diff --git a/01 EDA.ipynb b/01 EDA.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5549137e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "import seaborn as sns\n",
+    "#sns.set()\n",
+    "\n",
+    "#from scipy.stats import norm\n",
+    "#from sklearn import preprocessing\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f37934fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df    = pd.read_csv(\"reto_data/measurements.csv\", decimal=\",\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d2e50b97",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>distance</th>\n",
+       "      <th>consume</th>\n",
+       "      <th>speed</th>\n",
+       "      <th>temp_inside</th>\n",
+       "      <th>temp_outside</th>\n",
+       "      <th>specials</th>\n",
+       "      <th>gas_type</th>\n",
+       "      <th>AC</th>\n",
+       "      <th>rain</th>\n",
+       "      <th>sun</th>\n",
+       "      <th>refill liters</th>\n",
+       "      <th>refill gas</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>28.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>26</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>12</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>E10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>12.0</td>\n",
+       "      <td>4.2</td>\n",
+       "      <td>30</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>13</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11.2</td>\n",
+       "      <td>5.5</td>\n",
+       "      <td>38</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>12.9</td>\n",
+       "      <td>3.9</td>\n",
+       "      <td>36</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>14</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>18.5</td>\n",
+       "      <td>4.5</td>\n",
+       "      <td>46</td>\n",
+       "      <td>21.5</td>\n",
+       "      <td>15</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>E10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   distance  consume  speed  temp_inside  temp_outside specials gas_type  AC  \\\n",
+       "0      28.0      5.0     26         21.5            12      NaN      E10   0   \n",
+       "1      12.0      4.2     30         21.5            13      NaN      E10   0   \n",
+       "2      11.2      5.5     38         21.5            15      NaN      E10   0   \n",
+       "3      12.9      3.9     36         21.5            14      NaN      E10   0   \n",
+       "4      18.5      4.5     46         21.5            15      NaN      E10   0   \n",
+       "\n",
+       "   rain  sun  refill liters refill gas  \n",
+       "0     0    0           45.0        E10  \n",
+       "1     0    0            NaN        NaN  \n",
+       "2     0    0            NaN        NaN  \n",
+       "3     0    0            NaN        NaN  \n",
+       "4     0    0            NaN        NaN  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b8a23c19",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 388 entries, 0 to 387\n",
+      "Data columns (total 12 columns):\n",
+      " #   Column         Non-Null Count  Dtype  \n",
+      "---  ------         --------------  -----  \n",
+      " 0   distance       388 non-null    float64\n",
+      " 1   consume        388 non-null    float64\n",
+      " 2   speed          388 non-null    int64  \n",
+      " 3   temp_inside    376 non-null    float64\n",
+      " 4   temp_outside   388 non-null    int64  \n",
+      " 5   specials       93 non-null     object \n",
+      " 6   gas_type       388 non-null    object \n",
+      " 7   AC             388 non-null    int64  \n",
+      " 8   rain           388 non-null    int64  \n",
+      " 9   sun            388 non-null    int64  \n",
+      " 10  refill liters  13 non-null     float64\n",
+      " 11  refill gas     13 non-null     object \n",
+      "dtypes: float64(4), int64(5), object(3)\n",
+      "memory usage: 36.5+ KB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "481f869a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "distance           0\n",
+       "consume            0\n",
+       "speed              0\n",
+       "temp_inside       12\n",
+       "temp_outside       0\n",
+       "specials         295\n",
+       "gas_type           0\n",
+       "AC                 0\n",
+       "rain               0\n",
+       "sun                0\n",
+       "refill liters    375\n",
+       "refill gas       375\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.isnull().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "07d5d0b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.duplicated().sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "86405408",
+   "metadata": {},
+   "source": [
+    "# Variables CATEGORICAS:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "481eb5c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Variables categoricas encontradas: ['specials', 'gas_type', 'refill gas']\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>unique</th>\n",
+       "      <th>top</th>\n",
+       "      <th>freq</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>specials</th>\n",
+       "      <td>93</td>\n",
+       "      <td>12</td>\n",
+       "      <td>rain</td>\n",
+       "      <td>32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>gas_type</th>\n",
+       "      <td>388</td>\n",
+       "      <td>2</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>228</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>refill gas</th>\n",
+       "      <td>13</td>\n",
+       "      <td>2</td>\n",
+       "      <td>SP98</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           count unique   top freq\n",
+       "specials      93     12  rain   32\n",
+       "gas_type     388      2  SP98  228\n",
+       "refill gas    13      2  SP98    8"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(f\"Variables categoricas encontradas: {list(df.columns[df.dtypes == 'object'])}\")\n",
+    "df[[ c for c in df.columns if df[c].dtype == \"object\" ]].describe().T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "e0202aee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "rain                  32\n",
+       "sun                   27\n",
+       "AC rain                9\n",
+       "ac                     8\n",
+       "AC                     6\n",
+       "snow                   3\n",
+       "sun ac                 3\n",
+       "AC snow                1\n",
+       "half rain half sun     1\n",
+       "AC sun                 1\n",
+       "AC Sun                 1\n",
+       "ac rain                1\n",
+       "Name: specials, dtype: int64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.specials.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "98f62c55",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SP98    228\n",
+       "E10     160\n",
+       "Name: gas_type, dtype: int64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.gas_type.value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5279ae4b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SP98    8\n",
+       "E10     5\n",
+       "Name: refill gas, dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"refill gas\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a44e180",
+   "metadata": {},
+   "source": [
+    "# Variables NUMÉRICAS:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "4f5f634c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>distance</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>19.652835</td>\n",
+       "      <td>22.667837</td>\n",
+       "      <td>1.3</td>\n",
+       "      <td>11.80</td>\n",
+       "      <td>14.6</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>216.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>consume</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>4.912371</td>\n",
+       "      <td>1.033172</td>\n",
+       "      <td>3.3</td>\n",
+       "      <td>4.30</td>\n",
+       "      <td>4.7</td>\n",
+       "      <td>5.3</td>\n",
+       "      <td>12.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>speed</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>41.927835</td>\n",
+       "      <td>13.598524</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>32.75</td>\n",
+       "      <td>40.5</td>\n",
+       "      <td>50.0</td>\n",
+       "      <td>90.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>temp_inside</th>\n",
+       "      <td>376.0</td>\n",
+       "      <td>21.929521</td>\n",
+       "      <td>1.010455</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>21.50</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>22.5</td>\n",
+       "      <td>25.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>temp_outside</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>11.358247</td>\n",
+       "      <td>6.991542</td>\n",
+       "      <td>-5.0</td>\n",
+       "      <td>7.00</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>31.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>AC</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>0.077320</td>\n",
+       "      <td>0.267443</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>rain</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>0.123711</td>\n",
+       "      <td>0.329677</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sun</th>\n",
+       "      <td>388.0</td>\n",
+       "      <td>0.082474</td>\n",
+       "      <td>0.275441</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>refill liters</th>\n",
+       "      <td>13.0</td>\n",
+       "      <td>37.115385</td>\n",
+       "      <td>8.587282</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>37.60</td>\n",
+       "      <td>38.0</td>\n",
+       "      <td>39.0</td>\n",
+       "      <td>45.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               count       mean        std   min    25%   50%   75%    max\n",
+       "distance       388.0  19.652835  22.667837   1.3  11.80  14.6  19.0  216.1\n",
+       "consume        388.0   4.912371   1.033172   3.3   4.30   4.7   5.3   12.2\n",
+       "speed          388.0  41.927835  13.598524  14.0  32.75  40.5  50.0   90.0\n",
+       "temp_inside    376.0  21.929521   1.010455  19.0  21.50  22.0  22.5   25.5\n",
+       "temp_outside   388.0  11.358247   6.991542  -5.0   7.00  10.0  16.0   31.0\n",
+       "AC             388.0   0.077320   0.267443   0.0   0.00   0.0   0.0    1.0\n",
+       "rain           388.0   0.123711   0.329677   0.0   0.00   0.0   0.0    1.0\n",
+       "sun            388.0   0.082474   0.275441   0.0   0.00   0.0   0.0    1.0\n",
+       "refill liters   13.0  37.115385   8.587282  10.0  37.60  38.0  39.0   45.0"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.describe().T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "32525e32",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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znPXJe1e0Ti8M41vW5fgtVMP90HA/uA/GTZJD2qNQAX4eWLgC2cXAB5K8lebU4yOBTw0hoiRJkjSxuioIJdmPphh0XlV9BPxmV5LUvSQfBGaBg5NsB94IzCY5iuaLhW3ArwBU1Y1JLgBuohnH7hWOQydJkiT11l4LQkkCnA3cXFVv7ZjvN7uSpK5U1SlLzD57D8u/GXhz/xJJkiRJ062bI4SeDrwEuD7Jte28NwCn+M2uJEmSJEnS+OnmKmOfBLLEXZfuYR2/2ZUkSZIkSRpRDxp2AEmSJEmSJA2WBSFJkiRJYy3Jf0lyY5IbknwwyUOTHJHkqiRbk5yf5MHDzilJo8SCkCRJkqSxleRQ4NeBDVX1FGAf4GTgLcDbquoJwF3AGcNLKUmjx4KQJEmSpHG3L7B/kn2BhwE7gWcCF7b3nwu8YDjRJGk0dXOVMUmSJEkaSVW1I8kfAl8B/gn4OHANcHdV7W4X2w4cutT6STYCGwFmZmaYm5vre+aVmJ+fn8pMm9bv3vtCHWb2X/k6nfrRnmn9262UmbrTj0wWhCRJkiSNrSSPBk4EjgDuBv4SOL7b9atqC7AFYMOGDTU7O9v7kGswNzfHNGY6ffMlK1p+0/rdnHX96j/ebjt1dtXrLmda/3YrZabu9COTp4xJkiRJGmc/C3y5qr5aVd8BPgI8HTiwPYUM4DBgx7ACStIosiAkSZIkaZx9BTg2ycOSBDgOuAm4Anhhu8xpwEVDyidJI8mCkCRJkqSxVVVX0Qwe/RngeprPOFuA1wGvSbIVeAxw9tBCStIIcgwhSZIkSWOtqt4IvHHR7FuAY4YQR5LGgkcISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZfZaEEpyeJIrktyU5MYkr2rnH5TksiRfbH8/up2fJO9IsjXJdUmO7ncjJEmSJEmS1L1ujhDaDWyqqicDxwKvSPJkYDNweVUdCVzeTgM8Bziy/dkIvLvnqSVJkiRJkrRqey0IVdXOqvpMe/ubwM3AocCJwLntYucCL2hvnwi8rxpXAgcmOaTXwSVJkiRJkrQ6+65k4STrgKcBVwEzVbWzvet2YKa9fShwW8dq29t5OzvmkWQjzRFEzMzMMDc3t6Lg8/PzbFp/34rW6YWV5uyn+fn5kcozLO6HhvvBfSBJkiRJ3eq6IJTk4cCHgVdX1TeSfO++qqoktZINV9UWYAvAhg0banZ2diWrMzc3x1mfvHdF6/TCtlNnB77N5czNzbHS/TaJ3A8N94P7QJIkSZK61dVVxpLsR1MMOq+qPtLOvmPhVLD29652/g7g8I7VD2vnSZIkSZIkaQR0c5WxAGcDN1fVWzvuuhg4rb19GnBRx/yXtlcbOxa4p+PUMkmSJEmSJA1ZN6eMPR14CXB9kmvbeW8AzgQuSHIGcCtwUnvfpcAJwFbgW8DLehlYkiRJkiRJa7PXglBVfRLIMncft8TyBbxijbkkSZIkSZLUJ12NISRJkiRJkqTJYUFIkiRJkiRpynR92XlJkiRJ0nRat/mS793etH43p3dMSxpPFoQkSZIkacyssyAjaY08ZUySJEnSWEtyYJILk3w+yc1JfirJQUkuS/LF9vejh51TkkaJBSFJ0kAkeW+SXUlu6Ji35Jv1NN6RZGuS65IcPbzkkqQx8Hbgr6vqScBTgZuBzcDlVXUkcHk7LUlqWRCSJA3KOcDxi+Yt92b9OcCR7c9G4N0DyihJGjNJHgX8NHA2QFX9S1XdDZwInNsudi7wgmHkk6RR5RhCkqSBqKpPJFm3aPaJwGx7+1xgDnhdO/99VVXAle2pAIdU1c4BxZUkjY8jgK8Cf57kqcA1wKuAmY5+43ZgZqmVk2yk+fKBmZkZ5ubm+h54Jebn55fMtGn97sGHac3sP9ztL2Wtmfrxd1/ubzdMZurOtGSyICRJGqbl3qwfCtzWsdz2dt79CkK+ie/OMPbLKL6RGpRpbjtMd/unue1Dti9wNPBrVXVVkrez6PSwqqoktdTKVbUF2AKwYcOGmp2d7XPclZmbm2OpTMO8ytem9bs56/rR+ii51kzbTp3tXZjWcn+7YTJTd6Yl02j9F0uSptae3qzvYR3fxHehH29y92YU30gNyjS3Haa7/dPc9iHbDmyvqqva6QtpCkJ3LBxdmuQQYNfQEkrSCHIMIUnSMN3Rvkln0Zv1HcDhHcsd1s6TJOl+qup24LYkT2xnHQfcBFwMnNbOOw24aAjxJGlkWRCSJA3Tcm/WLwZe2l5t7FjgHscPkiTtwa8B5yW5DjgK+G/AmcCzknwR+Nl2WpLU8pQxSdJAJPkgzQDSByfZDryR5s35BUnOAG4FTmoXvxQ4AdgKfAt42cADS5LGRlVdC2xY4q7jBhxFksaGBSFJ0kBU1SnL3PWAN+vt1cVe0d9EkiRJ0vTaa0EoyXuB5wG7quop7bw3Ab9Mc3lHgDdU1aXtfa8HzgDuA369qv6mD7klSVKX1g16EOsznzvQ7UmSJGnluhlD6Bzg+CXmv62qjmp/FopBTwZOBn6sXed/JNmnV2ElSZIkSZK0dns9QqiqPpFkXZePdyLwoar6NvDlJFuBY4C/X31ESZIkSZImx6CP3gWP4NUDrWUMoVcmeSlwNbCpqu4CDgWu7FhmezvvAZJsBDYCzMzMMDc3t6KNz8/Ps2n9fauIvTYrzdlP8/PzI5VnWNwPDfeD+0CSJEmSurXagtC7gd8Dqv19FvDylTxAVW0BtgBs2LChZmdnVxRgbm6Osz5574rW6YVtp84OfJvLmZubY6X7bRK5HxruB/eBJEmSJHVrVQWhqrpj4XaS9wAfayd3AId3LHpYO0+SJEmSpJHUj1O4Nq3fzelDODVM6lY3g0o/QJJDOiZ/HrihvX0xcHKShyQ5AjgS+NTaIkqSJEmSJKmXurns/AeBWeDgJNuBNwKzSY6iOWVsG/ArAFV1Y5ILgJuA3cArqmrwA/1IkiRJkiRpWd1cZeyUJWafvYfl3wy8eS2hJEmSJEmS1D+rOmVMkiRJkiRJ48uCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU2avVxmTJGmSrdt8Sd8ee9P63Zzex8eXJEmSVssjhCRJkiRJkqaMBSFJkiRJYy/JPkk+m+Rj7fQRSa5KsjXJ+UkePOyMkjRKLAhJkiRJmgSvAm7umH4L8LaqegJwF3DGUFJJ0oiyICRJkiRprCU5DHgu8GftdIBnAhe2i5wLvGAo4SRpRDmotCRJkqRx90fAa4FHtNOPAe6uqt3t9Hbg0KVWTLIR2AgwMzPD3NxcX4Ou1Pz8/JKZNq3f/cCFB2Rm/+Fufylm2ru5ublln0/DZKbu9COTBSFJkiRJYyvJ84BdVXVNktmVrl9VW4AtABs2bKjZ2RU/RF/Nzc2xVKZhXsVy0/rdnHX9aH2UNNPebTt1dtnn0zCZqTv9yDQ6z05JkiRJWrmnA89PcgLwUOCRwNuBA5Ps2x4ldBiwY4gZJWnkOIaQJEmSpLFVVa+vqsOqah1wMvC3VXUqcAXwwnax04CLhhRRkkZSVwWhJO9NsivJDR3zDkpyWZIvtr8f3c5Pkne0l3e8LsnR/QovSZIkSct4HfCaJFtpxhQ6e8h5JGmkdHuE0DnA8YvmbQYur6ojgcvbaYDnAEe2PxuBd689piRJkiTtWVXNVdXz2tu3VNUxVfWEqnpRVX172PkkaZR0VRCqqk8Ady6afSLN5Rvh/pdxPBF4XzWupDl395AeZJUkSZIkSVIPrGVQ6Zmq2tnevh2YaW8fCtzWsdzCJR53dsxb8+Ud5+fn2bT+vpWnXqNRuvTcKF4KbxjcDw33g/tAkiRJkrrVk6uMVVUlqRWus6bLO87NzXHWJ+9d0Tq9sO3U2YFvczmjeCm8YXA/NNwP7gNJkiRJ6tZarjJ2x8KpYO3vXe38HcDhHct5iUdJkiRJkqQRspaC0MU0l2+E+1/G8WLgpe3Vxo4F7uk4tUySJEmSJElD1tUpY0k+CMwCByfZDrwROBO4IMkZwK3ASe3ilwInAFuBbwEv63FmSdKESbIN+CZwH7C7qjYkOQg4H1gHbANOqqq7hpVRkiRJmiRdFYSq6pRl7jpuiWULeMVaQkmSptLPVNXXOqY3A5dX1ZlJNrfTrxtONEmSJGmyrOWUMUmS+ulE4Nz29rnAC4YXRZIkSZosPbnKmCRJa1TAx9srVv5peyXKmY4x6G4HZhavlGQjsBFgZmaGubm5FW940/rdq828VzP79/fxR9Xc3Bzz8/Or+ntMgmluO0x3+6e57ZKk8WNBSJI0Cp5RVTuS/ABwWZLPd95ZVdUWi1g0fwuwBWDDhg01Ozu74g2fvvmS1SXuwqb1uznr+unraredOsvc3Byr+XtMgmluO0x3+6e57ZKk8eMpY5KkoauqHe3vXcBHgWOAO5IcAtD+3jW8hJIkSdJksSAkSRqqJAckecTCbeDZwA3AxcBp7WKnARcNJ6EkSZI0eabvOHZJ0qiZAT6aBJp+6QNV9ddJPg1ckOQM4FbgpCFmlCRJkiaKBSFJ0lBV1S3AU5eY/3XguMEnkiRJkiafp4xJkiRJkiRNGQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJGltJDk9yRZKbktyY5FXt/IOSXJbki+3vRw87qySNEgtCkiRJksbZbmBTVT0ZOBZ4RZInA5uBy6vqSODydlqS1PKy8yu0bvMlA93etjOfO9DtSZIkSeOkqnYCO9vb30xyM3AocCIw2y52LjAHvG4IESVpJK25IJRkG/BN4D5gd1VtSHIQcD6wDtgGnFRVd611W5IkSZK0nCTrgKcBVwEzbbEI4HZgZpl1NgIbAWZmZpibm+t/0BWYn59fMtOm9bsHH6Y1s/9wt78UM+3d3Nzcss+nYTJTd/qRqVdHCP1MVX2tY3rh8Mwzk2xup63GS5IkSeqLJA8HPgy8uqq+keR791VVJaml1quqLcAWgA0bNtTs7OwA0nZvbm6OpTKdPuAzFzptWr+bs64frZNNzLR3206dXfb5NExm6k4/MvXr2enhmZIkSZIGIsl+NMWg86rqI+3sO5IcUlU7kxwC7BpeQmn41m2+hE3rdw+smOjwJ6OvFwWhAj7eVtz/tK2w7/XwzLUemjk/P8+m9fetJfdY2NN+GcXD2IbB/dBwP7gPJEmaRmkOBTobuLmq3tpx18XAacCZ7e+LhhBPkkZWLwpCz6iqHUl+ALgsyec771zu8My1Hpo5NzfHWZ+8d/Wpx8S2U2eXvW8UD2MbBvdDw/3gPpAkaUo9HXgJcH2Sa9t5b6ApBF2Q5AzgVuCk4cSTpNG05oJQVe1of+9K8lHgGDw8U5IkSdIAVNUngSxz93GDzCJJ4+RBa1k5yQFJHrFwG3g2cAPfPzwTPDxTkiRJkiRppKz1CKEZ4KPtCP77Ah+oqr9O8mk8PFOSJEmSJGkkrakgVFW3AE9dYv7X8fBMSZKmklcxkSRJGn39uuy8JEmSJE2FdX0sgA+ywC5puqxpDCFJkiRJkiSNHwtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU8bLzkuSJEmSpLG2bvMlPXusTet3c/peHm/bmc/t2faGxSOEJEmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnKOIaQJEmSJEnqqW7H9OlmvB71hwUhSZIkSZKkFejlINbdOOf4A3r+mJ4yJkmSJEmSNGX6doRQkuOBtwP7AH9WVWf2a1uTbE9Vx34cWjcJl86TNDnsS9SNQX9DZ18pjRf7EklaWl8KQkn2Ad4FPAvYDnw6ycVVdVM/tidJmjz2JRpVeytA+YWNNDrsSyRpef06QugYYGtV3QKQ5EPAiYAvvCNu0N+y9sJK3nhPwxvqSf+m3KPmpop9idQap/55mgcHXa7t9iVDZV8iSctIVfX+QZMXAsdX1S+10y8BfrKqXtmxzEZgYzv5ROALK9zMwcDXehB3nLkPGu6HhvthtPbB46vqscMOMc4G1Jf02yg9JwfNtk+vaW5/r9tuX7JG9iV9Y6bumKk7ZurOajMt25cM7SpjVbUF2LLa9ZNcXVUbehhp7LgPGu6HhvvBfTCN1tqX9Ns0Pydt+3S2Haa7/dPc9nFmX7JyZuqOmbpjpu70I1O/rjK2Azi8Y/qwdp4kSd2yL5EkrZV9iSQto18FoU8DRyY5IsmDgZOBi/u0LUnSZLIvkSStlX2JJC2jL6eMVdXuJK8E/obm8o7vraobe7yZkT2sc4DcBw33Q8P94D6YKAPqS/ptmp+Ttn16TXP7p7ntI8m+pG/M1B0zdcdM3el5pr4MKi1JkiRJkqTR1a9TxiRJkiRJkjSiLAhJkiRJkiRNmbErCCU5PskXkmxNsnnYeQYpybYk1ye5NsnV7byDklyW5Ivt70cPO2evJXlvkl1JbuiYt2S703hH+/y4LsnRw0veO8vsgzcl2dE+H65NckLHfa9v98EXkvzccFL3VpLDk1yR5KYkNyZ5VTt/qp4LGh9J9kny2SQfG3aWQUpyYJILk3w+yc1JfmrYmQYpyX9pX6NuSPLBJA8ddqZ+WUn/PImWaf8ftM/965J8NMmBQ4yoMbPS9zoDyvTQJJ9K8rk20++0849IclX7Puv8dsDugVrczw470yh+VluqTx6BTE/s+PxybZJvJHn1COR6QP89As+pV7V5bkzy6nZeT/fTWBWEkuwDvAt4DvBk4JQkTx5uqoH7mao6qqo2tNObgcur6kjg8nZ60pwDHL9o3nLtfg5wZPuzEXj3gDL22zk8cB8AvK19PhxVVZcCtP8TJwM/1q7zP9r/nXG3G9hUVU8GjgVe0bZ12p4LGh+vAm4edogheDvw11X1JOCpTNE+SHIo8OvAhqp6Cs0AticPN1VfnUP3/fMkOocHtv8y4ClV9a+BfwBeP+hQGmsrfa8zCN8GnllVTwWOAo5PcizwFpr3oU8A7gLOGGCmBYv72VHINGqf1Zbqk4eaqaq+sPD5Bfhx4FvAR4eZaw/999CeU0meAvwycAzN3+55SZ5Aj/fTWBWEaHbG1qq6par+BfgQcOKQMw3bicC57e1zgRcML0p/VNUngDsXzV6u3ScC76vGlcCBSQ4ZSNA+WmYfLOdE4ENV9e2q+jKwleZ/Z6xV1c6q+kx7+5s0HdqhTNlzQeMhyWHAc4E/G3aWQUryKOCngbMBqupfquruoYYavH2B/ZPsCzwM+Mch5+mbFfbPE2ep9lfVx6tqdzt5JXDYwINpbK3ivc4gMlVVzbeT+7U/BTwTuHAYmeCB/WySDDvTMob2t9tDnzxKr9PHAV+qqlsZfq7F/fdOhvuc+lHgqqr6Vtuv/B/gF+jxfhq3gtChwG0d09vbedOigI8nuSbJxnbeTFXtbG/fDswMJ9rALdfuaXuOvLI9LP29HYcLTvw+SLIOeBpwFT4XNJr+CHgt8N0h5xi0I4CvAn/eHsb/Z0kOGHaoQamqHcAfAl+heSN5T1V9fLipBm5a35cs5eXA/xp2CI2nLt/rDCrLPkmuBXbRHAX3JeDujuLnMN5j/RH372cfMwKZRu2z2nJ98ii9Tp8MfLC9PbRcS/XfwDUM9zl1A/BvkzwmycOAE4DD6fF+GreC0LR7RlUdTXMqzCuS/HTnnVVVNC9EU2Va201zCtQP0xy+uxM4a6hpBiTJw4EPA6+uqm903jfFzwWNkCTPA3ZV1TXDzjIE+wJHA++uqqcB9zLZpwzdT1uYP5HmTfgPAgckefFwUw3PNL8mJ/ktmtN/zht2Fo2fUXuvU1X3taf3HEZz1PmTBrn9xUa4nx21z2p77ZOH+TrdjsfzfOAvF9836FxL9d8sPVzHwFTVzTSnrH0c+GvgWuC+RcuseT+NW0FoB01VbMFh7byp0FYuqapdNOdZHgPcsXAaTPt71/ASDtRy7Z6a50hV3dF20N8F3sP3Twub2H2QZD+aN0jnVdVH2tlT/1zQyHk68Pwk22hObX5mkr8YbqSB2Q5sr6qr2ukLad6MToufBb5cVV+tqu8AHwH+zZAzDdq0vi/5niSnA88DTm3frEtdW+F7nYFqTze6AvgpmlPx923vGvR7rAf0szRj5Qwz0yh+VluuTx6J5xNN4ewzVXVHOz3MXEv1309n+M+ps6vqx6vqp2nGMPoHeryfxq0g9GngyHa07wfTHGJ28ZAzDUSSA5I8YuE28Gyaw8guBk5rFzsNuGg4CQduuXZfDLw0jWNpDtffudQDjLtF4+H8PM3zAZp9cHKShyQ5gmZQ5U8NOl+vteeGnw3cXFVv7bhr6p8LGi1V9fqqOqyq1tH0U39bVVNxlEhV3Q7cluSJ7azjgJuGGGnQvgIcm+Rh7WvWcUzRoNqtaX1fAjRXw6U5jeX5VfWtYefReFnFe51BZHps2qvlJdkfeBbN69oVwAuHkWmZfvbUYWYaxc9qe+iTR+V1+hS+f7oYDDfXUv33TQzxOQWQ5Afa34+jGT/oA/R4P2XcvrhIc2ntP6IZ+fu9VfXm4SYajCQ/RFNphubwvw9U1ZuTPAa4AHgccCtwUlV1O/jwWEjyQWAWOBi4A3gj8Fcs0e72H/iPaQ7x+xbwsqq6egixe2qZfTBLc7pYAduAX1koeLSHqr+c5nD1V1fV2I9hkOQZwN8B1/P988XfQHNu/dQ8FzRekswCv1FVzxtylIFJchTNIJ8PBm6h+d+7a6ihBijNJZl/keb197PAL1XVt4ebqj9W0j8PKWJfLdP+1wMPAb7eLnZlVf3qUAJq7Kz0vc6AMv1rmoFr96E5mOCCqvrd9rPJh4CDaF7rXjyM17rOfnaYmUb1s9pSfTLt33FYmdpcB9AUYX6oqu5p5w17Xz2g/6YZM2hoz/Mkf0czPtZ3gNdU1eW93k9jVxCSJEmSJEnS2ozbKWOSJEmSJElaIwtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCmjpJTk3y8R48znySH1rmvtOTfHKt25AkTZe99VFJ5pL80iAzSZKkyWRBSH2XZFuSnx12jgVVdV5VPbsHj/PwqrqlF5kkSfc3an3HWiR5U5K/6GbZXvVRkqTR0Rbz70rykEXz/2OSq9svmncm+V9JnjGsnJo+FoQkSZIkSeqDJOuAfwsU8PyO+a8B/gj4b8AM8DjgfwAnDjykppYFIfVVkvfTvLj9z7by/dokxyb5f0nuTvK5JLMdy88l+f32/vkk/zPJY5Kcl+QbST7dvqguLF9Jfj3JLUm+luQPkuzxeb34dK72MX41yRfbTO9Kkva+JyT5P0nuaR///EXrPaG9/ZgkF7cZPwX88KJtPinJZUnuTPKFJCetZb9K0iQb0b7jQUl+O8mtSXYleV+SR7X3zSbZvmj5bUl+NsnxwBuAX2yzfa69//R2+99M8uUkp3bM7+yjnpXk820/9MdAFm3n5Ulubr95/pskj1/NPpck9c1LgSuBc4DTANr+43eBV1TVR6rq3qr6TlX9z6r6zeFF1bSxIKS+qqqXAF8B/n1VPRw4D7gE+H3gIOA3gA8neWzHaicDLwEOpSms/D3w5+3yNwNvXLSZnwc2AEfTVNRfvoqozwN+AvjXwEnAz7Xzfw/4OPBo4DDgncus/y7gn4FD2u1/L0OSA4DLgA8AP9C2738kefIqckrSxBvRvuP09udngB8CHg78cRdt+Wuab3/Pb081fmrbL7wDeE5VPQL4N8C1i9dNcjDwEeC3gYOBLwFP77j/RJpi0y8AjwX+Dvjg3jJJkgbqpTT92HnAzyWZAX4KeCjw0WEGkywIadBeDFxaVZdW1Xer6jLgauCEjmX+vKq+VFX3AP8L+FJV/e+q2g38JfC0RY/5lqq6s6q+QnPY5SmryHVmVd3dPsYVwFHt/O8Ajwd+sKr+uaoeMFB0kn2A/wD817a6fwNwbscizwO2VdWfV9Xuqvos8GHgRavIKUnTaBT6jlOBt1bVLVU1D7weODnJvqts03eBpyTZv6p2VtWNSyxzAnBjVV1YVd9pc97ecf+vAv9fVd3ctvO/AUd5lJAkjYZ2PKDHAxdU1TU0hf3/CDwG+Fr72i0NjQUhDdrjgRe1h/zfneRu4Bk0R9YsuKPj9j8tMf3wRY95W8ftW4EfXEWuzjfY3+rYxmtpDs//VJIbkyz1DfJjgX2XyLHg8cBPLmrzqcC/WkVOSZpGo9B3/CD3f22/lea1f2av6RepqnuBX6Qp6OxMckmSJy2zzds61qtFuR8PvL1jn9xJ02cdutJMkqS+OA34eFV9rZ3+QDvv68DBa/hSQeoJn4AahOq4fRvw/qr65R4+/uHAwjerjwP+sVcPXFW3A78M36vw/+8kn6iqrR2LfRXY3eb4fEeOBbcB/6eqntWrXJI0BUat7/hHmgLMgsfRvPbfQVO4edjCHe2Ro52ns3W2pZlR9TfA3yTZn+ZUuPfQDDraaWebc+Fx0zlNs1/eXFXn7SW7JGnA2tf3k4B9kix8+fwQ4ECa1/dvAy8ALhxGPgk8QkiDcQfNeAsAfwH8+yQ/l2SfJA9tB+M8bA2P/5tJHp3kcOBVwPl7W6FbSV7Uke0umjf13+1cpqruoxnj4U1JHtaODXRaxyIfA34kyUuS7Nf+/ESSH+1VTkmaQKPWd3wQ+C9JjkjycL4/LtBu4B+AhyZ5bpL9aMb86by08B3AuoWBq5PMJDmxHUvo28A8i/qW1iXAjyX5hfZb5F/n/keX/gnw+iQ/1j7uo5J4OrIkjYYXAPcBT6YZjuIo4Edpxnt7KfBfgXcleUH7GWK/JM9J8t+HE1fTyIKQBuH/A367PZz9F2kG73wDzZE1twG/ydqeixcB19AMyHkJcPYaHmuxnwCuSjIPXAy8qqpuWWK5V9KcjnA7zRUE/nzhjqr6JvBsmgFP/7Fd5i3c/8OCJOn+Rq3veC/wfuATwJdpLiTwawDtuEX/GfgzYAdwL9B51bG/bH9/Pcln2tyvoekT7gT+HfCfFm+wPcXgRcCZNKcXHAn83477P0rTn3woyTeAG4DndNF2SVL/nUYzvt1Xqur2hR+aCxKcCrydpi/4bb7ft70S+Ksh5dUUSnM6ujSekhRw5KJTuCRJWpZ9hyRJkkcISZIkSZIkTR0LQppISf4kyfwSP38y7GySpNFk3yFJkqaJp4xJkiRJkiRNGY8QkiRJkiRJmjIWhCRJEyHJXw87gyT1kq9rkqR+2ndvCyR5L/A8YFdVPaWd9ybgl2kujwfwhqq6tL3v9cAZwH3Ar1fV3+xtGwcffHCtW7duxeHvvfdeDjjggBWvNyzjlNes/TNOeccpK4xW3muuueZrVfXYYeeYJo985CN/bsOGDSs+D3qUnjdLGeV8Zlsds63OlGb7Rj8eVMubls8lqzHpbZz09sHkt9H2LW2Pn0uqao8/wE8DRwM3dMx7E/AbSyz7ZOBzwEOAI4AvAfvsbRs//uM/XqtxxRVXrGq9YRmnvGbtn3HKO05Zq0YrL3B17eW1z5/e/kxqXzLK+cy2OmZbnWnMZl9iXzJKJr2Nk96+qslvo+1b2p76kr2eMlZVnwDu7LL4dCLwoar6dlV9GdgKHNPlupIkSZIkSRqAvZ4ytgevTPJS4GpgU1XdBRwKXNmxzPZ23gMk2QhsBJiZmWFubm7FAebn51e13rCMU16z9s845R2nrDB+eSVJkiRpWFZbEHo38HtAtb/PAl6+kgeoqi3AFoANGzbU7OzsikPMzc2xmvWGZZzymrV/xinvOGWF8cs7bZYZk+4g4HxgHbANOKmq7koS4O3ACcC3gNOr6jPDyC1JkiRNolVdZayq7qiq+6rqu8B7+P5pYTuAwzsWPaydJ0nSOcDxi+ZtBi6vqiOBy9tpgOcAR7Y/G2m+iJAkSZLUI6sqCCU5pGPy54Eb2tsXAycneUiSI2jeyH9qbRElSZNgmTHpTgTObW+fC7ygY/772rHwrgQOXNT3SJIkSVqDbi47/0FgFjg4yXbgjcBskqNoThnbBvwKQFXdmOQC4CZgN/CKqrqvL8nVF+s2XwLApvW7Ob293U/bznxu37chaaTNVNXO9vbtwEx7+1Dgto7lFsak29kxbyrGoxvlfMtlu37HPQPNsf7QRz1g3jjut1FgttUZ5WwajOt33DOQ986dfB8taa32WhCqqlOWmH32HpZ/M/DmtYSSJE2fqqoktcJ1Jn48ulHOt1y2gX8oOvWBGcZxv40Cs63OKGeTJGk5qzplTJKkHrlj4VSw9veudr5j0kmSJEl9ZEFIkjRMFwOntbdPAy7qmP/SNI4F7uk4tUySJEnSGq32svOSJK3IMmPSnQlckOQM4FbgpHbxS2kuOb+V5rLzLxt4YEmSJGmCWRCSJA3EMmPSARy3xLIFvKK/iSRJkqTp5SljkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRl9loQSvLeJLuS3NAx7w+SfD7JdUk+muTAdv66JP+U5Nr250/6mF2SJEmSJEmr0M0RQucAxy+adxnwlKr618A/AK/vuO9LVXVU+/OrvYkpSZIkSZKkXtlrQaiqPgHcuWjex6tqdzt5JXBYH7JJkiRJkiSpD/btwWO8HDi/Y/qIJJ8FvgH8dlX93VIrJdkIbASYmZlhbm5uxRuen59f1XrDMg55N61v6nwz+3//dj/1Yn+Mw37tNE55xykrjF9eSZLUvSQPBT4BPITmc8yFVfXGJEcAHwIeA1wDvKSq/iXJQ4D3AT8OfB34xaraNpTwkjSC1lQQSvJbwG7gvHbWTuBxVfX1JD8O/FWSH6uqbyxet6q2AFsANmzYULOzsyve/tzcHKtZb1jGIe/pmy8BmmLQWdf3ol64Z9tOnV3zY4zDfu00TnnHKSuMX15JkrQi3waeWVXzSfYDPpnkfwGvAd5WVR9qxzA9A3h3+/uuqnpCkpOBtwC/OKzwkjRqVn2VsSSnA88DTq2qAqiqb1fV19vb1wBfAn6kBzklSZIkTbFqzLeT+7U/BTwTuLCdfy7wgvb2ie007f3HJclg0krS6FvVISBJjgdeC/y7qvpWx/zHAndW1X1Jfgg4ErilJ0klSZIkTbUk+9CcFvYE4F00X0Df3TG+6Xbg0Pb2ocBtAFW1O8k9NKeVfW3RY655KItBDbfQadCnyU/6qfmT3j6Y/DbavpXba0EoyQeBWeDgJNuBN9JcVewhwGVtkf3K9opiPw38bpLvAN8FfrWq7lzygSVJkiRpBarqPuCoJAcCHwWe1IPHXPNQFu8876KBDLfQqRdDL6zEpJ+aP+ntg8lvo+1bub2+alXVKUvMPnuZZT8MfHitoSRJ0yPJfwF+ieaw/+uBlwGHsMQAoUMLKUkaKVV1d5IrgJ8CDkyyb3uU0GHAjnaxHcDhwPYk+wKPohlcWpLEGsYQkiRprZIcCvw6sKGqngLsAywM/Pm2qnoCcBfNwKCSpCmW5LHtkUEk2R94FnAzcAXwwnax04CL2tsXt9O09//twtinkiQLQpKk4dsX2L/99vZhNFesXG6AUEnS9DoEuCLJdcCngcuq6mPA64DXJNlKc2TpwtkMZwOPaee/Btg8hMySNLIGe6KrJEkdqmpHkj8EvgL8E/BxmlPElhsg9H56MRDoqA9AOMr5lss2CgOrjuN+GwVmW51RzjZJquo64GlLzL8FOGaJ+f8MvGgA0SRpLFkQkiQNTZJH01wW+AjgbuAvgeO7Xb8XA4GO+gCEo5xvuWynb75koDmWGlh1HPfbKDDb6oxyNkmSluMpY5KkYfpZ4MtV9dWq+g7wEeDptAOEtst0DhAqSZIkqQcsCEmShukrwLFJHpYkwHHATSw/QKgkSZKkHrAgJEkamqq6imbw6M/QXHL+QTSngC03QKgkSZKkHnAMIUnSUFXVG4E3Lpq95AChkiRJknrDI4QkSZIkSZKmjAUhSZIkSZKkKWNBSJIkSZIkacpYEJIkSZIkSZoyFoQkSZIkSZKmjAUhSZIkSZKkKWNBSJIkSZIkacpYEJIkSZIkSZoyXRWEkrw3ya4kN3TMOyjJZUm+2P5+dDs/Sd6RZGuS65Ic3a/wkiRJkiRJWrl9u1zuHOCPgfd1zNsMXF5VZybZ3E6/DngOcGT785PAu9vf0gOs23zJmh9j0/rdnN7l42w787lr3p4kSZIkSeOuqyOEquoTwJ2LZp8InNvePhd4Qcf891XjSuDAJIf0IKskSZIkSZJ6oNsjhJYyU1U729u3AzPt7UOB2zqW297O29kxjyQbgY0AMzMzzM3NrTjA/Pz8qtYblnHIu2n9bgBm9v/+7VG3kqyjsP/H4XmwYJyywvjllSRJkqRhWUtB6HuqqpLUCtfZAmwB2LBhQ83Ozq54u3Nzc6xmvWEZh7wLp15tWr+bs67vydOj71aSddups/0N04VxeB4sGKesMH55JfXGUqcfr+R04pXy9GNJkjQJ1nKVsTsWTgVrf+9q5+8ADu9Y7rB2niRJkiRJkkbAWgpCFwOntbdPAy7qmP/S9mpjxwL3dJxaJkmSJEmSpCHr6jybJB8EZoGDk2wH3gicCVyQ5AzgVuCkdvFLgROArcC3gJf1OLMkSZIkSZLWoKuCUFWdssxdxy2xbAGvWEsoSZIkSZIk9c9aThmTJEmSJEnSGLIgJEmSJEmSNGUsCEmSJEmSJE0ZC0KSpKFKcmCSC5N8PsnNSX4qyUFJLkvyxfb3o4edU5IkSZokFoQkScP2duCvq+pJwFOBm4HNwOVVdSRweTstSZIkqUcsCEmShibJo4CfBs4GqKp/qaq7gROBc9vFzgVeMIx8kiRJ0qTq6rLzkiT1yRHAV4E/T/JU4BrgVcBMVe1sl7kdmFlq5SQbgY0AMzMzzM3NrTjA/Pz8qtYblFHOt1y2Tet3Dz7MIjP79y/HWv8e4/g3HQVmkySptywISZKGaV/gaODXquqqJG9n0elhVVVJaqmVq2oLsAVgw4YNNTs7u+IAc3NzrGa9QRnlfMtlO33zJYMPs8im9bs56/r+vM3ZdursmtYfx7/pKDCbJEm95SljkqRh2g5sr6qr2ukLaQpEdyQ5BKD9vWtI+SRJkqSJZEFIkjQ0VXU7cFuSJ7azjgNuAi4GTmvnnQZcNIR4kqQRkuTwJFckuSnJjUle1c5f8sqUabwjydYk1yU5ergtkKTR4iljkqRh+zXgvCQPBm4BXkbzhcUFSc4AbgVOGmI+SdJo2A1sqqrPJHkEcE2Sy4DTaa5MeWaSzTSnHr8OeA5wZPvzk8C729+SJCwISZKGrKquBTYscddxA44idWXdGsdI2rR+94rHWdp25nPXtE1pErQXG9jZ3v5mkpuBQ2muTDnbLnYuMEdTEDoReF9VFXBlkgOTHNJx0QJJmmoWhCRJkiSNlSTrgKcBV7H8lSkPBW7rWG17O+9+BaFeXLGyn1c2XM6gr2w36VfTm/T2weS30fatnAUhSZIkSWMjycOBDwOvrqpvJPnefXu6MuVyenHFyneed1Hfrmy4nLVe8XClJv1qepPePpj8Ntq+lXNQaUmSJEljIcl+NMWg86rqI+3s5a5MuQM4vGP1w9p5kiQsCEmSJEkaA2kOBTobuLmq3tpx13JXprwYeGl7tbFjgXscP0iSvm/VxzW2lwg+v2PWDwH/FTgQ+GXgq+38N1TVpavdjiRJkiQBTwdeAlyf5Np23huAM1n6ypSXAicAW4Fv0VzFUpLUWnVBqKq+ABwFkGQfmsMvP0rzQvu2qvrDXgSUJEmSpKr6JJBl7n7AlSnbq4u9oq+hJGmM9eqUseOAL1XVrT16PEmSJEmSJPVJr4bCPxn4YMf0K5O8FLga2FRVdy1eoReXdxy3y8qNQ96Fy2UO49KZq7WSrKOw/8fhebBgnLLC+OWVJEmSpGFZc0EoyYOB5wOvb2e9G/g9oNrfZwEvX7xeLy7vOG6XlRuHvKdvvgRoCiyDvnTmaq0k66Avz7mUcXgeLBinrDB+eSVJkiRpWHpxythzgM9U1R0AVXVHVd1XVd8F3gMc04NtSJIkSZIkqUd6URA6hY7TxZIc0nHfzwM39GAbkiRJkiRJ6pE1nROU5ADgWcCvdMz+70mOojllbNui+yRJkiRJkjRkayoIVdW9wGMWzXvJmhJJkiRJkiSpr3p12XlJkiRJkiSNCQtCkiRJkiRJU8aCkCRJkiRJ0pSxICRJkiRJkjRlLAhJkiRJkiRNGQtCkiRJkiRJU2ZNl52XJEmjb93mS/ryuJvW7+b0Pj227q9ff8PFFv6m28587kC2J0mShscjhCRJQ5dknySfTfKxdvqIJFcl2Zrk/CQPHnZGSZIkaZJYEJIkjYJXATd3TL8FeFtVPQG4CzhjKKkkSZKkCeUpY5oqgzrkvpOH3Ut7luQw4LnAm4HXJAnwTOA/toucC7wJePdQAkqSJEkTyIKQJGnY/gh4LfCIdvoxwN1Vtbud3g4cutSKSTYCGwFmZmaYm5tb8cbn5+dXtd6g9CLfpvW7977QKszs37/HXiuzrc5CtlH8nxjl/9VRziZJ0nIsCEmShibJ84BdVXVNktmVrl9VW4AtABs2bKjZ2RU/BHNzc6xmvUHpRb5+Dfy8af1uzrp+NN9KmG11FrJtO3V22FEeYJT/V0c5myRJyxnNdyOSpGnxdOD5SU4AHgo8Eng7cGCSfdujhA4DdgwxoyRJkjRxHFRakjQ0VfX6qjqsqtYBJwN/W1WnAlcAL2wXOw24aEgRJUmSpIlkQUiSNIpeRzPA9FaaMYXOHnIeSZIkaaKs+ZSxJNuAbwL3AburakOSg4DzgXXANuCkqrprrduSJE2uqpoD5trbtwDHDDOPJEmSNMl6dYTQz1TVUVW1oZ3eDFxeVUcCl7fTkiRJkiRJGgH9OmXsRODc9va5wAv6tB1JkiRJkiStUC+uMlbAx5MU8KftJYBnqmpne//twMzilZJsBDYCzMzMMDc3t+INz8/Pr2q9YRmHvJvW7wZgZv/v3x51o5518d98HJ4HC8YpK4xfXkmSJEkall4UhJ5RVTuS/ABwWZLPd95ZVdUWi1g0fwuwBWDDhg01Ozu74g3Pzc2xmvWGZRzynr75EqApsJx1fS+eHv036lm3nTp7v+lxeB4sGKesMH55JUmSJGlY1nzKWFXtaH/vAj5KMwjoHUkOAWh/71rrdiRJkiRJktQbayoIJTkgySMWbgPPBm4ALgZOaxc7DbhoLduRJEmSJElS76z1PJsZ4KNJFh7rA1X110k+DVyQ5AzgVuCkNW5HkiRJkiRJPbKmglBV3QI8dYn5XweOW8tjS5IkSZIkqT/6ddl5SZIkSeqpJO9NsivJDR3zDkpyWZIvtr8f3c5Pknck2ZrkuiRHDy+5JI0eC0KSJEmSxsU5wPGL5m0GLq+qI4HL22mA5wBHtj8bgXcPKKMkjQULQpIkSZLGQlV9Arhz0ewTgXPb2+cCL+iY/75qXAkcuHAlZEnS2geVliRJK7Ru8yVdL7tp/W5OX8HykjSFZqpqZ3v7dpoL3wAcCtzWsdz2dt7Ojnkk2UhzBBEzMzPMzc2tPMD+zev1IK0m51rMz88PfJuDNOntg8lvo+1bOQtCkiRJkiZCVVWSWuE6W4AtABs2bKjZ2dkVb/ed513EWdcP9qPVtlNnB7q9ubk5VrNvxsWktw8mv422b+U8ZUySJEnSOLtj4VSw9veudv4O4PCO5Q5r50mSsCAkSZIkabxdDJzW3j4NuKhj/kvbq40dC9zTcWqZJE09TxmTJEmSNBaSfBCYBQ5Osh14I3AmcEGSM4BbgZPaxS8FTgC2At8CXjbwwJI0wiwISZIkSRoLVXXKMncdt8SyBbyiv4kkaXx5ypgkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpKkoUlyeJIrktyU5MYkr2rnH5TksiRfbH8/ethZJUmSpEliQUiSNEy7gU1V9WTgWOAVSZ4MbAYur6ojgcvbaUmSJEk9YkFIkjQ0VbWzqj7T3v4mcDNwKHAicG672LnAC4YSUJIkSZpQXnZekjQSkqwDngZcBcxU1c72rtuBmWXW2QhsBJiZmWFubm7F252fn1/Vemuxaf3urped2X9lyw+S2VZnHLIN+n+iG8P4X+3WKGeTJGk5qy4IJTkceB/Nm/QCtlTV25O8Cfhl4Kvtom+oqkvXGlSSNLmSPBz4MPDqqvpGku/dV1WVpJZar6q2AFsANmzYULOzsyve9tzcHKtZby1O33xJ18tuWr+bs64fze9vzLY6Y5Ht+nuHHeUBNq2/j7M+2Ztc2858bk8eZ8EwXkckSVqrtbwbWRj34TNJHgFck+Sy9r63VdUfrj2eJGnSJdmPphh0XlV9pJ19R5JDqmpnkkOAXcNLKEmSJE2eVY8htIdxHyRJ6kqaQ4HOBm6uqrd23HUxcFp7+zTgokFnkyRJkiZZT45XXjTuw9OBVyZ5KXA1zVFEdy2xzliO+3D9jntWve7M/vDO81b2mWb9oY9a9fZWY2FMg1Ee32CxUc+6+Dk6TuMMjFNWGL+8Apo+4yXA9Umubee9ATgTuCDJGcCtwEnDiSdJkiRNpjUXhJYY9+HdwO/RjCv0e8BZwMsXrzcN4z4stpoxA7adOrvq7a3GQvtGeXyDxUY96+K/4TiNMzBOWWH88gqq6pNAlrn7uEFmkSRJkqbJmi47v9S4D1V1R1XdV1XfBd4DHLP2mJIkSZIkSeqVVReElhv3oR38c8HPAzesPp4kSZIkSZJ6bS3n2Sw37sMpSY6iOWVsG/Ara9iGJEmSJEmSemzVBaE9jPtw6erjSJIkSZIkqd/WNIaQJEmSJEmSxo8FIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMmu5ypikLqzbfMn9pjet383pi+b10rYzn9u3x5YkSZIkTQYLQpLGyuICW6d+FNsssEmSJEmaRBaEJEmSJEmSVmBPX1T3wznHH9Dzx7QgJEmSpKnS6zfxeztC1aNNJUmjyEGlJUmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMg4qLWlNBj26viRJkiRp7TxCSJIkSZIkacp4hJAkaapdv+OePV4uWpIkSZpEfSsIJTkeeDuwD/BnVXVmv7Y1yTwdR9I0sy+RJK2VfYkkLa0vBaEk+wDvAp4FbAc+neTiqrqpH9uT9H29LCJuWr/bIyc0NPYlkqS1si+RpOX1awyhY4CtVXVLVf0L8CHgxD5tS5I0mexLJElrZV8iScvo1yljhwK3dUxvB36y1xtx3AdJmmgD6UskSRPNvkSSlpGq6v2DJi8Ejq+qX2qnXwL8ZFW9smOZjcDGdvKJwBdWsamDga+tMe4gjVNes/bPOOUdp6wwWnkfX1WPHXaIcWZf8j2jnM9sq2O21ZnGbPYla2Rf0lOT3sZJbx9Mfhtt39KW7Uv6dYTQDuDwjunD2nnfU1VbgC1r2UiSq6tqw1oeY5DGKa9Z+2ec8o5TVhi/vNor+xJGO5/ZVsdsq2M2rZJ9SY9MehsnvX0w+W20fSvXrzGEPg0cmeSIJA8GTgYu7tO2JEmTyb5EkrRW9iWStIy+HCFUVbuTvBL4G5rLO763qm7sx7YkSZPJvkSStFb2JZK0vH6dMkZVXQpc2q/Hb63p0M4hGKe8Zu2fcco7Tllh/PJqL+xLgNHOZ7bVMdvqmE2rYl/SM5PexklvH0x+G23fCvVlUGlJkiRJkiSNrn6NISRJkiRJkqQRNTYFoSTvTbIryQ0d856a5O+TXJ/kfyZ55DAzLkhyeJIrktyU5MYkr2rnH5TksiRfbH8/ethZYY95X9ROfzfJSIzWvoesf5Dk80muS/LRJAcOOeqesv5em/PaJB9P8oPDzgrL5+24f1OSSnLwsDJ2ZFlu374pyY52316b5IRhZ9V4GMXnTpLjk3whydYkm4edp1OSbW3fe22Sq0cgz1LvEUaiz10m20g830b5/coov84neWiSTyX5XJvtd9r5RyS5qv2fPT/NAMaaMHt7bU7ykPbvv7V9PqwbQsxV66J9r2n/L69LcnmSxw8j51p0278m+Q/te9+R+BzUrW7al+SkjtfXDww641p18Tx9XNuHfLZ9rg79fV23lnrfsOj+JHlH2/brkhy9pg1W1Vj8AD8NHA3c0DHv08C/a2+/HPi9YedssxwCHN3efgTwD8CTgf8ObG7nbwbeMuyse8n7o8ATgTlgw7Bz7iXrs4F92/lvGYV9u4esj+xY5teBPxl21j3lbacPpxmM8Vbg4FHNCrwJ+I1h5/Nn/H5G7blDM/Dpl4AfAh4MfG7h/3EUfoBto/Ba0JFnqfcII9HnLpNtJJ5vo/x+ZZRf54EAD29v7wdcBRwLXACc3M7/E+A/Dftv7E/P//Z7fW0G/vPCezuaK5qdP+zcPW7fzwAPa2//p3FqX7dtbJd7BPAJ4EpG5HNQD/+GRwKfBR7dTv/AsHP3oY1bFl6D275j27Bzr6B9D3jfsOj+E4D/1fZFxwJXrWV7Y3OEUFV9Arhz0ewfoflHBbgM+A8DDbWMqtpZVZ9pb38TuBk4FDgROLdd7FzgBUMJuMhyeavq5qr6wnDT3d8esn68qna3i10JHDasjAv2kPUbHYsdAIzEQF57eN4CvA14LeORVZoExwBbq+qWqvoX4EM0fYiWsMx7hJHoc5fJNhJG+f3KKL/OV2O+ndyv/SngmcCF7fyReZ+nnurmtbnz/+dC4LgkGWDGtdhr+6rqiqr6Vjs5Eu+5V6jb/vX3aL5k/udBhuuBbtr3y8C7quougKraNeCMa9VNGwtYOHvoUcA/DjDfmnTxvuFE4H1tX3QlcGCSQ1a7vbEpCC3jRr7/x38RzVEMI6U9TPRpNN8ezVTVzvau24GZYeVazqK8I20PWV9OUzUdGYuzJnlzktuAU4H/OsRoS+rMm+REYEdVfW64qZa2xPPgle3hk+8d1ikiGluj9Nw5FLitY3o7I/JhuFXAx5Nck2TjsMMsY9T73FF6vo30+5VRfJ1Psk+Sa4FdNF9Kfgm4u+PLqVH7n1VvdPPa/L1l2ufDPcBjBpJu7Vba95zBiL3n7sJe29iegnN4VV0yyGA90s3f8EeAH0nyf5NcmeT4gaXrjW7a+CbgxUm201xh8NcGE20gevoecdwLQi8H/nOSa2gO6/uXIee5nyQPBz4MvHrRUSFUc7zXSBxtsWBPeUfNclmT/BawGzhvWNkWWyprVf1WVR1Ok/OVw8y3WGdemn35BkawaAVL7tt3Az8MHAXsBM4aXjqNmiT/O8kNS/yciM+dlXpGVR0NPAd4RZKfHnagPRnBPneknm+j/H5lVF/nq+q+qjqK5uiIY4AnDSOHNCxJXgxsAP5g2Fl6KcmDgLcCm4adpY/2pTltbBY4BXhPRmD81R47BTinqg6jOcXq/e3fVouM9U6pqs9X1bOr6seBD9J8OzMSkuxH8wbmvKr6SDv7joXDudrfI3N43jJ5R9JyWZOcDjwPOLV9Azt0XezX8xiRUx1hybw/DBwBfC7JNpo3vp9J8q+Gl7Kx1L6tqjvaN+nfBd5D8yZdAqCqfraqnrLEz0Uj+NzZwf2Pej2snTcSqmpH+3sX8FGGv7+WMrJ97ig930b5/co4vM5X1d3AFcBP0Ry2v29710j9z6pnunlt/t4y7fPhUcDXB5Ju7brqe5L8LPBbwPOr6tsDytYre2vjI4CnAHPte99jgYvHaGDpbv6G24GLq+o7VfVlmjHajhxQvl7opo1n0IzrRlX9PfBQYOgXxumRnr5HHOuCUJIfaH8/CPhtmgH8hq49T/hs4OaqemvHXRcDp7W3TwMuGnS2pewh78hZLmt7qONraTqmby23/iDtIWvnC+6JwOcHnW0pS+Wtquur6geqal1VraPpQI6uqtuHGHVP+7bz/NmfB5YcnV9abASfO58Gjkxz1aIH0wxMevGQMwGQ5IAkj1i4TTOo/7D311JGss+F0Xm+jfL7lVF+nU/y2IVv05PsDzyLZoyjK4AXtouN1HNOPdPNa3Pn/88Lgb8dlS8qu7DX9iV5GvCnNO+5R6bQvgJ7bGNV3VNVB3e8972Spq1Dv6Jml7p5jv4VzdFBpLl68I8Atwww41p108avAMcBJPlRmoLQVweasn8uBl6axrHAPR2nea9YxuX1KckHaZ64BwN3AG8EHg68ol3kI8DrR+EFN8kzgL8Drge+285+A8257xcAj6O5WtNJVTX0gSb3kPchwDuBxwJ3A9dW1c8NI+OCPWR9B03ehW9grqyqXx18wu/bQ9YzaK7e9l2a58GvLnzbPkzL5a2qSzuW2UZzpYWvDT7h9+1h355CcxpB0VwF6VfW8gKp6ZHk/YzYcyfNJVL/iOZqGu+tqjcPM8+CJD9Ec1QQNIedf2DY2ZZ5j/BXjECfu0y2WUbg+TbK71dG+XU+yb+mGTR4H5ovVy+oqt9t/zc+BBxEcwWfF4/h0RPai6Vem5P8LnB1VV2c5KHA+2nGvbqT5spzY/Nhu4v2/W9gPc0pmwBfqarnDyft6uytjYuWnaO5suG4FIS6+RuG5nTb44H7gDdX1YeGFngVumjjk2mOIn04TX/x2qr6+NACr8Ay7xv2A6iqP2n/fn9M8/f7FvCytTw/x6YgJEmSJEmSpN4Y61PGJEmSJEmStHIWhCRJkiRJkqaMBSFJkiRJkqQpY0FIkiRJkiRpylgQkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQpY0FIkiRJkiRpylgQkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQpY0FIkiRJkiRpylgQkiRJkiRJmjIWhCRJkiRJkqaMBSFNnSSnJvn4sHNIkiRJGj9JZpJ8Isk3k5yV5A1J/qy9b12SSrJvOz2X5JeWeZw3JfmL9vbjkswn2WdwLdG023fYAaRBq6rzgPOGnUOSJEnSWNoIfA14ZFVVLx6wqr4CPHxhOskc8BdV9We9eHxpKR4hpImzUI2XJEmSpJXo8rPE44GbelUM6gePNFI3LAhpIiTZluR1Sa4D7k3y20m+1B7GeVOSn+9Y9vQkn+yYriS/muSLSe5O8q4kGUpDJElD1fYlO9r+4wtJjktyTpLf71hmNsn2jultSX4jyXVJ7klyfpKHDqcFkqSVWuKzxL5Jjk3y/9rPB59LMtsuew5wGvDa9hSvn+089WsNGb53qlmSNwP/Fvjjdht/3C7zpCSXJbmz7aNO6lj/nCTvTnJpknuBn0lyQvtZ6Jtt3/Yba8moyeORFJokpwDPpTl883k0L6K3Ay8C/iLJE6pq5zLrPg/4CeCRwDXA/wT+uu+JJUkjI8kTgVcCP1FV/5hkHdDtN6wnAccD/wz8X+B04E/6EFOS1B+dnyVmgEuAl9B8JjgO+HCSJ1XV6e13x9ur6rcBkjyjl0Gq6reSPJ2OU8aSHABcBvxX4DnAeuCyJDdU1U3tqv8ROIHms82DgS8DJ1XV3yV5NHBEL3Nq/HmEkCbJO6rqtqr6p6r6y6r6x6r6blWdD3wROGYP655ZVXe35+5eARw1iMCSpJFyH/AQ4MlJ9quqbVX1pS7XfUfb79xJ86XCUf0KKUnqi+99lgBeDFxaVZe2nycuA66mKbYMy/OAbVX151W1u6o+C3yY5svvBRdV1f9tM/8z8B2aPu2RVXVXVX1mGME1uiwIaZLctnAjyUuTXNse4nk38BTg4D2se3vH7W/RMaCbJGk6VNVW4NXAm4BdST6U5Ae7XN1+RJLG220dtx8PvGjhs0T7eeIZwCFDSfb9TD+5KNOpwL/qWOa2Rev8B5oi1q1J/k+SnxpMVI0LTxnTJCmAJI8H3kNzaOffV9V9Sa4FHBdIkrRHVfUB4ANJHgn8KfAW4BvAwzoW+1dLrStJGmudA0TfBry/qn55WGG4fx5oMv2fqnpWt+tU1aeBE5PsR3NK9AXA4T1NqbHmEUKaRAfQvBh+FSDJy2iOEJIkaVlJnpjkmUkeQjMW0D8B3wWuBU5IclCSf0VzFJEkaXL9BfDvk/xckn2SPLS9oMBhA8xwB/BDHdMfA34kyUuS7Nf+/ESSH11q5SQPTnJqkkdV1Xdovtz47gBya4xYENLEaQdVOwv4e5oX0vU0A3xKkrQnDwHOpBlQ9HbgB4DXA+8HPgdsAz4OnD+kfJKkAaiq24ATgTfQfMl8G/CbDPbz89uBFya5K8k7quqbwLOBk4F/pOmn3kLTdy3nJcC2JN8AfpXmFDPpe1K1+Eg0SZIkSZIkTTKPEJIkSZIkSZoyFoQkSZIkSZKmjAUhSZIkSZKkKWNBSJIkSZIkacrsO+wAAAcffHCtW7duxevde++9HHDAAb0PNEImvY2T3j6Y/DbavqVdc801X6uqx/YhkpZhX7K8SW/jpLcPJr+Ntm9p9iWDN8l9yahnNN/ajHo+GP2Mk5pvT33JSBSE1q1bx9VXX73i9ebm5pidne19oBEy6W2c9PbB5LfR9i0tya29T6M9sS9Z3qS3cdLbB5PfRtu3NPuSwZvkvmTUM5pvbUY9H4x+xknNt6e+xFPGJEmSJEmSpowFIUmSJEmSpCkzEqeMSZIkSVI/JNkGfBO4D9hdVRuGm0iSRoMFIUmSJEmT7meq6mvDDiFJo8RTxiRJkiRJkqbMWB8hdP2Oezh98yUD3ea2M5870O1JkvrLvkSSJl4BH09SwJ9W1ZbOO5NsBDYCzMzMMDc3t+INzM/Pr2q9QRr1jOZbm1HMd/2Oe+43PbM/vPO8i4aUZu9Wmm/9oY/qY5oH6sffeKwLQpIkSZK0F8+oqh1JfgC4LMnnq+oTC3e2BaItABs2bKjVXNZ51C9XDaOf0XxrM4r5Fn/htmn9bs66fnRLECvNt+3U2f6FWUI//saeMiZJkiRpYlXVjvb3LuCjwDHDTSRJo8GCkCRJkqSJlOSAJI9YuA08G7hhuKkkaTSM7vFakiRJkrQ2M8BHk0Dz2ecDVfXXw40kSaPBgpAkSZKkiVRVtwBPHXYOSRpFnjImSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKU2WtBKMlDk3wqyeeS3Jjkd9r5RyS5KsnWJOcneXA7/yHt9Nb2/nV9boMkSZIkSZJWoJsjhL4NPLOqngocBRyf5FjgLcDbquoJwF3AGe3yZwB3tfPf1i4nSZIkSZKkEbHXglA15tvJ/dqfAp4JXNjOPxd4QXv7xHaa9v7jkqRXgSVJkiRJkrQ2+3azUJJ9gGuAJwDvAr4E3F1Vu9tFtgOHtrcPBW4DqKrdSe4BHgN8bdFjbgQ2AszMzDA3N7fi8DP7w6b1u/e+YA+tJudazM/PD3ybgzTp7YPJb6PtkyRJkqTx01VBqKruA45KciDwUeBJa91wVW0BtgBs2LChZmdnV/wY7zzvIs66vqsm9My2U2cHur25uTlWs2/GxaS3Dya/jbZPkiRJksbPiq4yVlV3A1cAPwUcmGShGnMYsKO9vQM4HKC9/1HA13sRVpIkSZIkSWvXzVXGHtseGUSS/YFnATfTFIZe2C52GnBRe/vidpr2/r+tquphZknSmPGKlZIkSdJo6eYIoUOAK5JcB3wauKyqPga8DnhNkq00YwSd3S5/NvCYdv5rgM29jy1JGjNesVKSJEkaIXsdgKeqrgOetsT8W4Bjlpj/z8CLepJOkjQR2iNFl7ti5X9s558LvAl4N80VK9/Uzr8Q+OMk8YhTSZIkqTcGOyKzJGlqecXK7/OKlb016e2DyW+j7ZMkafAsCEmSBsIrVn6fV6zsrUlvH0x+G22fJEmDt6KrjEmStFZesVKSJEkaPgtCkqS+84qVkqRhSrJPks8m+diws0jSqPCUMUnSIBwCnNuOI/Qg4IKq+liSm4APJfl94LPc/4qV72+vWHkncPIwQkuSJsaraL6IeOSwg0jSqLAgJEnqO69YKUkaliSHAc8F3gy8ZshxJGlkWBCSJEmSNMn+CHgt8Iil7uzFFSvH4Upyo57RfGszivkWX8V1GFd2XYmV5puEq8ZaEJIkSZI0kZI8D9hVVdckmV1qmV5csXIcriQ36hnNtzajmO/0zZfcb3rT+t0Dv7LrSqw03yRcNdZBpSVJkiRNqqcDz0+yDfgQ8MwkfzHcSJI0GiwISZIkSZpIVfX6qjqsqtbRXKDgb6vqxUOOJUkjwYKQJEmSJEnSlBndE/gkSZIkqUeqag6YG3IMSRoZHiEkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkSZI0ZSwISZIkSZIkTRkLQpIkSZIkSVPGgpAkSZIkSdKUsSAkSZIkaSIleWiSTyX5XJIbk/zOsDNJ0qjYa0EoyeFJrkhyU/si+qp2/kFJLkvyxfb3o9v5SfKOJFuTXJfk6H43QpIkSZKW8G3gmVX1VOAo4Pgkxw43kiSNhm6OENoNbKqqJwPHAq9I8mRgM3B5VR0JXN5OAzwHOLL92Qi8u+epJUmSJGkvqjHfTu7X/tQQI0nSyNh3bwtU1U5gZ3v7m0luBg4FTgRm28XOBeaA17Xz31dVBVyZ5MAkh7SPI0mSJEkDk2Qf4BrgCcC7quqqRfdvpPkim5mZGebm5la8jfn5+VWtN0ijntF8azOK+Tat332/6Zn9HzhvlKw036D3dz/+xnstCHVKsg54GnAVMNNR5LkdmGlvHwrc1rHa9nbe/QpCvXjhHcYTahL+6KNk0tsHk99G2ydJkkZZVd0HHJXkQOCjSZ5SVTd03L8F2AKwYcOGmp2dXfE25ubmWM16gzTqGc23NqOY7/TNl9xvetP63Zx1/YpKEAO10nzbTp3tX5gl9ONv3HVrkzwc+DDw6qr6RpLv3VdVlWRFh1724oX3neddNPAn1CT80UfJpLcPJr+Ntk/dSHI48D6aLw8K2FJVb09yEHA+sA7YBpxUVXel6WTeDpwAfAs4vao+M4zskqTJUFV3J7kCOB64YW/LS9Kk6+oqY0n2oykGnVdVH2ln35HkkPb+Q4Bd7fwdwOEdqx/WzpMkTS/Ho5MkDVySx7ZHBpFkf+BZwOeHGkqSRkQ3VxkLcDZwc1W9teOui4HT2tunARd1zH9pe7WxY4F7HD9IkqZbVe1cOMKnqr4JdI5Hd2672LnAC9rb3xuPrqquBA5c+BJCkqQVOAS4Isl1wKeBy6rqY0POJEkjoZvzrZ4OvAS4Psm17bw3AGcCFyQ5A7gVOKm971KaQ/y30hzm/7JeBpYkjTfHo3M8ul6b9PbB5LfR9qlfquo6mj5HkrRIN1cZ+ySQZe4+bonlC3jFGnNJkiaQ49E1HI+utya9fTD5bbR9kiQNXldjCEmStFaORydJkiSNDgtCkqS+czw6SZIkabQM9hh5SdK0cjw6SZIkaYRYEJIk9Z3j0UmSJEmjxVPGJEmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMhaEJEmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMhaEJEmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMhaEJEmSJEmSpowFIUmSJEmSpCljQUiSJEnSREpyeJIrktyU5MYkrxp2JkkaFfsOO4AkSZIk9cluYFNVfSbJI4BrklxWVTcNO5gkDZtHCEmSJEmaSFW1s6o+097+JnAzcOhwU0nSaPAIIUmSJEkTL8k64GnAVYvmbwQ2AszMzDA3N7fix56fn1/VeoM06hnNtzajmG/T+t33m57Z/4HzRslK873zvIv6mOaBjnjUPj3/G1sQkiRJkjTRkjwc+DDw6qr6Rud9VbUF2AKwYcOGmp2dXfHjz83NsZr1BmnUM5pvbUYx3+mbL7nf9Kb1uznr+tEtQYx6vnOOP6Dnf2NPGZMkSZI0sZLsR1MMOq+qPjLsPJI0KiwISZIkSZpISQKcDdxcVW8ddh5JGiUWhCRJkiRNqqcDLwGemeTa9ueEYYeSpFEwuifISZIkSdIaVNUngQw7hySNIo8QkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQpY0FIkiRJkiRpylgQkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQp01VBKMl7k+xKckPHvIOSXJbki+3vR7fzk+QdSbYmuS7J0f0KL0mSJEmSpJXr9gihc4DjF83bDFxeVUcCl7fTAM8Bjmx/NgLvXntMSdK488sFSZIkaXR0VRCqqk8Ady6afSJwbnv7XOAFHfPfV40rgQOTHNKDrJKk8XYOfrkgSZIkjYR917DuTFXtbG/fDsy0tw8FbutYbns7b2fHPJJspHmTz8zMDHNzcysPsD9sWr97xeutxWpyrsX8/PzAtzlIk94+mPw22j51q6o+kWTdotknArPt7XOBOeB1dHy5AFyZ5MAkh3T0O5IkSZLWYC0Foe+pqkpSK1xnC7AFYMOGDTU7O7vi7b7zvIs46/qeNKFr206dHej25ubmWM2+GReT3j6Y/DbaPq2RXy4MwKQXNie9fTD5bbR9kiQN3lqqKXcsfFvbnhK2q52/Azi8Y7nD2nmSJC3LLxf6Z9ILm5PePpj8Nto+SZIGby2Xnb8YOK29fRpwUcf8l7YDgh4L3OMh/pKkZdyxMM6cXy5IkiRJg9PtZec/CPw98MQk25OcAZwJPCvJF4GfbacBLgVuAbYC7wH+c89TS5ImhV8uSJIkSUPQ1THyVXXKMncdt8SyBbxiLaEkSZOn/XJhFjg4yXbgjTRfJlzQftFwK3BSu/ilwAk0Xy58C3jZwANLkiRJE2ywgyZIkqaWXy5IkiRJo2MtYwhJkiRJkiRpDFkQkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJEynJe5PsSnLDsLNI0qixICRJkiRpUp0DHD/sEJI0iiwISZIkSZpIVfUJ4M5h55CkUeRl5yVJkiRNrSQbgY0AMzMzzM3Nrfgxdt15D+8876IeJ9uz9Yc+akXLz8/Pr6ptg2K+tRnFfJvW777f9Mz+D5w3SkY9Xz/+xhaEJEmSJE2tqtoCbAHYsGFDzc7Orvgx3nneRZx1/WA/Wm07dXZFy8/NzbGatg2K+dZmFPOdvvmS+01vWr974P8nKzHq+c45/oCe/409ZUySJEmSJGnKWBCSJEmSJEmaMhaEJEmSJE2kJB8E/h54YpLtSc4YdiZJGhWje4KcJEmSJK1BVZ0y7AySNKo8QkiSJEmSJGnKWBCSJEmSJEmaMp4yJmmsrFt0+cp+O+f4Awa6PUmSJEkaBI8QkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQpY0FIkiRJkiRpylgQkiRJkiRJmjIWhCRJkiRJkqaMBSFJkiRJkqQps++wA0iSJEmDtG7zJQPd3jnHHzDQ7UmS1A2PEJIkSZIkSZoyFoQkSZIkSZKmjAUhSZIkSZKkKWNBSJIkSZIkacpYEJIkSZIkSZoyFoQkSZIkSZKmjAUhSZIkSZKkKWNBSJIkSZIkacpYEJIkSZIkSZoyfSsIJTk+yReSbE2yuV/bkSRNLvsSSdJa2ZdI0tL6UhBKsg/wLuA5wJOBU5I8uR/bkiRNJvsSSdJa2ZdI0vL6dYTQMcDWqrqlqv4F+BBwYp+2JUmaTPYlkqS1si+RpGXs26fHPRS4rWN6O/CTnQsk2QhsbCfnk3xhFds5GPjaqhKuUt4yyK0BQ2jjgE16+2Dy2zjR7fuZt6y6fY/vdZYpZF/SOxP9f8rktw8mv40T3T77kqGyL/m+Uf8/M9/ajHo+fn3EM456vn70Jf0qCO1VVW0BtqzlMZJcXVUbehRpJE16Gye9fTD5bbR9Gib7ku5MehsnvX0w+W20fRqmaelLRj2j+dZm1PPB6Gecxnz9OmVsB3B4x/Rh7TxJkrplXyJJWiv7EklaRr8KQp8GjkxyRJIHAycDF/dpW5KkyWRfIklaK/sSSVpGX04Zq6rdSV4J/A2wD/DeqrqxD5ta06GdY2LS2zjp7YPJb6PtU1/Yl/TUpLdx0tsHk99G26e+sC+5n1HPaL61GfV8MPoZpy5fqqrXjylJkiRJkqQR1q9TxiRJkiRJkjSiLAhJkiRJkiRNmbEoCCU5PskXkmxNsnmJ+x+S5Pz2/quSrBtCzFXron2vSXJTkuuSXJ7k8cPIuRZ7a2PHcv8hSSUZ2cv9LaWb9iU5qf073pjkA4POuFZdPE8fl+SKJJ9tn6snDCPnaiR5b5JdSW5Y5v4keUfb9uuSHD3ojFo7+xL7klFnX2JfovGw1N86yUFJLkvyxfb3o0cs35uS7EhybfsztP+tJIe3/+cLr2WvaueP0j5cLuNI7MckD03yqSSfa/P9Tjv/iPY9zNb2Pc2DRyzfOUm+3LH/jhpGvo6c+7T9zcfa6ZHYf3vI1/v9V1Uj/UMz+NuXgB8CHgx8DnjyomX+M/An7e2TgfOHnbvH7fsZ4GHt7f80Tu3rto3tco8APgFcCWwYdu4e/w2PBD4LPLqd/oFh5+5DG7cA/6m9/WRg27Bzr6B9Pw0cDdywzP0nAP8LCHAscNWwM/uz4r+xfYl9yUj/2Jd8bxn7En9G/mepvzXw34HN7e3NwFtGLN+bgN8Y9r5rsxwCHN3efgTwD+3/+yjtw+UyjsR+bF9HHt7e3g+4qn1duQA4uZ3/JwuvpyOU7xzghcPefx05XwN8APhYOz0S+28P+Xq+/8bhCKFjgK1VdUtV/QvwIeDERcucCJzb3r4QOC5JBphxLfbavqq6oqq+1U5eCRw24Ixr1c3fEOD3gLcA/zzIcD3QTft+GXhXVd0FUFW7BpxxrbppYwGPbG8/CvjHAeZbk6r6BHDnHhY5EXhfNa4EDkxyyGDSqUfsS+xLRp19ScO+RCNvmb91Zx9yLvCCQWbq1MVzcaiqamdVfaa9/U3gZuBQRmsfLpdxJLSvI/Pt5H7tTwHPpHkPA0Pch3vINzKSHAY8F/izdjqMyP5r89wvX7+MQ0HoUOC2juntPPCf8XvLVNVu4B7gMQNJt3bdtK/TGTTfLo2TvbaxPWz68Kq6ZJDBeqSbv+GPAD+S5P8muTLJ8QNL1xvdtPFNwIuTbAcuBX5tMNEGYqX/pxo99iX3Z18yeuxLGm/CvkTjaaaqdra3bwdmhhlmGa9sT1d87zBPx+qU5vTsp9EcQTKS+3BRRhiR/dieTnQtsAu4jOYIzLvb9zAw5NeYxfmqamH/vbndf29L8pBh5QP+CHgt8N12+jGM0P7jgfkW9HT/jUNBSK0kLwY2AH8w7Cy9lORBwFuBTcPO0kf70hzqPwucArwnyYHDDNQHpwDnVNVhNIfFv7/920oaIfYlY82+RBoD1ZzbMVJHQwDvBn4YOArYCZw11DRAkocDHwZeXVXf6LxvVPbhEhlHZj9W1X1VdRTNEb/HAE8aVpalLM6X5CnA62ly/gRwEPC6YWRL8jxgV1VdM4zt780e8vV8/41DB7sDOLxj+rB23pLLJNmX5hDjrw8k3dp10z6S/CzwW8Dzq+rbA8rWK3tr4yOApwBzSbbRnF96ccZnMNBu/obbgYur6jtV9WWa85CPHFC+XuimjWfQnHdLVf098FDg4IGk67+u/k810uxLsC8ZcfYlDfsSjas7Fk4BbH+P1CmdVXVH+wH9u8B7aAoIQ5NkP5pCy3lV9ZF29kjtw6Uyjtp+bDPdDVwB/BTNqaj7tneNxGtMR77j21Pxqn0P8ucMb/89HXh++37hQzSnir2d0dl/D8iX5C/6sf/GoSD0aeDIdsTvB9MM9HnxomUuBk5rb78Q+Nu2qjwO9tq+JE8D/pTmDfxIdS5d2mMbq+qeqjq4qtZV1TqasS2eX1VXDyfuinXzHP0rmm90SXIwzWH/twww41p108avAMcBJPlRmjfxXx1oyv65GHhpGscC93Qc0qzxYF9iXzLq7Esa9iUaV519yGnARUPM8gCLxqv6eWDJq+ENKEuAs4Gbq+qtHXeNzD5cLuOo7Mckj104QjTJ/sCzaMY5uoLmPQwMcR8uk+/zHQW/0IzPM5T9V1Wvr6rD2vcLJ9O85zuVEdl/y+R7cT/23757X2S4qmp3klcCf0NzdYr3VtWNSX4XuLqqLqb5Z31/kq00A6idPLzEK9Nl+/4AeDjwl83fnq9U1fOHFnqFumzj2OqyfX8DPDvJTcB9wG9W1bgcedBtGzfRnL7wX2gO8T19XD5MJ/kgzYesg9OMW/FGmsHvqKo/oRnH4gRgK/At4GXDSarVsi+xLxl19iX2JRofy/ytzwQuSHIGcCtw0ojlm01zieoCtgG/Mqx8NEc/vAS4Ps0YMwBvYIT2IctnPGVE9uMhwLlJ9qE5yOOCqvpY2z98KMnv01yV8uwRy/e3SR5LcxWya4FfHVK+5byO0dh/yzmv1/svY9LHSpIkSZIkqUfG4ZQxSZIkSZIk9ZAFIUmSJEmSpCljQUiSJEmSJGnKWBCSJEmSJEmaMhaEJEmSJEmSpowFIUmSJEmSpCljQUiSJEmSJGnK/P8B0CLd8uWNH9IAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 1440x720 with 9 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df.hist(figsize=(20,10));"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "88afe17f",
+   "metadata": {},
+   "source": [
+    "Las variables AC, rain y sun son datos booleanos.\n",
+    "Observando los datos manualmente, entendemos que los dias que no son lluviosos, son soleados.\n",
+    "Corregimos el dataset para que ponga 1 en \"Sun\" cuando no sean lluviosos."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a3057ca9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "48"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"rain\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "218b28d0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"sun\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "8559e9f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "340"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"sun\"] = 1 - df[\"rain\"]\n",
+    "df[\"sun\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "542834bc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "48"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"rain\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b59d645d",
+   "metadata": {},
+   "source": [
+    "## Chequeo de litros consumidos:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "325ebff3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "7625.299999999999"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"distance\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "73c033ef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "482.5"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"refill liters\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "1b0cc348",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SP98    8\n",
+       "E10     5\n",
+       "Name: refill gas, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"refill gas\"].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "a46fc72f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "284.5"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df[\"refill gas\"] == \"SP98\"][\"refill liters\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "42dcb01b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "198.0"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df[\"refill gas\"] == \"E10\"][\"refill liters\"].sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "15fd6e55",
+   "metadata": {},
+   "source": [
+    "Se observan un total de trece repostajes con un total de 482,5 litros: \n",
+    "\n",
+    "    - 8 repostajes de combustible SP98 con un total de 284,5 litros\n",
+    "    \n",
+    "    - 5 repostajes de combustible E10  con un total de 198   litros\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8b95f42",
+   "metadata": {},
+   "source": [
+    "Suponemos que el consumo es en litros/100 kilómetros.\n",
+    "Multiplicamos la distancia recorrida en cada trayecto por la media de consumo y tenemos el consumo en cada trayecto."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "f8f23fa7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "362.8942"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"liters_consumed\"] = df[\"distance\"]*df[\"consume\"]/100\n",
+    "df[\"liters_consumed\"].sum()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b746d417",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "El consumo medio según los litros repostado y los kilómetros realizados es 6.3 litros/100 km.\n",
+      "El consumo total según consumo * distancia registrados es                  4.8 litros/100 km.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"El consumo medio según los litros repostado y los kilómetros realizados es {(df['refill liters'].sum()/df['distance'].sum()*100).round(1)} litros/100 km.\")\n",
+    "print(f\"El consumo total según consumo * distancia registrados es                  {(df['liters_consumed'].sum()/df['distance'].sum()*100).round(1)} litros/100 km.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "da625437",
+   "metadata": {},
+   "source": [
+    "Hay una diferencia del 30% entre los litros totales repostados y el consumo indicado en cada trayecto.\n",
+    "O bien el dataset no tiene todos los trayectos entre repostaje y repostaje o bien el dato de consumo registrado está trucado.\n",
+    "como no sabemos la realidad con los datos, damos por hecho que los datos están bien y pasamos a analizar tendencias dependiendo del combustible. Podemos olvidarnos de las columnas de repostaje.\n",
+    "\n",
+    "Antes de ello analizamos si este mismo fenómeno se repite igualmente independientemente del combustible:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "f32011fa",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Para el combustible SP98:\n",
+      "Se han realizado un total de 4249.9 kilómetros.\n",
+      "Se han repostado un total de 284.5 litros de SP98.\n",
+      "El consumo medio según los litros repostado y los kilómetros realizados es 6.7 litros/100 km.\n",
+      "El consumo total según consumo * distancia registrados es                  4.7 litros/100 km.\n",
+      "La diferencia es de un 41.2 %\n",
+      "\n",
+      "\n",
+      "Para el combustible E10:\n",
+      "Se han realizado un total de 3375.4 kilómetros.\n",
+      "Se han repostado un total de 198.0 litros de E10.\n",
+      "El consumo medio según los litros repostado y los kilómetros realizados es 5.9 litros/100 km.\n",
+      "El consumo total según consumo * distancia registrados es                  4.8 litros/100 km.\n",
+      "La diferencia es de un 22.7 %\n"
+     ]
+    }
+   ],
+   "source": [
+    "df_SP98 = df[df[\"gas_type\"] == \"SP98\"]\n",
+    "print(\"Para el combustible SP98:\")\n",
+    "print(f\"Se han realizado un total de {df_SP98['distance'].sum()} kilómetros.\")\n",
+    "print(f\"Se han repostado un total de {df_SP98['refill liters'].sum()} litros de SP98.\")\n",
+    "print(f\"El consumo medio según los litros repostado y los kilómetros realizados es {(df_SP98['refill liters'].sum()/df_SP98['distance'].sum()*100).round(1)} litros/100 km.\")\n",
+    "print(f\"El consumo total según consumo * distancia registrados es                  {(df_SP98['liters_consumed'].sum()/df_SP98['distance'].sum()*100).round(1)} litros/100 km.\")\n",
+    "print(f\"La diferencia es de un {(100 * (df_SP98['refill liters'].sum()/df_SP98['distance'].sum()*100) / (df_SP98['liters_consumed'].sum()/df_SP98['distance'].sum()*100) - 100 ).round(1)} %\")\n",
+    "print(\"\\n\")\n",
+    "df_E10  = df[df[\"gas_type\"] == \"E10\"]\n",
+    "print(\"Para el combustible E10:\")\n",
+    "print(f\"Se han realizado un total de {df_E10['distance'].sum()} kilómetros.\")\n",
+    "print(f\"Se han repostado un total de {df_E10['refill liters'].sum()} litros de E10.\")\n",
+    "print(f\"El consumo medio según los litros repostado y los kilómetros realizados es {(df_E10['refill liters'].sum()/df_E10['distance'].sum()*100).round(1)} litros/100 km.\")\n",
+    "print(f\"El consumo total según consumo * distancia registrados es                  {(df_E10['liters_consumed'].sum()/df_E10['distance'].sum()*100).round(1)} litros/100 km.\")\n",
+    "print(f\"La diferencia es de un {(100 * (df_E10['refill liters'].sum()/df_E10['distance'].sum()*100) / (df_E10['liters_consumed'].sum()/df_E10['distance'].sum()*100) - 100 ).round(1)} %\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be0df9b9",
+   "metadata": {},
+   "source": [
+    "Se observa que con el combustible SP98, el error de medida del consumo se duplica."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1fa98518",
+   "metadata": {},
+   "source": [
+    "# Analizamos colinearidad entre los datos:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "609f018d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'PEARSON CORRELATION MATRIX')"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x648 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "corr = df.corr()\n",
+    "mask = np.zeros_like(corr)\n",
+    "mask[np.triu_indices_from(mask)] = True\n",
+    "\n",
+    "f, ax = plt.subplots(figsize=(15, 9))\n",
+    "sns.heatmap(corr, mask=mask , annot=True, ax=ax, cmap=\"YlGnBu\")\n",
+    "plt.title('PEARSON CORRELATION MATRIX', fontsize=18)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4addf71e",
+   "metadata": {},
+   "source": [
+    "No observamos ninguna colinearidad relevante para la variable consumo, aún así vamos a representarlo graficamente:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "4d277553",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 1080x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(figsize=(15,4))\n",
+    "plt.title(\"Influence of Gas Type in Consume\")\n",
+    "\n",
+    "sns.boxplot(x=df.consume, y=df.gas_type )\n",
+    "plt.xlabel(\"Consume\")\n",
+    "plt.ylabel(\"\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "4288d0c0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig,ax = plt.subplots(1,2,figsize=(15,4))\n",
+    "plt.title(\"Influence of Gas Type in Consume depending on climate factors\")\n",
+    "\n",
+    "ax[0] = plt.subplot(1, 2, 1)\n",
+    "sns.boxplot(x=df.consume, y=df.gas_type , hue = df.AC )\n",
+    "plt.xlabel(\"Consume\")\n",
+    "plt.ylabel(\"\")\n",
+    "\n",
+    "ax[1] = plt.subplot(1, 2, 2)\n",
+    "sns.boxplot(x=df.consume, y=df.gas_type , hue = df.rain)\n",
+    "plt.xlabel(\"Consume\")\n",
+    "plt.ylabel(\"\")\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "5d572576",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1080x720 with 4 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, 2, figsize=(15,10), sharey=True)\n",
+    "\n",
+    "alpha = .5\n",
+    "\n",
+    "ax[0,0] = plt.subplot(2, 2, 1)\n",
+    "sns.scatterplot(x=\"distance\", y=\"consume\", hue=\"gas_type\", data=df , alpha=alpha)\n",
+    "plt.xlabel('distance')\n",
+    "plt.ylabel('Consume')\n",
+    "\n",
+    "ax[0,1] = plt.subplot(2, 2, 2)\n",
+    "sns.scatterplot(x=\"speed\", y=\"consume\", hue=\"gas_type\", data=df , alpha=alpha)\n",
+    "plt.xlabel('speed')\n",
+    "plt.ylabel('Consume')\n",
+    "\n",
+    "ax[1,0] = plt.subplot(2, 2, 3)\n",
+    "sns.scatterplot(x=\"temp_inside\", y=\"consume\", hue=\"gas_type\", data=df , alpha=alpha)\n",
+    "plt.xlabel('temp_inside')\n",
+    "plt.ylabel('Consume')\n",
+    "\n",
+    "ax[1,1] = plt.subplot(2, 2, 4)\n",
+    "sns.scatterplot(x=\"temp_outside\", y=\"consume\", hue=\"gas_type\", data=df , alpha=alpha)\n",
+    "plt.xlabel('temp_outside')\n",
+    "plt.ylabel('Consume')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "0c09b76d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Consume')"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.scatterplot(x=\"distance\", y=\"consume\", hue=\"gas_type\" , data=df , alpha=0.4)\n",
+    "plt.xlabel('distance')\n",
+    "plt.ylabel('Consume')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fd0ae2e7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "ironhack",
+   "language": "python",
+   "name": "ironhack"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/README.md b/README.md
index 92bc4a9..b783125 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,19 @@
+# Análisis de consumo en flota COBIFY.
+
+En este repositorio se analizan los datos de consumo de los vehículos de la empresa COBIFY.
+Se compone por 
+- un Jupyter Notebook donde se cargan, limpian y analizan los datos.
+- un archivo main.py a ejecutar con STREAMLIT donde se muestran los resultados en una página web para "presentar al cliente".
+
+Atentamente,
+Daniel
+
+
+
+
+
+
+
 # Bienvenido al reto de Cobify 🚕
 
 <img src="https://kamisetas.com/image/bordados/Cobi-Barcelona-92-parche.gif" alt="drawing" width="200"/>
diff --git a/measurements.csv b/data/measurements.csv
similarity index 100%
rename from measurements.csv
rename to data/measurements.csv
diff --git a/measurements2.xlsx b/data/measurements2.xlsx
similarity index 100%
rename from measurements2.xlsx
rename to data/measurements2.xlsx
diff --git a/images/Cobify.gif b/images/Cobify.gif
new file mode 100644
index 0000000..ae71886
Binary files /dev/null and b/images/Cobify.gif differ
diff --git a/images/Gas_type.png b/images/Gas_type.png
new file mode 100644
index 0000000..371f9d1
Binary files /dev/null and b/images/Gas_type.png differ
diff --git a/images/Influencia AC y clima en el consumo.png b/images/Influencia AC y clima en el consumo.png
new file mode 100644
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+import streamlit as st
+
+from PIL import Image
+
+portada = Image.open("images/cobify.gif")
+st.image(portada, use_column_width=True)
+st.write("""
+    # Consumo COBIFY según combustible
+    
+    Se ha analizado el consumo de nuestros coches en función del combustible repostado.
+    
+    Tenemos registros de un total de 7625 km recorridos.
+    Para ello tenemos registros de trece repostajes con un total de 482,5 litros.
+    
+    En 8 repostajes se ha repostado combustible SP98. En total 284.5 litros.
+    En 5 repostajes se ha repostado combustible E10.  En total 198   litros.
+
+    El consumo medio según los litros repostado y los kilómetros realizados es 6.3 litros/100 km.    
+    Sin embargo, la media geométrica de los 388 trayectos registrados da un consumo de 4.8 litros/100 km.
+    La diferencia es significativa: 30 por ciento inferior al consumo real de litros repostados.
+    Esto puede ser debido por:
+        a) no tener registrados todos los trayectos realizados entre repostaje y repostaje
+        b) la precisión del medidor de consumo de cada trayecto es incorrecta (puede ser debido al tuning de los coches)
+        c) tener "perdidas" de combustible
+        
+    Recomendamos revisar la desviación de dichos registros.
+    
+    Para el combustible SP98:
+    Se han realizado un total de 4249.9 kilómetros.
+    Se han repostado un total de 284.5 litros de SP98.
+    El consumo medio según los litros repostado y los kilómetros realizados es 6.7 litros/100 km.
+    El consumo total según consumo * distancia registrados es                  4.7 litros/100 km.
+    La diferencia es de un 41.2 %
+
+
+    Para el combustible E10:
+    Se han realizado un total de 3375.4 kilómetros.
+    Se han repostado un total de 198.0 litros de E10.
+    El consumo medio según los litros repostado y los kilómetros realizados es 5.9 litros/100 km.
+    El consumo total según consumo * distancia registrados es                  4.8 litros/100 km.
+    La diferencia es de un 22.7 %
+    
+    Conclusión:
+    El error de medición de consumo se duplica con el combustible SP98 en vez de con el E10.
+    Realmente el consumo con ambos combustibles es practicamente el mismo.
+    """)
+st.image(Image.open("images/Gas_type.png"), use_column_width=True)
+
+st.write("""
+    ## Consumo según uso del Aire Acondicionado y/o en días lluviosos
+    """)
+st.image(Image.open("images/Influencia AC y clima en el consumo.png"), use_column_width=True) 
+
+st.write("""
+    ## Recomendación de combustible en función del perfil de trayectos esperados:
+    Se tiene información del consumo en función de 
+        a) la distancia recorrida
+        b) velocidad media
+        c) temperatura interior del vehículo
+        d) temperatura exterior del vehículo
+    No se observa ninguna diferencia de tendencia en el consumo entre los dos combustibles para todas estas variables:
+    """)
+st.image(Image.open("images/Scatter plots.png"), use_column_width=True)  
+
+
+
+st.write("""
+    Esto se puede ver también en la siguiente matriz de correlación, donde todos los valores en la columna "consumo" son muy bajos.
+    (el 0,99 para los litros consumidos no es determinante por que han sido calculados matemáticamente usando la distancia.)
+    """)
+st.image(Image.open("images/corr.png"), use_column_width=True) 
+
+
+
+st.write("""
+    ## Análisis de Daniel Helguera para COBIFY
+    """)
+st.image(Image.open("images/coche.png"), use_column_width=True) 
+