14_StandMap.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Map of the Stands"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I got a txt formatted map of the stands, so lets take a look at it!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "kartta = pd.read_csv('../boreal_data/StandMap.txt', sep='\\t', header=None)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1701, 1169)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(kartta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1671</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1672</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1673</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1674</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1675</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1676</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1677</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1678</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1679</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1680</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1681</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1682</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1683</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1684</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1686</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1687</th>\n",
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       "    <tr>\n",
       "      <th>1688</th>\n",
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       "    <tr>\n",
       "      <th>1689</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1690</th>\n",
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       "    <tr>\n",
       "      <th>1691</th>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1692</th>\n",
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       "    <tr>\n",
       "      <th>1693</th>\n",
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       "      <th>1694</th>\n",
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       "      <th>1695</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1696</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1697</th>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1698</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1699</th>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1700</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1701 rows × 1169 columns</p>\n",
       "</div>"
      ],
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       "1680     0     0     0     0     0     0     0     0     0  \n",
       "1681     0     0     0     0     0     0     0     0     0  \n",
       "1682     0     0     0     0     0     0     0     0     0  \n",
       "1683     0     0     0     0     0     0     0     0     0  \n",
       "1684     0     0     0     0     0     0     0     0     0  \n",
       "1685     0     0     0     0     0     0     0     0     0  \n",
       "1686     0     0     0     0     0     0     0     0     0  \n",
       "1687     0     0     0     0     0     0     0     0     0  \n",
       "1688     0     0     0     0     0     0     0     0     0  \n",
       "1689     0     0     0     0     0     0     0     0     0  \n",
       "1690     0     0     0     0     0     0     0     0     0  \n",
       "1691     0     0     0     0     0     0     0     0     0  \n",
       "1692     0     0     0     0     0     0     0     0     0  \n",
       "1693     0     0     0     0     0     0     0     0     0  \n",
       "1694     0     0     0     0     0     0     0     0     0  \n",
       "1695     0     0     0     0     0     0     0     0     0  \n",
       "1696     0     0     0     0     0     0     0     0     0  \n",
       "1697     0     0     0     0     0     0     0     0     0  \n",
       "1698     0     0     0     0     0     0     0     0     0  \n",
       "1699     0     0     0     0     0     0     0     0     0  \n",
       "1700     0     0     0     0     0     0     0     0     0  \n",
       "\n",
       "[1701 rows x 1169 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kartta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all(kartta[0]== 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10968, 10969, 10969, 10969, 10969, 10969, 26796, 26796, 26796,\n",
       "       26796, 26796, 26796, 26796, 26796, 26796, 26735, 26735, 26735,\n",
       "       26735, 26735, 26647, 26647, 26647, 26619, 26619, 26619, 26619,\n",
       "       26619, 26619, 26604, 26546])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kartta[0].values[np.where(kartta[0] != 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10849, 10849, 10973, 10849, 10851, 10851, 10851, 10972, 10972,\n",
       "       10972, 10972, 10972, 10971, 10971, 14118, 14127, 14127, 14127,\n",
       "       14127, 14127, 14127, 14127, 14127, 26647, 26647, 26607, 26607,\n",
       "       26607, 26574, 26574, 26574, 26574, 26574, 26528, 26528, 26528,\n",
       "       26498, 26498, 26498, 26437, 26437])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ind = 8\n",
    "kartta[ind].values[np.where(kartta[ind] != 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jousi/Documents/gradujose/env/lib/python3.5/site-packages/ipykernel_launcher.py:2: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  \n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc1f298dcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pylab.rcParams['figure.figsize'] = (10,8)\n",
    "plt.imshow(1/kartta.values, interpolation='nearest',cmap='gist_ncar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 7min 12s, sys: 24 ms, total: 7min 12s\n",
      "Wall time: 7min 13s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "sizes = [len(np.where(kartta == i)[0]) for i in range(np.max(np.max(kartta)))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 319, 23.121787817981748)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.min(sizes), np.max(sizes[1:]), np.mean(sizes[1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([12836]),)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(sizes==np.max(sizes[1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(np.where(sizes==np.min(sizes))[0])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "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
}