYIik5YB7JbWW/w8tTeY+GAZNxiVrh47k7ctCz+De1sDu5Erv26/FlNx8iJldGKG9RXzN\n",
       "uL/5S+beSeLv/wVOLrtmpe+7Sty+PzxcY1lxJjCPxXbe7Hb2/MK80ug1rySpb/BzT2AX4JlK35kN\n",
       "o0aU9ZaPh/d/BIORbkbaOEzZ5jVi7HbrJY2z+DYCrsHp0yWAv5jZeWX3mJUNiLZIbf1h5LLQc2Hi\n",
       "dtdK/wj4KfAI8GvMnkvkF/F0ST0D2rFUzYlX7dDL4CSDtw1uNtg4heYoFtt5s1vX87N0zlmJHrNP\n",
       "MLsA17OeAoxHuglX+3pyQL7mmsMbWIaOJvshXJM9LSL3PFUowlxzOMw+xux8XFbZx4AJvobMNs0Z\n",
       "iO0sGpCPT4AHkP6G1BJ1UXmbE87aXHNzB2I7LiB/fyQcDDwBTIwrID310ZwasXoBywA/Bk4GHsRp\n",
       "yOmxlVcwvEYMS1BD4prsfwD3Id2ItGHKnhWWQgXiYrrIBeR5uIB8Eri/3oDMm5bzGjGLmH0UVUB6\n",
       "6qOYGrG6A8sCRwM/ASYBZ2L2fGr+5AyvEaPC1ZC/w9WQT+NqyBt8DRkfhQrEmnXRogH5DB0BuUHD\n",
       "tkOSN7v1UqhArBsXkL+lIyAnIV3fWUB66sNrxHpwGvIY4CTgfpyGrLjdoUh4jZgUHTXkIOBZYLKv\n",
       "IRujUIEYuS4ym4fZucDAS2EeLiCvQxocVRFeI3rCYzbvGLgOpyGfwy2uiDQgmx2vEeNA6g0cC5wI\n",
       "TMRpyBfSdSo5vEbMCq7JPgdXQ07D1ZDXIq2fsmeZpVCBmHjum0UDcjrwYK0B6TWiJzo6AnIQ8Dzw\n",
       "kK8hF8VrxDSQ+tChIe/FaciX0nUqOrxGzAtmH2L2G1yT/QLwMNJfkdZL2bPUKFQgZi4/ogvIs6kQ\n",
       "kF4jepKj84D8S5FqSK8Rs4jLkjYSOB4YB5yVJw3pNWKzYDYXs7NwveyX6Kgh103Zs9goVCBmTiNW\n",
       "w2yu4GE6AvIRpDFRBKTXiAGSukl6RtJdafmQGxatIWcCj0YVkFkhNY0o6SRgc6C3me1V9lmxNWI1\n",
       "nIY8Dqchx+I05MvpOtVBbjSipLWANuBywAdcrbga8kxcL3smrsm+BmmdFqltmDTuQGnyMGlci9SW\n",
       "srfhiCtHXpX8eTcBmwI7AHdFkV8vZLmtMf5OsdgOZRf6GpxxH8z9CXxYmt55OMzcENoS/lvU/PzS\n",
       "SF28B/CemT2Drw2jwWwOZr++EJ78PfQu/Sgvpy+kcarAUGAvuSajB9BH0hgz+17pTaWnCgBzgKkW\n",
       "bVb9yN+X+B6ZfavhFIQD3Jk1C09daHdqLqxeenJDDP42fKpAqgPaknbAnSiwZ9l1M99ZqZlh0rh7\n",
       "YLfy620wbqzZsKT8yE1npYzE/ifkbhyxRrudnb4wHF59Ay5uxG4SpHLgTztm9gDwQJo+NBPTzca2\n",
       "SLTByD6wzNqw1QI4Nw9nFvq55mZGOhvoi9kxyRZb+/PzgdjMSKsDM4BBmP0nuWLzqRETo9k14mKY\n",
       "vQ3cjsuOG53dGChUIBaUC4BjkHqk7UglfNNcBKRxwN8wuzKZ4nzT7Omc84GTkDL7n7tQgVg4jdjB\n",
       "RGA+JYPdXiN6ksfprwtwqZgzideIRUFaCngdaMPs2XiL8hrR0xVmXwCX4JKLZo5CBWKBNWI7lwF7\n",
       "Iq3hNaInPcw+AK4lg+sTvUYsGtJA4HFgAGYfxVOE14ieapi9ilvx9IO0XSmlUIHoNeJCzh8HpyJ1\n",
       "i8F2XRQqED0BZo9+6bZf7JO2K+14jVhUpP2BkzAbGr1prxE94bkNWA1pm7QdgYIFoteIJXZhe+BC\n",
       "MjLtV6hA9CzGlUBrMKSTKl4jFh3pXGAZzCIb5PZ7Vjy1I62JO3pjYDDzEoFJ31mpiNeIndg1ewu4\n",
       "CzgqjnLCUqhA9HTJ+cDIYKlYKvim2eOQJgJ/weyaxk35ptlTP78HfpLWvpZCBaLXiBXt3ouLh53j\n",
       "KK8aXea+kbQ51RMkfWlm06J1yZMKZobUvq9lQtLFd6kRJc0Dnqzy/a+b2YCaC5VmAR/idpZ9aWZb\n",
       "ln3uNWIaSEvjchzugtn0+s3U/vwqZQN70sx2rFLgpFoKK8FwqXMjGbfyRITZ50j/h9vXckSSRXep\n",
       "EasFYdh7KpB4jec1Yii7f5wEB+wtTUoyIXyo/IiSNgEGlNxvZnZrA+UaMFHSfOAyMxvdgC1PhLTA\n",
       "VrvB/Ds6Mh8zAga2SMSZZ7HqOKKkq4CNcAdeL2i/bmZ1LzWXtLqZvS1pZZwwHmlmD5V87jViSnxL\n",
       "Gn837FJ+vZb0x1FrxHa2Aja0CEe+zaVLw8z+Lek2YEvgodJ78pjMPc/vvw39b4WNN4PWyThag38n\n",
       "4xLCB29jSeYe5syMa3CBGNUZHL1wp00BLAM8Auxado9FVV6Z3dY47MZpO1a70MvgcIOHDN42OGdf\n",
       "eLD0nJb21zC4pwbbNT+/MDXiVcAUSe8An3fEr21cZ+yvCtwWDOB3B641s/F12vLUg7TZGDgRtzj2\n",
       "Udxc892YffmS1DYCVh/tzv0Duk4IH6lLQQRX8Fmv4pyezqIacVZsTnmNGD1SX+BgYDiwPHAFcDVm\n",
       "b5bf2iK19YeRy0LPj+DTN+DiWjoqsaxHlDTFzBLd1+ADMSJcs7MdLvj2xk3jXQ7ch9mCSl9tsNhY\n",
       "AvFSoC9uzdoXwWWzxoZvqpUZSyCWnr6UF9t12ZVWBb6HC8D5uOD7C2b/bshu6OLj6TX3wmnDXcuu\n",
       "xxaInjpwm+V3wQXfTrhdej8AplCttskAfj1i3pG+hgu4I4B3cbXf9Zh9mJ5LEa5HlPTDEAVWvccT\n",
       "A9JSSPsHSdqfBlYE9sJsC8wuSzMI66XS6pvXgJPpfE7YgutnmtkGkTvlNWLndqX1gSNx+m8Grva7\n",
       "FbNPG7IbMVFrxAeBPSt8DuDH/2JmDVga6XCc9lsHuBrYDrOZqToWMV4jZhVpM1zwfQeYgqv97sbs\n",
       "y1T9CkFcvWZPUiw66LwCbtB5CGazU/UrAfyelbRtS0LaHuka3KKBHYBTgLUxO1MQSzqQrOXQ9jVi\n",
       "Wkir0DHovADX9J5cOuhcJMLMrPQA9mPxhbG/js2pZtWIiw4674wbdB5NTgadwxKXRrwDtx7wKeCz\n",
       "ehwrPFJ/Ogad38PVfkdiNjdVv7JEiLVl0+NYDxf1eraQdltj9HlR27CUwX4G9xj8x+ASgyFZ8Tnm\n",
       "v0XNzy9MjfiopI3N7LkY/h80H4sOOr+Aq/32pY5B5yJRaWalfeN8N9xA6utEszC2ulN504hSL2B/\n",
       "nPZbF7eq/QrMXk7Vr5SIdBmYpAHBj+3TeaWYmf2zVgdDO5WXQOwYdP4uHYPOfycHg85xEumiBzOb\n",
       "ZW4V9lntP5dea8zVdIhk7ExaDunHSE/her3vAJsIzsPstqiDMG/7pesljEZsKX0jqTuweTzuZBS3\n",
       "0nlbYARupfN44DTcSuf5wT2p56HOM5Wa5tNxf+yeQKnQ/hL4s5mdGptTWWmaFx10NtyY3yIrnT2L\n",
       "E9dWgXPjDLouykwvEN2g88642q990Ply4FGq/bE8QHyBKGBf3CacBcDDZnZb3V6GcSqN9YiLDjr/\n",
       "G1f73UDIQedM7VlJ0W5gu+bnF0YjXoqbeL8e13v+kaRdzOzoOnzMFi5n9J64pndL3O+4D2bPpOpX\n",
       "AQlTI74IbGDB9kNJSwAzzGz92JyKu2mW1sMNOh8OvIir/W7xg87REFeN+ArQn468Jv2Da/mi80Hn\n",
       "7Ys66Jw1wqxH7AO8IOkBSZNxeyV6S7pL0p2xehcF0qZB8snZt8LRwB+AfpidEmUQ5m28L4/jiGdU\n",
       "+CybvUhpOTpWOq9EsNJ5PxgYl0D3NEaoPSvBdN8gM5so18R1txi3LNalETsGnYfjDsSegNN+HYPO\n",
       "nkSI5ZyVYO/yTcBlwaW1cGNrdSOpr6SbJb0gaYakrRswtgrSybiVLqOBacC6mB2A2XgfhPkgjEY8\n",
       "BjeG+CGAOV21SoPlXgSMNbPBwMa4IAqP1A1pN6SbgJdx05BHAhtgdj5m73X+tQzuWWkyu/USRiN+\n",
       "bmafB/kM2+ea69aGcvptezM7HMDMvgIWGzRukdr6wXG9occ8+Gw2jJruarsj6Bh0vhwYHnbQ2ZNd\n",
       "wowjnofbKvA94Fhcz3OGmf28rgKlIbhmfgawCW4LwvFm9knJPTYcXilNFvlT+GQYzP8mjMGt9fOD\n",
       "zhklrim+brhmrz0b2L3A5VbnvKuk/8Gt3RtqZv+QdCHwoZmdUXJPp8b3gAl/NyvPSubJGLEMaJvZ\n",
       "fEm3A7dbF9qrRt4E3jSzfwTvbwYWW1Txfdy2QXDJGYcAvWAp6NA3VmPy8vZrMSVHH2JmF0ZobxFf\n",
       "M+5vfMnccfPKvwTeB/4bvN4HfkFQk9b7wuXVWTf4+ZfAb8s+t0YTindRbmsj30/Ddt7sLnx+NX6n\n",
       "Uq/5RNy43BZmtryZLY9bGLBt8FkjjASulfQsrtf8m/IbRpRNI54K89eBhg6csRgHs+OynTe79VJp\n",
       "YexUYBcrWwSq4JAeMxsSm1OSbQjfKk0o/g146lQ4CjgMs3Fxle1pnLomJCpUr13uZ670WaxVOww1\n",
       "eMfgiAw2R7HYzpvdis+vwqtSZ6XSJqB0dqmZPYq0A3BPsJD1V+2/uSffVGqa5wOfdPoh9DSz2BI4\n",
       "Va3aXdb8u4HngKMo+PbNrBHLOGIahPpFpGWBG3EJAA7AbF4SvnmqE8uih8xi9hFua+cbwANIq1f5\n",
       "hp9rTsBuveQ3EAHcPPVRwC3AFKTBKXvkqZP8Ns2Lf+l7wHnA/pSc/exJnmI1zeWYjQEOBW5BOjBt\n",
       "dzy10TyBCGA2AZeR9Xykk2hfuxbgNWL8duuluQIRwOxZYChuzeIfgswNnozTPBpxcSN9cVsaPgAO\n",
       "xe9ZToxia8RyzOYAu+OSi05EWjFljzwVaN5ABDD7HNeBeQh4dJh0UFxF5U3LZU0jNv85Ky5VyqlI\n",
       "s0+Ei5FmYvZk2m55FqV5NWLnhvfGbbg6HLOG1jZ6usZrxGqY3YHL/nUF0oi03fF0UKhAlNSK2WPA\n",
       "N4BTkM4sH2tsyHYM5M1uvRQqEBfizjoeituZeHWQJ9GTIsXSiIsXtAwuOWdPYD9izOdTJLxGrBWz\n",
       "j3FpmWcCDyGtmbJHhaVQgdipLnJLyY7B1YyPIm0Yme0IyJvdemn+ccQwOH1yLtJsYBLSgWRsu2Wz\n",
       "U2yN2Hnh3wRuAI7H7PpUfMg5ceXQLhZm9yPtBNyN1A93tFn2/rc2GV4jdobZNNzwzqG4acGqS8ny\n",
       "puWyphELFYg1YfYmsD0wGLfqu1fKHjU1XiNWww12X4E7s3pP/Dl8VfHjiHFg9gUuSel9uOGdQVW+\n",
       "4amDxANR0nqSnil5zZV0XEJlt9b1RZeg5efA+biB760is12FvNmtl8R7zWb2ErApLDxO7S0aPKUg\n",
       "Mcz+hPQW8HekIzHL/oFHOSFVjShpV+AMM9uu7Hp2NGJnSFsCdwC/boF/LpZ0vuBrHfM4jvhd4LqU\n",
       "fagdsyeQthsPD+wCvf4Ay7d/NAIGtkgUPRhrJbXOijqOqL0pwTJbIzNm9uol8HJ7EE4OLo+GQf1d\n",
       "RtxI8BoxfoYBT1kXwyGSrqYjOfgcYKo1mMy8xHZd3y9/f0DwH3kyMBVoL2QurK6Sg7ljSh7f6Psh\n",
       "geuZSOaemkaUdAMuOfs1nXyWbY0YMEwadw/sVn69DcaNNRuWhk9ZIDfjiHILUncGbk2j/KiYDaN+\n",
       "7NLiLWQ4vPoGXJyWT3kllUA0s4/NbCVLOLlm1LpoutnY/jDmBHhvW3i2DcY9BsdF2VHxGtETitNc\n",
       "eucxgrvNr2GsGz/X3CiuU/UQZlek7UpWyI1GbDLWB15K24m8U6hAjFwXuT3R6wEv5U3LZU0jFioQ\n",
       "Y2AVYAHujEJPA3iN2AjSN4BzMRuatitZwmvE5FkfeDFtJ5qBQgViDLpoPYKOSt60nNeIzYWvESPC\n",
       "a8RGkF4B9sDMB2MJxTqLL22kpYG5QG9/KOWi+M5KFSLWRYOAf7YHYd60nNeIzYPXhxHim+Z6kU4H\n",
       "+mL2s7RdyRq+aU4WXyNGSKECMWJdtHAMMQbbC8mb3XopVCBGhlvs4GvECPEasR6k1YDpmK2UtitZ\n",
       "xGvE5FgPXxtGSqECMUJdtNhi2LxpOa8RmwNfI0aM14j1II0F/uSTMHWO14jJ4WvEiClUIEaii6Qe\n",
       "wJrA65Hb7rS4fNmtl0IFYkQMAl73K26ixWvEWpH2Bw7FbJ+0XckqXiMmg9eHMVCoQIxIF3W6oT5v\n",
       "Ws5rxPzja8QYSEUjSjoNd6rTAmAa8AMz+7zk82xqRLfYYS4wALMP0nYnq+RCI0oaAIwANjOzjYBu\n",
       "uFzamaZFatsH7v9f6DEMrmuR2tL2qZlIo2n+EPgS6CWpO9ALd8RF7NSri1qktm3gotuh9UxY8h7Y\n",
       "bRu4qDQY86blCq8RzTVp5+Myrf4LmGNmE5P2oxb6wXGj3fjhQqJO2l50Ek/UKWkgcAIwAKe3bpJ0\n",
       "iJldW3bf1USczL3e9x/CapPpSNY+Ofh3WehZen+J75GVb2aT4/r9IvQ3f8ncJX0H2MXMhgfvDwO2\n",
       "NrNjSu7JVGelq6Tt+8IDt5q1puBSpslFZwU39LG1pJ5yvdCdgRlJFFyvLpoNo0bAK6XXToAPjoVN\n",
       "kX6OtHTetFzWNGIaZ/E9K2kM8CRu+OZp4M9J+1EL083Gtki0wchloedH8OkbcPGF7j/QH4DpP4PL\n",
       "6Wi1PTXi55qjQNodGIWr7U/A7LWUPUqVvDTNzYfZOGAj4FHgCaRfIfVM2atcUahAjFMXCbbB7Fzc\n",
       "EcDrAzOQ9glmY+q3WxCNWKhATASz2Zh9BzgSOBsYi7Ruyl5lHq8R40RaEjfofTowGjgLs4/TdSp+\n",
       "vEbMGmZfYnYBTj+uBbyAdGCjzXUzUqhAjFUjVrJt9jZmhwGHAD8HJiJt0LDdBvAasciYPQRsDtwG\n",
       "PIB0PlKflL3KBF4jpoW0CnAOsDtwCnAtWXwYdeBzaOcRaWvg/3CnnB6L2bMpe9QwvrNShdQ0YiXM\n",
       "HgO2BP4KjEe6GKlvw3ar4DWiZ3HM5mN2GbABsCTwItIRSIV5Pr5pziLS5rjmGlxz/WSa7tSKb5qb\n",
       "BbOngKHAZcBdSJchrZiyV7FSqEDMpEbsCrMFmF012G00+xw3GP4jpG5RmPca0VMTL8JHmB2HW0B8\n",
       "MPB40NNuKrxGzBNuavBg4HfAvcCpmL2XrlOL4zVis2NmuE1mg4EPgOeRRuK25eaaQgVirjRiJbtm\n",
       "H2J2MrADsA/wFNL2DdtNkUIFYtNhNgOnHc8CrkX6K9LqKXtVF14jNgvSMriVPT/EzWGPSiuZqJ9r\n",
       "9hCsBh8F9AdGYnZf8i74zkpFmkYjVsLsZWAYcBpwOdLfkPo1bDdmChWIhcH1ru/AzV3PAJ5BOg1p\n",
       "6ZQ96xLfNBcBaW1cIoDBwHHB9tcYi/Ma0VMJl0ZvFDAdOBGz16t8o85ivEasSCE0YiXMxgItwBMT\n",
       "YSrSL7KSCKBQgegBzD7D7DfnuMUULbjZmb3S3lnom+aiI+2Ca65fB47HbGbjJnPSNEs6XtI0SdMl\n",
       "HZ+GD54AswnAJsD9wBSks4PB8URJI5l7CzAc2AL3B9gjyCKbRNmtebOdiF2zLzD7Pe55DMDl7dk/\n",
       "yeY6jVXODdMUAAAHN0lEQVQb6wOPm9lnAJIeAPYFzkvBF08pZm8BhyDtAFwCHHWUdPMb8O3e0GMe\n",
       "fDYbRk13nZ6oy7ZEX3Sc3LQC7kSBKcBFZfdY0n75V9kLuv8R/nQqfGVg7a/hMHNDaKvyjGt+fmmc\n",
       "KvAi8FtgPHAP8Awuc6wnS5h9dQcMOMedg7OQuE5TSGVBpZldCVwJIOk3uKMuFiGOUwXar8WUpX+I\n",
       "mV0Yob1FfE3D3wOgB3TkY253ZC6sLqnVIjxVIJVqH1gl+Lc/8ALQp9GqPWS5rTH+TrHYTtPu7jCu\n",
       "tFlufw2De6rYrvn5pXUW34PAirgTqE40s0lln5v5ccTUaZHahsKoP8PCUY3h8OpjcFylDoufa/ZE\n",
       "zpnSL+bA8bPhufbTFKr1mn0gVrfbaoGuyYvt1O1KlwEzceOMYW3X/Pxyv/vLEyMu986euE1a8RZV\n",
       "pBrRUyPSlsDVmIXKbtvxtZzMNXtyw97AnUkUVKhA9HPNNdvdC7gjjvLLKVQgemrAbS9YGXg8keK8\n",
       "RvR0inQisAFmI2r/qteInuhITB9CwQLRa8SQdl1S0E2BiXGU3RmFCkRPaNqA+zH7NKkCvUb0LI50\n",
       "M3A3ZlfV93U/xedpFKkH8A6wDmb/rs+E76xUxGvEUHZ3BKbVG4T1UqhA9IQi0d5yO75p9nTgFjm8\n",
       "CbTisorVacY3zZ7G2ByY20gQ1kuhAtFrxKp29yahueVyChWInqqkog/Ba0RPO26RwxRgDczmN2bK\n",
       "a0RP/ewF3NVoENZLoQLRa8SKdlNrlqFggejpAmkFXI85sUUOi7ngNaIH6VBgf8z2icac14ie+ki1\n",
       "WYaCBaLXiJ3YdUde7AL8PY5ywlKoQPR0yo7AdFI+btdrxKIj/RF4DbPIEqX6TA+e2nCLHPYCvpm2\n",
       "K7E1zZKulPSupGkl11aQNEHSy5LGS+obV/ld+NSaN9sx290cmIfZS3GUUQtxasSrgN3Lrp0KTDCz\n",
       "dYH7gvdJMiSHtuO0m9gG+mrEFohm9hDw37LLewHXBD9fgzt9PUnirIHjsh253RaprT8cezqc+F3Y\n",
       "ocUdjZYqSWvEVc3s3eDnd4FVEy6/8LRIbdvARWvCwF+6S1uNgItaJGI5LSAkqQ3fmOuuJ91lH5BD\n",
       "25Ha7QfHjYZBs0quxZWgvRZiHb6RNAC4y8w2Ct6/iMvd/I6k1YFJZrZ+J9/L3piSpyayPnxzJ3A4\n",
       "7niLw4HbO7vJjyEWj9hqREnX4zKNroTTg2fgemh/w50mMAs40MzmxOKAJ1dkcmbFUzxSnWuWtLuk\n",
       "FyXNlHRKF/eMCj5/VtKmUdiVdEhg7zlJj0jaOCp/g/u2kPSVpH3D2A1rW1KrpGfkTnWdHIVdSStJ\n",
       "GidpamD3+yHtLjZh0ck94Z9dHIfJhHnhjtZ6BdcrXBKYCgwuu6cNGBv8vBXwWER2twGWC37ePSq7\n",
       "Jffdj1vNsl+Ef4u+wPPAWsH7lSKy+0vgnHabwH+A7iFsb4/LGDati89renZp1ohbAq+Y2Swz+xK4\n",
       "AbcurpSFA+Bm9jjQV1K1sceqds1sipnNDd4+DqwVkb/ghkFuBmpJ2RHG9sHALWb2ZvA7vB+R3beB\n",
       "PsHPfYD/mNlX1Qxb5xMWpdT07NIMxDWB2SXv3wyuVbunWtCEsVvKkUCYgdyqdiWtiXvQfwwuhRXg\n",
       "YXxeB1hB0iRJT0o6LCK7o4ENJf0LeBaI6iD3mp5dmqtvwj6k8qGcat8L3fuStCNwBLBtiNvD2L0Q\n",
       "ONXMTJJY3PdGbC8JbAbsRHC8sKTHzGxmg3ZPxx242Sp3gPsESZuY2bwQ361G6GeXZiC+BfQred8P\n",
       "97+m0j1rBdcatUvQQRkN7G5mlZqYWuxuDtzgYpCVgGGSvjSzasvww9ieDbxvLnnmp3LnGW4CVArE\n",
       "MHaHAmcDmNmrkl4H1gOerOJzNWp7dkl2UMrEbHfgVZyQXorqnZWtCdepCGO3P07Ebx2lv2X3XwXs\n",
       "G+HfYn3cLrtuuBpxGrBBBHYvAH4R/LwqLlBXCOn3AMJ1Vqo+u9QCMXBwGO40+1eA04JrRwFHldxz\n",
       "SfD5s8BmUdgFLsf1Dp8JXk9E5W89gVjD3+JkXM95GnBcRH+LlYC7gr/vNODgkHavB/4FfIGrrY9o\n",
       "5Nn5AW1PJvCbpzyZwAeiJxP4QPRkAh+InkzgA9GTCXwgejKBD8QEkLSypIclTZO0d8n12yWtlqZv\n",
       "WcEHYjIcBFyKWw1zAoCkPYGnzeydNB3LCj7lSDJ8ASwD9ADmS+qGW+WyR6peZQg/s5IAkvoA1+Hm\n",
       "cn8GbATMMbMxqTqWIXwgJoyk5YEbgW/jlo31Bc43s8dSdSxlfCAmjKQLcNto1wM+A24BbjWz8jxB\n",
       "hcJ3VhJE0jrAGmb2INCTjoWiPdPzKhv4GjFBJN0InG5uAerKuJpxOeB/zey2dL1LFx+Inkzgm2ZP\n",
       "JvCB6MkEPhA9mcAHoicT+ED0ZAIfiJ5M4APRkwl8IHoywf8DpFzm4rlOeHwAAAAASUVORK5CYII=\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fca99c346d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(2, 6))\n",
    "plt.plot(df['loi'], df['depth'], 'ro-')\n",
    "plt.gca().invert_yaxis()\n",
    "plt.title('TOC (LOI)')\n",
    "plt.xlabel('%')\n",
    "plt.ylabel('Depth [m]')\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  }
 ],
 "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": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}