ploteo_test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "auctions_dtypes = {'auction_type_id': np.float16, 'country': 'category', 'platform': 'category',\n",
    "                   'ref_type_id': 'category', 'source_id': 'category', 'device_id': 'category'}\n",
    "auctions = pd.read_csv('auctions.csv.gzip', compression = 'gzip', dtype = auctions_dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "auctions.drop('auction_type_id', axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "auctions[\"date\"] =  pd.to_datetime(auctions[\"date\"], errors = \"coerce\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>device_id</th>\n",
       "      <th>platform</th>\n",
       "      <th>ref_type_id</th>\n",
       "      <th>source_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:33.290763</td>\n",
       "      <td>6059599345986491085</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:34.440157</td>\n",
       "      <td>1115994996230693426</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:35.862360</td>\n",
       "      <td>7463856250762200923</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:36.167163</td>\n",
       "      <td>7829815350267792040</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:37.728590</td>\n",
       "      <td>1448534231953777480</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               country                       date            device_id  \\\n",
       "0  6333597102633388268 2019-03-11 14:18:33.290763  6059599345986491085   \n",
       "1  6333597102633388268 2019-03-11 14:18:34.440157  1115994996230693426   \n",
       "2  6333597102633388268 2019-03-11 14:18:35.862360  7463856250762200923   \n",
       "3  6333597102633388268 2019-03-11 14:18:36.167163  7829815350267792040   \n",
       "4  6333597102633388268 2019-03-11 14:18:37.728590  1448534231953777480   \n",
       "\n",
       "  platform ref_type_id source_id  \n",
       "0        1           1         0  \n",
       "1        1           1         0  \n",
       "2        1           1         0  \n",
       "3        1           1         0  \n",
       "4        1           1         0  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auctions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country              category\n",
       "date           datetime64[ns]\n",
       "device_id            category\n",
       "platform             category\n",
       "ref_type_id          category\n",
       "source_id            category\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auctions.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "clicks_dtypes = {'advertiser': np.int8, 'action_id': np.float16, 'source_id': np.int8, 'country_code': 'category',\n",
    "                 'latitude': np.float16, 'longitude': np.float16, 'carrier_id': np.float16, 'brand': np.float16,\n",
    "                 'touchX': np.float16, 'touchY': np.float16}\n",
    "clicks = pd.read_csv('clicks.csv.gzip', compression = 'gzip', dtype = clicks_dtypes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "clicks[\"created\"] =  pd.to_datetime(clicks[\"created\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "clicks[\"hora\"] = clicks[\"created\"].dt.hour\n",
    "clicks[\"click_count\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\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>click_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>hora</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2726</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      click_count\n",
       "hora             \n",
       "0             440\n",
       "1            4209\n",
       "2            2327\n",
       "3             754\n",
       "4            1079\n",
       "5             945\n",
       "6             678\n",
       "7             518\n",
       "8             537\n",
       "9             754\n",
       "10           1143\n",
       "11           1455\n",
       "12           1199\n",
       "13            926\n",
       "14            834\n",
       "15            959\n",
       "16            966\n",
       "17            641\n",
       "18            655\n",
       "19            380\n",
       "20            389\n",
       "21            451\n",
       "22           1386\n",
       "23           2726"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clicks.groupby(by=\"hora\").agg({\"click_count\":\"count\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "auctions[\"hora\"] = auctions[\"date\"].dt.hour\n",
    "auctions[\"auction_count\"] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "auc_x_hora = auctions.groupby(by=\"hora\").agg({\"auction_count\":\"count\"})\n",
    "clicks_x_hora = clicks.groupby(by=\"hora\").agg({\"click_count\":\"count\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "join_por_hora = auc_x_hora.join(clicks_x_hora)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "join_por_hora[\"porcentaje\"] =  join_por_hora[\"click_count\"] * 100 / join_por_hora[\"auction_count\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x193009988d0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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xK2DFHO3L232TfAG4kSYYbg3sU1W3jvTNHP0vn7VfkiRJkrQahr7lRs3Rlo722V4K7A48F7gbcEqSjSf0nzGPS5JDkpyd5OwrrriiRwmSJEmStG4bMjQuB7aco30L5h6BvJ2q+lFVfauqjgeeCPwBcOBI38zR/8z2nP1X1T9X1W5VtduiRYsmlSBJkiRJ67whQ+OFzLp2Mcl2wKbc8VrEsarqUuBXwH3aph8DN83uv92+FfjvVahXkiRJkjTLkKHxFOCJSTYbaTsAuB5YtjIdtYvh3J3m/o1U1Y3AV4FnzDr0AOCbVXX1qhYtSZIkSfqtIe/T+D7gUOCkJG+iGSVcChw9ehuOJBcBy6rq+e32W4GbgW/RTDN9APD3NKOLJ4z0fyTNPRzfAZwMPLn9etKAz0mSJEmS1imDjTRW1XLgscD6wGeBI4C3A6+ZdegG7TEzzgb+CPgg8Hma4HkisHtV/Wak/zOBpwOPA04FngocWFWnDfF8JEmSJGldNORII1V1PrDXhGOWzNo+gduPKI4792SaUUZJkiRJ0gCGvuWGJEmSJOlOzNAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVInQ6MkSZIkqZOhUZIkSZLUydAoSZIkSepkaJQkSZIkdTI0SpIkSZI6GRolSZIkSZ0MjZIkSZKkToZGSZIkSVKnQUNjkgcm+XKS65JcnuS1SdafcM7Dkhyb5KL2vB8meU2SjWcdtzRJzfH1pCGfkyRJkiStSzYYquMkWwFfAs4H9gN2BN5GE1QPH3PqAe2xbwJ+BOwCHNl+/5NZx14NzA6JF6xu7ZIkSZKkxmChEXgxsAmwf1VdA5yeZHNgaZI3t21zeVNVXTGy/bUkNwDvT7J9VV06su/mqvqPYcqXJEmSJA05PXVv4NRZ4fAEmiC5R9dJswLjjO+137eZv/IkSZIkSZMMGRp3Ai4cbaiqnwDXtftWxqOAW4EfzmrfMsmVSW5K8r0k+69ytZIkSZKkOxgyNG4FrJijfXm7r5ck9wReBXxk1qjlRcDfA8+kudbxcuBEg6MkSZIkzZ8hr2kEqDna0tF+xwOTjYBPAr8GXna7jquOn3XsZ4GzgFcDJ3X0dwhwCMDixYv7lCBJkiRJ67QhRxqXA1vO0b4Fc49A3k6SAB8GdgaeXFXLxx1fVUUTFnfpuq1HVf1zVe1WVbstWrRoUgmSJEmStM4bcqTxQmZdu5hkO2BTZl3r2OHtNLfqeHxV9Tl+Rq9RTEmSJEnSZEOONJ4CPDHJZiNtBwDXA8vGnZjkFcBLgedU1Zl9Hqwdmfxj4PtVdcuqlSxJkiRJGjXkSOP7gEOBk5K8CbgPsBQ4enRBmyQXAcuq6vnt9oHAG4APAT9LsvtInz+euSVHkmXAiTSjlpsCLwR2B5424HOSJEmSpHXKYKGxqpYneSzwLuCzNNcxvp0mOM6uYfQaxCe03w9qv0YdTBMmoVk99W+A36W5Hcd3gadU1SnzUb8kSZIkaeDVU6vqfGCvCccsmbV9EHcMi3Od9/zVKE2SJEmS1MOQ1zRKkiRJku7kDI2SJEmSpE6GRkmSJElSJ0OjJEmSJKmToVGSJEmS1MnQKEmSJEnqZGiUJEmSJHUyNEqSJEmSOhkaJUmSJEmdDI2SJEmSpE6GRkmSJElSJ0OjJEmSJKmToVGSJEmS1MnQKEmSJEnqZGiUJEmSJHUyNEqSJEmSOhkaJUmSJEmdDI2SJEmSpE6GRkmSJElSJ0OjJEmSJKmToVGSJEmS1MnQKEmSJEnqZGiUJEmSJHXaYNIBSZ4BfLGqrk1yOLAr8Lqq+u7g1UmSJEnSumTpFvPUz9Xz0w89QiPwj1X1b0keDTwReCvwXuAR81aFJElTYsnLP7/afVxy1FPmoRJJkqZDn9B4S/v9KcB7q+rTSZYOV5IkaV1jUJMkaXr1uabxZ0neDzwT+EKSu/Q8T5IkSZJ0J9cn/D0TOBV4UlWtALYG/m7QqiRJkiRJU2FiaKyq66rqJODqJIuBDYELB69MkiRJkrTg+qye+lTgbcC2wC+BxTShcedhS5MkDemeXz13Xvr5xZ4PmZd+JEnSdOozPfVIYHfgv6tqB+BxwDcGrUqSJEmSNBX6hMabquoqYL0k61XVVwH/W1mSJEmS1gF9brmxIsndgDOAjyb5JXDzsGVJkiRJkqZBn5HG/YDrgJcBXwR+DOwzZFGSJEmSpOnQJzS+uqpuraqbq+q4qnon8A9DFyZJkiRJWnh9QuPj52jbe74LkSRJkiRNn85rGpP8BfASYMck/zmyazNcPVWSJEmS1gnjFsL5GHAK8Ebg5SPt11bVrwatSpIkSZI0FTqnp1bV1VV1CXA48IuquhTYAXhOki3XUH2SJEmSpAXU55rGE4FbktwX+CBNcPzYoFVJkiRJkqZCn9B4a1XdDOwPvKOqXgb87rBlSZIkSZKmQZ/QeFOSZwF/BnyubdtwuJIkSZIkSdOiT2g8GHgk8PqqujjJDsDxw5YlSZIkSZoG41ZPBaCqzgcOHdm+GDhqyKIkSZIkSdNhYmhMcj+a2248ENh4pr2q7jNgXZIkSZKkKdBneuqxwHuBm4E9gQ8DHxmyKEmSJEnSdOgTGjepqi8DqapLq2opsNewZUmSJEmSpsHE6anADUnWA36U5K+AnwHbDFuWJEmSJGka9Blp/BvgrjSL4TwUeC7w50MWJUmSJEmaDn1WT/0OQDvaeGhVXTt4VZK0lvryV3acl34eu9eP56UfSZKkSSaONCbZLcl5wH8C5yX5fpKHDl+aJEmSJGmh9bmm8V+Bl1TV1wGSPJpmRdVdhixMkiRJkrTw+lzTeO1MYASoqjMBp6hKkiRJ0jqgc6Qxya7tj99O8n7g40ABBwBfG740SZIkSdJCGzc99W2ztl8z8nMNUIskSZIkacp0hsaq2nNNFiJJkiRJmj4TF8JJ8uq52qvqtfNfjiRJkiRpmvRZPfU3Iz9vDOwDXDBMOZIkSZKkaTIxNFbV7a5tTPJW4DODVSRJ82zp0qVT1Y8kSdKdSZ9bbsx2V+A+812IJEmSJGn69Lmm8Tx+u1rq+sAiwOsZJUmSJGkd0Oeaxn1Gfr4Z+N+qunmgeiRJkiRJU6TP9NQNgF9U1aXA/YCXJNly2LIkSZIkSdOgT2g8EbglyX2BDwI7AB8btCpJkiRJ0lToMz311qq6Ocn+wDuq6pgk3xu6MEl3fj99+ddXu497H/VH81CJJEmSVlWfkcabkjwL+DPgc23bhsOVJEmSJEmaFn1C48HAI4HXV9XFSXYAjh+2LEmSJEnSNJg4PbWqzgcOHdm+GDhqyKIkSZIkSdOhz0ijJEmSJGkdZWiUJEmSJHXqHRqTbDpkIZIkSZKk6TMxNCZ5VJLzgQva7Qcnec/glUmSJEmSFlyfkca3A08ErgKoqu8Dj+nTeZIHJvlykuuSXJ7ktUnWn3DOw5Icm+Si9rwfJnlNko3nOPYPk3wryfVJLk5y6Fx9SpIkSZJWzcTVUwGq6rIko023TDonyVbAl4Dzgf2AHYG30QTVw8ecekB77JuAHwG7AEe23/9kpP/7AqfS3DvyFcDDgaOTXFdVH+jzvCRJkiRJ4/UJjZcleRRQSTaiuf3GBT3OezGwCbB/VV0DnJ5kc2Bpkje3bXN5U1VdMbL9tSQ3AO9Psn1VXdq2/x1wOfCcqroZ+EqSxcBrknywqqpHjZIkSZKkMfpMT30x8JfAvYCfAg9ptyfZGzh1Vjg8gSZI7tF10qzAOON77fdtZvV/UhsYR/u/N/D7PeqTJEmSJE0wcaSxqq4Enr0Kfe8EfGVWXz9Jcl2777Mr0dejgFuBH8JtK7luB1w467iZEdCdgPNWoWZJkiRJ0ojO0JjkGKBzimdVTVp0ZitgxRzty9t9vSS5J/Aq4CMjo5Zbtt9n97985LHn6usQ4BCAxYsX9y1BkiRJktZZ46anng2cA2wM7EqzKM2PaKanTlwIpzVX6ExH+x0PbK6h/CTwa+BlPfvvbK+qf66q3apqt0WLFvUpQZIkSZLWaZ0jjVV1HECSg4A9q+qmdvt9wGk9+l7Ob0cER23B3COQt5NmudYPAzsDf1hVy0d2z5w/u/+tZu2XJEmSJK2GPgvhbAtsNrJ9t7Ztkgtpri28TZLtgE2547WIc3k7za069quq2x1fVb8BLpvd/8h2n/4lSZIkSRP0CY1HAd9L8qEkHwK+C7yhx3mnAE9MMho4DwCuB5aNOzHJK4CX0txO48wx/f9xkvVn9X8Z8IMe9UmSJEmSJuizeuqxSU4BHtE2vbyqftGj7/fR3NPxpCRvAu4DLAWOHr0NR5KLgGVV9fx2+0CaUPoh4GdJdh/p88cjt+R4C82qrh9J8i/Aw4AXAX/hPRolSZIkaX5MDI0AbUj89Mp0XFXLkzwWeBfN7TVW0Ew5XTpHDaOjhU9ovx/Ufo06mCZMUlUXJXkScDTNqOMvgMOq6gMrU6ckSZIkqVuv0Liqqup8YK8JxyyZtX0QdwyLXeeeCTx81aqTJEmSJE3S55pGSZIkSdI6qnOkMcnW406sql/NfzmSJEmSpGkybnrqOUABARbT3HcxNPdG/Amww+DVSVppbztgn9Xu47BPfG4eKpEkSdLaoHN6alXtUFX3AU4F9q2qe1TV3YF9gJPWVIGSJEmSpIXT55rGh1XVF2Y2quoUYI/hSpIkSZIkTYs+q6demeRw4Hia6arPAa4atCpJkiRJ0lToM9L4LGAR8CngZGCbtk2SJEmStJabONLYrpL612ugFkmSJEnSlJkYGpMsAv4e2BnYeKa9qvYasC5JkiRJ0hToMz31o8CFNLfYOAK4BPjOgDVJkiRJkqZEn9B496r6IHBTVS2rqucBuw9clyRJkiRpCvRZPfWm9vvPkzwFuBy493AlSZIkSZKmRZ/Q+LokWwCHAccAmwMvG7QqSZIkSdJU6LN66ufaH68G9hy2HEmSJEnSNOkMjUmOAaprf1UdOkhFkiRJkqSpMW4hnLOBc2hus7Er8KP26yHALcOXJkmSJElaaJ0jjVV1HECSg4A9q+qmdvt9wGlrpDpJkiRJ0oLqc8uNbYHNRrbv1rZJkiRJktZyfVZPPQr4XpKvttt7AEsHq0iSJEmSNDX6rJ56bJJTgEe0TS+vql8MW5YkSZIkaRp0Tk9NslP7fVea6aiXtV/btm2SJEmSpLXcuJHGvwUOAd42x74C9hqkIkmSJEnS1Bi3euoh7Y97V9UNo/uSbDxoVZIkSZKkqdBn9dSzerZJkiRJktYynSONSe4J3AvYJMkfAGl3bQ7cdQ3UJkmSJElaYOOuaXwicBBwb+DokfZrgVcOWJMkSZIkaUqMu6bxOOC4JH9SVSeuwZokSZIkSVNi4n0agc8lORBYMnp8Vb12qKIkSZIkSdOhT2j8NHA1cA5w47DlSJIkSZKmSZ/QeO+qetLglUiSJEmSpk6vW24kedDglUiSJEmSpk6fkcZHAwcluZhmemqAqqpdBq1MkiRJkrTg+oTGvQevQpIkSZI0lSYqZnuKAAAgAElEQVSGxqq6FCDJNsDGg1ckSZIkSZoaE69pTPLUJD8CLgaWAZcApwxclyRJkiRpCvRZCOdIYHfgv6tqB+CxwDcGrUqSJEmSNBX6hMabquoqYL0k61XVV4GHDFyXJEmSJGkK9FkIZ0WSuwFnAB9N8kvg5mHLkiRJkiRNgz4jjfsB1wEvA74I/BjYd8iiJEmSJEnToc9I4zbAz6vqBuC4JJsAvwNcNWhlkiRJkqQF12ek8d+AW0e2b2nbJEmSJElruT6hcYOq+n8zG+3PGw1XkiRJkiRpWvQJjVckeerMRpL9gCuHK0mSJEmSNC36XNP4YppVU9/Vbv8UeO5wJUmSJEmSpsXE0FhVPwZ2b2+7kaq6dviyJEmSJEnToM9IIwBV9eshC5EkSZIkTZ8+1zRKkiRJktZRvUcaJYAHHfeg1e7jvD8/bx4qkSRJkrQm9AqNSR4FLBk9vqo+PFBNkiRJkqQpMTE0JvkIsCNwLnBL21yAoVGSJEmS1nJ9Rhp3Ax5YVTV0MZIkSZKk6dJnIZwfAPccuhBJkiRJ0vTpM9J4D+D8JN8GbpxprKqnDlaVJEmSJGkq9AmNS4cuQpIkSZI0nSaGxqpatiYKkSRJkiRNnz6rp15Ls1oqwEbAhsBvqmrzIQuTJEmSJC28PiONm41uJ3ka8PDBKpIkSZIkTY0+q6feTlWdDOw1QC2SJEmSpCnTZ3rq/iOb69Hct9F7NkqSJEnSOqDP6qn7jvx8M3AJsN8g1UiSJEmSpkqfaxoPXhOFSJKkWZZuMQ99XL36fUiS1ml9pqe+c47mq4Gzq+rT81+SJEmSJGla9FkIZ2PgIcCP2q9dgK2B5yd5x4C1SZIkSZIWWJ9rGu8L7FVVNwMkeS9wGvB44LwBa5MkSZIkLbA+I433AjYd2d4U2LaqbgFuHKQqSZIkSdJU6DPS+Gbg3CRfAwI8BnhDkk2BLw1YmyRJkiRpgfVZPfWDSb4APJwmNL6yqi5vd//dkMVJkiRJkhbWxOmpSQI8FnhwVZ0MbJDk4YNXJkmSJElacH2uaXwP8EjgWe32tcC7B6tIkiRJkjQ1+lzT+Iiq2jXJ9wCqanmSjQauS5IkSZI0BfqMNN6UZH2gAJIsAm4dtCpJkiRJ0lToExrfCXwK2CbJ64EzgTf06TzJA5N8Ocl1SS5P8to2gI47Z6Mkb0ny9STXJ6mO4z6UpOb42qlPbZIkSZKkyfqsnvrRJOfQLIYT4GlVdcGk85JsRXNLjvOB/YAdgbfRBNXDx5x6V+AFwLeBs4C9xhx7IXDwrLZLJtUmSZIkSepnYmhMsiNwcVW9O8n/AR6f5OdVtWLCqS8GNgH2r6prgNOTbA4sTfLmtu0OqmpFkq2rqpL8FeND42+q6j8mPQdJkiRJ0qrpMz31ROCWJPcFPgDsAHysx3l7A6fOCocn0ATJPcadWFVzTkmVJEmSJK1ZfVZPvbWqbk6yP/BPVXXMzEqqE+wEfGW0oap+kuS6dt9nV77cO3hgkmuAuwDfAV5VVcvmoV9ppbz7xV+ZfNAEf/m+cYPqkiRJ0sLou3rqs4A/Az7Xtm3Y47ytgLmmsC5v962u7wGHAfsCzwbWp5kC+/B56FuSJEmSRL+RxoNprk98fVVdnGQH4Pie/c81zTQd7Sulqv7pdp0mn6dZdOeVwNPmOifJIcAhAIsXL17dEiRJkiRprTdxpLGqzq+qQ6vq4+32xVV1VI++lwNbztG+BXOPQK6Wqroe+AKw65hj/rmqdquq3RYtWjTfJUiSJEnSWqfP9NRVdSHNtYu3SbIdsGm7byguoiNJkiRJ82TI0HgK8MQkm420HQBcD8z7YjVJNqFZsfWc+e5bkiRJktZVfa5pvE2S9YC7dd1jcZb3AYcCJyV5E3AfYClw9Oj5SS4CllXV80fa9qYZkXxIu/30dtd3qurSJFvQLMpzPHARcA/gZcC9gGeuzHOSJEmSJHWbGBqTfIxmIZxbaEbxtkhydFW9Zdx5VbU8yWOBd9HcXmMF8Haa4Di7hvVntb0X2H5k+9/a7wcDHwJuBK4ADge2AW4AvgnsUVVnT3pOkiRJkqR++ow0PrCqrknybJqFZv6BJjyODY3QLKIDjL35XFUt6dM2a/8NwP6THl+SJEmStHr6XNO4YZINaW5j8emqumngmiRJkiRJU6JPaHw/cAnNNYZnJNkeuHrIoiRJkiRJ06FXaKyqe1XVk6uqgJ/QjDpKkiRJktZyfULjSUlGr328J3DaQPVIkiRJkqZIn9B4MvDvSdZPsgQ4FXjFkEVJkiRJkqbDxNVTq+pfkmxEEx6XAC+qqrOGLkySJEmStPA6Q2OSvx3dBLYDzgV2T7J7VR09dHGSJEmSpIU1bqRxs1nbn+polyRJkiStpTpDY1UdsSYLkSRJkiRNn4kL4SQ5PcmWI9tbJTl12LIkSZIkSdOgz+qpi6pqxcxGVS0HthmuJEmSJEnStOgTGm9JsnhmI8n2QA1XkiRJkiRpWky85QbwKuDMJMva7ccAhwxXkiRJkiRpWvS5T+MXk+wK7E5z642XVdWVg1cmSZIkSVpwndNTk+zUft8VWAxcDvwMWNy2SZIkSZLWcuNGGg8DXgi8bY59Bew1SEWSJEmSpKkx7j6NL2y/77nmypEkSZIkTZPO0Jhk/3EnVtVJ81+OJEmSJGmajJueuu+YfQUYGiVJkiRpLTdueurBa7IQSZIkSdL06Vw9dUaSNyTZcmR7qySvG7YsSZIkSdI0mBgagb2rasXMRlUtB548XEmSJEmSpGnRJzSun+QuMxtJNgHuMuZ4SZIkSdJaYtxCODOOB76c5FiaBXCeBxw3aFWSJEmSpKkwMTRW1ZuT/CfwOCDAkVV16uCVSZIkSZIWXJ+RRqrqi8AXB65FkiRJkjRl+lzTKEmSJElaRxkaJUmSJEmdeoXGJJskuf/QxUiSJEmSpsvE0JhkX+Bc2msakzwkyWeGLkySJEmStPD6jDQuBR4OrACoqnOBJcOVJEmSJEmaFn1C481VdfXglUiSJEmSpk6fW278IMmBwPpJ7gccCpw1bFmSJEmSpGnQZ6TxpcDOwI3Ax4FrgL8ZsihJkiRJ0nSYONJYVdcBr2q/JEmSJEnrkM7QmOSzQHXtr6qnDlKRJEmaOg867kGr3cd5f37ePFQiScNY8vLPr3Yflxz1lHmoZPqMG2l8a/t9f+CewPHt9rOASwasSZIkSZI0JTpDY1UtA0hyZFU9ZmTXZ5OcMXhlkiRJkqQF12chnEVJ7jOzkWQHYNFwJUmSJEmSpkWfW268DPhakv9pt5cAhwxWkSRJkiRpavRZPfWL7f0Zd2qbLqyqG4ctS5IkSZI0DfqMNNKGxO8PXIskSZIkacr0uaZRkiRJkrSOMjRKkiRJkjpNDI1pPCfJq9vtxUkePnxpkiRJkqSF1mek8T3AI4FntdvXAu8erCJJkiRJ0tTosxDOI6pq1yTfA6iq5Uk2GrguSZIkSdIU6DPSeFOS9YECSLIIuHXQqiRJkiRJU6FPaHwn8ClgmySvB84E3jBoVZIkSZKkqTBxempVfTTJOcBjgQBPq6oLBq9MkiRJkrTgOkNjks2r6pokWwO/BD4+sm8r4JqqumUN1ChJkiRJWiDjRho/BuwDnENzPWNGvgPcLcm/VNUrhy1RkiRJkrRQOkNjVe3Tft9hrv3t4jg/AAyNkiRJkrSW6nPLjZnpqPcDNp5pq6ozgAcMVJckSZIkaQpMDI1JXgD8NXBv4Fxgd+CbwF7DliZJkiRJWmh9brnx18DDgEurak/gD4ArBq1KkiRJkjQV+oTGG6rqBoAkd6mqC4H7D1uWJEmSJGka9Lmm8adJtgROBk5Pshy4fNiyJEmSJEnTYGJorKo/bn9cmuSrwBbAKYNWJUmSJEmaChOnpyb5yMzPVbWsqj4D/OugVUmSJEmSpkKfaxp3Ht1o78/40GHKkSRJkiRNk87QmOQVSa4FdklyTft1LfBL4NNrrEJJkiRJ0oLpDI1V9caq2gx4S1Vt3n5tVlV3r6pXrMEaJUmSJEkLpM9COK9Ici9g+9Hjq+qMIQuTJEmaZu9+8VfmpZ+/fN9e89KPJA1lYmhMchTwp8D5wC1tcwGGRkmSJElay/W5T+MfA/evqhuHLkaSJEmSNF36rJ76P8CGQxciSZIkSZo+fUYarwPOTfJl4LbRxqo6dLCqJEmSJElToU9o/Ez7JUmSJElax/RZPfW4JJsAi6vqh2ugJkmSJEnSlJh4TWOSfYFzgS+22w9J4sijJEmSJK0D+kxPXQo8HPgaQFWdm2SHPp0neSBwDPBIYAXwAeCIqrplzDkbAa8Hdgd2AzauqnQcux/wOuB+NAv2HFFVn+hTmyRJunO6YKcHrHYfD7jwgnmoRJLWDX1WT725qq6e1VaTTkqyFfCl9tj9gNcChwFHTDj1rsALaBbgOWtM/48GTgS+CuwNfB74eJInTKpNkiRJktRPn5HGHyQ5EFg/yf2AQxkT5ka8GNgE2L+qrgFOT7I5sDTJm9u2O6iqFUm2rqpK8lfAXh39/yNwxsgqrl9NsjPwauC0HvVJkiStFd52wD7z0s9hn/jcvPQjae3SZ6TxpcDONLfb+BhwNfA3Pc7bGzh1Vjg8gSZI7jHuxKoaO5KZ5C7AnsAnZ+06AXhkki161CdJkiRJmmBiaKyq66rqVVX1sPbr8Kq6oUffOwEXzurrJzTTTndatXJvsyOw4ez+gQtontPvrWb/kiRJkiT6rZ56epItR7a3SnJqj763oln8Zrbl7b7VMXP+7P6Xz9ovSZIkSVoNfaan3qOqbgtnVbUc2KZn/3NNM01H+6qY3U862pudySFJzk5y9hVXXDFPJUiSJEnS2qtPaLw1yeKZjSTb0y/0LQe2nKN9C+YegVwZMyOKs/uf2Z6z/6r656rarap2W7Ro0WqWIEmSJElrvz6rp74KODPJsnb7McAhPc67kFnXLibZDtiUO16LuLJ+DNzU9r9spH0n4Fbgv1ezf0mSJEkSE0YakwT4L2BX4BM0q5U+tKr6XNN4CvDEJJuNtB0AXM/tg95Kq6obae7P+IxZuw4AvjnHfSUlSZIkSatg7Ehje6/Ek6vqocDK3rjnfTT3dDwpyZuA+wBLgaNHb8OR5CJgWVU9f6Rtb5oRyYe0209vd32nqi5tfz4S+FqSdwAnA09uv560knVKkiRJkjr0mZ76H0keVlXfWZmOq2p5kscC7wI+S3Od4dtpguPsGtaf1fZeYPuR7X9rvx8MfKjt/8w2TL4O+AvgYuDAqjptZeqUJEmSJHXrExr3BF6U5FLgN7Srn1bVLpNOrKrzgb0mHLOkT1vHuSfTjDJKkiRJkgbQJzTuPXgVkiRJkqSpNPGWG+01hFsC+7ZfW45cVyhJkiRJWotNDI1J/hr4KLBN+3V8kpcOXZgkSZIkaeH1mZ76fOARVfUbgHYl1G8CxwxZmCRJkiRp4U0caaRZ+OaWke1b2jZJkiRJ0lquz0jjscC3knyq3X4a8MHhSpIkSZIkTYuJobGqjk7yNeDRNCOMB1fV94YuTJIkSZK08DpDY5KNgRcD9wXOA95TVTevqcIkSZIkSQtv3DWNxwG70QTGvYG3rpGKJEmSJElTY9z01AdW1YMAknwQ+PaaKUmSJEmSNC3GjTTeNPOD01IlSZIkad00bqTxwUmuaX8OsEm7HaCqavPBq5MkSZIkLajO0FhV66/JQiRJkiRJ02fc9FRJkiRJ0jrO0ChJkiRJ6mRolCRJkiR1MjRKkiRJkjoZGiVJkiRJnQyNkiRJkqROhkZJkiRJUidDoyRJkiSpk6FRkiRJktTJ0ChJkiRJ6mRolCRJkiR1MjRKkiRJkjoZGiVJkiRJnQyNkiRJkqROhkZJkiRJUidDoyRJkiSpk6FRkiRJktTJ0ChJkiRJ6mRolCRJkiR1MjRKkiRJkjoZGiVJkiRJnQyNkiRJkqROhkZJkiRJUidDoyRJkiSpk6FRkiRJktRpg4UuQFpVF+z0gNXu4wEXXjAPlUiSJElrL0caJUmSJEmdDI2SJEmSpE6GRkmSJElSJ0OjJEmSJKmToVGSJEmS1MnQKEmSJEnqZGiUJEmSJHUyNEqSJEmSOhkaJUmSJEmdDI2SJEmSpE6GRkmSJElSpw0WugBJkiStPX768q/PSz/3PuqPVruPpUuXTkUf0p2dI42SJEmSpE6GRkmSJEnS/2/v3qMlKetzj38fkYRByYAGD5iIKFEQEoOCIF4AGRSJGgRB0Byz8MRDSFQiajQmaoAkRvEWBS9hxYgaEEWN8YIHAbmIoAkIiHLzAmKAIMpwEQYkzO/88dYOPT1de2+dqZ49zPezVq+9q/rtrmfX7q7u31tvVfWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPUatGhMsm2SM5LcmeT6JEclWW8ej1uc5MNJlia5NckJSR461ub4JDXhts1wf5EkSZIkrVseONQTJ9kEOB24DNgH2Ap4J61QfeMcD/8EsDXwMmA58Dbgs8DTx9pdAbx0bN41q5JbkiRJknSfwYpG4FBgEbBfVd0GnJbk14AjkhzdzVtJkl2AvYDdquqcbt51wDeS7FlVp480v6Oqvj7g3yBJkiRJ67Qhh6fuDZw6VhyeRCskd5vjcTfOFIwAVfXvwNXdfZIkSZKkKRmyaNyGNnz0f1TVtcCd3X3zflzn8gmP2zbJbUnuTnJuktmKUUmSJEnSL2jIonET4JYJ85d2963q4y4CXgM8D/gDYD3aENidfqm0kiRJkqSVDHlMI0BNmJee+b/Q46rqPSvcmXyRdtKdvwSeP+lJkxwCHAKwxRZbzBFBkiRJkjTknsalwMYT5i9m8p7EuR638WyPq6plwCnAE2dpc1xV7VhVO2666aazRJAkSZIkwbBF4xWMHYOY5BHAg5h8zGLv4zp9xzqOm2svpiRJkiRpnoYsGr8E7JVko5F5BwLLgLPneNxmSZ42MyPJjsCju/smSrKIdnbVC1cltCRJkiTpPkMWjR8E7gY+k2TP7njCI4B3jV6GI8n3knxoZrqqzgdOBT6aZL8kzwdOAM6duUZjksVJvprkj5MsSXIgcCbwG8BbBvybJEmSJGmdMtiJcKpqaZIlwLHA52nHI76bVjiOZ1hvbN5BXdt/phW2XwAOG7n/buAm4I3Aw4C7gPOB3arqgtX6h0iSJEnSOmzQs6dW1WXAHnO02XLCvFuAl3a3SY+5C9hvNUSUJEmSJM1iyOGpkiRJkqS1nEWjJEmSJKmXRaMkSZIkqdegxzRKkiRJUp8t/+KLq/wc17z1OashiWZj0dhjdbyAwRexJEmSpLWbw1MlSZIkSb0sGiVJkiRJvRyeKkmSJK1DNjvz4lV+jv96xvarIYnWFu5plCRJkiT1smiUJEmSJPWyaJQkSZIk9bJolCRJkiT1smiUJEmSJPXy7KmSJEnSwM74ylar/BxL9vj+akgi/eLc0yhJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6mXRKEmSJEnqZdEoSZIkSepl0ShJkiRJ6jVo0Zhk2yRnJLkzyfVJjkqy3jwetzjJh5MsTXJrkhOSPHRCu32SXJrkriSXJTlwmL9EkiRJktZNgxWNSTYBTgcK2Ac4CngNcOQ8Hv4JYHfgZcDBwJOAz449/9OATwNnAnsDXwQ+nuRZq+UPkCRJkiTxwAGf+1BgEbBfVd0GnJbk14AjkhzdzVtJkl2AvYDdquqcbt51wDeS7FlVp3dN3wScU1WHddNnJtkOeDPw5eH+LEmSJEladww5PHVv4NSx4vAkWiG52xyPu3GmYASoqn8Hru7uI8mvAs8APjn22JOAXZIsXvX4kiRJkqQhi8ZtgCtGZ1TVtcCd3X3zflzn8pHHbQWsP6Hd5bS/6bG/RF5JkiRJ0pghi8ZNgFsmzF/a3bcqj5v5Od5u6dj9kiRJkqRVkKoa5omTe4DXVtV7xuZfBxxfVX/V87jTgJ9V1b5j808AtqyqpyZ5KnAusH1VXTLS5jHAVcCzquq0Cc99CHBIN7k1cOUv/Qc2vw78ZBWfY3Uxy2RmWdlCyQFm6WOWycwy2ULJslBygFn6mGUys0y2ULIslBxw/8zyyKradK5GQ54IZymw8YT5i5m8J3H0cZOCbzzyuKUj88bb0Pf8VXUccNwsy/6FJLmgqnZcXc+3KswymVkWbg4wSx+zTGaWyRZKloWSA8zSxyyTmWWyhZJloeSAdTvLkMNTr2Ds2MUkjwAexORjFnsf1xk91vH7wD0T2m0DLKftbZQkSZIkraIhi8YvAXsl2Whk3oHAMuDsOR63WXcdRgCS7Ag8uruPqrqbdn3GA8YeeyBwflXduurxJUmSJElDFo0fBO4GPpNkz+54wiOAd41ehiPJ95J8aGa6qs4HTgU+mmS/JM8HTgDOHblGI8DfALsn+Yckuyc5Gvg94KgB/6Zxq22o62pglsnMsrKFkgPM0scsk5llsoWSZaHkALP0MctkZplsoWRZKDlgHc4y2IlwAJJsCxwL7EI7zvCfgCOq6t6RNtcAZ1XVwSPzNgbeDexLK2y/ABxWVSsc7NkVlH8LPIZ2Hccjquqkwf4gSZIkSVrHDFo0SpIkSZLWbkMOT5UkSZIkreUsGqUpSLJBkuO6a4lKkiRJaw2Hp85TkgcDu9Eu67EJULTjNK8Azq6qn63BeCtIsgHwsKq6dg3nWB/YfE3lSPIo4FHA1VV19RSWt+Esd28M/AjYGzgXoKruHDrTJEm2bIuvH66J5Y/keAawLe0yOZdU1XlTWObOwH9U1fKhlzVfSbambYuv6KYD7ANsBVwDnFJVy6aQ44G0488fBzwEuBe4Efh6VXkZI0mS1mEWjXPovsAdCbwa2BC4E1gKBFhMu+7kncA7aSfiWeMrNMkLgE9W1XoDLuPltHXyMOAy4Niq+thYm52B8wbOsT5t3f9v4FeA91fV65K8DziU9n8q4CTgD0dPwjRAlrmeeyYLAAOvl0OAz4yePCrJnwFvpBUEAD8Bjqyq9w+Vo1vuO4FlVfXGbnpz4DPAzsDPaevlgcBpwIFDXjInyXLgJuBk4ONV9bWhljWPLJsDnwee0M36CvAC4LPA7rTLEy0CfgDsWVXXDJjlMODNtA6xdLOL+16z5wGHVtV3hsowR74H0jo6Bnv/6v4nycOBm6rqnjWdRVobJHkoIztGquqnaziSFhCHp87tCFpxdCTwyKp6cFU9oqp+s6o2ArYYafPXayzlFCU5CDgG+DptvVwPHJ/kU0kWTTnO64CXAe+nfek9IMmHgRcDBwO/A/wp8PvAHw+cZRltz8yfA/9n7PbKrs3RI/OG9AHatU2B/yki3w2cQbue6YG0a50ek+TFA2d5Ia1jYcaxwOa0PfeLgA2AJbS9ju8aOAvAxcCLgHOSXJvk6CRPnMJyx70VeCjwfOAZtE6PLwL/C9imqh4EbAf8N/CWoUIkORx4B/AR2mWL9gDeQOtUeAWwE/Bd4GvdGbEHl+RhSY5K8h9JbqddvunnSW7v5h2ZZNNpZJmPJDsk+ecpLGfDJC9J8pokz06yUsdTkkdPKcuWSV6V5HVJHtHN2ybJ8UnO6X7+7tA5Zsm3mDa648lrMMNGSQ7r1sWHk7y8G7U09HKfkOQpY/OeneTsJDcluTHJl8fbDJTlS0lemWSzoZc1H0n2SfLxJCcl2a2b96wkF3fbl0uTDP1dYSbLg5O8OskZSa5PcleSO5L8IMmJSfaYUo5tk3w0yU3Aj4ErgauAH3evl49Ma9s/H0l2TfKVKSznN5K8KckxSQ5NssmENo+bUpad0i4x+P4kO3Tzdk1yVvc95uwkew2dg6ryNssNuA44ZB7tDgGuGzjLV+Z5uxS4d8AcFwBHj81bAvwXrZB8aDdv5yFzdMu4Avjzkemn0YY7vmqs3ZHABQNneThwIu3L9iuB9UbuW9zl2nXIDCPLWw7sNLaejp/Q7mO04ZpDZrkLePrI9B3AARPavRj46TTWC7A+rSPhROA22lDMK2kdP1tP6X/0n8CLR6Yf2+U7YKzdHwA/GjDHD4C/mjB/L+B2YMNu+mTg81NYL79L2xv8Y+BDwGuBP6J1Dr2WdummG7v7Hz+N/9U8Mr9gCtu6zbv/1XLgZ93Py4Edx9pNY7v7RNrhGXd1P3/Sva9u6rY1JwPf797rjxswx9Gz3N7TraOPz8wbeJ1cD2w/Mr0FbXj5PcC3u9s9tA6YzQbO8vXR9zStk3I5rdPwr2gjTs6kdUjtM3CW5d3tHlQQD1EAAA00SURBVOD0LsvGQy5zliwv7rJc2K2LZbQOxGXdZ8GfA5/oPg9eNnCWrWiXirsDOB84q3sf3dNt9z7f5foQ8IABc+xBGy33LeBNwP6073N7dr+/Ebiky7n7mvi/Tcg8je3tY4CbaZ+B3+62dTcBvz/Wbhrb2yW0UVk/HPlfPLf7eTrwduBr3Wtnp0GzrOl//kK/df+UJfP8p94xcJb/Br7TfSDPdjtvyBdx9ybafcL8LWlfYq7qNojTeDMtA3YbmV7UfSg8ZazdM4Gbp/SaeTpwEW3v2l7dvDVdNN4zk2Ws3XOm8Lq9avQDGLi1J8tzgdunuV5GXjMHAv/avZ7uBb7JSGfEQFluB54xMr3RpNdIt20ZbL10H4Z7Tpi/cZdnu256X9pwpaFfu2fT9rhuOEubDbs2Zw2cZdd53t48hW3d8d329THd9ONpX/zvBPYfaTeN7e4ptC+5D6INYX47rdPwi3SdZbQRBOfQhoEPlWM57XCRqyfcfti9l2/opn8w8DoZ3+aeTOsY2m5k3m938z40cJbbgGeNTH8POGZCuw/Sjicfer0cQBsVdGE3fRfwOeCg2d7nA2T5JvC+kemDuyxvHWv3buCigbOcAnyDdv6JmXkb0EZ8nN1NP4bWOfbaAXNc0C0zs7RJt/0ZuuP9D+d5O2YK27jP0Ir5TbrpTYGP0r6Hv3qk3TS2t2cDn6LrPAAO797jHxlr9zngc4NmGfLJ7w83Wm/UqcCDZmnzIODLwOkDZ7kY+MQ82u0/5Iu4+9Dbv+e+TWhF6420oW1Dv5l+wkhPKW3I9TJGeny7+c8Gbpvi6+YBwMuBnwJfoPXCT7to3JX25XpD2he6SYXBs4GfDZzlL7rXzNbd9DG0L5Mbj7R5SPe6+cIU1ktvTxzwa7QvEv8PuHvgLBcC7xmZfkn32n3LWLt3ABcPmOMS4B8nzH8ZrXdzcTe9ZBrvIVoRtMc82u3B8B0ey2mFx/J53Ibe1l0LvHBsXoC30b7IHN7Nm8aXmB8z0uNOG1K9HHjOWLuDGLBYA/6B1gl1JLBo7L6ZTo811VF3CxP2VgF/Alw/cJZbWLFovIeRztWR+XsCd015vfwWrZPlO9y31/xE4HnA+gNn+UU66gbd1nVZnjth/ubdNmfLbvow4KoBc6zQ8T5Lu91p5yYY+rWyULa3NwDPmzD/T7r303u66Wlsb28G9h6Zfki3Dp411m4/4NohszwQzeUVtN2/1yY5lTb05hbaQcIb086muhftmJslA2f5Bu1L/lyK+05mMYQLacdhfWqlBVctTbKku++9jJz4ZSBXAjsC/9Ytfzltz9G47WhDhaaiy/G+JCcBfwd8leHXxbgzR34PrXA9fazN42nH/Qzp7bT1/61u7P9VwPa099SlIzl+Sjuh0RpTVbfRelSP704IMKS3Ayd2xxXdSttD/VLgg0l+k1bMPZG2F/TlA+b4a+DTaWdxPZ1WKD6JdgbXD9Z9Jybanrb9G9pPgK1pQ+1nsw3tNTOkm2kdCH8/R7tn0Yr7IW1C64z7H9W+Kbw+yQ+B93bHFp48cA6AB9N6umfMnHDrhrF2N9C+BA+iql6V5DjaUNSrkry+qk6cuXuo5c7TItqe4XGX045lHtJXacPav9xNf4f2OXn2WLsn0Q7BmZqq+h5wFHBUd8zrQbTj3g+i7TUect3cSuvgmDHz+/jx0Zuy4ut7CD+ndVKO24j2eb1+N/0t4BED5vgR8FRWfm2MeyrDf1f4L9qw3FfP0W5f2t7RIS2idWCuoKo+kOQ64OPdibaOHTgHtNfCz0emZz6TfzLW7qes/FperSwa51BVlyfZjta78GxaYThzMOxS2peod9C+XN0ycJyjacN/5nIK7VITQ/kX4PAkD6mqm8fvrKplSX6fdjKWZw6YA9qJU+bzIbMnbfjhVFU789ihSd5LG2ry7Skt+qUT5o1/oYNWSH56yCDVznj5kiQndLn2oZ30JbRhzJfTTiZ1XFXdPmQW2gfjvL4M1MBnjauqk5LcSTumZn1g36o6JckNtG3KC2hD7F5dVf84YI7PJtmVdjzLK2hDpL5HO4HU6AlVzmXFjoihfBB4R5KH0Aqg73bF0czZrH+LNtztL2kdMkP6OvComuOssUm2GTgHtGMEd2LCl7uqen+SG2nb5t2nkOUG2nv3rG759yZ5A21EwaiH0z4nB1NVlwHPTLI/7XXzCuDPaJ1T0/bK7v0LbU/Sb05o83Bax/OQ/pJ24qoH0EZ2vAH4SPeeOqtrswR4FW0kyBpRVZfQOsfekOTJtA6yIZ0G/G2S22ifA0fRCuwjklxUVT9Iu5bym2jHiA3p34C3dQXIOVVV3XfN44DvV9V3u3a/zsrFwer0duADaZcoO5nJO0YOoH12HzpgDmjDQXeoqjtma5Rk8EtQ0XZIPJ022nAFVfW5JM+kFbhPmkKW/6R1pJ7RLf/eJC+ifSaM2oJ23OVgvOSGJGlB6QqQ19N63e+lDWGrbno92hfyt1bVWwfO8afAS6pqlzna7QC8oqomddasrixvp3W4bFM91xlNsjvtki0b1bCX9PkkbUjWi+Zo9xHgIVX1vKGyjC1vA1rB9Bpa5+l+tOGI50xh2dew8t7Nz1bV4WPtTgQ2rapBO1STbE/ruN2ZFUcfzfy+FDiqqt4zcI7lwJOr6t+HXM48s2xG+6K/Qzfr67QzRv8L7RrKd9IO5/gRbYj8DwbMshj4JK1j/R7aEPMNaCOiDqqq/+javZF2csHDe55qdWQ5iNZx+1hWfg2H1gFzRFWdNFSGLscLaYc+vXCOdo+jDdU/csAsR9JOwLZVVd3d02Y72kiUhw+8vf0AsMFcny9J/hW4Z671t0pZLBolSQtNkl8FnkLr6R4f3XFe3wf5/VX3hXcH4KvdMOq+dtsAO1fVYMO30q6Pu15V3TVHu4OAK6vqoqGy9Cz3UbRL2jwW+KOq+uY0lz+bJL9HOxvypXM2Xj3LexytcNyMdqz9zbTRHefVFK5f2V3W4sKq+tnQy5qPbrTCY2nHT357ZN7zaHtzfgicMq283R7W7blvhMep0/i/9GR5NG0drLC9raqr10SeNSnJzCX1rq6qlYapjrTbFNi2quYa3ju4JE+jbVt+ONgyLBolSWubbq/Sw6rqWrMs2CyLaHvV1mgW10lvloW0XsyygLN0HUWbr+kcZpk1y6/QLuczWJYHDPXEkiQN6Dm0SyksBGaZ7PdYGFlcJ5MtpPVilskGz5Lk5Um+n+T2JN9I8pIJzZ44dA6zrHKWJwydxaJRkiRJWsd0Q8iPoR3feSRwPe3s4Z/q9oqbxSz3ZXF4qiRpoUi7LMt8zBxLMuQJCMyygLMslBxmMcvamiXJBcBXqup1I/OWACfQTsrznKr6aZKdacfBDrlOzLLAs3jJDUnSQrIr7XTnl83RbgOzrPNZFkoOs5hlbc2yNfDa0RlVdUZ3gp4vAecn2XvgDGZZS7JYNEqSFpJv0864Oes129Kuy/cJs6zTWRZKDrOYZW3NcivtWpArqKprkjyFdm3w84C/GTCDWdaSLB7TKElaSL4BPHke7UavPWeWdTPLQslhFrOsrVkuBJ4/ccFVS4ElwAXAewfMYJa1JIvHNEqSFowkWwHbVdXn5mi3iHYq+uGuSWWWBZ1loeQwi1nW1ixJDgAOB55bVTf3tFkP+ADwzKp61BA5zLKWZLFolCRJkiT1cXiqJEmSJKmXRaMkSfczSbZM8qI1nUOSdP9g0ShJWucl+dnY9MFJjp3Cco/vzpC4qm22TPLt7vf1gPcB31x9SSVJ6zKLRkmSVlGShXQJq98C3lpVV67pIJKk+weLRkmSZpHkkUnOSPKt7ucW3fzjk7wryZnA25LslOS8JBd1P7ee8FxJcmySy5J8EXjYyH07JDk7yYVJTk2y+Ry5dkhySZLzgZeP3LU58PquzZyZJEmai0WjJEmwKMnFMzfgqJH7jgU+WlWPB05gxethPRbYs6peA1wB7FpVTwDeDLxlwnL2BbYGfgf4v8BTAJKsDxwD7F9VOwD/DPzdHJk/DBxWVbvM0mY+mSRJmtVCGk4jSdKasqyqtp+ZSHIwsGM3uQuwX/f7x4CjRx53clXd2/2+GPhIksfQLsq9/oTl7Ap8vHvM9Um+0s3fGvht4LQkAOsBN/SFTbIY2Liqzh7JtfeEpvPJJEnSrCwaJUn6xYxe4PiOkd//BjizqvZNsiVw1jwePyPAd+bYazjefj4XWp5vJkmSejk8VZKk2Z0HHNT9/gfAuT3tFgPXdb8f3NPmHOCgJOt1xyw+o5t/JbBpkl2gDVdNsl1foKq6Bbg1ydNGcv2ymSRJmpVFoyRJszsMeGmSbwEvAf6sp93RwN8n+RpteOkk/wp8F7gU+ABwNkBV/RzYn3ZCnUuAi+mOd5zFS4H3dSfCWbYKmSRJmlWq5jO6RZIkSZK0LnJPoyRJkiSpl0WjJEmSJKmXRaMkSZIkqZdFoyRJkiSpl0WjJEmSJKmXRaMkSZIkqZdFoyRJkiSpl0WjJEmSJKnX/wfb1VO2AkrvqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = join_por_hora[\"porcentaje\"].plot(kind=\"bar\",figsize=(15,10),fontsize=15 , title=\"Porcentaje clicks por subasta según hora del día\")\n",
    "ax.set_xlabel(\"Hora del día\")\n",
    "ax.set_ylabel(\"Porcentaje de clicks segun cantidad de subastas\")\n",
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>country</th>\n",
       "      <th>date</th>\n",
       "      <th>device_id</th>\n",
       "      <th>platform</th>\n",
       "      <th>ref_type_id</th>\n",
       "      <th>source_id</th>\n",
       "      <th>hora</th>\n",
       "      <th>auction_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6333597102633388268</td>\n",
       "      <td>2019-03-11 14:18:33.290763</td>\n",
       "      <td>6059599345986491085</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               country                       date            device_id  \\\n",
       "0  6333597102633388268 2019-03-11 14:18:33.290763  6059599345986491085   \n",
       "\n",
       "  platform ref_type_id source_id  hora  auction_count  \n",
       "0        1           1         0    14              1  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auctions.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    26263\n",
       "0       70\n",
       "2       12\n",
       "7        2\n",
       "1        2\n",
       "8        1\n",
       "5        1\n",
       "Name: advertiser_id, dtype: int64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clicks.advertiser_id.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "633139769114048761     27762\n",
       "7202276635029175071    23055\n",
       "7298861376107043945    18188\n",
       "6302840482782120473    16400\n",
       "5376802567578262905    16367\n",
       "8963711959081981780    14362\n",
       "795159065504552200     12275\n",
       "6841615430383729819    12077\n",
       "5384039226444052914    11632\n",
       "3198179064438296471    11565\n",
       "519658456951133298     10541\n",
       "2435544514359302887    10274\n",
       "8751190726444323885    10256\n",
       "1835469468095030098    10121\n",
       "1800317677967270083    10036\n",
       "9027154272484048876     9958\n",
       "7574657722181550308     9767\n",
       "5051610571898428259     9642\n",
       "320899491737875154      9388\n",
       "8292793494956750501     9315\n",
       "201759600719985554      9158\n",
       "8021195662481548645     9128\n",
       "7650408579713341483     9020\n",
       "6392567838173461255     8994\n",
       "1478017482044456084     8839\n",
       "6203407103275384250     8823\n",
       "68016455690089173       8809\n",
       "8496718680483076445     8682\n",
       "8491787427844905567     8513\n",
       "4834359787191717922     8495\n",
       "                       ...  \n",
       "5965915879234710356        1\n",
       "5962371857976871552        1\n",
       "8775830221902480502        1\n",
       "6400673246409330938        1\n",
       "8848059905278451239        1\n",
       "2387472711882692396        1\n",
       "6919864391159784728        1\n",
       "6918436643991280288        1\n",
       "1265394499505454114        1\n",
       "1192257502202972678        1\n",
       "9203091890242370281        1\n",
       "116130905366082001         1\n",
       "6746874540432696049        1\n",
       "2349117575888212633        1\n",
       "3115384134991732020        1\n",
       "6658609489857321554        1\n",
       "6703916290356312366        1\n",
       "3122486780808724561        1\n",
       "9128287699651516130        1\n",
       "9090768995352915488        1\n",
       "9043530082076844214        1\n",
       "8981735392801911779        1\n",
       "3142217809159395792        1\n",
       "6583122778867177908        1\n",
       "6552357094313704           1\n",
       "8900190054383012348        1\n",
       "6516634122275645386        1\n",
       "8850035083239840651        1\n",
       "6420983180219968660        1\n",
       "954913365148193776         1\n",
       "Name: device_id, Length: 206977, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auctions['device_id'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KdBnICuNg6KSSooMPF6esC9etYfFfVg    1\n",
       "3AgOlw7z-Za2j6MYclzx6dpk6AYB95s    1\n",
       "tN_3SRf49hg8oYfZiCvidgUseUQ_iEI    1\n",
       "S2CPC7rgiM6sVT5igiooVR-x5Rg0g4o    1\n",
       "1l93qjMA5p13HbhnXCwJzUA6LEdIF4s    1\n",
       "qd3FEH_z1Dq_jKnHTmUXZIZxsnwzzsA    1\n",
       "an7PTGuvvH96RptBzwcWpXJ925JK4gI    1\n",
       "4cD_VGQgwW2hdg-B8zJpkfIaRb0flmg    1\n",
       "TAeXObB9PJBuU3vSr5fvxo70JwiKe4c    1\n",
       "fSSsRSBC6i_MfrachRM8xKACs6hilW0    1\n",
       "cFHu-FxBZXnSlvaTb7AizXIAVzlJ8IY    1\n",
       "tJKV0r4k3IAqGTYOZbedWhvA_N81ITY    1\n",
       "2KGRowz2gYhHxQ2VeWasrNhvhFWxXcg    1\n",
       "Brim4pMpBZQHs9hn3QmGUyfgoHlh9rk    1\n",
       "aljaHutN9crWOLXWNgmi3BGwxQ8fiKs    1\n",
       "Ztvo_ceafAPoUv2nKN4lllukpbQbWUE    1\n",
       "084MHRqbJV7qXzD04K3X_25u-xmx4ag    1\n",
       "7Z-dZyzMI3Eu9triAx9BOzA_2CMZU3Q    1\n",
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       "                                  ..\n",
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       "_RGLCf-v2YA7UCdlHuCw9_0qOH7F9rg    1\n",
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       "-DbicJ8xdMkOQnAHpJP9bVEmzDwLmZs    1\n",
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       "y895svtTTQEOXROXJT-C0v3QBwxXggI    1\n",
       "Name: trans_id, Length: 26351, dtype: int64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clicks['trans_id'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    13354597\n",
       "1     4016739\n",
       "5     1466494\n",
       "2      582083\n",
       "6      151406\n",
       "Name: source_id, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "auctions.source_id.value_counts()"
   ]
  }
 ],
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