VAR_APARCH.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: MASS\n",
      "Loading required package: strucchange\n",
      "Loading required package: zoo\n",
      "\n",
      "Attaching package: ‘zoo’\n",
      "\n",
      "The following objects are masked from ‘package:base’:\n",
      "\n",
      "    as.Date, as.Date.numeric\n",
      "\n",
      "Loading required package: sandwich\n",
      "Loading required package: urca\n",
      "Loading required package: lmtest\n",
      "Registered S3 method overwritten by 'xts':\n",
      "  method     from\n",
      "  as.zoo.xts zoo \n",
      "\n",
      "Please cite as: \n",
      "\n",
      " Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.\n",
      " R package version 5.2.2. https://CRAN.R-project.org/package=stargazer \n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(\"vars\")\n",
    "library(\"tidyr\")\n",
    "library(\"xts\")\n",
    "library(\"stargazer\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "data <- read.csv(\"//home/ostapkharysh/Documents/bt_data/DescriptiveFebruary29June05_2016/ET/AMZN/PR.csv\")\n",
    "data <- drop_na(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 1265 × 9</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>date</th><th scope=col>tone</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>polarity</th><th scope=col>activ_den</th><th scope=col>self_den</th><th scope=col>fin_return</th><th scope=col>weight</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>54</th><td>2016-02-29 13:45:00</td><td> 0.9022556</td><td>2.406015</td><td>1.50375940</td><td>3.909774</td><td>20.45113</td><td>0.00000000</td><td> 3.236863e-04</td><td>2.228867e-06</td></tr>\n",
       "\t<tr><th scope=row>55</th><td>2016-02-29 14:00:00</td><td> 0.3456533</td><td>3.788557</td><td>3.44290364</td><td>7.231461</td><td>22.24363</td><td>0.86363555</td><td> 3.044711e-03</td><td>1.067255e-04</td></tr>\n",
       "\t<tr><th scope=row>56</th><td>2016-02-29 14:15:00</td><td> 1.1032072</td><td>2.711936</td><td>1.60872880</td><td>4.320665</td><td>21.05964</td><td>0.06702841</td><td> 3.560728e-03</td><td>1.330447e-05</td></tr>\n",
       "\t<tr><th scope=row>57</th><td>2016-02-29 14:30:00</td><td> 4.7190417</td><td>5.312533</td><td>0.59349119</td><td>5.906024</td><td>25.99383</td><td>1.32800871</td><td> 8.355592e-04</td><td>4.031775e-04</td></tr>\n",
       "\t<tr><th scope=row>58</th><td>2016-02-29 14:45:00</td><td>-2.5359256</td><td>1.606086</td><td>4.14201183</td><td>5.748098</td><td>20.96365</td><td>1.18343195</td><td>-3.321365e-03</td><td>3.659334e-06</td></tr>\n",
       "\t<tr><th scope=row>60</th><td>2016-02-29 15:15:00</td><td>-1.7043454</td><td>1.435621</td><td>3.13996680</td><td>4.575588</td><td>20.80098</td><td>0.23696648</td><td>-1.900743e-03</td><td>1.274351e-05</td></tr>\n",
       "\t<tr><th scope=row>61</th><td>2016-02-29 15:30:00</td><td>-1.8556842</td><td>1.517347</td><td>3.37303111</td><td>4.890378</td><td>21.66980</td><td>0.27667246</td><td>-6.469331e-04</td><td>3.556666e-04</td></tr>\n",
       "\t<tr><th scope=row>62</th><td>2016-02-29 15:45:00</td><td> 0.7792567</td><td>2.959870</td><td>2.18061330</td><td>5.140483</td><td>22.19366</td><td>0.46813383</td><td> 3.641381e-03</td><td>9.824652e-06</td></tr>\n",
       "\t<tr><th scope=row>63</th><td>2016-02-29 16:00:00</td><td> 0.2886140</td><td>2.918574</td><td>2.62996036</td><td>5.548535</td><td>21.93399</td><td>1.30747378</td><td>-2.179307e-04</td><td>3.424705e-05</td></tr>\n",
       "\t<tr><th scope=row>64</th><td>2016-02-29 16:15:00</td><td> 1.1656561</td><td>2.420149</td><td>1.25449333</td><td>3.674643</td><td>22.31254</td><td>0.85043888</td><td> 4.465283e-04</td><td>5.104687e-03</td></tr>\n",
       "\t<tr><th scope=row>65</th><td>2016-02-29 16:30:00</td><td>-1.4251781</td><td>2.375297</td><td>3.80047506</td><td>6.175772</td><td>23.27791</td><td>0.00000000</td><td>-6.734410e-04</td><td>1.562558e-07</td></tr>\n",
       "\t<tr><th scope=row>69</th><td>2016-02-29 17:30:00</td><td>-3.4456558</td><td>1.600357</td><td>5.04601270</td><td>6.646370</td><td>22.08203</td><td>0.26847041</td><td>-8.762026e-04</td><td>2.988712e-03</td></tr>\n",
       "\t<tr><th scope=row>70</th><td>2016-02-29 17:45:00</td><td>-0.2047093</td><td>2.568016</td><td>2.77272505</td><td>5.340741</td><td>22.39894</td><td>0.42360760</td><td>-1.155196e-03</td><td>3.258908e-05</td></tr>\n",
       "\t<tr><th scope=row>71</th><td>2016-02-29 18:00:00</td><td>-1.0292699</td><td>2.283693</td><td>3.31296237</td><td>5.596655</td><td>19.17015</td><td>0.83628176</td><td>-1.624522e-03</td><td>2.840858e-05</td></tr>\n",
       "\t<tr><th scope=row>72</th><td>2016-02-29 18:15:00</td><td> 0.5594259</td><td>3.838818</td><td>3.27939184</td><td>7.118210</td><td>24.14970</td><td>1.28659797</td><td>-3.418317e-03</td><td>5.132428e-05</td></tr>\n",
       "\t<tr><th scope=row>73</th><td>2016-02-29 18:30:00</td><td> 1.7408315</td><td>3.083057</td><td>1.34222582</td><td>4.425283</td><td>24.80592</td><td>0.58025328</td><td> 1.110892e-03</td><td>1.009724e-03</td></tr>\n",
       "\t<tr><th scope=row>74</th><td>2016-02-29 18:45:00</td><td> 1.4150943</td><td>2.830189</td><td>1.41509434</td><td>4.245283</td><td>24.52830</td><td>0.70754717</td><td>-3.354353e-03</td><td>5.737168e-06</td></tr>\n",
       "\t<tr><th scope=row>75</th><td>2016-02-29 19:00:00</td><td>-0.0889748</td><td>2.046772</td><td>2.13574633</td><td>4.182518</td><td>23.97355</td><td>1.33402596</td><td>-1.060665e-03</td><td>5.131520e-03</td></tr>\n",
       "\t<tr><th scope=row>76</th><td>2016-02-29 19:15:00</td><td>-1.1107428</td><td>2.067217</td><td>3.17795971</td><td>5.245177</td><td>21.61734</td><td>0.05857083</td><td>-2.142736e-03</td><td>9.825757e-06</td></tr>\n",
       "\t<tr><th scope=row>77</th><td>2016-02-29 19:30:00</td><td>-2.1300136</td><td>1.975517</td><td>4.10553090</td><td>6.081048</td><td>22.12364</td><td>0.75119707</td><td> 3.424256e-04</td><td>8.276189e-06</td></tr>\n",
       "\t<tr><th scope=row>78</th><td>2016-02-29 19:45:00</td><td>-1.0318115</td><td>2.290277</td><td>3.32208823</td><td>5.612365</td><td>19.20755</td><td>0.83510869</td><td>-3.964328e-05</td><td>3.992140e-04</td></tr>\n",
       "\t<tr><th scope=row>151</th><td>2016-03-01 14:00:00</td><td> 0.8324155</td><td>1.437770</td><td>0.60535457</td><td>2.043125</td><td>20.37194</td><td>0.94594595</td><td> 4.281516e-03</td><td>8.326803e-05</td></tr>\n",
       "\t<tr><th scope=row>152</th><td>2016-03-01 14:15:00</td><td> 2.1452950</td><td>3.754266</td><td>1.60897123</td><td>5.363237</td><td>18.52755</td><td>0.73135056</td><td> 2.098375e-03</td><td>4.098459e-07</td></tr>\n",
       "\t<tr><th scope=row>153</th><td>2016-03-01 14:30:00</td><td>-0.2967359</td><td>2.225519</td><td>2.52225519</td><td>4.747774</td><td>24.62908</td><td>1.18694362</td><td> 7.080553e-03</td><td>3.497907e-04</td></tr>\n",
       "\t<tr><th scope=row>155</th><td>2016-03-01 15:00:00</td><td> 0.3438350</td><td>1.882116</td><td>1.53828112</td><td>3.420397</td><td>18.19764</td><td>0.19740311</td><td>-2.102679e-03</td><td>6.458633e-05</td></tr>\n",
       "\t<tr><th scope=row>156</th><td>2016-03-01 15:15:00</td><td> 2.4076293</td><td>3.434227</td><td>1.02659728</td><td>4.460824</td><td>19.17997</td><td>1.20192351</td><td> 1.809629e-03</td><td>5.154214e-05</td></tr>\n",
       "\t<tr><th scope=row>157</th><td>2016-03-01 15:30:00</td><td>-0.2976190</td><td>1.190476</td><td>1.48809524</td><td>2.678571</td><td>18.45238</td><td>1.19047619</td><td> 2.813963e-03</td><td>1.674573e-06</td></tr>\n",
       "\t<tr><th scope=row>158</th><td>2016-03-01 15:45:00</td><td> 4.1280723</td><td>4.150654</td><td>0.02258215</td><td>4.173237</td><td>26.94541</td><td>2.98243777</td><td> 3.041306e-03</td><td>1.354039e-04</td></tr>\n",
       "\t<tr><th scope=row>159</th><td>2016-03-01 16:00:00</td><td> 2.5646237</td><td>3.597666</td><td>1.03304271</td><td>4.630709</td><td>25.44714</td><td>2.05505380</td><td> 2.734541e-03</td><td>2.746101e-05</td></tr>\n",
       "\t<tr><th scope=row>160</th><td>2016-03-01 16:15:00</td><td> 1.0487364</td><td>1.671060</td><td>0.62232388</td><td>2.293384</td><td>22.18780</td><td>0.41454594</td><td>-1.171782e-03</td><td>2.079547e-04</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>9082</th><td>2016-06-02 14:45:00</td><td>-1.9882849</td><td>2.496322</td><td>4.4846065</td><td>6.980928</td><td>22.51924</td><td>1.0579480</td><td> 1.819692e-03</td><td>3.520374e-03</td></tr>\n",
       "\t<tr><th scope=row>9083</th><td>2016-06-02 15:00:00</td><td> 1.5845773</td><td>2.605657</td><td>1.0210797</td><td>3.626737</td><td>26.78812</td><td>1.8411905</td><td>-7.744948e-04</td><td>1.299813e-04</td></tr>\n",
       "\t<tr><th scope=row>9084</th><td>2016-06-02 15:15:00</td><td>-0.4991681</td><td>2.273988</td><td>2.7731559</td><td>5.047144</td><td>22.68441</td><td>0.6655574</td><td> 4.867364e-04</td><td>6.445534e-04</td></tr>\n",
       "\t<tr><th scope=row>9085</th><td>2016-06-02 15:30:00</td><td> 0.4489683</td><td>3.497895</td><td>3.0489271</td><td>6.546822</td><td>24.12478</td><td>3.4076244</td><td> 2.664504e-03</td><td>3.003542e-03</td></tr>\n",
       "\t<tr><th scope=row>9088</th><td>2016-06-02 16:15:00</td><td> 0.5899705</td><td>2.064897</td><td>1.4749263</td><td>3.539823</td><td>24.77876</td><td>0.5899705</td><td>-1.134011e-03</td><td>3.721735e-05</td></tr>\n",
       "\t<tr><th scope=row>9089</th><td>2016-06-02 16:30:00</td><td>-2.6652452</td><td>1.492537</td><td>4.1577825</td><td>5.650320</td><td>20.14925</td><td>0.0000000</td><td> 6.344830e-04</td><td>1.145675e-03</td></tr>\n",
       "\t<tr><th scope=row>9092</th><td>2016-06-02 17:15:00</td><td>-2.0695519</td><td>1.401146</td><td>3.4706979</td><td>4.871844</td><td>22.07021</td><td>0.6061744</td><td> 1.038654e-03</td><td>6.472343e-04</td></tr>\n",
       "\t<tr><th scope=row>9095</th><td>2016-06-02 18:00:00</td><td>-2.5637980</td><td>1.068517</td><td>3.6323148</td><td>4.700832</td><td>22.57222</td><td>0.3286605</td><td>-3.093376e-04</td><td>9.365468e-03</td></tr>\n",
       "\t<tr><th scope=row>9096</th><td>2016-06-02 18:15:00</td><td>-2.6143750</td><td>1.185144</td><td>3.7995189</td><td>4.984663</td><td>23.64676</td><td>0.7279446</td><td> 9.980985e-04</td><td>2.810801e-04</td></tr>\n",
       "\t<tr><th scope=row>9097</th><td>2016-06-02 18:30:00</td><td>-2.6304720</td><td>1.039555</td><td>3.6700272</td><td>4.709582</td><td>22.55767</td><td>0.3331398</td><td> 9.805619e-04</td><td>5.488089e-04</td></tr>\n",
       "\t<tr><th scope=row>9099</th><td>2016-06-02 19:00:00</td><td>-1.7055663</td><td>2.053103</td><td>3.7586690</td><td>5.811772</td><td>22.82752</td><td>0.2582886</td><td> 1.047886e-03</td><td>3.769268e-03</td></tr>\n",
       "\t<tr><th scope=row>9100</th><td>2016-06-02 19:15:00</td><td> 0.6319049</td><td>2.471373</td><td>1.8394684</td><td>4.310842</td><td>23.34993</td><td>0.8460192</td><td>-1.102521e-04</td><td>1.611637e-04</td></tr>\n",
       "\t<tr><th scope=row>9101</th><td>2016-06-02 19:30:00</td><td> 2.2727273</td><td>4.261364</td><td>1.9886364</td><td>6.250000</td><td>22.72727</td><td>1.4204545</td><td> 4.271591e-04</td><td>3.050196e-05</td></tr>\n",
       "\t<tr><th scope=row>9102</th><td>2016-06-02 19:45:00</td><td> 0.4791361</td><td>2.659365</td><td>2.1802293</td><td>4.839595</td><td>21.73432</td><td>0.8900456</td><td> 5.550341e-04</td><td>3.636684e-04</td></tr>\n",
       "\t<tr><th scope=row>9176</th><td>2016-06-03 14:15:00</td><td> 2.3338407</td><td>3.044140</td><td>0.7102993</td><td>3.754439</td><td>17.14866</td><td>0.8625063</td><td>-6.672072e-03</td><td>2.583215e-06</td></tr>\n",
       "\t<tr><th scope=row>9179</th><td>2016-06-03 15:00:00</td><td>-0.4435407</td><td>1.211850</td><td>1.6553911</td><td>2.867242</td><td>21.54125</td><td>1.1280309</td><td> 1.011284e-03</td><td>3.861201e-05</td></tr>\n",
       "\t<tr><th scope=row>9180</th><td>2016-06-03 15:15:00</td><td> 1.8095238</td><td>3.238095</td><td>1.4285714</td><td>4.666667</td><td>23.04762</td><td>1.8095238</td><td>-1.551978e-03</td><td>1.236814e-06</td></tr>\n",
       "\t<tr><th scope=row>9181</th><td>2016-06-03 15:30:00</td><td> 0.5604081</td><td>1.879578</td><td>1.3191698</td><td>3.198748</td><td>21.41277</td><td>0.6994322</td><td> 1.109355e-04</td><td>3.517427e-04</td></tr>\n",
       "\t<tr><th scope=row>9182</th><td>2016-06-03 15:45:00</td><td> 0.6488252</td><td>2.098174</td><td>1.4493487</td><td>3.547523</td><td>22.10613</td><td>0.7455359</td><td> 2.257634e-03</td><td>4.007891e-05</td></tr>\n",
       "\t<tr><th scope=row>9184</th><td>2016-06-03 16:15:00</td><td> 1.6837041</td><td>3.307276</td><td>1.6235719</td><td>4.930848</td><td>26.81900</td><td>3.7282020</td><td> 1.243180e-03</td><td>1.518452e-04</td></tr>\n",
       "\t<tr><th scope=row>9186</th><td>2016-06-03 16:45:00</td><td>-1.6759777</td><td>1.675978</td><td>3.3519553</td><td>5.027933</td><td>20.94972</td><td>0.2793296</td><td>-9.662303e-05</td><td>1.200138e-05</td></tr>\n",
       "\t<tr><th scope=row>9187</th><td>2016-06-03 17:00:00</td><td> 1.8583683</td><td>3.150898</td><td>1.2925295</td><td>4.443427</td><td>22.88999</td><td>3.8550764</td><td> 1.104256e-04</td><td>6.936105e-04</td></tr>\n",
       "\t<tr><th scope=row>9189</th><td>2016-06-03 17:30:00</td><td> 0.7518797</td><td>1.879699</td><td>1.1278195</td><td>3.007519</td><td>19.92481</td><td>1.5037594</td><td>-1.103936e-03</td><td>3.639941e-05</td></tr>\n",
       "\t<tr><th scope=row>9190</th><td>2016-06-03 17:45:00</td><td> 0.3022356</td><td>3.428692</td><td>3.1264568</td><td>6.555149</td><td>20.48614</td><td>0.5154711</td><td>-7.596633e-04</td><td>2.147879e-04</td></tr>\n",
       "\t<tr><th scope=row>9191</th><td>2016-06-03 18:00:00</td><td> 0.3054990</td><td>3.462322</td><td>3.1568228</td><td>6.619145</td><td>19.55193</td><td>0.5091650</td><td>-1.105446e-04</td><td>1.379544e-05</td></tr>\n",
       "\t<tr><th scope=row>9192</th><td>2016-06-03 18:15:00</td><td> 0.5379013</td><td>3.782747</td><td>3.2448456</td><td>7.027593</td><td>20.40042</td><td>0.5138497</td><td>-5.529062e-04</td><td>1.252105e-04</td></tr>\n",
       "\t<tr><th scope=row>9193</th><td>2016-06-03 18:30:00</td><td> 1.0357309</td><td>3.031873</td><td>1.9961419</td><td>5.028015</td><td>25.35427</td><td>0.2777627</td><td> 1.106057e-04</td><td>6.438303e-05</td></tr>\n",
       "\t<tr><th scope=row>9194</th><td>2016-06-03 18:45:00</td><td> 0.2688172</td><td>1.881720</td><td>1.6129032</td><td>3.494624</td><td>20.96774</td><td>0.2688172</td><td> 1.761129e-03</td><td>1.508306e-05</td></tr>\n",
       "\t<tr><th scope=row>9197</th><td>2016-06-03 19:30:00</td><td> 0.4780115</td><td>3.441683</td><td>2.9636711</td><td>6.405354</td><td>18.92925</td><td>0.4780115</td><td> 3.586553e-04</td><td>1.076465e-06</td></tr>\n",
       "\t<tr><th scope=row>9198</th><td>2016-06-03 19:45:00</td><td> 1.7179653</td><td>3.205392</td><td>1.4874270</td><td>4.692819</td><td>23.18482</td><td>0.7909638</td><td>-5.794302e-04</td><td>1.483143e-04</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1265 × 9\n",
       "\\begin{tabular}{r|lllllllll}\n",
       "  & date & tone & positive & negative & polarity & activ\\_den & self\\_den & fin\\_return & weight\\\\\n",
       "  & <fct> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t54 & 2016-02-29 13:45:00 &  0.9022556 & 2.406015 & 1.50375940 & 3.909774 & 20.45113 & 0.00000000 &  3.236863e-04 & 2.228867e-06\\\\\n",
       "\t55 & 2016-02-29 14:00:00 &  0.3456533 & 3.788557 & 3.44290364 & 7.231461 & 22.24363 & 0.86363555 &  3.044711e-03 & 1.067255e-04\\\\\n",
       "\t56 & 2016-02-29 14:15:00 &  1.1032072 & 2.711936 & 1.60872880 & 4.320665 & 21.05964 & 0.06702841 &  3.560728e-03 & 1.330447e-05\\\\\n",
       "\t57 & 2016-02-29 14:30:00 &  4.7190417 & 5.312533 & 0.59349119 & 5.906024 & 25.99383 & 1.32800871 &  8.355592e-04 & 4.031775e-04\\\\\n",
       "\t58 & 2016-02-29 14:45:00 & -2.5359256 & 1.606086 & 4.14201183 & 5.748098 & 20.96365 & 1.18343195 & -3.321365e-03 & 3.659334e-06\\\\\n",
       "\t60 & 2016-02-29 15:15:00 & -1.7043454 & 1.435621 & 3.13996680 & 4.575588 & 20.80098 & 0.23696648 & -1.900743e-03 & 1.274351e-05\\\\\n",
       "\t61 & 2016-02-29 15:30:00 & -1.8556842 & 1.517347 & 3.37303111 & 4.890378 & 21.66980 & 0.27667246 & -6.469331e-04 & 3.556666e-04\\\\\n",
       "\t62 & 2016-02-29 15:45:00 &  0.7792567 & 2.959870 & 2.18061330 & 5.140483 & 22.19366 & 0.46813383 &  3.641381e-03 & 9.824652e-06\\\\\n",
       "\t63 & 2016-02-29 16:00:00 &  0.2886140 & 2.918574 & 2.62996036 & 5.548535 & 21.93399 & 1.30747378 & -2.179307e-04 & 3.424705e-05\\\\\n",
       "\t64 & 2016-02-29 16:15:00 &  1.1656561 & 2.420149 & 1.25449333 & 3.674643 & 22.31254 & 0.85043888 &  4.465283e-04 & 5.104687e-03\\\\\n",
       "\t65 & 2016-02-29 16:30:00 & -1.4251781 & 2.375297 & 3.80047506 & 6.175772 & 23.27791 & 0.00000000 & -6.734410e-04 & 1.562558e-07\\\\\n",
       "\t69 & 2016-02-29 17:30:00 & -3.4456558 & 1.600357 & 5.04601270 & 6.646370 & 22.08203 & 0.26847041 & -8.762026e-04 & 2.988712e-03\\\\\n",
       "\t70 & 2016-02-29 17:45:00 & -0.2047093 & 2.568016 & 2.77272505 & 5.340741 & 22.39894 & 0.42360760 & -1.155196e-03 & 3.258908e-05\\\\\n",
       "\t71 & 2016-02-29 18:00:00 & -1.0292699 & 2.283693 & 3.31296237 & 5.596655 & 19.17015 & 0.83628176 & -1.624522e-03 & 2.840858e-05\\\\\n",
       "\t72 & 2016-02-29 18:15:00 &  0.5594259 & 3.838818 & 3.27939184 & 7.118210 & 24.14970 & 1.28659797 & -3.418317e-03 & 5.132428e-05\\\\\n",
       "\t73 & 2016-02-29 18:30:00 &  1.7408315 & 3.083057 & 1.34222582 & 4.425283 & 24.80592 & 0.58025328 &  1.110892e-03 & 1.009724e-03\\\\\n",
       "\t74 & 2016-02-29 18:45:00 &  1.4150943 & 2.830189 & 1.41509434 & 4.245283 & 24.52830 & 0.70754717 & -3.354353e-03 & 5.737168e-06\\\\\n",
       "\t75 & 2016-02-29 19:00:00 & -0.0889748 & 2.046772 & 2.13574633 & 4.182518 & 23.97355 & 1.33402596 & -1.060665e-03 & 5.131520e-03\\\\\n",
       "\t76 & 2016-02-29 19:15:00 & -1.1107428 & 2.067217 & 3.17795971 & 5.245177 & 21.61734 & 0.05857083 & -2.142736e-03 & 9.825757e-06\\\\\n",
       "\t77 & 2016-02-29 19:30:00 & -2.1300136 & 1.975517 & 4.10553090 & 6.081048 & 22.12364 & 0.75119707 &  3.424256e-04 & 8.276189e-06\\\\\n",
       "\t78 & 2016-02-29 19:45:00 & -1.0318115 & 2.290277 & 3.32208823 & 5.612365 & 19.20755 & 0.83510869 & -3.964328e-05 & 3.992140e-04\\\\\n",
       "\t151 & 2016-03-01 14:00:00 &  0.8324155 & 1.437770 & 0.60535457 & 2.043125 & 20.37194 & 0.94594595 &  4.281516e-03 & 8.326803e-05\\\\\n",
       "\t152 & 2016-03-01 14:15:00 &  2.1452950 & 3.754266 & 1.60897123 & 5.363237 & 18.52755 & 0.73135056 &  2.098375e-03 & 4.098459e-07\\\\\n",
       "\t153 & 2016-03-01 14:30:00 & -0.2967359 & 2.225519 & 2.52225519 & 4.747774 & 24.62908 & 1.18694362 &  7.080553e-03 & 3.497907e-04\\\\\n",
       "\t155 & 2016-03-01 15:00:00 &  0.3438350 & 1.882116 & 1.53828112 & 3.420397 & 18.19764 & 0.19740311 & -2.102679e-03 & 6.458633e-05\\\\\n",
       "\t156 & 2016-03-01 15:15:00 &  2.4076293 & 3.434227 & 1.02659728 & 4.460824 & 19.17997 & 1.20192351 &  1.809629e-03 & 5.154214e-05\\\\\n",
       "\t157 & 2016-03-01 15:30:00 & -0.2976190 & 1.190476 & 1.48809524 & 2.678571 & 18.45238 & 1.19047619 &  2.813963e-03 & 1.674573e-06\\\\\n",
       "\t158 & 2016-03-01 15:45:00 &  4.1280723 & 4.150654 & 0.02258215 & 4.173237 & 26.94541 & 2.98243777 &  3.041306e-03 & 1.354039e-04\\\\\n",
       "\t159 & 2016-03-01 16:00:00 &  2.5646237 & 3.597666 & 1.03304271 & 4.630709 & 25.44714 & 2.05505380 &  2.734541e-03 & 2.746101e-05\\\\\n",
       "\t160 & 2016-03-01 16:15:00 &  1.0487364 & 1.671060 & 0.62232388 & 2.293384 & 22.18780 & 0.41454594 & -1.171782e-03 & 2.079547e-04\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t9082 & 2016-06-02 14:45:00 & -1.9882849 & 2.496322 & 4.4846065 & 6.980928 & 22.51924 & 1.0579480 &  1.819692e-03 & 3.520374e-03\\\\\n",
       "\t9083 & 2016-06-02 15:00:00 &  1.5845773 & 2.605657 & 1.0210797 & 3.626737 & 26.78812 & 1.8411905 & -7.744948e-04 & 1.299813e-04\\\\\n",
       "\t9084 & 2016-06-02 15:15:00 & -0.4991681 & 2.273988 & 2.7731559 & 5.047144 & 22.68441 & 0.6655574 &  4.867364e-04 & 6.445534e-04\\\\\n",
       "\t9085 & 2016-06-02 15:30:00 &  0.4489683 & 3.497895 & 3.0489271 & 6.546822 & 24.12478 & 3.4076244 &  2.664504e-03 & 3.003542e-03\\\\\n",
       "\t9088 & 2016-06-02 16:15:00 &  0.5899705 & 2.064897 & 1.4749263 & 3.539823 & 24.77876 & 0.5899705 & -1.134011e-03 & 3.721735e-05\\\\\n",
       "\t9089 & 2016-06-02 16:30:00 & -2.6652452 & 1.492537 & 4.1577825 & 5.650320 & 20.14925 & 0.0000000 &  6.344830e-04 & 1.145675e-03\\\\\n",
       "\t9092 & 2016-06-02 17:15:00 & -2.0695519 & 1.401146 & 3.4706979 & 4.871844 & 22.07021 & 0.6061744 &  1.038654e-03 & 6.472343e-04\\\\\n",
       "\t9095 & 2016-06-02 18:00:00 & -2.5637980 & 1.068517 & 3.6323148 & 4.700832 & 22.57222 & 0.3286605 & -3.093376e-04 & 9.365468e-03\\\\\n",
       "\t9096 & 2016-06-02 18:15:00 & -2.6143750 & 1.185144 & 3.7995189 & 4.984663 & 23.64676 & 0.7279446 &  9.980985e-04 & 2.810801e-04\\\\\n",
       "\t9097 & 2016-06-02 18:30:00 & -2.6304720 & 1.039555 & 3.6700272 & 4.709582 & 22.55767 & 0.3331398 &  9.805619e-04 & 5.488089e-04\\\\\n",
       "\t9099 & 2016-06-02 19:00:00 & -1.7055663 & 2.053103 & 3.7586690 & 5.811772 & 22.82752 & 0.2582886 &  1.047886e-03 & 3.769268e-03\\\\\n",
       "\t9100 & 2016-06-02 19:15:00 &  0.6319049 & 2.471373 & 1.8394684 & 4.310842 & 23.34993 & 0.8460192 & -1.102521e-04 & 1.611637e-04\\\\\n",
       "\t9101 & 2016-06-02 19:30:00 &  2.2727273 & 4.261364 & 1.9886364 & 6.250000 & 22.72727 & 1.4204545 &  4.271591e-04 & 3.050196e-05\\\\\n",
       "\t9102 & 2016-06-02 19:45:00 &  0.4791361 & 2.659365 & 2.1802293 & 4.839595 & 21.73432 & 0.8900456 &  5.550341e-04 & 3.636684e-04\\\\\n",
       "\t9176 & 2016-06-03 14:15:00 &  2.3338407 & 3.044140 & 0.7102993 & 3.754439 & 17.14866 & 0.8625063 & -6.672072e-03 & 2.583215e-06\\\\\n",
       "\t9179 & 2016-06-03 15:00:00 & -0.4435407 & 1.211850 & 1.6553911 & 2.867242 & 21.54125 & 1.1280309 &  1.011284e-03 & 3.861201e-05\\\\\n",
       "\t9180 & 2016-06-03 15:15:00 &  1.8095238 & 3.238095 & 1.4285714 & 4.666667 & 23.04762 & 1.8095238 & -1.551978e-03 & 1.236814e-06\\\\\n",
       "\t9181 & 2016-06-03 15:30:00 &  0.5604081 & 1.879578 & 1.3191698 & 3.198748 & 21.41277 & 0.6994322 &  1.109355e-04 & 3.517427e-04\\\\\n",
       "\t9182 & 2016-06-03 15:45:00 &  0.6488252 & 2.098174 & 1.4493487 & 3.547523 & 22.10613 & 0.7455359 &  2.257634e-03 & 4.007891e-05\\\\\n",
       "\t9184 & 2016-06-03 16:15:00 &  1.6837041 & 3.307276 & 1.6235719 & 4.930848 & 26.81900 & 3.7282020 &  1.243180e-03 & 1.518452e-04\\\\\n",
       "\t9186 & 2016-06-03 16:45:00 & -1.6759777 & 1.675978 & 3.3519553 & 5.027933 & 20.94972 & 0.2793296 & -9.662303e-05 & 1.200138e-05\\\\\n",
       "\t9187 & 2016-06-03 17:00:00 &  1.8583683 & 3.150898 & 1.2925295 & 4.443427 & 22.88999 & 3.8550764 &  1.104256e-04 & 6.936105e-04\\\\\n",
       "\t9189 & 2016-06-03 17:30:00 &  0.7518797 & 1.879699 & 1.1278195 & 3.007519 & 19.92481 & 1.5037594 & -1.103936e-03 & 3.639941e-05\\\\\n",
       "\t9190 & 2016-06-03 17:45:00 &  0.3022356 & 3.428692 & 3.1264568 & 6.555149 & 20.48614 & 0.5154711 & -7.596633e-04 & 2.147879e-04\\\\\n",
       "\t9191 & 2016-06-03 18:00:00 &  0.3054990 & 3.462322 & 3.1568228 & 6.619145 & 19.55193 & 0.5091650 & -1.105446e-04 & 1.379544e-05\\\\\n",
       "\t9192 & 2016-06-03 18:15:00 &  0.5379013 & 3.782747 & 3.2448456 & 7.027593 & 20.40042 & 0.5138497 & -5.529062e-04 & 1.252105e-04\\\\\n",
       "\t9193 & 2016-06-03 18:30:00 &  1.0357309 & 3.031873 & 1.9961419 & 5.028015 & 25.35427 & 0.2777627 &  1.106057e-04 & 6.438303e-05\\\\\n",
       "\t9194 & 2016-06-03 18:45:00 &  0.2688172 & 1.881720 & 1.6129032 & 3.494624 & 20.96774 & 0.2688172 &  1.761129e-03 & 1.508306e-05\\\\\n",
       "\t9197 & 2016-06-03 19:30:00 &  0.4780115 & 3.441683 & 2.9636711 & 6.405354 & 18.92925 & 0.4780115 &  3.586553e-04 & 1.076465e-06\\\\\n",
       "\t9198 & 2016-06-03 19:45:00 &  1.7179653 & 3.205392 & 1.4874270 & 4.692819 & 23.18482 & 0.7909638 & -5.794302e-04 & 1.483143e-04\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1265 × 9\n",
       "\n",
       "| <!--/--> | date &lt;fct&gt; | tone &lt;dbl&gt; | positive &lt;dbl&gt; | negative &lt;dbl&gt; | polarity &lt;dbl&gt; | activ_den &lt;dbl&gt; | self_den &lt;dbl&gt; | fin_return &lt;dbl&gt; | weight &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|\n",
       "| 54 | 2016-02-29 13:45:00 |  0.9022556 | 2.406015 | 1.50375940 | 3.909774 | 20.45113 | 0.00000000 |  3.236863e-04 | 2.228867e-06 |\n",
       "| 55 | 2016-02-29 14:00:00 |  0.3456533 | 3.788557 | 3.44290364 | 7.231461 | 22.24363 | 0.86363555 |  3.044711e-03 | 1.067255e-04 |\n",
       "| 56 | 2016-02-29 14:15:00 |  1.1032072 | 2.711936 | 1.60872880 | 4.320665 | 21.05964 | 0.06702841 |  3.560728e-03 | 1.330447e-05 |\n",
       "| 57 | 2016-02-29 14:30:00 |  4.7190417 | 5.312533 | 0.59349119 | 5.906024 | 25.99383 | 1.32800871 |  8.355592e-04 | 4.031775e-04 |\n",
       "| 58 | 2016-02-29 14:45:00 | -2.5359256 | 1.606086 | 4.14201183 | 5.748098 | 20.96365 | 1.18343195 | -3.321365e-03 | 3.659334e-06 |\n",
       "| 60 | 2016-02-29 15:15:00 | -1.7043454 | 1.435621 | 3.13996680 | 4.575588 | 20.80098 | 0.23696648 | -1.900743e-03 | 1.274351e-05 |\n",
       "| 61 | 2016-02-29 15:30:00 | -1.8556842 | 1.517347 | 3.37303111 | 4.890378 | 21.66980 | 0.27667246 | -6.469331e-04 | 3.556666e-04 |\n",
       "| 62 | 2016-02-29 15:45:00 |  0.7792567 | 2.959870 | 2.18061330 | 5.140483 | 22.19366 | 0.46813383 |  3.641381e-03 | 9.824652e-06 |\n",
       "| 63 | 2016-02-29 16:00:00 |  0.2886140 | 2.918574 | 2.62996036 | 5.548535 | 21.93399 | 1.30747378 | -2.179307e-04 | 3.424705e-05 |\n",
       "| 64 | 2016-02-29 16:15:00 |  1.1656561 | 2.420149 | 1.25449333 | 3.674643 | 22.31254 | 0.85043888 |  4.465283e-04 | 5.104687e-03 |\n",
       "| 65 | 2016-02-29 16:30:00 | -1.4251781 | 2.375297 | 3.80047506 | 6.175772 | 23.27791 | 0.00000000 | -6.734410e-04 | 1.562558e-07 |\n",
       "| 69 | 2016-02-29 17:30:00 | -3.4456558 | 1.600357 | 5.04601270 | 6.646370 | 22.08203 | 0.26847041 | -8.762026e-04 | 2.988712e-03 |\n",
       "| 70 | 2016-02-29 17:45:00 | -0.2047093 | 2.568016 | 2.77272505 | 5.340741 | 22.39894 | 0.42360760 | -1.155196e-03 | 3.258908e-05 |\n",
       "| 71 | 2016-02-29 18:00:00 | -1.0292699 | 2.283693 | 3.31296237 | 5.596655 | 19.17015 | 0.83628176 | -1.624522e-03 | 2.840858e-05 |\n",
       "| 72 | 2016-02-29 18:15:00 |  0.5594259 | 3.838818 | 3.27939184 | 7.118210 | 24.14970 | 1.28659797 | -3.418317e-03 | 5.132428e-05 |\n",
       "| 73 | 2016-02-29 18:30:00 |  1.7408315 | 3.083057 | 1.34222582 | 4.425283 | 24.80592 | 0.58025328 |  1.110892e-03 | 1.009724e-03 |\n",
       "| 74 | 2016-02-29 18:45:00 |  1.4150943 | 2.830189 | 1.41509434 | 4.245283 | 24.52830 | 0.70754717 | -3.354353e-03 | 5.737168e-06 |\n",
       "| 75 | 2016-02-29 19:00:00 | -0.0889748 | 2.046772 | 2.13574633 | 4.182518 | 23.97355 | 1.33402596 | -1.060665e-03 | 5.131520e-03 |\n",
       "| 76 | 2016-02-29 19:15:00 | -1.1107428 | 2.067217 | 3.17795971 | 5.245177 | 21.61734 | 0.05857083 | -2.142736e-03 | 9.825757e-06 |\n",
       "| 77 | 2016-02-29 19:30:00 | -2.1300136 | 1.975517 | 4.10553090 | 6.081048 | 22.12364 | 0.75119707 |  3.424256e-04 | 8.276189e-06 |\n",
       "| 78 | 2016-02-29 19:45:00 | -1.0318115 | 2.290277 | 3.32208823 | 5.612365 | 19.20755 | 0.83510869 | -3.964328e-05 | 3.992140e-04 |\n",
       "| 151 | 2016-03-01 14:00:00 |  0.8324155 | 1.437770 | 0.60535457 | 2.043125 | 20.37194 | 0.94594595 |  4.281516e-03 | 8.326803e-05 |\n",
       "| 152 | 2016-03-01 14:15:00 |  2.1452950 | 3.754266 | 1.60897123 | 5.363237 | 18.52755 | 0.73135056 |  2.098375e-03 | 4.098459e-07 |\n",
       "| 153 | 2016-03-01 14:30:00 | -0.2967359 | 2.225519 | 2.52225519 | 4.747774 | 24.62908 | 1.18694362 |  7.080553e-03 | 3.497907e-04 |\n",
       "| 155 | 2016-03-01 15:00:00 |  0.3438350 | 1.882116 | 1.53828112 | 3.420397 | 18.19764 | 0.19740311 | -2.102679e-03 | 6.458633e-05 |\n",
       "| 156 | 2016-03-01 15:15:00 |  2.4076293 | 3.434227 | 1.02659728 | 4.460824 | 19.17997 | 1.20192351 |  1.809629e-03 | 5.154214e-05 |\n",
       "| 157 | 2016-03-01 15:30:00 | -0.2976190 | 1.190476 | 1.48809524 | 2.678571 | 18.45238 | 1.19047619 |  2.813963e-03 | 1.674573e-06 |\n",
       "| 158 | 2016-03-01 15:45:00 |  4.1280723 | 4.150654 | 0.02258215 | 4.173237 | 26.94541 | 2.98243777 |  3.041306e-03 | 1.354039e-04 |\n",
       "| 159 | 2016-03-01 16:00:00 |  2.5646237 | 3.597666 | 1.03304271 | 4.630709 | 25.44714 | 2.05505380 |  2.734541e-03 | 2.746101e-05 |\n",
       "| 160 | 2016-03-01 16:15:00 |  1.0487364 | 1.671060 | 0.62232388 | 2.293384 | 22.18780 | 0.41454594 | -1.171782e-03 | 2.079547e-04 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 9082 | 2016-06-02 14:45:00 | -1.9882849 | 2.496322 | 4.4846065 | 6.980928 | 22.51924 | 1.0579480 |  1.819692e-03 | 3.520374e-03 |\n",
       "| 9083 | 2016-06-02 15:00:00 |  1.5845773 | 2.605657 | 1.0210797 | 3.626737 | 26.78812 | 1.8411905 | -7.744948e-04 | 1.299813e-04 |\n",
       "| 9084 | 2016-06-02 15:15:00 | -0.4991681 | 2.273988 | 2.7731559 | 5.047144 | 22.68441 | 0.6655574 |  4.867364e-04 | 6.445534e-04 |\n",
       "| 9085 | 2016-06-02 15:30:00 |  0.4489683 | 3.497895 | 3.0489271 | 6.546822 | 24.12478 | 3.4076244 |  2.664504e-03 | 3.003542e-03 |\n",
       "| 9088 | 2016-06-02 16:15:00 |  0.5899705 | 2.064897 | 1.4749263 | 3.539823 | 24.77876 | 0.5899705 | -1.134011e-03 | 3.721735e-05 |\n",
       "| 9089 | 2016-06-02 16:30:00 | -2.6652452 | 1.492537 | 4.1577825 | 5.650320 | 20.14925 | 0.0000000 |  6.344830e-04 | 1.145675e-03 |\n",
       "| 9092 | 2016-06-02 17:15:00 | -2.0695519 | 1.401146 | 3.4706979 | 4.871844 | 22.07021 | 0.6061744 |  1.038654e-03 | 6.472343e-04 |\n",
       "| 9095 | 2016-06-02 18:00:00 | -2.5637980 | 1.068517 | 3.6323148 | 4.700832 | 22.57222 | 0.3286605 | -3.093376e-04 | 9.365468e-03 |\n",
       "| 9096 | 2016-06-02 18:15:00 | -2.6143750 | 1.185144 | 3.7995189 | 4.984663 | 23.64676 | 0.7279446 |  9.980985e-04 | 2.810801e-04 |\n",
       "| 9097 | 2016-06-02 18:30:00 | -2.6304720 | 1.039555 | 3.6700272 | 4.709582 | 22.55767 | 0.3331398 |  9.805619e-04 | 5.488089e-04 |\n",
       "| 9099 | 2016-06-02 19:00:00 | -1.7055663 | 2.053103 | 3.7586690 | 5.811772 | 22.82752 | 0.2582886 |  1.047886e-03 | 3.769268e-03 |\n",
       "| 9100 | 2016-06-02 19:15:00 |  0.6319049 | 2.471373 | 1.8394684 | 4.310842 | 23.34993 | 0.8460192 | -1.102521e-04 | 1.611637e-04 |\n",
       "| 9101 | 2016-06-02 19:30:00 |  2.2727273 | 4.261364 | 1.9886364 | 6.250000 | 22.72727 | 1.4204545 |  4.271591e-04 | 3.050196e-05 |\n",
       "| 9102 | 2016-06-02 19:45:00 |  0.4791361 | 2.659365 | 2.1802293 | 4.839595 | 21.73432 | 0.8900456 |  5.550341e-04 | 3.636684e-04 |\n",
       "| 9176 | 2016-06-03 14:15:00 |  2.3338407 | 3.044140 | 0.7102993 | 3.754439 | 17.14866 | 0.8625063 | -6.672072e-03 | 2.583215e-06 |\n",
       "| 9179 | 2016-06-03 15:00:00 | -0.4435407 | 1.211850 | 1.6553911 | 2.867242 | 21.54125 | 1.1280309 |  1.011284e-03 | 3.861201e-05 |\n",
       "| 9180 | 2016-06-03 15:15:00 |  1.8095238 | 3.238095 | 1.4285714 | 4.666667 | 23.04762 | 1.8095238 | -1.551978e-03 | 1.236814e-06 |\n",
       "| 9181 | 2016-06-03 15:30:00 |  0.5604081 | 1.879578 | 1.3191698 | 3.198748 | 21.41277 | 0.6994322 |  1.109355e-04 | 3.517427e-04 |\n",
       "| 9182 | 2016-06-03 15:45:00 |  0.6488252 | 2.098174 | 1.4493487 | 3.547523 | 22.10613 | 0.7455359 |  2.257634e-03 | 4.007891e-05 |\n",
       "| 9184 | 2016-06-03 16:15:00 |  1.6837041 | 3.307276 | 1.6235719 | 4.930848 | 26.81900 | 3.7282020 |  1.243180e-03 | 1.518452e-04 |\n",
       "| 9186 | 2016-06-03 16:45:00 | -1.6759777 | 1.675978 | 3.3519553 | 5.027933 | 20.94972 | 0.2793296 | -9.662303e-05 | 1.200138e-05 |\n",
       "| 9187 | 2016-06-03 17:00:00 |  1.8583683 | 3.150898 | 1.2925295 | 4.443427 | 22.88999 | 3.8550764 |  1.104256e-04 | 6.936105e-04 |\n",
       "| 9189 | 2016-06-03 17:30:00 |  0.7518797 | 1.879699 | 1.1278195 | 3.007519 | 19.92481 | 1.5037594 | -1.103936e-03 | 3.639941e-05 |\n",
       "| 9190 | 2016-06-03 17:45:00 |  0.3022356 | 3.428692 | 3.1264568 | 6.555149 | 20.48614 | 0.5154711 | -7.596633e-04 | 2.147879e-04 |\n",
       "| 9191 | 2016-06-03 18:00:00 |  0.3054990 | 3.462322 | 3.1568228 | 6.619145 | 19.55193 | 0.5091650 | -1.105446e-04 | 1.379544e-05 |\n",
       "| 9192 | 2016-06-03 18:15:00 |  0.5379013 | 3.782747 | 3.2448456 | 7.027593 | 20.40042 | 0.5138497 | -5.529062e-04 | 1.252105e-04 |\n",
       "| 9193 | 2016-06-03 18:30:00 |  1.0357309 | 3.031873 | 1.9961419 | 5.028015 | 25.35427 | 0.2777627 |  1.106057e-04 | 6.438303e-05 |\n",
       "| 9194 | 2016-06-03 18:45:00 |  0.2688172 | 1.881720 | 1.6129032 | 3.494624 | 20.96774 | 0.2688172 |  1.761129e-03 | 1.508306e-05 |\n",
       "| 9197 | 2016-06-03 19:30:00 |  0.4780115 | 3.441683 | 2.9636711 | 6.405354 | 18.92925 | 0.4780115 |  3.586553e-04 | 1.076465e-06 |\n",
       "| 9198 | 2016-06-03 19:45:00 |  1.7179653 | 3.205392 | 1.4874270 | 4.692819 | 23.18482 | 0.7909638 | -5.794302e-04 | 1.483143e-04 |\n",
       "\n"
      ],
      "text/plain": [
       "     date                tone       positive negative   polarity activ_den\n",
       "54   2016-02-29 13:45:00  0.9022556 2.406015 1.50375940 3.909774 20.45113 \n",
       "55   2016-02-29 14:00:00  0.3456533 3.788557 3.44290364 7.231461 22.24363 \n",
       "56   2016-02-29 14:15:00  1.1032072 2.711936 1.60872880 4.320665 21.05964 \n",
       "57   2016-02-29 14:30:00  4.7190417 5.312533 0.59349119 5.906024 25.99383 \n",
       "58   2016-02-29 14:45:00 -2.5359256 1.606086 4.14201183 5.748098 20.96365 \n",
       "60   2016-02-29 15:15:00 -1.7043454 1.435621 3.13996680 4.575588 20.80098 \n",
       "61   2016-02-29 15:30:00 -1.8556842 1.517347 3.37303111 4.890378 21.66980 \n",
       "62   2016-02-29 15:45:00  0.7792567 2.959870 2.18061330 5.140483 22.19366 \n",
       "63   2016-02-29 16:00:00  0.2886140 2.918574 2.62996036 5.548535 21.93399 \n",
       "64   2016-02-29 16:15:00  1.1656561 2.420149 1.25449333 3.674643 22.31254 \n",
       "65   2016-02-29 16:30:00 -1.4251781 2.375297 3.80047506 6.175772 23.27791 \n",
       "69   2016-02-29 17:30:00 -3.4456558 1.600357 5.04601270 6.646370 22.08203 \n",
       "70   2016-02-29 17:45:00 -0.2047093 2.568016 2.77272505 5.340741 22.39894 \n",
       "71   2016-02-29 18:00:00 -1.0292699 2.283693 3.31296237 5.596655 19.17015 \n",
       "72   2016-02-29 18:15:00  0.5594259 3.838818 3.27939184 7.118210 24.14970 \n",
       "73   2016-02-29 18:30:00  1.7408315 3.083057 1.34222582 4.425283 24.80592 \n",
       "74   2016-02-29 18:45:00  1.4150943 2.830189 1.41509434 4.245283 24.52830 \n",
       "75   2016-02-29 19:00:00 -0.0889748 2.046772 2.13574633 4.182518 23.97355 \n",
       "76   2016-02-29 19:15:00 -1.1107428 2.067217 3.17795971 5.245177 21.61734 \n",
       "77   2016-02-29 19:30:00 -2.1300136 1.975517 4.10553090 6.081048 22.12364 \n",
       "78   2016-02-29 19:45:00 -1.0318115 2.290277 3.32208823 5.612365 19.20755 \n",
       "151  2016-03-01 14:00:00  0.8324155 1.437770 0.60535457 2.043125 20.37194 \n",
       "152  2016-03-01 14:15:00  2.1452950 3.754266 1.60897123 5.363237 18.52755 \n",
       "153  2016-03-01 14:30:00 -0.2967359 2.225519 2.52225519 4.747774 24.62908 \n",
       "155  2016-03-01 15:00:00  0.3438350 1.882116 1.53828112 3.420397 18.19764 \n",
       "156  2016-03-01 15:15:00  2.4076293 3.434227 1.02659728 4.460824 19.17997 \n",
       "157  2016-03-01 15:30:00 -0.2976190 1.190476 1.48809524 2.678571 18.45238 \n",
       "158  2016-03-01 15:45:00  4.1280723 4.150654 0.02258215 4.173237 26.94541 \n",
       "159  2016-03-01 16:00:00  2.5646237 3.597666 1.03304271 4.630709 25.44714 \n",
       "160  2016-03-01 16:15:00  1.0487364 1.671060 0.62232388 2.293384 22.18780 \n",
       "⋮    ⋮                   ⋮          ⋮        ⋮          ⋮        ⋮        \n",
       "9082 2016-06-02 14:45:00 -1.9882849 2.496322 4.4846065  6.980928 22.51924 \n",
       "9083 2016-06-02 15:00:00  1.5845773 2.605657 1.0210797  3.626737 26.78812 \n",
       "9084 2016-06-02 15:15:00 -0.4991681 2.273988 2.7731559  5.047144 22.68441 \n",
       "9085 2016-06-02 15:30:00  0.4489683 3.497895 3.0489271  6.546822 24.12478 \n",
       "9088 2016-06-02 16:15:00  0.5899705 2.064897 1.4749263  3.539823 24.77876 \n",
       "9089 2016-06-02 16:30:00 -2.6652452 1.492537 4.1577825  5.650320 20.14925 \n",
       "9092 2016-06-02 17:15:00 -2.0695519 1.401146 3.4706979  4.871844 22.07021 \n",
       "9095 2016-06-02 18:00:00 -2.5637980 1.068517 3.6323148  4.700832 22.57222 \n",
       "9096 2016-06-02 18:15:00 -2.6143750 1.185144 3.7995189  4.984663 23.64676 \n",
       "9097 2016-06-02 18:30:00 -2.6304720 1.039555 3.6700272  4.709582 22.55767 \n",
       "9099 2016-06-02 19:00:00 -1.7055663 2.053103 3.7586690  5.811772 22.82752 \n",
       "9100 2016-06-02 19:15:00  0.6319049 2.471373 1.8394684  4.310842 23.34993 \n",
       "9101 2016-06-02 19:30:00  2.2727273 4.261364 1.9886364  6.250000 22.72727 \n",
       "9102 2016-06-02 19:45:00  0.4791361 2.659365 2.1802293  4.839595 21.73432 \n",
       "9176 2016-06-03 14:15:00  2.3338407 3.044140 0.7102993  3.754439 17.14866 \n",
       "9179 2016-06-03 15:00:00 -0.4435407 1.211850 1.6553911  2.867242 21.54125 \n",
       "9180 2016-06-03 15:15:00  1.8095238 3.238095 1.4285714  4.666667 23.04762 \n",
       "9181 2016-06-03 15:30:00  0.5604081 1.879578 1.3191698  3.198748 21.41277 \n",
       "9182 2016-06-03 15:45:00  0.6488252 2.098174 1.4493487  3.547523 22.10613 \n",
       "9184 2016-06-03 16:15:00  1.6837041 3.307276 1.6235719  4.930848 26.81900 \n",
       "9186 2016-06-03 16:45:00 -1.6759777 1.675978 3.3519553  5.027933 20.94972 \n",
       "9187 2016-06-03 17:00:00  1.8583683 3.150898 1.2925295  4.443427 22.88999 \n",
       "9189 2016-06-03 17:30:00  0.7518797 1.879699 1.1278195  3.007519 19.92481 \n",
       "9190 2016-06-03 17:45:00  0.3022356 3.428692 3.1264568  6.555149 20.48614 \n",
       "9191 2016-06-03 18:00:00  0.3054990 3.462322 3.1568228  6.619145 19.55193 \n",
       "9192 2016-06-03 18:15:00  0.5379013 3.782747 3.2448456  7.027593 20.40042 \n",
       "9193 2016-06-03 18:30:00  1.0357309 3.031873 1.9961419  5.028015 25.35427 \n",
       "9194 2016-06-03 18:45:00  0.2688172 1.881720 1.6129032  3.494624 20.96774 \n",
       "9197 2016-06-03 19:30:00  0.4780115 3.441683 2.9636711  6.405354 18.92925 \n",
       "9198 2016-06-03 19:45:00  1.7179653 3.205392 1.4874270  4.692819 23.18482 \n",
       "     self_den   fin_return    weight      \n",
       "54   0.00000000  3.236863e-04 2.228867e-06\n",
       "55   0.86363555  3.044711e-03 1.067255e-04\n",
       "56   0.06702841  3.560728e-03 1.330447e-05\n",
       "57   1.32800871  8.355592e-04 4.031775e-04\n",
       "58   1.18343195 -3.321365e-03 3.659334e-06\n",
       "60   0.23696648 -1.900743e-03 1.274351e-05\n",
       "61   0.27667246 -6.469331e-04 3.556666e-04\n",
       "62   0.46813383  3.641381e-03 9.824652e-06\n",
       "63   1.30747378 -2.179307e-04 3.424705e-05\n",
       "64   0.85043888  4.465283e-04 5.104687e-03\n",
       "65   0.00000000 -6.734410e-04 1.562558e-07\n",
       "69   0.26847041 -8.762026e-04 2.988712e-03\n",
       "70   0.42360760 -1.155196e-03 3.258908e-05\n",
       "71   0.83628176 -1.624522e-03 2.840858e-05\n",
       "72   1.28659797 -3.418317e-03 5.132428e-05\n",
       "73   0.58025328  1.110892e-03 1.009724e-03\n",
       "74   0.70754717 -3.354353e-03 5.737168e-06\n",
       "75   1.33402596 -1.060665e-03 5.131520e-03\n",
       "76   0.05857083 -2.142736e-03 9.825757e-06\n",
       "77   0.75119707  3.424256e-04 8.276189e-06\n",
       "78   0.83510869 -3.964328e-05 3.992140e-04\n",
       "151  0.94594595  4.281516e-03 8.326803e-05\n",
       "152  0.73135056  2.098375e-03 4.098459e-07\n",
       "153  1.18694362  7.080553e-03 3.497907e-04\n",
       "155  0.19740311 -2.102679e-03 6.458633e-05\n",
       "156  1.20192351  1.809629e-03 5.154214e-05\n",
       "157  1.19047619  2.813963e-03 1.674573e-06\n",
       "158  2.98243777  3.041306e-03 1.354039e-04\n",
       "159  2.05505380  2.734541e-03 2.746101e-05\n",
       "160  0.41454594 -1.171782e-03 2.079547e-04\n",
       "⋮    ⋮          ⋮             ⋮           \n",
       "9082 1.0579480   1.819692e-03 3.520374e-03\n",
       "9083 1.8411905  -7.744948e-04 1.299813e-04\n",
       "9084 0.6655574   4.867364e-04 6.445534e-04\n",
       "9085 3.4076244   2.664504e-03 3.003542e-03\n",
       "9088 0.5899705  -1.134011e-03 3.721735e-05\n",
       "9089 0.0000000   6.344830e-04 1.145675e-03\n",
       "9092 0.6061744   1.038654e-03 6.472343e-04\n",
       "9095 0.3286605  -3.093376e-04 9.365468e-03\n",
       "9096 0.7279446   9.980985e-04 2.810801e-04\n",
       "9097 0.3331398   9.805619e-04 5.488089e-04\n",
       "9099 0.2582886   1.047886e-03 3.769268e-03\n",
       "9100 0.8460192  -1.102521e-04 1.611637e-04\n",
       "9101 1.4204545   4.271591e-04 3.050196e-05\n",
       "9102 0.8900456   5.550341e-04 3.636684e-04\n",
       "9176 0.8625063  -6.672072e-03 2.583215e-06\n",
       "9179 1.1280309   1.011284e-03 3.861201e-05\n",
       "9180 1.8095238  -1.551978e-03 1.236814e-06\n",
       "9181 0.6994322   1.109355e-04 3.517427e-04\n",
       "9182 0.7455359   2.257634e-03 4.007891e-05\n",
       "9184 3.7282020   1.243180e-03 1.518452e-04\n",
       "9186 0.2793296  -9.662303e-05 1.200138e-05\n",
       "9187 3.8550764   1.104256e-04 6.936105e-04\n",
       "9189 1.5037594  -1.103936e-03 3.639941e-05\n",
       "9190 0.5154711  -7.596633e-04 2.147879e-04\n",
       "9191 0.5091650  -1.105446e-04 1.379544e-05\n",
       "9192 0.5138497  -5.529062e-04 1.252105e-04\n",
       "9193 0.2777627   1.106057e-04 6.438303e-05\n",
       "9194 0.2688172   1.761129e-03 1.508306e-05\n",
       "9197 0.4780115   3.586553e-04 1.076465e-06\n",
       "9198 0.7909638  -5.794302e-04 1.483143e-04"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "f_return <- ts(data$fin_return)\n",
    "tone <- ts(data$tone)\n",
    "polarity <- ts(data$polarity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "VAR_data <- window(ts.union(tone, polarity, f_return))\n",
    "VAR_est <- VAR(y = VAR_data, p = 8)\n",
    "#summary(VAR_est)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "% Error: Unrecognized object type.\n"
     ]
    }
   ],
   "source": [
    "stargazer(summary(VAR_est))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# APARCH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(\"vars\")\n",
    "library(\"tidyr\")\n",
    "library(\"xts\", quietly=TRUE, warn.conflicts=FALSE);\n",
    "library(\"quantreg\")\n",
    "library(\"rugarch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ap <- available.packages()\n",
    "idx <- 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "all = read.csv(\"//home/ostapkharysh/Documents/bt_data/DescriptiveFebruary29June05_2016/ET/AMZN/PR.csv\", header=TRUE);\n",
    "date = as.POSIXct(all[,idx]);\n",
    "all.xts = xts(all[-idx], order.by = date);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "all.xts = all[,c(\"tone\", \"polarity\", \"positive\", \"negative\", \"fin_return\", \"date\")]\n",
    "all.raw.clean = na.omit(all.xts);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 1265 × 6</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>tone</th><th scope=col>polarity</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>fin_return</th><th scope=col>date</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>54</th><td> 0.9022556</td><td>3.909774</td><td>2.406015</td><td>1.50375940</td><td> 3.236863e-04</td><td>2016-02-29 13:45:00</td></tr>\n",
       "\t<tr><th scope=row>55</th><td> 0.3456533</td><td>7.231461</td><td>3.788557</td><td>3.44290364</td><td> 3.044711e-03</td><td>2016-02-29 14:00:00</td></tr>\n",
       "\t<tr><th scope=row>56</th><td> 1.1032072</td><td>4.320665</td><td>2.711936</td><td>1.60872880</td><td> 3.560728e-03</td><td>2016-02-29 14:15:00</td></tr>\n",
       "\t<tr><th scope=row>57</th><td> 4.7190417</td><td>5.906024</td><td>5.312533</td><td>0.59349119</td><td> 8.355592e-04</td><td>2016-02-29 14:30:00</td></tr>\n",
       "\t<tr><th scope=row>58</th><td>-2.5359256</td><td>5.748098</td><td>1.606086</td><td>4.14201183</td><td>-3.321365e-03</td><td>2016-02-29 14:45:00</td></tr>\n",
       "\t<tr><th scope=row>60</th><td>-1.7043454</td><td>4.575588</td><td>1.435621</td><td>3.13996680</td><td>-1.900743e-03</td><td>2016-02-29 15:15:00</td></tr>\n",
       "\t<tr><th scope=row>61</th><td>-1.8556842</td><td>4.890378</td><td>1.517347</td><td>3.37303111</td><td>-6.469331e-04</td><td>2016-02-29 15:30:00</td></tr>\n",
       "\t<tr><th scope=row>62</th><td> 0.7792567</td><td>5.140483</td><td>2.959870</td><td>2.18061330</td><td> 3.641381e-03</td><td>2016-02-29 15:45:00</td></tr>\n",
       "\t<tr><th scope=row>63</th><td> 0.2886140</td><td>5.548535</td><td>2.918574</td><td>2.62996036</td><td>-2.179307e-04</td><td>2016-02-29 16:00:00</td></tr>\n",
       "\t<tr><th scope=row>64</th><td> 1.1656561</td><td>3.674643</td><td>2.420149</td><td>1.25449333</td><td> 4.465283e-04</td><td>2016-02-29 16:15:00</td></tr>\n",
       "\t<tr><th scope=row>65</th><td>-1.4251781</td><td>6.175772</td><td>2.375297</td><td>3.80047506</td><td>-6.734410e-04</td><td>2016-02-29 16:30:00</td></tr>\n",
       "\t<tr><th scope=row>69</th><td>-3.4456558</td><td>6.646370</td><td>1.600357</td><td>5.04601270</td><td>-8.762026e-04</td><td>2016-02-29 17:30:00</td></tr>\n",
       "\t<tr><th scope=row>70</th><td>-0.2047093</td><td>5.340741</td><td>2.568016</td><td>2.77272505</td><td>-1.155196e-03</td><td>2016-02-29 17:45:00</td></tr>\n",
       "\t<tr><th scope=row>71</th><td>-1.0292699</td><td>5.596655</td><td>2.283693</td><td>3.31296237</td><td>-1.624522e-03</td><td>2016-02-29 18:00:00</td></tr>\n",
       "\t<tr><th scope=row>72</th><td> 0.5594259</td><td>7.118210</td><td>3.838818</td><td>3.27939184</td><td>-3.418317e-03</td><td>2016-02-29 18:15:00</td></tr>\n",
       "\t<tr><th scope=row>73</th><td> 1.7408315</td><td>4.425283</td><td>3.083057</td><td>1.34222582</td><td> 1.110892e-03</td><td>2016-02-29 18:30:00</td></tr>\n",
       "\t<tr><th scope=row>74</th><td> 1.4150943</td><td>4.245283</td><td>2.830189</td><td>1.41509434</td><td>-3.354353e-03</td><td>2016-02-29 18:45:00</td></tr>\n",
       "\t<tr><th scope=row>75</th><td>-0.0889748</td><td>4.182518</td><td>2.046772</td><td>2.13574633</td><td>-1.060665e-03</td><td>2016-02-29 19:00:00</td></tr>\n",
       "\t<tr><th scope=row>76</th><td>-1.1107428</td><td>5.245177</td><td>2.067217</td><td>3.17795971</td><td>-2.142736e-03</td><td>2016-02-29 19:15:00</td></tr>\n",
       "\t<tr><th scope=row>77</th><td>-2.1300136</td><td>6.081048</td><td>1.975517</td><td>4.10553090</td><td> 3.424256e-04</td><td>2016-02-29 19:30:00</td></tr>\n",
       "\t<tr><th scope=row>78</th><td>-1.0318115</td><td>5.612365</td><td>2.290277</td><td>3.32208823</td><td>-3.964328e-05</td><td>2016-02-29 19:45:00</td></tr>\n",
       "\t<tr><th scope=row>151</th><td> 0.8324155</td><td>2.043125</td><td>1.437770</td><td>0.60535457</td><td> 4.281516e-03</td><td>2016-03-01 14:00:00</td></tr>\n",
       "\t<tr><th scope=row>152</th><td> 2.1452950</td><td>5.363237</td><td>3.754266</td><td>1.60897123</td><td> 2.098375e-03</td><td>2016-03-01 14:15:00</td></tr>\n",
       "\t<tr><th scope=row>153</th><td>-0.2967359</td><td>4.747774</td><td>2.225519</td><td>2.52225519</td><td> 7.080553e-03</td><td>2016-03-01 14:30:00</td></tr>\n",
       "\t<tr><th scope=row>155</th><td> 0.3438350</td><td>3.420397</td><td>1.882116</td><td>1.53828112</td><td>-2.102679e-03</td><td>2016-03-01 15:00:00</td></tr>\n",
       "\t<tr><th scope=row>156</th><td> 2.4076293</td><td>4.460824</td><td>3.434227</td><td>1.02659728</td><td> 1.809629e-03</td><td>2016-03-01 15:15:00</td></tr>\n",
       "\t<tr><th scope=row>157</th><td>-0.2976190</td><td>2.678571</td><td>1.190476</td><td>1.48809524</td><td> 2.813963e-03</td><td>2016-03-01 15:30:00</td></tr>\n",
       "\t<tr><th scope=row>158</th><td> 4.1280723</td><td>4.173237</td><td>4.150654</td><td>0.02258215</td><td> 3.041306e-03</td><td>2016-03-01 15:45:00</td></tr>\n",
       "\t<tr><th scope=row>159</th><td> 2.5646237</td><td>4.630709</td><td>3.597666</td><td>1.03304271</td><td> 2.734541e-03</td><td>2016-03-01 16:00:00</td></tr>\n",
       "\t<tr><th scope=row>160</th><td> 1.0487364</td><td>2.293384</td><td>1.671060</td><td>0.62232388</td><td>-1.171782e-03</td><td>2016-03-01 16:15:00</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>9082</th><td>-1.9882849</td><td>6.980928</td><td>2.496322</td><td>4.4846065</td><td> 1.819692e-03</td><td>2016-06-02 14:45:00</td></tr>\n",
       "\t<tr><th scope=row>9083</th><td> 1.5845773</td><td>3.626737</td><td>2.605657</td><td>1.0210797</td><td>-7.744948e-04</td><td>2016-06-02 15:00:00</td></tr>\n",
       "\t<tr><th scope=row>9084</th><td>-0.4991681</td><td>5.047144</td><td>2.273988</td><td>2.7731559</td><td> 4.867364e-04</td><td>2016-06-02 15:15:00</td></tr>\n",
       "\t<tr><th scope=row>9085</th><td> 0.4489683</td><td>6.546822</td><td>3.497895</td><td>3.0489271</td><td> 2.664504e-03</td><td>2016-06-02 15:30:00</td></tr>\n",
       "\t<tr><th scope=row>9088</th><td> 0.5899705</td><td>3.539823</td><td>2.064897</td><td>1.4749263</td><td>-1.134011e-03</td><td>2016-06-02 16:15:00</td></tr>\n",
       "\t<tr><th scope=row>9089</th><td>-2.6652452</td><td>5.650320</td><td>1.492537</td><td>4.1577825</td><td> 6.344830e-04</td><td>2016-06-02 16:30:00</td></tr>\n",
       "\t<tr><th scope=row>9092</th><td>-2.0695519</td><td>4.871844</td><td>1.401146</td><td>3.4706979</td><td> 1.038654e-03</td><td>2016-06-02 17:15:00</td></tr>\n",
       "\t<tr><th scope=row>9095</th><td>-2.5637980</td><td>4.700832</td><td>1.068517</td><td>3.6323148</td><td>-3.093376e-04</td><td>2016-06-02 18:00:00</td></tr>\n",
       "\t<tr><th scope=row>9096</th><td>-2.6143750</td><td>4.984663</td><td>1.185144</td><td>3.7995189</td><td> 9.980985e-04</td><td>2016-06-02 18:15:00</td></tr>\n",
       "\t<tr><th scope=row>9097</th><td>-2.6304720</td><td>4.709582</td><td>1.039555</td><td>3.6700272</td><td> 9.805619e-04</td><td>2016-06-02 18:30:00</td></tr>\n",
       "\t<tr><th scope=row>9099</th><td>-1.7055663</td><td>5.811772</td><td>2.053103</td><td>3.7586690</td><td> 1.047886e-03</td><td>2016-06-02 19:00:00</td></tr>\n",
       "\t<tr><th scope=row>9100</th><td> 0.6319049</td><td>4.310842</td><td>2.471373</td><td>1.8394684</td><td>-1.102521e-04</td><td>2016-06-02 19:15:00</td></tr>\n",
       "\t<tr><th scope=row>9101</th><td> 2.2727273</td><td>6.250000</td><td>4.261364</td><td>1.9886364</td><td> 4.271591e-04</td><td>2016-06-02 19:30:00</td></tr>\n",
       "\t<tr><th scope=row>9102</th><td> 0.4791361</td><td>4.839595</td><td>2.659365</td><td>2.1802293</td><td> 5.550341e-04</td><td>2016-06-02 19:45:00</td></tr>\n",
       "\t<tr><th scope=row>9176</th><td> 2.3338407</td><td>3.754439</td><td>3.044140</td><td>0.7102993</td><td>-6.672072e-03</td><td>2016-06-03 14:15:00</td></tr>\n",
       "\t<tr><th scope=row>9179</th><td>-0.4435407</td><td>2.867242</td><td>1.211850</td><td>1.6553911</td><td> 1.011284e-03</td><td>2016-06-03 15:00:00</td></tr>\n",
       "\t<tr><th scope=row>9180</th><td> 1.8095238</td><td>4.666667</td><td>3.238095</td><td>1.4285714</td><td>-1.551978e-03</td><td>2016-06-03 15:15:00</td></tr>\n",
       "\t<tr><th scope=row>9181</th><td> 0.5604081</td><td>3.198748</td><td>1.879578</td><td>1.3191698</td><td> 1.109355e-04</td><td>2016-06-03 15:30:00</td></tr>\n",
       "\t<tr><th scope=row>9182</th><td> 0.6488252</td><td>3.547523</td><td>2.098174</td><td>1.4493487</td><td> 2.257634e-03</td><td>2016-06-03 15:45:00</td></tr>\n",
       "\t<tr><th scope=row>9184</th><td> 1.6837041</td><td>4.930848</td><td>3.307276</td><td>1.6235719</td><td> 1.243180e-03</td><td>2016-06-03 16:15:00</td></tr>\n",
       "\t<tr><th scope=row>9186</th><td>-1.6759777</td><td>5.027933</td><td>1.675978</td><td>3.3519553</td><td>-9.662303e-05</td><td>2016-06-03 16:45:00</td></tr>\n",
       "\t<tr><th scope=row>9187</th><td> 1.8583683</td><td>4.443427</td><td>3.150898</td><td>1.2925295</td><td> 1.104256e-04</td><td>2016-06-03 17:00:00</td></tr>\n",
       "\t<tr><th scope=row>9189</th><td> 0.7518797</td><td>3.007519</td><td>1.879699</td><td>1.1278195</td><td>-1.103936e-03</td><td>2016-06-03 17:30:00</td></tr>\n",
       "\t<tr><th scope=row>9190</th><td> 0.3022356</td><td>6.555149</td><td>3.428692</td><td>3.1264568</td><td>-7.596633e-04</td><td>2016-06-03 17:45:00</td></tr>\n",
       "\t<tr><th scope=row>9191</th><td> 0.3054990</td><td>6.619145</td><td>3.462322</td><td>3.1568228</td><td>-1.105446e-04</td><td>2016-06-03 18:00:00</td></tr>\n",
       "\t<tr><th scope=row>9192</th><td> 0.5379013</td><td>7.027593</td><td>3.782747</td><td>3.2448456</td><td>-5.529062e-04</td><td>2016-06-03 18:15:00</td></tr>\n",
       "\t<tr><th scope=row>9193</th><td> 1.0357309</td><td>5.028015</td><td>3.031873</td><td>1.9961419</td><td> 1.106057e-04</td><td>2016-06-03 18:30:00</td></tr>\n",
       "\t<tr><th scope=row>9194</th><td> 0.2688172</td><td>3.494624</td><td>1.881720</td><td>1.6129032</td><td> 1.761129e-03</td><td>2016-06-03 18:45:00</td></tr>\n",
       "\t<tr><th scope=row>9197</th><td> 0.4780115</td><td>6.405354</td><td>3.441683</td><td>2.9636711</td><td> 3.586553e-04</td><td>2016-06-03 19:30:00</td></tr>\n",
       "\t<tr><th scope=row>9198</th><td> 1.7179653</td><td>4.692819</td><td>3.205392</td><td>1.4874270</td><td>-5.794302e-04</td><td>2016-06-03 19:45:00</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1265 × 6\n",
       "\\begin{tabular}{r|llllll}\n",
       "  & tone & polarity & positive & negative & fin\\_return & date\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <fct>\\\\\n",
       "\\hline\n",
       "\t54 &  0.9022556 & 3.909774 & 2.406015 & 1.50375940 &  3.236863e-04 & 2016-02-29 13:45:00\\\\\n",
       "\t55 &  0.3456533 & 7.231461 & 3.788557 & 3.44290364 &  3.044711e-03 & 2016-02-29 14:00:00\\\\\n",
       "\t56 &  1.1032072 & 4.320665 & 2.711936 & 1.60872880 &  3.560728e-03 & 2016-02-29 14:15:00\\\\\n",
       "\t57 &  4.7190417 & 5.906024 & 5.312533 & 0.59349119 &  8.355592e-04 & 2016-02-29 14:30:00\\\\\n",
       "\t58 & -2.5359256 & 5.748098 & 1.606086 & 4.14201183 & -3.321365e-03 & 2016-02-29 14:45:00\\\\\n",
       "\t60 & -1.7043454 & 4.575588 & 1.435621 & 3.13996680 & -1.900743e-03 & 2016-02-29 15:15:00\\\\\n",
       "\t61 & -1.8556842 & 4.890378 & 1.517347 & 3.37303111 & -6.469331e-04 & 2016-02-29 15:30:00\\\\\n",
       "\t62 &  0.7792567 & 5.140483 & 2.959870 & 2.18061330 &  3.641381e-03 & 2016-02-29 15:45:00\\\\\n",
       "\t63 &  0.2886140 & 5.548535 & 2.918574 & 2.62996036 & -2.179307e-04 & 2016-02-29 16:00:00\\\\\n",
       "\t64 &  1.1656561 & 3.674643 & 2.420149 & 1.25449333 &  4.465283e-04 & 2016-02-29 16:15:00\\\\\n",
       "\t65 & -1.4251781 & 6.175772 & 2.375297 & 3.80047506 & -6.734410e-04 & 2016-02-29 16:30:00\\\\\n",
       "\t69 & -3.4456558 & 6.646370 & 1.600357 & 5.04601270 & -8.762026e-04 & 2016-02-29 17:30:00\\\\\n",
       "\t70 & -0.2047093 & 5.340741 & 2.568016 & 2.77272505 & -1.155196e-03 & 2016-02-29 17:45:00\\\\\n",
       "\t71 & -1.0292699 & 5.596655 & 2.283693 & 3.31296237 & -1.624522e-03 & 2016-02-29 18:00:00\\\\\n",
       "\t72 &  0.5594259 & 7.118210 & 3.838818 & 3.27939184 & -3.418317e-03 & 2016-02-29 18:15:00\\\\\n",
       "\t73 &  1.7408315 & 4.425283 & 3.083057 & 1.34222582 &  1.110892e-03 & 2016-02-29 18:30:00\\\\\n",
       "\t74 &  1.4150943 & 4.245283 & 2.830189 & 1.41509434 & -3.354353e-03 & 2016-02-29 18:45:00\\\\\n",
       "\t75 & -0.0889748 & 4.182518 & 2.046772 & 2.13574633 & -1.060665e-03 & 2016-02-29 19:00:00\\\\\n",
       "\t76 & -1.1107428 & 5.245177 & 2.067217 & 3.17795971 & -2.142736e-03 & 2016-02-29 19:15:00\\\\\n",
       "\t77 & -2.1300136 & 6.081048 & 1.975517 & 4.10553090 &  3.424256e-04 & 2016-02-29 19:30:00\\\\\n",
       "\t78 & -1.0318115 & 5.612365 & 2.290277 & 3.32208823 & -3.964328e-05 & 2016-02-29 19:45:00\\\\\n",
       "\t151 &  0.8324155 & 2.043125 & 1.437770 & 0.60535457 &  4.281516e-03 & 2016-03-01 14:00:00\\\\\n",
       "\t152 &  2.1452950 & 5.363237 & 3.754266 & 1.60897123 &  2.098375e-03 & 2016-03-01 14:15:00\\\\\n",
       "\t153 & -0.2967359 & 4.747774 & 2.225519 & 2.52225519 &  7.080553e-03 & 2016-03-01 14:30:00\\\\\n",
       "\t155 &  0.3438350 & 3.420397 & 1.882116 & 1.53828112 & -2.102679e-03 & 2016-03-01 15:00:00\\\\\n",
       "\t156 &  2.4076293 & 4.460824 & 3.434227 & 1.02659728 &  1.809629e-03 & 2016-03-01 15:15:00\\\\\n",
       "\t157 & -0.2976190 & 2.678571 & 1.190476 & 1.48809524 &  2.813963e-03 & 2016-03-01 15:30:00\\\\\n",
       "\t158 &  4.1280723 & 4.173237 & 4.150654 & 0.02258215 &  3.041306e-03 & 2016-03-01 15:45:00\\\\\n",
       "\t159 &  2.5646237 & 4.630709 & 3.597666 & 1.03304271 &  2.734541e-03 & 2016-03-01 16:00:00\\\\\n",
       "\t160 &  1.0487364 & 2.293384 & 1.671060 & 0.62232388 & -1.171782e-03 & 2016-03-01 16:15:00\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t9082 & -1.9882849 & 6.980928 & 2.496322 & 4.4846065 &  1.819692e-03 & 2016-06-02 14:45:00\\\\\n",
       "\t9083 &  1.5845773 & 3.626737 & 2.605657 & 1.0210797 & -7.744948e-04 & 2016-06-02 15:00:00\\\\\n",
       "\t9084 & -0.4991681 & 5.047144 & 2.273988 & 2.7731559 &  4.867364e-04 & 2016-06-02 15:15:00\\\\\n",
       "\t9085 &  0.4489683 & 6.546822 & 3.497895 & 3.0489271 &  2.664504e-03 & 2016-06-02 15:30:00\\\\\n",
       "\t9088 &  0.5899705 & 3.539823 & 2.064897 & 1.4749263 & -1.134011e-03 & 2016-06-02 16:15:00\\\\\n",
       "\t9089 & -2.6652452 & 5.650320 & 1.492537 & 4.1577825 &  6.344830e-04 & 2016-06-02 16:30:00\\\\\n",
       "\t9092 & -2.0695519 & 4.871844 & 1.401146 & 3.4706979 &  1.038654e-03 & 2016-06-02 17:15:00\\\\\n",
       "\t9095 & -2.5637980 & 4.700832 & 1.068517 & 3.6323148 & -3.093376e-04 & 2016-06-02 18:00:00\\\\\n",
       "\t9096 & -2.6143750 & 4.984663 & 1.185144 & 3.7995189 &  9.980985e-04 & 2016-06-02 18:15:00\\\\\n",
       "\t9097 & -2.6304720 & 4.709582 & 1.039555 & 3.6700272 &  9.805619e-04 & 2016-06-02 18:30:00\\\\\n",
       "\t9099 & -1.7055663 & 5.811772 & 2.053103 & 3.7586690 &  1.047886e-03 & 2016-06-02 19:00:00\\\\\n",
       "\t9100 &  0.6319049 & 4.310842 & 2.471373 & 1.8394684 & -1.102521e-04 & 2016-06-02 19:15:00\\\\\n",
       "\t9101 &  2.2727273 & 6.250000 & 4.261364 & 1.9886364 &  4.271591e-04 & 2016-06-02 19:30:00\\\\\n",
       "\t9102 &  0.4791361 & 4.839595 & 2.659365 & 2.1802293 &  5.550341e-04 & 2016-06-02 19:45:00\\\\\n",
       "\t9176 &  2.3338407 & 3.754439 & 3.044140 & 0.7102993 & -6.672072e-03 & 2016-06-03 14:15:00\\\\\n",
       "\t9179 & -0.4435407 & 2.867242 & 1.211850 & 1.6553911 &  1.011284e-03 & 2016-06-03 15:00:00\\\\\n",
       "\t9180 &  1.8095238 & 4.666667 & 3.238095 & 1.4285714 & -1.551978e-03 & 2016-06-03 15:15:00\\\\\n",
       "\t9181 &  0.5604081 & 3.198748 & 1.879578 & 1.3191698 &  1.109355e-04 & 2016-06-03 15:30:00\\\\\n",
       "\t9182 &  0.6488252 & 3.547523 & 2.098174 & 1.4493487 &  2.257634e-03 & 2016-06-03 15:45:00\\\\\n",
       "\t9184 &  1.6837041 & 4.930848 & 3.307276 & 1.6235719 &  1.243180e-03 & 2016-06-03 16:15:00\\\\\n",
       "\t9186 & -1.6759777 & 5.027933 & 1.675978 & 3.3519553 & -9.662303e-05 & 2016-06-03 16:45:00\\\\\n",
       "\t9187 &  1.8583683 & 4.443427 & 3.150898 & 1.2925295 &  1.104256e-04 & 2016-06-03 17:00:00\\\\\n",
       "\t9189 &  0.7518797 & 3.007519 & 1.879699 & 1.1278195 & -1.103936e-03 & 2016-06-03 17:30:00\\\\\n",
       "\t9190 &  0.3022356 & 6.555149 & 3.428692 & 3.1264568 & -7.596633e-04 & 2016-06-03 17:45:00\\\\\n",
       "\t9191 &  0.3054990 & 6.619145 & 3.462322 & 3.1568228 & -1.105446e-04 & 2016-06-03 18:00:00\\\\\n",
       "\t9192 &  0.5379013 & 7.027593 & 3.782747 & 3.2448456 & -5.529062e-04 & 2016-06-03 18:15:00\\\\\n",
       "\t9193 &  1.0357309 & 5.028015 & 3.031873 & 1.9961419 &  1.106057e-04 & 2016-06-03 18:30:00\\\\\n",
       "\t9194 &  0.2688172 & 3.494624 & 1.881720 & 1.6129032 &  1.761129e-03 & 2016-06-03 18:45:00\\\\\n",
       "\t9197 &  0.4780115 & 6.405354 & 3.441683 & 2.9636711 &  3.586553e-04 & 2016-06-03 19:30:00\\\\\n",
       "\t9198 &  1.7179653 & 4.692819 & 3.205392 & 1.4874270 & -5.794302e-04 & 2016-06-03 19:45:00\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1265 × 6\n",
       "\n",
       "| <!--/--> | tone &lt;dbl&gt; | polarity &lt;dbl&gt; | positive &lt;dbl&gt; | negative &lt;dbl&gt; | fin_return &lt;dbl&gt; | date &lt;fct&gt; |\n",
       "|---|---|---|---|---|---|---|\n",
       "| 54 |  0.9022556 | 3.909774 | 2.406015 | 1.50375940 |  3.236863e-04 | 2016-02-29 13:45:00 |\n",
       "| 55 |  0.3456533 | 7.231461 | 3.788557 | 3.44290364 |  3.044711e-03 | 2016-02-29 14:00:00 |\n",
       "| 56 |  1.1032072 | 4.320665 | 2.711936 | 1.60872880 |  3.560728e-03 | 2016-02-29 14:15:00 |\n",
       "| 57 |  4.7190417 | 5.906024 | 5.312533 | 0.59349119 |  8.355592e-04 | 2016-02-29 14:30:00 |\n",
       "| 58 | -2.5359256 | 5.748098 | 1.606086 | 4.14201183 | -3.321365e-03 | 2016-02-29 14:45:00 |\n",
       "| 60 | -1.7043454 | 4.575588 | 1.435621 | 3.13996680 | -1.900743e-03 | 2016-02-29 15:15:00 |\n",
       "| 61 | -1.8556842 | 4.890378 | 1.517347 | 3.37303111 | -6.469331e-04 | 2016-02-29 15:30:00 |\n",
       "| 62 |  0.7792567 | 5.140483 | 2.959870 | 2.18061330 |  3.641381e-03 | 2016-02-29 15:45:00 |\n",
       "| 63 |  0.2886140 | 5.548535 | 2.918574 | 2.62996036 | -2.179307e-04 | 2016-02-29 16:00:00 |\n",
       "| 64 |  1.1656561 | 3.674643 | 2.420149 | 1.25449333 |  4.465283e-04 | 2016-02-29 16:15:00 |\n",
       "| 65 | -1.4251781 | 6.175772 | 2.375297 | 3.80047506 | -6.734410e-04 | 2016-02-29 16:30:00 |\n",
       "| 69 | -3.4456558 | 6.646370 | 1.600357 | 5.04601270 | -8.762026e-04 | 2016-02-29 17:30:00 |\n",
       "| 70 | -0.2047093 | 5.340741 | 2.568016 | 2.77272505 | -1.155196e-03 | 2016-02-29 17:45:00 |\n",
       "| 71 | -1.0292699 | 5.596655 | 2.283693 | 3.31296237 | -1.624522e-03 | 2016-02-29 18:00:00 |\n",
       "| 72 |  0.5594259 | 7.118210 | 3.838818 | 3.27939184 | -3.418317e-03 | 2016-02-29 18:15:00 |\n",
       "| 73 |  1.7408315 | 4.425283 | 3.083057 | 1.34222582 |  1.110892e-03 | 2016-02-29 18:30:00 |\n",
       "| 74 |  1.4150943 | 4.245283 | 2.830189 | 1.41509434 | -3.354353e-03 | 2016-02-29 18:45:00 |\n",
       "| 75 | -0.0889748 | 4.182518 | 2.046772 | 2.13574633 | -1.060665e-03 | 2016-02-29 19:00:00 |\n",
       "| 76 | -1.1107428 | 5.245177 | 2.067217 | 3.17795971 | -2.142736e-03 | 2016-02-29 19:15:00 |\n",
       "| 77 | -2.1300136 | 6.081048 | 1.975517 | 4.10553090 |  3.424256e-04 | 2016-02-29 19:30:00 |\n",
       "| 78 | -1.0318115 | 5.612365 | 2.290277 | 3.32208823 | -3.964328e-05 | 2016-02-29 19:45:00 |\n",
       "| 151 |  0.8324155 | 2.043125 | 1.437770 | 0.60535457 |  4.281516e-03 | 2016-03-01 14:00:00 |\n",
       "| 152 |  2.1452950 | 5.363237 | 3.754266 | 1.60897123 |  2.098375e-03 | 2016-03-01 14:15:00 |\n",
       "| 153 | -0.2967359 | 4.747774 | 2.225519 | 2.52225519 |  7.080553e-03 | 2016-03-01 14:30:00 |\n",
       "| 155 |  0.3438350 | 3.420397 | 1.882116 | 1.53828112 | -2.102679e-03 | 2016-03-01 15:00:00 |\n",
       "| 156 |  2.4076293 | 4.460824 | 3.434227 | 1.02659728 |  1.809629e-03 | 2016-03-01 15:15:00 |\n",
       "| 157 | -0.2976190 | 2.678571 | 1.190476 | 1.48809524 |  2.813963e-03 | 2016-03-01 15:30:00 |\n",
       "| 158 |  4.1280723 | 4.173237 | 4.150654 | 0.02258215 |  3.041306e-03 | 2016-03-01 15:45:00 |\n",
       "| 159 |  2.5646237 | 4.630709 | 3.597666 | 1.03304271 |  2.734541e-03 | 2016-03-01 16:00:00 |\n",
       "| 160 |  1.0487364 | 2.293384 | 1.671060 | 0.62232388 | -1.171782e-03 | 2016-03-01 16:15:00 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 9082 | -1.9882849 | 6.980928 | 2.496322 | 4.4846065 |  1.819692e-03 | 2016-06-02 14:45:00 |\n",
       "| 9083 |  1.5845773 | 3.626737 | 2.605657 | 1.0210797 | -7.744948e-04 | 2016-06-02 15:00:00 |\n",
       "| 9084 | -0.4991681 | 5.047144 | 2.273988 | 2.7731559 |  4.867364e-04 | 2016-06-02 15:15:00 |\n",
       "| 9085 |  0.4489683 | 6.546822 | 3.497895 | 3.0489271 |  2.664504e-03 | 2016-06-02 15:30:00 |\n",
       "| 9088 |  0.5899705 | 3.539823 | 2.064897 | 1.4749263 | -1.134011e-03 | 2016-06-02 16:15:00 |\n",
       "| 9089 | -2.6652452 | 5.650320 | 1.492537 | 4.1577825 |  6.344830e-04 | 2016-06-02 16:30:00 |\n",
       "| 9092 | -2.0695519 | 4.871844 | 1.401146 | 3.4706979 |  1.038654e-03 | 2016-06-02 17:15:00 |\n",
       "| 9095 | -2.5637980 | 4.700832 | 1.068517 | 3.6323148 | -3.093376e-04 | 2016-06-02 18:00:00 |\n",
       "| 9096 | -2.6143750 | 4.984663 | 1.185144 | 3.7995189 |  9.980985e-04 | 2016-06-02 18:15:00 |\n",
       "| 9097 | -2.6304720 | 4.709582 | 1.039555 | 3.6700272 |  9.805619e-04 | 2016-06-02 18:30:00 |\n",
       "| 9099 | -1.7055663 | 5.811772 | 2.053103 | 3.7586690 |  1.047886e-03 | 2016-06-02 19:00:00 |\n",
       "| 9100 |  0.6319049 | 4.310842 | 2.471373 | 1.8394684 | -1.102521e-04 | 2016-06-02 19:15:00 |\n",
       "| 9101 |  2.2727273 | 6.250000 | 4.261364 | 1.9886364 |  4.271591e-04 | 2016-06-02 19:30:00 |\n",
       "| 9102 |  0.4791361 | 4.839595 | 2.659365 | 2.1802293 |  5.550341e-04 | 2016-06-02 19:45:00 |\n",
       "| 9176 |  2.3338407 | 3.754439 | 3.044140 | 0.7102993 | -6.672072e-03 | 2016-06-03 14:15:00 |\n",
       "| 9179 | -0.4435407 | 2.867242 | 1.211850 | 1.6553911 |  1.011284e-03 | 2016-06-03 15:00:00 |\n",
       "| 9180 |  1.8095238 | 4.666667 | 3.238095 | 1.4285714 | -1.551978e-03 | 2016-06-03 15:15:00 |\n",
       "| 9181 |  0.5604081 | 3.198748 | 1.879578 | 1.3191698 |  1.109355e-04 | 2016-06-03 15:30:00 |\n",
       "| 9182 |  0.6488252 | 3.547523 | 2.098174 | 1.4493487 |  2.257634e-03 | 2016-06-03 15:45:00 |\n",
       "| 9184 |  1.6837041 | 4.930848 | 3.307276 | 1.6235719 |  1.243180e-03 | 2016-06-03 16:15:00 |\n",
       "| 9186 | -1.6759777 | 5.027933 | 1.675978 | 3.3519553 | -9.662303e-05 | 2016-06-03 16:45:00 |\n",
       "| 9187 |  1.8583683 | 4.443427 | 3.150898 | 1.2925295 |  1.104256e-04 | 2016-06-03 17:00:00 |\n",
       "| 9189 |  0.7518797 | 3.007519 | 1.879699 | 1.1278195 | -1.103936e-03 | 2016-06-03 17:30:00 |\n",
       "| 9190 |  0.3022356 | 6.555149 | 3.428692 | 3.1264568 | -7.596633e-04 | 2016-06-03 17:45:00 |\n",
       "| 9191 |  0.3054990 | 6.619145 | 3.462322 | 3.1568228 | -1.105446e-04 | 2016-06-03 18:00:00 |\n",
       "| 9192 |  0.5379013 | 7.027593 | 3.782747 | 3.2448456 | -5.529062e-04 | 2016-06-03 18:15:00 |\n",
       "| 9193 |  1.0357309 | 5.028015 | 3.031873 | 1.9961419 |  1.106057e-04 | 2016-06-03 18:30:00 |\n",
       "| 9194 |  0.2688172 | 3.494624 | 1.881720 | 1.6129032 |  1.761129e-03 | 2016-06-03 18:45:00 |\n",
       "| 9197 |  0.4780115 | 6.405354 | 3.441683 | 2.9636711 |  3.586553e-04 | 2016-06-03 19:30:00 |\n",
       "| 9198 |  1.7179653 | 4.692819 | 3.205392 | 1.4874270 | -5.794302e-04 | 2016-06-03 19:45:00 |\n",
       "\n"
      ],
      "text/plain": [
       "     tone       polarity positive negative   fin_return    date               \n",
       "54    0.9022556 3.909774 2.406015 1.50375940  3.236863e-04 2016-02-29 13:45:00\n",
       "55    0.3456533 7.231461 3.788557 3.44290364  3.044711e-03 2016-02-29 14:00:00\n",
       "56    1.1032072 4.320665 2.711936 1.60872880  3.560728e-03 2016-02-29 14:15:00\n",
       "57    4.7190417 5.906024 5.312533 0.59349119  8.355592e-04 2016-02-29 14:30:00\n",
       "58   -2.5359256 5.748098 1.606086 4.14201183 -3.321365e-03 2016-02-29 14:45:00\n",
       "60   -1.7043454 4.575588 1.435621 3.13996680 -1.900743e-03 2016-02-29 15:15:00\n",
       "61   -1.8556842 4.890378 1.517347 3.37303111 -6.469331e-04 2016-02-29 15:30:00\n",
       "62    0.7792567 5.140483 2.959870 2.18061330  3.641381e-03 2016-02-29 15:45:00\n",
       "63    0.2886140 5.548535 2.918574 2.62996036 -2.179307e-04 2016-02-29 16:00:00\n",
       "64    1.1656561 3.674643 2.420149 1.25449333  4.465283e-04 2016-02-29 16:15:00\n",
       "65   -1.4251781 6.175772 2.375297 3.80047506 -6.734410e-04 2016-02-29 16:30:00\n",
       "69   -3.4456558 6.646370 1.600357 5.04601270 -8.762026e-04 2016-02-29 17:30:00\n",
       "70   -0.2047093 5.340741 2.568016 2.77272505 -1.155196e-03 2016-02-29 17:45:00\n",
       "71   -1.0292699 5.596655 2.283693 3.31296237 -1.624522e-03 2016-02-29 18:00:00\n",
       "72    0.5594259 7.118210 3.838818 3.27939184 -3.418317e-03 2016-02-29 18:15:00\n",
       "73    1.7408315 4.425283 3.083057 1.34222582  1.110892e-03 2016-02-29 18:30:00\n",
       "74    1.4150943 4.245283 2.830189 1.41509434 -3.354353e-03 2016-02-29 18:45:00\n",
       "75   -0.0889748 4.182518 2.046772 2.13574633 -1.060665e-03 2016-02-29 19:00:00\n",
       "76   -1.1107428 5.245177 2.067217 3.17795971 -2.142736e-03 2016-02-29 19:15:00\n",
       "77   -2.1300136 6.081048 1.975517 4.10553090  3.424256e-04 2016-02-29 19:30:00\n",
       "78   -1.0318115 5.612365 2.290277 3.32208823 -3.964328e-05 2016-02-29 19:45:00\n",
       "151   0.8324155 2.043125 1.437770 0.60535457  4.281516e-03 2016-03-01 14:00:00\n",
       "152   2.1452950 5.363237 3.754266 1.60897123  2.098375e-03 2016-03-01 14:15:00\n",
       "153  -0.2967359 4.747774 2.225519 2.52225519  7.080553e-03 2016-03-01 14:30:00\n",
       "155   0.3438350 3.420397 1.882116 1.53828112 -2.102679e-03 2016-03-01 15:00:00\n",
       "156   2.4076293 4.460824 3.434227 1.02659728  1.809629e-03 2016-03-01 15:15:00\n",
       "157  -0.2976190 2.678571 1.190476 1.48809524  2.813963e-03 2016-03-01 15:30:00\n",
       "158   4.1280723 4.173237 4.150654 0.02258215  3.041306e-03 2016-03-01 15:45:00\n",
       "159   2.5646237 4.630709 3.597666 1.03304271  2.734541e-03 2016-03-01 16:00:00\n",
       "160   1.0487364 2.293384 1.671060 0.62232388 -1.171782e-03 2016-03-01 16:15:00\n",
       "⋮    ⋮          ⋮        ⋮        ⋮          ⋮             ⋮                  \n",
       "9082 -1.9882849 6.980928 2.496322 4.4846065   1.819692e-03 2016-06-02 14:45:00\n",
       "9083  1.5845773 3.626737 2.605657 1.0210797  -7.744948e-04 2016-06-02 15:00:00\n",
       "9084 -0.4991681 5.047144 2.273988 2.7731559   4.867364e-04 2016-06-02 15:15:00\n",
       "9085  0.4489683 6.546822 3.497895 3.0489271   2.664504e-03 2016-06-02 15:30:00\n",
       "9088  0.5899705 3.539823 2.064897 1.4749263  -1.134011e-03 2016-06-02 16:15:00\n",
       "9089 -2.6652452 5.650320 1.492537 4.1577825   6.344830e-04 2016-06-02 16:30:00\n",
       "9092 -2.0695519 4.871844 1.401146 3.4706979   1.038654e-03 2016-06-02 17:15:00\n",
       "9095 -2.5637980 4.700832 1.068517 3.6323148  -3.093376e-04 2016-06-02 18:00:00\n",
       "9096 -2.6143750 4.984663 1.185144 3.7995189   9.980985e-04 2016-06-02 18:15:00\n",
       "9097 -2.6304720 4.709582 1.039555 3.6700272   9.805619e-04 2016-06-02 18:30:00\n",
       "9099 -1.7055663 5.811772 2.053103 3.7586690   1.047886e-03 2016-06-02 19:00:00\n",
       "9100  0.6319049 4.310842 2.471373 1.8394684  -1.102521e-04 2016-06-02 19:15:00\n",
       "9101  2.2727273 6.250000 4.261364 1.9886364   4.271591e-04 2016-06-02 19:30:00\n",
       "9102  0.4791361 4.839595 2.659365 2.1802293   5.550341e-04 2016-06-02 19:45:00\n",
       "9176  2.3338407 3.754439 3.044140 0.7102993  -6.672072e-03 2016-06-03 14:15:00\n",
       "9179 -0.4435407 2.867242 1.211850 1.6553911   1.011284e-03 2016-06-03 15:00:00\n",
       "9180  1.8095238 4.666667 3.238095 1.4285714  -1.551978e-03 2016-06-03 15:15:00\n",
       "9181  0.5604081 3.198748 1.879578 1.3191698   1.109355e-04 2016-06-03 15:30:00\n",
       "9182  0.6488252 3.547523 2.098174 1.4493487   2.257634e-03 2016-06-03 15:45:00\n",
       "9184  1.6837041 4.930848 3.307276 1.6235719   1.243180e-03 2016-06-03 16:15:00\n",
       "9186 -1.6759777 5.027933 1.675978 3.3519553  -9.662303e-05 2016-06-03 16:45:00\n",
       "9187  1.8583683 4.443427 3.150898 1.2925295   1.104256e-04 2016-06-03 17:00:00\n",
       "9189  0.7518797 3.007519 1.879699 1.1278195  -1.103936e-03 2016-06-03 17:30:00\n",
       "9190  0.3022356 6.555149 3.428692 3.1264568  -7.596633e-04 2016-06-03 17:45:00\n",
       "9191  0.3054990 6.619145 3.462322 3.1568228  -1.105446e-04 2016-06-03 18:00:00\n",
       "9192  0.5379013 7.027593 3.782747 3.2448456  -5.529062e-04 2016-06-03 18:15:00\n",
       "9193  1.0357309 5.028015 3.031873 1.9961419   1.106057e-04 2016-06-03 18:30:00\n",
       "9194  0.2688172 3.494624 1.881720 1.6129032   1.761129e-03 2016-06-03 18:45:00\n",
       "9197  0.4780115 6.405354 3.441683 2.9636711   3.586553e-04 2016-06-03 19:30:00\n",
       "9198  1.7179653 4.692819 3.205392 1.4874270  -5.794302e-04 2016-06-03 19:45:00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "all.raw.clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "all.raw = data.frame(coredata(all.raw.clean), ret.abs = abs(all.raw.clean[,5]));\n",
    "names(all.raw)[6] <- \"abs_return\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 5 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>tone</th><th scope=col>polarity</th><th scope=col>positive</th><th scope=col>negative</th><th scope=col>fin_return</th><th scope=col>abs_return</th><th scope=col>ret.abs</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>54</th><td> 0.9022556</td><td>3.909774</td><td>2.406015</td><td>1.5037594</td><td> 0.0003236863</td><td>2016-02-29 13:45:00</td><td>0.0003236863</td></tr>\n",
       "\t<tr><th scope=row>55</th><td> 0.3456533</td><td>7.231461</td><td>3.788557</td><td>3.4429036</td><td> 0.0030447107</td><td>2016-02-29 14:00:00</td><td>0.0030447107</td></tr>\n",
       "\t<tr><th scope=row>56</th><td> 1.1032072</td><td>4.320665</td><td>2.711936</td><td>1.6087288</td><td> 0.0035607284</td><td>2016-02-29 14:15:00</td><td>0.0035607284</td></tr>\n",
       "\t<tr><th scope=row>57</th><td> 4.7190417</td><td>5.906024</td><td>5.312533</td><td>0.5934912</td><td> 0.0008355592</td><td>2016-02-29 14:30:00</td><td>0.0008355592</td></tr>\n",
       "\t<tr><th scope=row>58</th><td>-2.5359256</td><td>5.748098</td><td>1.606086</td><td>4.1420118</td><td>-0.0033213654</td><td>2016-02-29 14:45:00</td><td>0.0033213654</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 5 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & tone & polarity & positive & negative & fin\\_return & abs\\_return & ret.abs\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\t54 &  0.9022556 & 3.909774 & 2.406015 & 1.5037594 &  0.0003236863 & 2016-02-29 13:45:00 & 0.0003236863\\\\\n",
       "\t55 &  0.3456533 & 7.231461 & 3.788557 & 3.4429036 &  0.0030447107 & 2016-02-29 14:00:00 & 0.0030447107\\\\\n",
       "\t56 &  1.1032072 & 4.320665 & 2.711936 & 1.6087288 &  0.0035607284 & 2016-02-29 14:15:00 & 0.0035607284\\\\\n",
       "\t57 &  4.7190417 & 5.906024 & 5.312533 & 0.5934912 &  0.0008355592 & 2016-02-29 14:30:00 & 0.0008355592\\\\\n",
       "\t58 & -2.5359256 & 5.748098 & 1.606086 & 4.1420118 & -0.0033213654 & 2016-02-29 14:45:00 & 0.0033213654\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 5 × 7\n",
       "\n",
       "| <!--/--> | tone &lt;dbl&gt; | polarity &lt;dbl&gt; | positive &lt;dbl&gt; | negative &lt;dbl&gt; | fin_return &lt;dbl&gt; | abs_return &lt;fct&gt; | ret.abs &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| 54 |  0.9022556 | 3.909774 | 2.406015 | 1.5037594 |  0.0003236863 | 2016-02-29 13:45:00 | 0.0003236863 |\n",
       "| 55 |  0.3456533 | 7.231461 | 3.788557 | 3.4429036 |  0.0030447107 | 2016-02-29 14:00:00 | 0.0030447107 |\n",
       "| 56 |  1.1032072 | 4.320665 | 2.711936 | 1.6087288 |  0.0035607284 | 2016-02-29 14:15:00 | 0.0035607284 |\n",
       "| 57 |  4.7190417 | 5.906024 | 5.312533 | 0.5934912 |  0.0008355592 | 2016-02-29 14:30:00 | 0.0008355592 |\n",
       "| 58 | -2.5359256 | 5.748098 | 1.606086 | 4.1420118 | -0.0033213654 | 2016-02-29 14:45:00 | 0.0033213654 |\n",
       "\n"
      ],
      "text/plain": [
       "   tone       polarity positive negative  fin_return    abs_return         \n",
       "54  0.9022556 3.909774 2.406015 1.5037594  0.0003236863 2016-02-29 13:45:00\n",
       "55  0.3456533 7.231461 3.788557 3.4429036  0.0030447107 2016-02-29 14:00:00\n",
       "56  1.1032072 4.320665 2.711936 1.6087288  0.0035607284 2016-02-29 14:15:00\n",
       "57  4.7190417 5.906024 5.312533 0.5934912  0.0008355592 2016-02-29 14:30:00\n",
       "58 -2.5359256 5.748098 1.606086 4.1420118 -0.0033213654 2016-02-29 14:45:00\n",
       "   ret.abs     \n",
       "54 0.0003236863\n",
       "55 0.0030447107\n",
       "56 0.0035607284\n",
       "57 0.0008355592\n",
       "58 0.0033213654"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(all.raw, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPORTANT OUTLIERS FILTERING"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "all.raw$fin_return[all.raw$fin_return> 0.08]=0.01\n",
    "#plot(all.raw$fin_return)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp = data.frame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1), external.regressors = cbind(all.raw$tone)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "#r.garch = ugarchfit(r.garch.spec, all.raw$fin_return,  solver=\"solnp\",  solver.control=list( maxeval=20, rseed=9876 ))\n",
    "aptone = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "\n",
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "#r.garch = ugarchfit(r.garch.spec, all.raw$fin_return,  solver=\"solnp\",  solver.control=list( maxeval=20, rseed=9876 ))\n",
    "ap = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "\n",
    "\n",
    "r.garch.spec = ugarchspec(variance.model=list(model=\"sGARCH\", garchOrder=c(1,1)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "#r.garch = ugarchfit(r.garch.spec, all.raw$fin_return,  solver=\"solnp\",  solver.control=list( maxeval=20, rseed=9876 ))\n",
    "ga = ugarchfit(r.garch.spec, all.raw$fin_return)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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cBh2/yrifWLW716dfA4fV1G/EKSu7aY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zKeBU2Jnb+//yuvvHKQ9yZISUlBYCBtNLIR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THPIqz9TdtvvxasdXV159vsb59jbt9Z6fnp6e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\nARM7AAAAAAAF8V804LGFol9TgwAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Sys.setlocale(category = \"LC_ALL\", locale = \"english\")\n",
    "\n",
    "exp.data = data.frame(all.raw.clean$date, c(sigma(aptone)), c(sigma(ap)), c(sigma(ga)))\n",
    "temp10 = zoo(exp.data[,2], exp.data[,1])\n",
    "temp11 = xts(exp.data[,-1], order.by = as.POSIXct(exp.data[,1]), locale = \"english\")\n",
    "\n",
    "\n",
    "#pdf(\"hgh.pdf\", width=10, height=6)\n",
    "plot.xts(temp11, observation.based=TRUE)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "names(exp.data) <-c(\"date\", \"aptone\", \"ap\", \"ga\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp.data$date <- as.POSIXct(exp.data$date,tz=Sys.timezone())\n",
    "exp.data$tone <- all.raw$tone\n",
    "exp.data$fin_return <- all.raw$fin_return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "write.csv(exp.data, \"results.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 1265 × 4</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>date</th><th scope=col>aptone</th><th scope=col>ap</th><th scope=col>ga</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dttm&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1970-01-02 01:00:00</th><td>2016-02-29 13:45:00</td><td>0.002101314</td><td>0.003995562</td><td>0.002827219</td></tr>\n",
       "\t<tr><th scope=row>1970-01-03 01:00:00</th><td>2016-02-29 14:00:00</td><td>0.002086370</td><td>0.003899455</td><td>0.002812891</td></tr>\n",
       "\t<tr><th scope=row>1970-01-04 01:00:00</th><td>2016-02-29 14:15:00</td><td>0.002086549</td><td>0.003821481</td><td>0.002813811</td></tr>\n",
       "\t<tr><th scope=row>1970-01-05 01:00:00</th><td>2016-02-29 14:30:00</td><td>0.002156445</td><td>0.003754256</td><td>0.002820272</td></tr>\n",
       "\t<tr><th scope=row>1970-01-06 01:00:00</th><td>2016-02-29 14:45:00</td><td>0.002085325</td><td>0.003667615</td><td>0.002806798</td></tr>\n",
       "\t<tr><th scope=row>1970-01-07 01:00:00</th><td>2016-02-29 15:15:00</td><td>0.002104835</td><td>0.003655799</td><td>0.002813307</td></tr>\n",
       "\t<tr><th scope=row>1970-01-08 01:00:00</th><td>2016-02-29 15:30:00</td><td>0.002081148</td><td>0.003587299</td><td>0.002805928</td></tr>\n",
       "\t<tr><th scope=row>1970-01-09 01:00:00</th><td>2016-02-29 15:45:00</td><td>0.002083335</td><td>0.003508380</td><td>0.002792655</td></tr>\n",
       "\t<tr><th scope=row>1970-01-10 01:00:00</th><td>2016-02-29 16:00:00</td><td>0.002067835</td><td>0.003462335</td><td>0.002800764</td></tr>\n",
       "\t<tr><th scope=row>1970-01-11 01:00:00</th><td>2016-02-29 16:15:00</td><td>0.002073060</td><td>0.003387951</td><td>0.002786787</td></tr>\n",
       "\t<tr><th scope=row>1970-01-12 01:00:00</th><td>2016-02-29 16:30:00</td><td>0.002023922</td><td>0.003316328</td><td>0.002772926</td></tr>\n",
       "\t<tr><th scope=row>1970-01-13 01:00:00</th><td>2016-02-29 17:30:00</td><td>0.001945354</td><td>0.003249624</td><td>0.002760059</td></tr>\n",
       "\t<tr><th scope=row>1970-01-14 01:00:00</th><td>2016-02-29 17:45:00</td><td>0.001934774</td><td>0.003187080</td><td>0.002747920</td></tr>\n",
       "\t<tr><th scope=row>1970-01-15 01:00:00</th><td>2016-02-29 18:00:00</td><td>0.001913531</td><td>0.003130265</td><td>0.002737008</td></tr>\n",
       "\t<tr><th scope=row>1970-01-16 01:00:00</th><td>2016-02-29 18:15:00</td><td>0.001934441</td><td>0.003084143</td><td>0.002728716</td></tr>\n",
       "\t<tr><th scope=row>1970-01-17 01:00:00</th><td>2016-02-29 18:30:00</td><td>0.002025162</td><td>0.003123331</td><td>0.002737467</td></tr>\n",
       "\t<tr><th scope=row>1970-01-18 01:00:00</th><td>2016-02-29 18:45:00</td><td>0.002032055</td><td>0.003064754</td><td>0.002725740</td></tr>\n",
       "\t<tr><th scope=row>1970-01-19 01:00:00</th><td>2016-02-29 19:00:00</td><td>0.002084935</td><td>0.003108202</td><td>0.002733978</td></tr>\n",
       "\t<tr><th scope=row>1970-01-20 01:00:00</th><td>2016-02-29 19:15:00</td><td>0.002057427</td><td>0.003053246</td><td>0.002722712</td></tr>\n",
       "\t<tr><th scope=row>1970-01-21 01:00:00</th><td>2016-02-29 19:30:00</td><td>0.002036160</td><td>0.003026570</td><td>0.002718305</td></tr>\n",
       "\t<tr><th scope=row>1970-01-22 01:00:00</th><td>2016-02-29 19:45:00</td><td>0.001994971</td><td>0.002971397</td><td>0.002704929</td></tr>\n",
       "\t<tr><th scope=row>1970-01-23 01:00:00</th><td>2016-03-01 14:00:00</td><td>0.001991464</td><td>0.002918972</td><td>0.002691587</td></tr>\n",
       "\t<tr><th scope=row>1970-01-24 01:00:00</th><td>2016-03-01 14:15:00</td><td>0.002013522</td><td>0.002935983</td><td>0.002710342</td></tr>\n",
       "\t<tr><th scope=row>1970-01-25 01:00:00</th><td>2016-03-01 14:30:00</td><td>0.001987107</td><td>0.002891355</td><td>0.002703979</td></tr>\n",
       "\t<tr><th scope=row>1970-01-26 01:00:00</th><td>2016-03-01 15:00:00</td><td>0.001974271</td><td>0.003113801</td><td>0.002778211</td></tr>\n",
       "\t<tr><th scope=row>1970-01-27 01:00:00</th><td>2016-03-01 15:15:00</td><td>0.002046960</td><td>0.003092388</td><td>0.002773295</td></tr>\n",
       "\t<tr><th scope=row>1970-01-28 01:00:00</th><td>2016-03-01 15:30:00</td><td>0.002020197</td><td>0.003039039</td><td>0.002764636</td></tr>\n",
       "\t<tr><th scope=row>1970-01-29 01:00:00</th><td>2016-03-01 15:45:00</td><td>0.002080120</td><td>0.002999963</td><td>0.002763793</td></tr>\n",
       "\t<tr><th scope=row>1970-01-30 01:00:00</th><td>2016-03-01 16:00:00</td><td>0.002108641</td><td>0.002967057</td><td>0.002765173</td></tr>\n",
       "\t<tr><th scope=row>1970-01-31 01:00:00</th><td>2016-03-01 16:15:00</td><td>0.002107424</td><td>0.002929954</td><td>0.002763487</td></tr>\n",
       "\t<tr><th scope=row>⋮</th><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
       "\t<tr><th scope=row>1973-05-21 01:00:00</th><td>2016-06-02 14:45:00</td><td>0.002439407</td><td>0.002300283</td><td>0.002030695</td></tr>\n",
       "\t<tr><th scope=row>1973-05-22 01:00:00</th><td>2016-06-02 15:00:00</td><td>0.002443701</td><td>0.002293765</td><td>0.002030584</td></tr>\n",
       "\t<tr><th scope=row>1973-05-23 01:00:00</th><td>2016-06-02 15:15:00</td><td>0.002421179</td><td>0.002285887</td><td>0.002025276</td></tr>\n",
       "\t<tr><th scope=row>1973-05-24 01:00:00</th><td>2016-06-02 15:30:00</td><td>0.002404584</td><td>0.002273327</td><td>0.002018455</td></tr>\n",
       "\t<tr><th scope=row>1973-05-25 01:00:00</th><td>2016-06-02 16:15:00</td><td>0.002390999</td><td>0.002286058</td><td>0.002027340</td></tr>\n",
       "\t<tr><th scope=row>1973-05-26 01:00:00</th><td>2016-06-02 16:30:00</td><td>0.002335916</td><td>0.002286313</td><td>0.002023984</td></tr>\n",
       "\t<tr><th scope=row>1973-05-27 01:00:00</th><td>2016-06-02 17:15:00</td><td>0.002272935</td><td>0.002273878</td><td>0.002017517</td></tr>\n",
       "\t<tr><th scope=row>1973-05-28 01:00:00</th><td>2016-06-02 18:00:00</td><td>0.002200893</td><td>0.002263178</td><td>0.002012530</td></tr>\n",
       "\t<tr><th scope=row>1973-05-29 01:00:00</th><td>2016-06-02 18:15:00</td><td>0.002132293</td><td>0.002253080</td><td>0.002005899</td></tr>\n",
       "\t<tr><th scope=row>1973-05-30 01:00:00</th><td>2016-06-02 18:30:00</td><td>0.002059435</td><td>0.002243852</td><td>0.002000888</td></tr>\n",
       "\t<tr><th scope=row>1973-05-31 01:00:00</th><td>2016-06-02 19:00:00</td><td>0.002004928</td><td>0.002235075</td><td>0.001995814</td></tr>\n",
       "\t<tr><th scope=row>1973-06-01 01:00:00</th><td>2016-06-02 19:15:00</td><td>0.001996746</td><td>0.002227185</td><td>0.001991098</td></tr>\n",
       "\t<tr><th scope=row>1973-06-02 01:00:00</th><td>2016-06-02 19:30:00</td><td>0.002022385</td><td>0.002219047</td><td>0.001984368</td></tr>\n",
       "\t<tr><th scope=row>1973-06-03 01:00:00</th><td>2016-06-02 19:45:00</td><td>0.002010954</td><td>0.002211259</td><td>0.001977847</td></tr>\n",
       "\t<tr><th scope=row>1973-06-04 01:00:00</th><td>2016-06-03 14:15:00</td><td>0.002035947</td><td>0.002204108</td><td>0.001971632</td></tr>\n",
       "\t<tr><th scope=row>1973-06-05 01:00:00</th><td>2016-06-03 15:00:00</td><td>0.002187242</td><td>0.003027255</td><td>0.002077347</td></tr>\n",
       "\t<tr><th scope=row>1973-06-06 01:00:00</th><td>2016-06-03 15:15:00</td><td>0.002199347</td><td>0.002973352</td><td>0.002071821</td></tr>\n",
       "\t<tr><th scope=row>1973-06-07 01:00:00</th><td>2016-06-03 15:30:00</td><td>0.002215240</td><td>0.002936113</td><td>0.002070777</td></tr>\n",
       "\t<tr><th scope=row>1973-06-08 01:00:00</th><td>2016-06-03 15:45:00</td><td>0.002204782</td><td>0.002885369</td><td>0.002063139</td></tr>\n",
       "\t<tr><th scope=row>1973-06-09 01:00:00</th><td>2016-06-03 16:15:00</td><td>0.002214339</td><td>0.002847094</td><td>0.002066693</td></tr>\n",
       "\t<tr><th scope=row>1973-06-10 01:00:00</th><td>2016-06-03 16:45:00</td><td>0.002159555</td><td>0.002802059</td><td>0.002062123</td></tr>\n",
       "\t<tr><th scope=row>1973-06-11 01:00:00</th><td>2016-06-03 17:00:00</td><td>0.002174424</td><td>0.002758374</td><td>0.002054673</td></tr>\n",
       "\t<tr><th scope=row>1973-06-12 01:00:00</th><td>2016-06-03 17:30:00</td><td>0.002166427</td><td>0.002716850</td><td>0.002047191</td></tr>\n",
       "\t<tr><th scope=row>1973-06-13 01:00:00</th><td>2016-06-03 17:45:00</td><td>0.002167823</td><td>0.002685119</td><td>0.002043316</td></tr>\n",
       "\t<tr><th scope=row>1973-06-14 01:00:00</th><td>2016-06-03 18:00:00</td><td>0.002162077</td><td>0.002650517</td><td>0.002037720</td></tr>\n",
       "\t<tr><th scope=row>1973-06-15 01:00:00</th><td>2016-06-03 18:15:00</td><td>0.002151228</td><td>0.002615068</td><td>0.002030511</td></tr>\n",
       "\t<tr><th scope=row>1973-06-16 01:00:00</th><td>2016-06-03 18:30:00</td><td>0.002156537</td><td>0.002583247</td><td>0.002024317</td></tr>\n",
       "\t<tr><th scope=row>1973-06-17 01:00:00</th><td>2016-06-03 18:45:00</td><td>0.002139485</td><td>0.002551564</td><td>0.002017134</td></tr>\n",
       "\t<tr><th scope=row>1973-06-18 01:00:00</th><td>2016-06-03 19:30:00</td><td>0.002126782</td><td>0.002527348</td><td>0.002016762</td></tr>\n",
       "\t<tr><th scope=row>1973-06-19 01:00:00</th><td>2016-06-03 19:45:00</td><td>0.002137977</td><td>0.002498995</td><td>0.002009799</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1265 × 4\n",
       "\\begin{tabular}{r|llll}\n",
       "  & date & aptone & ap & ga\\\\\n",
       "  & <dttm> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t1970-01-02 01:00:00 & 2016-02-29 13:45:00 & 0.002101314 & 0.003995562 & 0.002827219\\\\\n",
       "\t1970-01-03 01:00:00 & 2016-02-29 14:00:00 & 0.002086370 & 0.003899455 & 0.002812891\\\\\n",
       "\t1970-01-04 01:00:00 & 2016-02-29 14:15:00 & 0.002086549 & 0.003821481 & 0.002813811\\\\\n",
       "\t1970-01-05 01:00:00 & 2016-02-29 14:30:00 & 0.002156445 & 0.003754256 & 0.002820272\\\\\n",
       "\t1970-01-06 01:00:00 & 2016-02-29 14:45:00 & 0.002085325 & 0.003667615 & 0.002806798\\\\\n",
       "\t1970-01-07 01:00:00 & 2016-02-29 15:15:00 & 0.002104835 & 0.003655799 & 0.002813307\\\\\n",
       "\t1970-01-08 01:00:00 & 2016-02-29 15:30:00 & 0.002081148 & 0.003587299 & 0.002805928\\\\\n",
       "\t1970-01-09 01:00:00 & 2016-02-29 15:45:00 & 0.002083335 & 0.003508380 & 0.002792655\\\\\n",
       "\t1970-01-10 01:00:00 & 2016-02-29 16:00:00 & 0.002067835 & 0.003462335 & 0.002800764\\\\\n",
       "\t1970-01-11 01:00:00 & 2016-02-29 16:15:00 & 0.002073060 & 0.003387951 & 0.002786787\\\\\n",
       "\t1970-01-12 01:00:00 & 2016-02-29 16:30:00 & 0.002023922 & 0.003316328 & 0.002772926\\\\\n",
       "\t1970-01-13 01:00:00 & 2016-02-29 17:30:00 & 0.001945354 & 0.003249624 & 0.002760059\\\\\n",
       "\t1970-01-14 01:00:00 & 2016-02-29 17:45:00 & 0.001934774 & 0.003187080 & 0.002747920\\\\\n",
       "\t1970-01-15 01:00:00 & 2016-02-29 18:00:00 & 0.001913531 & 0.003130265 & 0.002737008\\\\\n",
       "\t1970-01-16 01:00:00 & 2016-02-29 18:15:00 & 0.001934441 & 0.003084143 & 0.002728716\\\\\n",
       "\t1970-01-17 01:00:00 & 2016-02-29 18:30:00 & 0.002025162 & 0.003123331 & 0.002737467\\\\\n",
       "\t1970-01-18 01:00:00 & 2016-02-29 18:45:00 & 0.002032055 & 0.003064754 & 0.002725740\\\\\n",
       "\t1970-01-19 01:00:00 & 2016-02-29 19:00:00 & 0.002084935 & 0.003108202 & 0.002733978\\\\\n",
       "\t1970-01-20 01:00:00 & 2016-02-29 19:15:00 & 0.002057427 & 0.003053246 & 0.002722712\\\\\n",
       "\t1970-01-21 01:00:00 & 2016-02-29 19:30:00 & 0.002036160 & 0.003026570 & 0.002718305\\\\\n",
       "\t1970-01-22 01:00:00 & 2016-02-29 19:45:00 & 0.001994971 & 0.002971397 & 0.002704929\\\\\n",
       "\t1970-01-23 01:00:00 & 2016-03-01 14:00:00 & 0.001991464 & 0.002918972 & 0.002691587\\\\\n",
       "\t1970-01-24 01:00:00 & 2016-03-01 14:15:00 & 0.002013522 & 0.002935983 & 0.002710342\\\\\n",
       "\t1970-01-25 01:00:00 & 2016-03-01 14:30:00 & 0.001987107 & 0.002891355 & 0.002703979\\\\\n",
       "\t1970-01-26 01:00:00 & 2016-03-01 15:00:00 & 0.001974271 & 0.003113801 & 0.002778211\\\\\n",
       "\t1970-01-27 01:00:00 & 2016-03-01 15:15:00 & 0.002046960 & 0.003092388 & 0.002773295\\\\\n",
       "\t1970-01-28 01:00:00 & 2016-03-01 15:30:00 & 0.002020197 & 0.003039039 & 0.002764636\\\\\n",
       "\t1970-01-29 01:00:00 & 2016-03-01 15:45:00 & 0.002080120 & 0.002999963 & 0.002763793\\\\\n",
       "\t1970-01-30 01:00:00 & 2016-03-01 16:00:00 & 0.002108641 & 0.002967057 & 0.002765173\\\\\n",
       "\t1970-01-31 01:00:00 & 2016-03-01 16:15:00 & 0.002107424 & 0.002929954 & 0.002763487\\\\\n",
       "\t⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
       "\t1973-05-21 01:00:00 & 2016-06-02 14:45:00 & 0.002439407 & 0.002300283 & 0.002030695\\\\\n",
       "\t1973-05-22 01:00:00 & 2016-06-02 15:00:00 & 0.002443701 & 0.002293765 & 0.002030584\\\\\n",
       "\t1973-05-23 01:00:00 & 2016-06-02 15:15:00 & 0.002421179 & 0.002285887 & 0.002025276\\\\\n",
       "\t1973-05-24 01:00:00 & 2016-06-02 15:30:00 & 0.002404584 & 0.002273327 & 0.002018455\\\\\n",
       "\t1973-05-25 01:00:00 & 2016-06-02 16:15:00 & 0.002390999 & 0.002286058 & 0.002027340\\\\\n",
       "\t1973-05-26 01:00:00 & 2016-06-02 16:30:00 & 0.002335916 & 0.002286313 & 0.002023984\\\\\n",
       "\t1973-05-27 01:00:00 & 2016-06-02 17:15:00 & 0.002272935 & 0.002273878 & 0.002017517\\\\\n",
       "\t1973-05-28 01:00:00 & 2016-06-02 18:00:00 & 0.002200893 & 0.002263178 & 0.002012530\\\\\n",
       "\t1973-05-29 01:00:00 & 2016-06-02 18:15:00 & 0.002132293 & 0.002253080 & 0.002005899\\\\\n",
       "\t1973-05-30 01:00:00 & 2016-06-02 18:30:00 & 0.002059435 & 0.002243852 & 0.002000888\\\\\n",
       "\t1973-05-31 01:00:00 & 2016-06-02 19:00:00 & 0.002004928 & 0.002235075 & 0.001995814\\\\\n",
       "\t1973-06-01 01:00:00 & 2016-06-02 19:15:00 & 0.001996746 & 0.002227185 & 0.001991098\\\\\n",
       "\t1973-06-02 01:00:00 & 2016-06-02 19:30:00 & 0.002022385 & 0.002219047 & 0.001984368\\\\\n",
       "\t1973-06-03 01:00:00 & 2016-06-02 19:45:00 & 0.002010954 & 0.002211259 & 0.001977847\\\\\n",
       "\t1973-06-04 01:00:00 & 2016-06-03 14:15:00 & 0.002035947 & 0.002204108 & 0.001971632\\\\\n",
       "\t1973-06-05 01:00:00 & 2016-06-03 15:00:00 & 0.002187242 & 0.003027255 & 0.002077347\\\\\n",
       "\t1973-06-06 01:00:00 & 2016-06-03 15:15:00 & 0.002199347 & 0.002973352 & 0.002071821\\\\\n",
       "\t1973-06-07 01:00:00 & 2016-06-03 15:30:00 & 0.002215240 & 0.002936113 & 0.002070777\\\\\n",
       "\t1973-06-08 01:00:00 & 2016-06-03 15:45:00 & 0.002204782 & 0.002885369 & 0.002063139\\\\\n",
       "\t1973-06-09 01:00:00 & 2016-06-03 16:15:00 & 0.002214339 & 0.002847094 & 0.002066693\\\\\n",
       "\t1973-06-10 01:00:00 & 2016-06-03 16:45:00 & 0.002159555 & 0.002802059 & 0.002062123\\\\\n",
       "\t1973-06-11 01:00:00 & 2016-06-03 17:00:00 & 0.002174424 & 0.002758374 & 0.002054673\\\\\n",
       "\t1973-06-12 01:00:00 & 2016-06-03 17:30:00 & 0.002166427 & 0.002716850 & 0.002047191\\\\\n",
       "\t1973-06-13 01:00:00 & 2016-06-03 17:45:00 & 0.002167823 & 0.002685119 & 0.002043316\\\\\n",
       "\t1973-06-14 01:00:00 & 2016-06-03 18:00:00 & 0.002162077 & 0.002650517 & 0.002037720\\\\\n",
       "\t1973-06-15 01:00:00 & 2016-06-03 18:15:00 & 0.002151228 & 0.002615068 & 0.002030511\\\\\n",
       "\t1973-06-16 01:00:00 & 2016-06-03 18:30:00 & 0.002156537 & 0.002583247 & 0.002024317\\\\\n",
       "\t1973-06-17 01:00:00 & 2016-06-03 18:45:00 & 0.002139485 & 0.002551564 & 0.002017134\\\\\n",
       "\t1973-06-18 01:00:00 & 2016-06-03 19:30:00 & 0.002126782 & 0.002527348 & 0.002016762\\\\\n",
       "\t1973-06-19 01:00:00 & 2016-06-03 19:45:00 & 0.002137977 & 0.002498995 & 0.002009799\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1265 × 4\n",
       "\n",
       "| <!--/--> | date &lt;dttm&gt; | aptone &lt;dbl&gt; | ap &lt;dbl&gt; | ga &lt;dbl&gt; |\n",
       "|---|---|---|---|---|\n",
       "| 1970-01-02 01:00:00 | 2016-02-29 13:45:00 | 0.002101314 | 0.003995562 | 0.002827219 |\n",
       "| 1970-01-03 01:00:00 | 2016-02-29 14:00:00 | 0.002086370 | 0.003899455 | 0.002812891 |\n",
       "| 1970-01-04 01:00:00 | 2016-02-29 14:15:00 | 0.002086549 | 0.003821481 | 0.002813811 |\n",
       "| 1970-01-05 01:00:00 | 2016-02-29 14:30:00 | 0.002156445 | 0.003754256 | 0.002820272 |\n",
       "| 1970-01-06 01:00:00 | 2016-02-29 14:45:00 | 0.002085325 | 0.003667615 | 0.002806798 |\n",
       "| 1970-01-07 01:00:00 | 2016-02-29 15:15:00 | 0.002104835 | 0.003655799 | 0.002813307 |\n",
       "| 1970-01-08 01:00:00 | 2016-02-29 15:30:00 | 0.002081148 | 0.003587299 | 0.002805928 |\n",
       "| 1970-01-09 01:00:00 | 2016-02-29 15:45:00 | 0.002083335 | 0.003508380 | 0.002792655 |\n",
       "| 1970-01-10 01:00:00 | 2016-02-29 16:00:00 | 0.002067835 | 0.003462335 | 0.002800764 |\n",
       "| 1970-01-11 01:00:00 | 2016-02-29 16:15:00 | 0.002073060 | 0.003387951 | 0.002786787 |\n",
       "| 1970-01-12 01:00:00 | 2016-02-29 16:30:00 | 0.002023922 | 0.003316328 | 0.002772926 |\n",
       "| 1970-01-13 01:00:00 | 2016-02-29 17:30:00 | 0.001945354 | 0.003249624 | 0.002760059 |\n",
       "| 1970-01-14 01:00:00 | 2016-02-29 17:45:00 | 0.001934774 | 0.003187080 | 0.002747920 |\n",
       "| 1970-01-15 01:00:00 | 2016-02-29 18:00:00 | 0.001913531 | 0.003130265 | 0.002737008 |\n",
       "| 1970-01-16 01:00:00 | 2016-02-29 18:15:00 | 0.001934441 | 0.003084143 | 0.002728716 |\n",
       "| 1970-01-17 01:00:00 | 2016-02-29 18:30:00 | 0.002025162 | 0.003123331 | 0.002737467 |\n",
       "| 1970-01-18 01:00:00 | 2016-02-29 18:45:00 | 0.002032055 | 0.003064754 | 0.002725740 |\n",
       "| 1970-01-19 01:00:00 | 2016-02-29 19:00:00 | 0.002084935 | 0.003108202 | 0.002733978 |\n",
       "| 1970-01-20 01:00:00 | 2016-02-29 19:15:00 | 0.002057427 | 0.003053246 | 0.002722712 |\n",
       "| 1970-01-21 01:00:00 | 2016-02-29 19:30:00 | 0.002036160 | 0.003026570 | 0.002718305 |\n",
       "| 1970-01-22 01:00:00 | 2016-02-29 19:45:00 | 0.001994971 | 0.002971397 | 0.002704929 |\n",
       "| 1970-01-23 01:00:00 | 2016-03-01 14:00:00 | 0.001991464 | 0.002918972 | 0.002691587 |\n",
       "| 1970-01-24 01:00:00 | 2016-03-01 14:15:00 | 0.002013522 | 0.002935983 | 0.002710342 |\n",
       "| 1970-01-25 01:00:00 | 2016-03-01 14:30:00 | 0.001987107 | 0.002891355 | 0.002703979 |\n",
       "| 1970-01-26 01:00:00 | 2016-03-01 15:00:00 | 0.001974271 | 0.003113801 | 0.002778211 |\n",
       "| 1970-01-27 01:00:00 | 2016-03-01 15:15:00 | 0.002046960 | 0.003092388 | 0.002773295 |\n",
       "| 1970-01-28 01:00:00 | 2016-03-01 15:30:00 | 0.002020197 | 0.003039039 | 0.002764636 |\n",
       "| 1970-01-29 01:00:00 | 2016-03-01 15:45:00 | 0.002080120 | 0.002999963 | 0.002763793 |\n",
       "| 1970-01-30 01:00:00 | 2016-03-01 16:00:00 | 0.002108641 | 0.002967057 | 0.002765173 |\n",
       "| 1970-01-31 01:00:00 | 2016-03-01 16:15:00 | 0.002107424 | 0.002929954 | 0.002763487 |\n",
       "| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
       "| 1973-05-21 01:00:00 | 2016-06-02 14:45:00 | 0.002439407 | 0.002300283 | 0.002030695 |\n",
       "| 1973-05-22 01:00:00 | 2016-06-02 15:00:00 | 0.002443701 | 0.002293765 | 0.002030584 |\n",
       "| 1973-05-23 01:00:00 | 2016-06-02 15:15:00 | 0.002421179 | 0.002285887 | 0.002025276 |\n",
       "| 1973-05-24 01:00:00 | 2016-06-02 15:30:00 | 0.002404584 | 0.002273327 | 0.002018455 |\n",
       "| 1973-05-25 01:00:00 | 2016-06-02 16:15:00 | 0.002390999 | 0.002286058 | 0.002027340 |\n",
       "| 1973-05-26 01:00:00 | 2016-06-02 16:30:00 | 0.002335916 | 0.002286313 | 0.002023984 |\n",
       "| 1973-05-27 01:00:00 | 2016-06-02 17:15:00 | 0.002272935 | 0.002273878 | 0.002017517 |\n",
       "| 1973-05-28 01:00:00 | 2016-06-02 18:00:00 | 0.002200893 | 0.002263178 | 0.002012530 |\n",
       "| 1973-05-29 01:00:00 | 2016-06-02 18:15:00 | 0.002132293 | 0.002253080 | 0.002005899 |\n",
       "| 1973-05-30 01:00:00 | 2016-06-02 18:30:00 | 0.002059435 | 0.002243852 | 0.002000888 |\n",
       "| 1973-05-31 01:00:00 | 2016-06-02 19:00:00 | 0.002004928 | 0.002235075 | 0.001995814 |\n",
       "| 1973-06-01 01:00:00 | 2016-06-02 19:15:00 | 0.001996746 | 0.002227185 | 0.001991098 |\n",
       "| 1973-06-02 01:00:00 | 2016-06-02 19:30:00 | 0.002022385 | 0.002219047 | 0.001984368 |\n",
       "| 1973-06-03 01:00:00 | 2016-06-02 19:45:00 | 0.002010954 | 0.002211259 | 0.001977847 |\n",
       "| 1973-06-04 01:00:00 | 2016-06-03 14:15:00 | 0.002035947 | 0.002204108 | 0.001971632 |\n",
       "| 1973-06-05 01:00:00 | 2016-06-03 15:00:00 | 0.002187242 | 0.003027255 | 0.002077347 |\n",
       "| 1973-06-06 01:00:00 | 2016-06-03 15:15:00 | 0.002199347 | 0.002973352 | 0.002071821 |\n",
       "| 1973-06-07 01:00:00 | 2016-06-03 15:30:00 | 0.002215240 | 0.002936113 | 0.002070777 |\n",
       "| 1973-06-08 01:00:00 | 2016-06-03 15:45:00 | 0.002204782 | 0.002885369 | 0.002063139 |\n",
       "| 1973-06-09 01:00:00 | 2016-06-03 16:15:00 | 0.002214339 | 0.002847094 | 0.002066693 |\n",
       "| 1973-06-10 01:00:00 | 2016-06-03 16:45:00 | 0.002159555 | 0.002802059 | 0.002062123 |\n",
       "| 1973-06-11 01:00:00 | 2016-06-03 17:00:00 | 0.002174424 | 0.002758374 | 0.002054673 |\n",
       "| 1973-06-12 01:00:00 | 2016-06-03 17:30:00 | 0.002166427 | 0.002716850 | 0.002047191 |\n",
       "| 1973-06-13 01:00:00 | 2016-06-03 17:45:00 | 0.002167823 | 0.002685119 | 0.002043316 |\n",
       "| 1973-06-14 01:00:00 | 2016-06-03 18:00:00 | 0.002162077 | 0.002650517 | 0.002037720 |\n",
       "| 1973-06-15 01:00:00 | 2016-06-03 18:15:00 | 0.002151228 | 0.002615068 | 0.002030511 |\n",
       "| 1973-06-16 01:00:00 | 2016-06-03 18:30:00 | 0.002156537 | 0.002583247 | 0.002024317 |\n",
       "| 1973-06-17 01:00:00 | 2016-06-03 18:45:00 | 0.002139485 | 0.002551564 | 0.002017134 |\n",
       "| 1973-06-18 01:00:00 | 2016-06-03 19:30:00 | 0.002126782 | 0.002527348 | 0.002016762 |\n",
       "| 1973-06-19 01:00:00 | 2016-06-03 19:45:00 | 0.002137977 | 0.002498995 | 0.002009799 |\n",
       "\n"
      ],
      "text/plain": [
       "                    date                aptone      ap          ga         \n",
       "1970-01-02 01:00:00 2016-02-29 13:45:00 0.002101314 0.003995562 0.002827219\n",
       "1970-01-03 01:00:00 2016-02-29 14:00:00 0.002086370 0.003899455 0.002812891\n",
       "1970-01-04 01:00:00 2016-02-29 14:15:00 0.002086549 0.003821481 0.002813811\n",
       "1970-01-05 01:00:00 2016-02-29 14:30:00 0.002156445 0.003754256 0.002820272\n",
       "1970-01-06 01:00:00 2016-02-29 14:45:00 0.002085325 0.003667615 0.002806798\n",
       "1970-01-07 01:00:00 2016-02-29 15:15:00 0.002104835 0.003655799 0.002813307\n",
       "1970-01-08 01:00:00 2016-02-29 15:30:00 0.002081148 0.003587299 0.002805928\n",
       "1970-01-09 01:00:00 2016-02-29 15:45:00 0.002083335 0.003508380 0.002792655\n",
       "1970-01-10 01:00:00 2016-02-29 16:00:00 0.002067835 0.003462335 0.002800764\n",
       "1970-01-11 01:00:00 2016-02-29 16:15:00 0.002073060 0.003387951 0.002786787\n",
       "1970-01-12 01:00:00 2016-02-29 16:30:00 0.002023922 0.003316328 0.002772926\n",
       "1970-01-13 01:00:00 2016-02-29 17:30:00 0.001945354 0.003249624 0.002760059\n",
       "1970-01-14 01:00:00 2016-02-29 17:45:00 0.001934774 0.003187080 0.002747920\n",
       "1970-01-15 01:00:00 2016-02-29 18:00:00 0.001913531 0.003130265 0.002737008\n",
       "1970-01-16 01:00:00 2016-02-29 18:15:00 0.001934441 0.003084143 0.002728716\n",
       "1970-01-17 01:00:00 2016-02-29 18:30:00 0.002025162 0.003123331 0.002737467\n",
       "1970-01-18 01:00:00 2016-02-29 18:45:00 0.002032055 0.003064754 0.002725740\n",
       "1970-01-19 01:00:00 2016-02-29 19:00:00 0.002084935 0.003108202 0.002733978\n",
       "1970-01-20 01:00:00 2016-02-29 19:15:00 0.002057427 0.003053246 0.002722712\n",
       "1970-01-21 01:00:00 2016-02-29 19:30:00 0.002036160 0.003026570 0.002718305\n",
       "1970-01-22 01:00:00 2016-02-29 19:45:00 0.001994971 0.002971397 0.002704929\n",
       "1970-01-23 01:00:00 2016-03-01 14:00:00 0.001991464 0.002918972 0.002691587\n",
       "1970-01-24 01:00:00 2016-03-01 14:15:00 0.002013522 0.002935983 0.002710342\n",
       "1970-01-25 01:00:00 2016-03-01 14:30:00 0.001987107 0.002891355 0.002703979\n",
       "1970-01-26 01:00:00 2016-03-01 15:00:00 0.001974271 0.003113801 0.002778211\n",
       "1970-01-27 01:00:00 2016-03-01 15:15:00 0.002046960 0.003092388 0.002773295\n",
       "1970-01-28 01:00:00 2016-03-01 15:30:00 0.002020197 0.003039039 0.002764636\n",
       "1970-01-29 01:00:00 2016-03-01 15:45:00 0.002080120 0.002999963 0.002763793\n",
       "1970-01-30 01:00:00 2016-03-01 16:00:00 0.002108641 0.002967057 0.002765173\n",
       "1970-01-31 01:00:00 2016-03-01 16:15:00 0.002107424 0.002929954 0.002763487\n",
       "⋮                   ⋮                   ⋮           ⋮           ⋮          \n",
       "1973-05-21 01:00:00 2016-06-02 14:45:00 0.002439407 0.002300283 0.002030695\n",
       "1973-05-22 01:00:00 2016-06-02 15:00:00 0.002443701 0.002293765 0.002030584\n",
       "1973-05-23 01:00:00 2016-06-02 15:15:00 0.002421179 0.002285887 0.002025276\n",
       "1973-05-24 01:00:00 2016-06-02 15:30:00 0.002404584 0.002273327 0.002018455\n",
       "1973-05-25 01:00:00 2016-06-02 16:15:00 0.002390999 0.002286058 0.002027340\n",
       "1973-05-26 01:00:00 2016-06-02 16:30:00 0.002335916 0.002286313 0.002023984\n",
       "1973-05-27 01:00:00 2016-06-02 17:15:00 0.002272935 0.002273878 0.002017517\n",
       "1973-05-28 01:00:00 2016-06-02 18:00:00 0.002200893 0.002263178 0.002012530\n",
       "1973-05-29 01:00:00 2016-06-02 18:15:00 0.002132293 0.002253080 0.002005899\n",
       "1973-05-30 01:00:00 2016-06-02 18:30:00 0.002059435 0.002243852 0.002000888\n",
       "1973-05-31 01:00:00 2016-06-02 19:00:00 0.002004928 0.002235075 0.001995814\n",
       "1973-06-01 01:00:00 2016-06-02 19:15:00 0.001996746 0.002227185 0.001991098\n",
       "1973-06-02 01:00:00 2016-06-02 19:30:00 0.002022385 0.002219047 0.001984368\n",
       "1973-06-03 01:00:00 2016-06-02 19:45:00 0.002010954 0.002211259 0.001977847\n",
       "1973-06-04 01:00:00 2016-06-03 14:15:00 0.002035947 0.002204108 0.001971632\n",
       "1973-06-05 01:00:00 2016-06-03 15:00:00 0.002187242 0.003027255 0.002077347\n",
       "1973-06-06 01:00:00 2016-06-03 15:15:00 0.002199347 0.002973352 0.002071821\n",
       "1973-06-07 01:00:00 2016-06-03 15:30:00 0.002215240 0.002936113 0.002070777\n",
       "1973-06-08 01:00:00 2016-06-03 15:45:00 0.002204782 0.002885369 0.002063139\n",
       "1973-06-09 01:00:00 2016-06-03 16:15:00 0.002214339 0.002847094 0.002066693\n",
       "1973-06-10 01:00:00 2016-06-03 16:45:00 0.002159555 0.002802059 0.002062123\n",
       "1973-06-11 01:00:00 2016-06-03 17:00:00 0.002174424 0.002758374 0.002054673\n",
       "1973-06-12 01:00:00 2016-06-03 17:30:00 0.002166427 0.002716850 0.002047191\n",
       "1973-06-13 01:00:00 2016-06-03 17:45:00 0.002167823 0.002685119 0.002043316\n",
       "1973-06-14 01:00:00 2016-06-03 18:00:00 0.002162077 0.002650517 0.002037720\n",
       "1973-06-15 01:00:00 2016-06-03 18:15:00 0.002151228 0.002615068 0.002030511\n",
       "1973-06-16 01:00:00 2016-06-03 18:30:00 0.002156537 0.002583247 0.002024317\n",
       "1973-06-17 01:00:00 2016-06-03 18:45:00 0.002139485 0.002551564 0.002017134\n",
       "1973-06-18 01:00:00 2016-06-03 19:30:00 0.002126782 0.002527348 0.002016762\n",
       "1973-06-19 01:00:00 2016-06-03 19:45:00 0.002137977 0.002498995 0.002009799"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(\"ggplot2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   [1] \"2016-02-29 13:45:00 CET\"  \"2016-02-29 14:00:00 CET\" \n",
       "   [3] \"2016-02-29 14:15:00 CET\"  \"2016-02-29 14:30:00 CET\" \n",
       "   [5] \"2016-02-29 14:45:00 CET\"  \"2016-02-29 15:15:00 CET\" \n",
       "   [7] \"2016-02-29 15:30:00 CET\"  \"2016-02-29 15:45:00 CET\" \n",
       "   [9] \"2016-02-29 16:00:00 CET\"  \"2016-02-29 16:15:00 CET\" \n",
       "  [11] \"2016-02-29 16:30:00 CET\"  \"2016-02-29 17:30:00 CET\" \n",
       "  [13] \"2016-02-29 17:45:00 CET\"  \"2016-02-29 18:00:00 CET\" \n",
       "  [15] \"2016-02-29 18:15:00 CET\"  \"2016-02-29 18:30:00 CET\" \n",
       "  [17] \"2016-02-29 18:45:00 CET\"  \"2016-02-29 19:00:00 CET\" \n",
       "  [19] \"2016-02-29 19:15:00 CET\"  \"2016-02-29 19:30:00 CET\" \n",
       "  [21] \"2016-02-29 19:45:00 CET\"  \"2016-03-01 14:00:00 CET\" \n",
       "  [23] \"2016-03-01 14:15:00 CET\"  \"2016-03-01 14:30:00 CET\" \n",
       "  [25] \"2016-03-01 15:00:00 CET\"  \"2016-03-01 15:15:00 CET\" \n",
       "  [27] \"2016-03-01 15:30:00 CET\"  \"2016-03-01 15:45:00 CET\" \n",
       "  [29] \"2016-03-01 16:00:00 CET\"  \"2016-03-01 16:15:00 CET\" \n",
       "  [31] \"2016-03-01 16:30:00 CET\"  \"2016-03-01 16:45:00 CET\" \n",
       "  [33] \"2016-03-01 17:00:00 CET\"  \"2016-03-01 17:15:00 CET\" \n",
       "  [35] \"2016-03-01 17:30:00 CET\"  \"2016-03-01 17:45:00 CET\" \n",
       "  [37] \"2016-03-01 18:00:00 CET\"  \"2016-03-01 18:15:00 CET\" \n",
       "  [39] \"2016-03-01 18:30:00 CET\"  \"2016-03-01 18:45:00 CET\" \n",
       "  [41] \"2016-03-01 19:30:00 CET\"  \"2016-03-01 19:45:00 CET\" \n",
       "  [43] \"2016-03-02 13:45:00 CET\"  \"2016-03-02 14:00:00 CET\" \n",
       "  [45] \"2016-03-02 15:15:00 CET\"  \"2016-03-02 15:30:00 CET\" \n",
       "  [47] \"2016-03-02 15:45:00 CET\"  \"2016-03-02 16:00:00 CET\" \n",
       "  [49] \"2016-03-02 16:15:00 CET\"  \"2016-03-02 16:30:00 CET\" \n",
       "  [51] \"2016-03-02 16:45:00 CET\"  \"2016-03-02 17:15:00 CET\" \n",
       "  [53] \"2016-03-02 18:00:00 CET\"  \"2016-03-02 18:15:00 CET\" \n",
       "  [55] \"2016-03-02 19:00:00 CET\"  \"2016-03-02 19:30:00 CET\" \n",
       "  [57] \"2016-03-03 13:45:00 CET\"  \"2016-03-03 14:00:00 CET\" \n",
       "  [59] \"2016-03-03 14:30:00 CET\"  \"2016-03-03 14:45:00 CET\" \n",
       "  [61] \"2016-03-03 15:00:00 CET\"  \"2016-03-03 15:15:00 CET\" \n",
       "  [63] \"2016-03-03 15:30:00 CET\"  \"2016-03-03 15:45:00 CET\" \n",
       "  [65] \"2016-03-03 16:15:00 CET\"  \"2016-03-03 16:30:00 CET\" \n",
       "  [67] \"2016-03-03 16:45:00 CET\"  \"2016-03-03 17:00:00 CET\" \n",
       "  [69] \"2016-03-03 17:15:00 CET\"  \"2016-03-03 17:30:00 CET\" \n",
       "  [71] \"2016-03-03 17:45:00 CET\"  \"2016-03-03 18:00:00 CET\" \n",
       "  [73] \"2016-03-03 18:15:00 CET\"  \"2016-03-03 18:30:00 CET\" \n",
       "  [75] \"2016-03-03 18:45:00 CET\"  \"2016-03-03 19:00:00 CET\" \n",
       "  [77] \"2016-03-03 19:15:00 CET\"  \"2016-03-03 19:30:00 CET\" \n",
       "  [79] \"2016-03-03 19:45:00 CET\"  \"2016-03-04 13:45:00 CET\" \n",
       "  [81] \"2016-03-04 14:30:00 CET\"  \"2016-03-04 14:45:00 CET\" \n",
       "  [83] \"2016-03-04 15:00:00 CET\"  \"2016-03-04 15:15:00 CET\" \n",
       "  [85] \"2016-03-04 15:30:00 CET\"  \"2016-03-04 15:45:00 CET\" \n",
       "  [87] \"2016-03-04 17:15:00 CET\"  \"2016-03-04 17:30:00 CET\" \n",
       "  [89] \"2016-03-04 17:45:00 CET\"  \"2016-03-04 18:00:00 CET\" \n",
       "  [91] \"2016-03-04 18:15:00 CET\"  \"2016-03-04 18:30:00 CET\" \n",
       "  [93] \"2016-03-04 18:45:00 CET\"  \"2016-03-04 19:15:00 CET\" \n",
       "  [95] \"2016-03-04 19:30:00 CET\"  \"2016-03-07 14:45:00 CET\" \n",
       "  [97] \"2016-03-07 15:15:00 CET\"  \"2016-03-07 15:30:00 CET\" \n",
       "  [99] \"2016-03-07 16:00:00 CET\"  \"2016-03-07 16:15:00 CET\" \n",
       " [101] \"2016-03-07 16:30:00 CET\"  \"2016-03-07 16:45:00 CET\" \n",
       " [103] \"2016-03-07 17:00:00 CET\"  \"2016-03-07 17:15:00 CET\" \n",
       " [105] \"2016-03-07 17:45:00 CET\"  \"2016-03-07 18:30:00 CET\" \n",
       " [107] \"2016-03-07 18:45:00 CET\"  \"2016-03-07 19:45:00 CET\" \n",
       " [109] \"2016-03-08 13:45:00 CET\"  \"2016-03-08 14:00:00 CET\" \n",
       " [111] \"2016-03-08 14:45:00 CET\"  \"2016-03-08 15:15:00 CET\" \n",
       " [113] \"2016-03-08 15:30:00 CET\"  \"2016-03-08 15:45:00 CET\" \n",
       " [115] \"2016-03-08 16:00:00 CET\"  \"2016-03-08 16:15:00 CET\" \n",
       " [117] \"2016-03-08 16:30:00 CET\"  \"2016-03-08 16:45:00 CET\" \n",
       " [119] \"2016-03-08 17:15:00 CET\"  \"2016-03-08 17:30:00 CET\" \n",
       " [121] \"2016-03-08 18:00:00 CET\"  \"2016-03-08 18:15:00 CET\" \n",
       " [123] \"2016-03-08 18:30:00 CET\"  \"2016-03-08 19:00:00 CET\" \n",
       " [125] \"2016-03-08 19:15:00 CET\"  \"2016-03-08 19:30:00 CET\" \n",
       " [127] \"2016-03-09 14:00:00 CET\"  \"2016-03-09 14:15:00 CET\" \n",
       " [129] \"2016-03-09 14:30:00 CET\"  \"2016-03-09 15:00:00 CET\" \n",
       " [131] \"2016-03-09 15:15:00 CET\"  \"2016-03-09 15:45:00 CET\" \n",
       " [133] \"2016-03-09 16:00:00 CET\"  \"2016-03-09 16:15:00 CET\" \n",
       " [135] \"2016-03-09 16:30:00 CET\"  \"2016-03-09 16:45:00 CET\" \n",
       " [137] \"2016-03-09 17:00:00 CET\"  \"2016-03-09 17:30:00 CET\" \n",
       " [139] \"2016-03-09 17:45:00 CET\"  \"2016-03-09 18:00:00 CET\" \n",
       " [141] \"2016-03-09 18:15:00 CET\"  \"2016-03-09 18:30:00 CET\" \n",
       " [143] \"2016-03-09 18:45:00 CET\"  \"2016-03-09 19:00:00 CET\" \n",
       " [145] \"2016-03-09 19:15:00 CET\"  \"2016-03-09 19:30:00 CET\" \n",
       " [147] \"2016-03-09 19:45:00 CET\"  \"2016-03-10 13:45:00 CET\" \n",
       " [149] \"2016-03-10 14:00:00 CET\"  \"2016-03-10 14:15:00 CET\" \n",
       " [151] \"2016-03-10 14:30:00 CET\"  \"2016-03-10 14:45:00 CET\" \n",
       " [153] \"2016-03-10 15:00:00 CET\"  \"2016-03-10 15:30:00 CET\" \n",
       " [155] \"2016-03-10 15:45:00 CET\"  \"2016-03-10 16:00:00 CET\" \n",
       " [157] \"2016-03-10 16:15:00 CET\"  \"2016-03-10 16:30:00 CET\" \n",
       " [159] \"2016-03-10 16:45:00 CET\"  \"2016-03-10 17:00:00 CET\" \n",
       " [161] \"2016-03-10 17:15:00 CET\"  \"2016-03-10 17:45:00 CET\" \n",
       " [163] \"2016-03-10 18:00:00 CET\"  \"2016-03-10 18:15:00 CET\" \n",
       " [165] \"2016-03-10 18:45:00 CET\"  \"2016-03-10 19:00:00 CET\" \n",
       " [167] \"2016-03-10 19:15:00 CET\"  \"2016-03-10 19:30:00 CET\" \n",
       " [169] \"2016-03-10 19:45:00 CET\"  \"2016-03-11 14:00:00 CET\" \n",
       " [171] \"2016-03-11 14:15:00 CET\"  \"2016-03-11 14:30:00 CET\" \n",
       " [173] \"2016-03-11 14:45:00 CET\"  \"2016-03-11 15:15:00 CET\" \n",
       " [175] \"2016-03-11 15:30:00 CET\"  \"2016-03-11 15:45:00 CET\" \n",
       " [177] \"2016-03-11 16:15:00 CET\"  \"2016-03-11 16:30:00 CET\" \n",
       " [179] \"2016-03-11 16:45:00 CET\"  \"2016-03-11 17:00:00 CET\" \n",
       " [181] \"2016-03-11 17:30:00 CET\"  \"2016-03-11 17:45:00 CET\" \n",
       " [183] \"2016-03-11 18:00:00 CET\"  \"2016-03-11 18:15:00 CET\" \n",
       " [185] \"2016-03-11 18:30:00 CET\"  \"2016-03-11 19:00:00 CET\" \n",
       " [187] \"2016-03-11 19:15:00 CET\"  \"2016-03-11 19:30:00 CET\" \n",
       " [189] \"2016-03-11 19:45:00 CET\"  \"2016-03-14 14:00:00 CET\" \n",
       " [191] \"2016-03-14 14:30:00 CET\"  \"2016-03-14 15:00:00 CET\" \n",
       " [193] \"2016-03-14 15:30:00 CET\"  \"2016-03-14 15:45:00 CET\" \n",
       " [195] \"2016-03-14 16:15:00 CET\"  \"2016-03-14 16:45:00 CET\" \n",
       " [197] \"2016-03-14 17:15:00 CET\"  \"2016-03-14 17:45:00 CET\" \n",
       " [199] \"2016-03-14 18:00:00 CET\"  \"2016-03-14 18:15:00 CET\" \n",
       " [201] \"2016-03-14 18:30:00 CET\"  \"2016-03-14 18:45:00 CET\" \n",
       " [203] \"2016-03-14 19:15:00 CET\"  \"2016-03-14 19:45:00 CET\" \n",
       " [205] \"2016-03-15 13:45:00 CET\"  \"2016-03-15 14:00:00 CET\" \n",
       " [207] \"2016-03-15 14:15:00 CET\"  \"2016-03-15 14:45:00 CET\" \n",
       " [209] \"2016-03-15 15:15:00 CET\"  \"2016-03-15 15:30:00 CET\" \n",
       " [211] \"2016-03-15 16:00:00 CET\"  \"2016-03-15 16:15:00 CET\" \n",
       " [213] \"2016-03-15 16:30:00 CET\"  \"2016-03-15 17:30:00 CET\" \n",
       " [215] \"2016-03-15 18:30:00 CET\"  \"2016-03-15 18:45:00 CET\" \n",
       " [217] \"2016-03-15 19:00:00 CET\"  \"2016-03-15 19:15:00 CET\" \n",
       " [219] \"2016-03-15 19:30:00 CET\"  \"2016-03-15 19:45:00 CET\" \n",
       " [221] \"2016-03-16 13:45:00 CET\"  \"2016-03-16 14:00:00 CET\" \n",
       " [223] \"2016-03-16 14:15:00 CET\"  \"2016-03-16 14:45:00 CET\" \n",
       " [225] \"2016-03-16 15:00:00 CET\"  \"2016-03-16 15:15:00 CET\" \n",
       " [227] \"2016-03-16 15:30:00 CET\"  \"2016-03-16 15:45:00 CET\" \n",
       " [229] \"2016-03-16 16:00:00 CET\"  \"2016-03-16 16:30:00 CET\" \n",
       " [231] \"2016-03-16 16:45:00 CET\"  \"2016-03-16 17:00:00 CET\" \n",
       " [233] \"2016-03-16 17:15:00 CET\"  \"2016-03-16 18:00:00 CET\" \n",
       " [235] \"2016-03-16 18:15:00 CET\"  \"2016-03-16 18:30:00 CET\" \n",
       " [237] \"2016-03-16 18:45:00 CET\"  \"2016-03-16 19:15:00 CET\" \n",
       " [239] \"2016-03-16 19:45:00 CET\"  \"2016-03-17 13:45:00 CET\" \n",
       " [241] \"2016-03-17 14:15:00 CET\"  \"2016-03-17 14:30:00 CET\" \n",
       " [243] \"2016-03-17 14:45:00 CET\"  \"2016-03-17 15:00:00 CET\" \n",
       " [245] \"2016-03-17 15:15:00 CET\"  \"2016-03-17 15:45:00 CET\" \n",
       " [247] \"2016-03-17 16:00:00 CET\"  \"2016-03-17 16:15:00 CET\" \n",
       " [249] \"2016-03-17 16:30:00 CET\"  \"2016-03-17 17:15:00 CET\" \n",
       " [251] \"2016-03-17 17:30:00 CET\"  \"2016-03-17 18:00:00 CET\" \n",
       " [253] \"2016-03-17 18:15:00 CET\"  \"2016-03-17 18:30:00 CET\" \n",
       " [255] \"2016-03-17 18:45:00 CET\"  \"2016-03-17 19:00:00 CET\" \n",
       " [257] \"2016-03-17 19:15:00 CET\"  \"2016-03-17 19:30:00 CET\" \n",
       " [259] \"2016-03-17 19:45:00 CET\"  \"2016-03-18 13:45:00 CET\" \n",
       " [261] \"2016-03-18 14:00:00 CET\"  \"2016-03-18 14:15:00 CET\" \n",
       " [263] \"2016-03-18 14:30:00 CET\"  \"2016-03-18 14:45:00 CET\" \n",
       " [265] \"2016-03-18 15:00:00 CET\"  \"2016-03-18 15:15:00 CET\" \n",
       " [267] \"2016-03-18 15:30:00 CET\"  \"2016-03-18 15:45:00 CET\" \n",
       " [269] \"2016-03-18 16:00:00 CET\"  \"2016-03-18 16:15:00 CET\" \n",
       " [271] \"2016-03-18 16:30:00 CET\"  \"2016-03-18 16:45:00 CET\" \n",
       " [273] \"2016-03-18 17:00:00 CET\"  \"2016-03-18 17:15:00 CET\" \n",
       " [275] \"2016-03-18 17:45:00 CET\"  \"2016-03-18 18:00:00 CET\" \n",
       " [277] \"2016-03-18 18:15:00 CET\"  \"2016-03-18 18:30:00 CET\" \n",
       " [279] \"2016-03-18 18:45:00 CET\"  \"2016-03-18 19:00:00 CET\" \n",
       " [281] \"2016-03-18 19:15:00 CET\"  \"2016-03-18 19:30:00 CET\" \n",
       " [283] \"2016-03-18 19:45:00 CET\"  \"2016-03-21 13:45:00 CET\" \n",
       " [285] \"2016-03-21 14:15:00 CET\"  \"2016-03-21 14:45:00 CET\" \n",
       " [287] \"2016-03-21 15:00:00 CET\"  \"2016-03-21 15:15:00 CET\" \n",
       " [289] \"2016-03-21 15:30:00 CET\"  \"2016-03-21 15:45:00 CET\" \n",
       " [291] \"2016-03-21 16:00:00 CET\"  \"2016-03-21 16:30:00 CET\" \n",
       " [293] \"2016-03-21 16:45:00 CET\"  \"2016-03-21 17:30:00 CET\" \n",
       " [295] \"2016-03-21 17:45:00 CET\"  \"2016-03-21 18:00:00 CET\" \n",
       " [297] \"2016-03-21 18:30:00 CET\"  \"2016-03-21 19:00:00 CET\" \n",
       " [299] \"2016-03-21 19:15:00 CET\"  \"2016-03-21 19:30:00 CET\" \n",
       " [301] \"2016-03-21 19:45:00 CET\"  \"2016-03-22 13:45:00 CET\" \n",
       " [303] \"2016-03-22 14:15:00 CET\"  \"2016-03-22 14:30:00 CET\" \n",
       " [305] \"2016-03-22 15:15:00 CET\"  \"2016-03-22 15:30:00 CET\" \n",
       " [307] \"2016-03-22 15:45:00 CET\"  \"2016-03-22 16:00:00 CET\" \n",
       " [309] \"2016-03-22 16:15:00 CET\"  \"2016-03-22 16:30:00 CET\" \n",
       " [311] \"2016-03-22 16:45:00 CET\"  \"2016-03-22 17:00:00 CET\" \n",
       " [313] \"2016-03-22 17:15:00 CET\"  \"2016-03-22 17:30:00 CET\" \n",
       " [315] \"2016-03-22 17:45:00 CET\"  \"2016-03-22 18:15:00 CET\" \n",
       " [317] \"2016-03-22 18:30:00 CET\"  \"2016-03-22 18:45:00 CET\" \n",
       " [319] \"2016-03-22 19:00:00 CET\"  \"2016-03-22 19:15:00 CET\" \n",
       " [321] \"2016-03-22 19:30:00 CET\"  \"2016-03-23 14:00:00 CET\" \n",
       " [323] \"2016-03-23 15:00:00 CET\"  \"2016-03-23 15:30:00 CET\" \n",
       " [325] \"2016-03-23 16:00:00 CET\"  \"2016-03-23 16:30:00 CET\" \n",
       " [327] \"2016-03-23 16:45:00 CET\"  \"2016-03-23 17:00:00 CET\" \n",
       " [329] \"2016-03-23 17:15:00 CET\"  \"2016-03-23 17:30:00 CET\" \n",
       " [331] \"2016-03-23 18:00:00 CET\"  \"2016-03-23 18:15:00 CET\" \n",
       " [333] \"2016-03-23 19:00:00 CET\"  \"2016-03-23 19:15:00 CET\" \n",
       " [335] \"2016-03-23 19:30:00 CET\"  \"2016-03-23 19:45:00 CET\" \n",
       " [337] \"2016-03-24 13:45:00 CET\"  \"2016-03-24 14:00:00 CET\" \n",
       " [339] \"2016-03-24 14:15:00 CET\"  \"2016-03-24 14:30:00 CET\" \n",
       " [341] \"2016-03-24 14:45:00 CET\"  \"2016-03-24 15:00:00 CET\" \n",
       " [343] \"2016-03-24 15:30:00 CET\"  \"2016-03-24 15:45:00 CET\" \n",
       " [345] \"2016-03-24 16:00:00 CET\"  \"2016-03-24 16:30:00 CET\" \n",
       " [347] \"2016-03-24 16:45:00 CET\"  \"2016-03-24 17:00:00 CET\" \n",
       " [349] \"2016-03-24 17:15:00 CET\"  \"2016-03-24 17:45:00 CET\" \n",
       " [351] \"2016-03-24 18:00:00 CET\"  \"2016-03-24 18:15:00 CET\" \n",
       " [353] \"2016-03-24 18:30:00 CET\"  \"2016-03-24 18:45:00 CET\" \n",
       " [355] \"2016-03-24 19:45:00 CET\"  \"2016-03-28 13:45:00 CEST\"\n",
       " [357] \"2016-03-28 14:00:00 CEST\" \"2016-03-28 14:15:00 CEST\"\n",
       " [359] \"2016-03-28 15:00:00 CEST\" \"2016-03-28 15:30:00 CEST\"\n",
       " [361] \"2016-03-28 16:00:00 CEST\" \"2016-03-28 16:30:00 CEST\"\n",
       " [363] \"2016-03-28 16:45:00 CEST\" \"2016-03-28 17:00:00 CEST\"\n",
       " [365] \"2016-03-28 17:15:00 CEST\" \"2016-03-28 17:30:00 CEST\"\n",
       " [367] \"2016-03-28 18:00:00 CEST\" \"2016-03-28 18:15:00 CEST\"\n",
       " [369] \"2016-03-28 18:30:00 CEST\" \"2016-03-29 14:00:00 CEST\"\n",
       " [371] \"2016-03-29 14:15:00 CEST\" \"2016-03-29 15:15:00 CEST\"\n",
       " [373] \"2016-03-29 15:30:00 CEST\" \"2016-03-29 15:45:00 CEST\"\n",
       " [375] \"2016-03-29 16:00:00 CEST\" \"2016-03-29 16:15:00 CEST\"\n",
       " [377] \"2016-03-29 16:45:00 CEST\" \"2016-03-29 17:00:00 CEST\"\n",
       " [379] \"2016-03-29 17:30:00 CEST\" \"2016-03-29 17:45:00 CEST\"\n",
       " [381] \"2016-03-29 18:15:00 CEST\" \"2016-03-29 18:30:00 CEST\"\n",
       " [383] \"2016-03-29 18:45:00 CEST\" \"2016-03-29 19:00:00 CEST\"\n",
       " [385] \"2016-03-29 19:15:00 CEST\" \"2016-03-29 19:30:00 CEST\"\n",
       " [387] \"2016-03-29 19:45:00 CEST\" \"2016-03-30 14:00:00 CEST\"\n",
       " [389] \"2016-03-30 14:30:00 CEST\" \"2016-03-30 14:45:00 CEST\"\n",
       " [391] \"2016-03-30 15:00:00 CEST\" \"2016-03-30 15:15:00 CEST\"\n",
       " [393] \"2016-03-30 15:45:00 CEST\" \"2016-03-30 16:00:00 CEST\"\n",
       " [395] \"2016-03-30 16:15:00 CEST\" \"2016-03-30 16:30:00 CEST\"\n",
       " [397] \"2016-03-30 16:45:00 CEST\" \"2016-03-30 17:15:00 CEST\"\n",
       " [399] \"2016-03-30 17:30:00 CEST\" \"2016-03-30 17:45:00 CEST\"\n",
       " [401] \"2016-03-30 18:00:00 CEST\" \"2016-03-30 18:45:00 CEST\"\n",
       " [403] \"2016-03-30 19:00:00 CEST\" \"2016-03-30 19:15:00 CEST\"\n",
       " [405] \"2016-03-31 14:00:00 CEST\" \"2016-03-31 14:15:00 CEST\"\n",
       " [407] \"2016-03-31 14:30:00 CEST\" \"2016-03-31 14:45:00 CEST\"\n",
       " [409] \"2016-03-31 15:15:00 CEST\" \"2016-03-31 15:30:00 CEST\"\n",
       " [411] \"2016-03-31 16:00:00 CEST\" \"2016-03-31 16:15:00 CEST\"\n",
       " [413] \"2016-03-31 16:30:00 CEST\" \"2016-03-31 16:45:00 CEST\"\n",
       " [415] \"2016-03-31 17:00:00 CEST\" \"2016-03-31 17:15:00 CEST\"\n",
       " [417] \"2016-03-31 17:30:00 CEST\" \"2016-03-31 17:45:00 CEST\"\n",
       " [419] \"2016-03-31 18:00:00 CEST\" \"2016-03-31 18:30:00 CEST\"\n",
       " [421] \"2016-03-31 18:45:00 CEST\" \"2016-03-31 19:00:00 CEST\"\n",
       " [423] \"2016-03-31 19:15:00 CEST\" \"2016-03-31 19:30:00 CEST\"\n",
       " [425] \"2016-03-31 19:45:00 CEST\" \"2016-04-01 13:45:00 CEST\"\n",
       " [427] \"2016-04-01 14:15:00 CEST\" \"2016-04-01 14:30:00 CEST\"\n",
       " [429] \"2016-04-01 14:45:00 CEST\" \"2016-04-01 15:30:00 CEST\"\n",
       " [431] \"2016-04-01 15:45:00 CEST\" \"2016-04-01 16:00:00 CEST\"\n",
       " [433] \"2016-04-01 16:15:00 CEST\" \"2016-04-01 16:30:00 CEST\"\n",
       " [435] \"2016-04-01 17:00:00 CEST\" \"2016-04-01 17:15:00 CEST\"\n",
       " [437] \"2016-04-01 17:30:00 CEST\" \"2016-04-01 17:45:00 CEST\"\n",
       " [439] \"2016-04-01 18:00:00 CEST\" \"2016-04-01 18:15:00 CEST\"\n",
       " [441] \"2016-04-01 18:30:00 CEST\" \"2016-04-01 18:45:00 CEST\"\n",
       " [443] \"2016-04-01 19:00:00 CEST\" \"2016-04-01 19:15:00 CEST\"\n",
       " [445] \"2016-04-04 13:45:00 CEST\" \"2016-04-04 14:00:00 CEST\"\n",
       " [447] \"2016-04-04 14:15:00 CEST\" \"2016-04-04 14:45:00 CEST\"\n",
       " [449] \"2016-04-04 15:00:00 CEST\" \"2016-04-04 15:45:00 CEST\"\n",
       " [451] \"2016-04-04 16:00:00 CEST\" \"2016-04-04 16:15:00 CEST\"\n",
       " [453] \"2016-04-04 17:15:00 CEST\" \"2016-04-04 17:30:00 CEST\"\n",
       " [455] \"2016-04-04 18:00:00 CEST\" \"2016-04-04 18:30:00 CEST\"\n",
       " [457] \"2016-04-04 19:00:00 CEST\" \"2016-04-04 19:15:00 CEST\"\n",
       " [459] \"2016-04-04 19:30:00 CEST\" \"2016-04-04 19:45:00 CEST\"\n",
       " [461] \"2016-04-05 14:00:00 CEST\" \"2016-04-05 14:15:00 CEST\"\n",
       " [463] \"2016-04-05 14:45:00 CEST\" \"2016-04-05 15:00:00 CEST\"\n",
       " [465] \"2016-04-05 15:15:00 CEST\" \"2016-04-05 15:30:00 CEST\"\n",
       " [467] \"2016-04-05 15:45:00 CEST\" \"2016-04-05 16:00:00 CEST\"\n",
       " [469] \"2016-04-05 16:15:00 CEST\" \"2016-04-05 16:30:00 CEST\"\n",
       " [471] \"2016-04-05 16:45:00 CEST\" \"2016-04-05 17:00:00 CEST\"\n",
       " [473] \"2016-04-05 17:15:00 CEST\" \"2016-04-05 17:30:00 CEST\"\n",
       " [475] \"2016-04-05 18:00:00 CEST\" \"2016-04-05 18:15:00 CEST\"\n",
       " [477] \"2016-04-05 18:30:00 CEST\" \"2016-04-05 18:45:00 CEST\"\n",
       " [479] \"2016-04-05 19:00:00 CEST\" \"2016-04-05 19:15:00 CEST\"\n",
       " [481] \"2016-04-05 19:30:00 CEST\" \"2016-04-05 19:45:00 CEST\"\n",
       " [483] \"2016-04-06 14:30:00 CEST\" \"2016-04-06 14:45:00 CEST\"\n",
       " [485] \"2016-04-06 15:00:00 CEST\" \"2016-04-06 15:15:00 CEST\"\n",
       " [487] \"2016-04-06 15:30:00 CEST\" \"2016-04-06 15:45:00 CEST\"\n",
       " [489] \"2016-04-06 16:00:00 CEST\" \"2016-04-06 16:15:00 CEST\"\n",
       " [491] \"2016-04-06 17:15:00 CEST\" \"2016-04-06 17:45:00 CEST\"\n",
       " [493] \"2016-04-06 18:00:00 CEST\" \"2016-04-06 18:15:00 CEST\"\n",
       " [495] \"2016-04-06 18:30:00 CEST\" \"2016-04-06 18:45:00 CEST\"\n",
       " [497] \"2016-04-06 19:00:00 CEST\" \"2016-04-06 19:30:00 CEST\"\n",
       " [499] \"2016-04-06 19:45:00 CEST\" \"2016-04-07 13:45:00 CEST\"\n",
       " [501] \"2016-04-07 14:00:00 CEST\" \"2016-04-07 14:30:00 CEST\"\n",
       " [503] \"2016-04-07 14:45:00 CEST\" \"2016-04-07 15:00:00 CEST\"\n",
       " [505] \"2016-04-07 15:45:00 CEST\" \"2016-04-07 16:00:00 CEST\"\n",
       " [507] \"2016-04-07 16:15:00 CEST\" \"2016-04-07 17:15:00 CEST\"\n",
       " [509] \"2016-04-07 17:30:00 CEST\" \"2016-04-07 18:15:00 CEST\"\n",
       " [511] \"2016-04-07 18:30:00 CEST\" \"2016-04-07 18:45:00 CEST\"\n",
       " [513] \"2016-04-07 19:00:00 CEST\" \"2016-04-07 19:15:00 CEST\"\n",
       " [515] \"2016-04-08 13:45:00 CEST\" \"2016-04-08 14:00:00 CEST\"\n",
       " [517] \"2016-04-08 14:30:00 CEST\" \"2016-04-08 14:45:00 CEST\"\n",
       " [519] \"2016-04-08 15:00:00 CEST\" \"2016-04-08 15:15:00 CEST\"\n",
       " [521] \"2016-04-08 15:30:00 CEST\" \"2016-04-08 16:00:00 CEST\"\n",
       " [523] \"2016-04-08 16:15:00 CEST\" \"2016-04-08 16:30:00 CEST\"\n",
       " [525] \"2016-04-08 17:00:00 CEST\" \"2016-04-08 17:45:00 CEST\"\n",
       " [527] \"2016-04-08 18:00:00 CEST\" \"2016-04-08 18:15:00 CEST\"\n",
       " [529] \"2016-04-08 19:45:00 CEST\" \"2016-04-11 14:15:00 CEST\"\n",
       " [531] \"2016-04-11 14:45:00 CEST\" \"2016-04-11 15:45:00 CEST\"\n",
       " [533] \"2016-04-11 16:30:00 CEST\" \"2016-04-11 17:00:00 CEST\"\n",
       " [535] \"2016-04-11 17:30:00 CEST\" \"2016-04-11 17:45:00 CEST\"\n",
       " [537] \"2016-04-11 18:00:00 CEST\" \"2016-04-11 18:15:00 CEST\"\n",
       " [539] \"2016-04-11 18:30:00 CEST\" \"2016-04-11 19:00:00 CEST\"\n",
       " [541] \"2016-04-11 19:45:00 CEST\" \"2016-04-12 13:45:00 CEST\"\n",
       " [543] \"2016-04-12 14:30:00 CEST\" \"2016-04-12 14:45:00 CEST\"\n",
       " [545] \"2016-04-12 15:15:00 CEST\" \"2016-04-12 15:30:00 CEST\"\n",
       " [547] \"2016-04-12 16:00:00 CEST\" \"2016-04-12 16:30:00 CEST\"\n",
       " [549] \"2016-04-12 16:45:00 CEST\" \"2016-04-12 17:00:00 CEST\"\n",
       " [551] \"2016-04-12 17:30:00 CEST\" \"2016-04-12 17:45:00 CEST\"\n",
       " [553] \"2016-04-12 18:15:00 CEST\" \"2016-04-12 18:30:00 CEST\"\n",
       " [555] \"2016-04-12 18:45:00 CEST\" \"2016-04-12 19:00:00 CEST\"\n",
       " [557] \"2016-04-12 19:30:00 CEST\" \"2016-04-12 19:45:00 CEST\"\n",
       " [559] \"2016-04-13 13:45:00 CEST\" \"2016-04-13 14:00:00 CEST\"\n",
       " [561] \"2016-04-13 14:15:00 CEST\" \"2016-04-13 15:15:00 CEST\"\n",
       " [563] \"2016-04-13 15:30:00 CEST\" \"2016-04-13 15:45:00 CEST\"\n",
       " [565] \"2016-04-13 16:00:00 CEST\" \"2016-04-13 16:15:00 CEST\"\n",
       " [567] \"2016-04-13 16:30:00 CEST\" \"2016-04-13 17:00:00 CEST\"\n",
       " [569] \"2016-04-13 17:45:00 CEST\" \"2016-04-13 18:00:00 CEST\"\n",
       " [571] \"2016-04-13 19:15:00 CEST\" \"2016-04-14 13:45:00 CEST\"\n",
       " [573] \"2016-04-14 14:00:00 CEST\" \"2016-04-14 14:30:00 CEST\"\n",
       " [575] \"2016-04-14 14:45:00 CEST\" \"2016-04-14 15:30:00 CEST\"\n",
       " [577] \"2016-04-14 15:45:00 CEST\" \"2016-04-14 16:00:00 CEST\"\n",
       " [579] \"2016-04-14 16:15:00 CEST\" \"2016-04-14 16:30:00 CEST\"\n",
       " [581] \"2016-04-14 17:00:00 CEST\" \"2016-04-14 17:30:00 CEST\"\n",
       " [583] \"2016-04-15 14:00:00 CEST\" \"2016-04-18 13:45:00 CEST\"\n",
       " [585] \"2016-04-18 14:00:00 CEST\" \"2016-04-18 14:15:00 CEST\"\n",
       " [587] \"2016-04-18 14:30:00 CEST\" \"2016-04-18 14:45:00 CEST\"\n",
       " [589] \"2016-04-18 15:00:00 CEST\" \"2016-04-18 15:30:00 CEST\"\n",
       " [591] \"2016-04-18 15:45:00 CEST\" \"2016-04-18 16:00:00 CEST\"\n",
       " [593] \"2016-04-18 16:15:00 CEST\" \"2016-04-18 16:30:00 CEST\"\n",
       " [595] \"2016-04-18 16:45:00 CEST\" \"2016-04-18 17:00:00 CEST\"\n",
       " [597] \"2016-04-18 17:15:00 CEST\" \"2016-04-18 17:30:00 CEST\"\n",
       " [599] \"2016-04-18 17:45:00 CEST\" \"2016-04-18 18:00:00 CEST\"\n",
       " [601] \"2016-04-18 18:15:00 CEST\" \"2016-04-18 18:30:00 CEST\"\n",
       " [603] \"2016-04-18 18:45:00 CEST\" \"2016-04-18 19:30:00 CEST\"\n",
       " [605] \"2016-04-18 19:45:00 CEST\" \"2016-04-19 13:45:00 CEST\"\n",
       " [607] \"2016-04-19 14:15:00 CEST\" \"2016-04-19 14:45:00 CEST\"\n",
       " [609] \"2016-04-19 15:00:00 CEST\" \"2016-04-19 15:15:00 CEST\"\n",
       " [611] \"2016-04-19 15:30:00 CEST\" \"2016-04-19 15:45:00 CEST\"\n",
       " [613] \"2016-04-19 16:00:00 CEST\" \"2016-04-19 16:15:00 CEST\"\n",
       " [615] \"2016-04-19 16:30:00 CEST\" \"2016-04-19 16:45:00 CEST\"\n",
       " [617] \"2016-04-19 17:00:00 CEST\" \"2016-04-19 17:30:00 CEST\"\n",
       " [619] \"2016-04-19 17:45:00 CEST\" \"2016-04-19 18:00:00 CEST\"\n",
       " [621] \"2016-04-19 18:15:00 CEST\" \"2016-04-19 18:30:00 CEST\"\n",
       " [623] \"2016-04-19 18:45:00 CEST\" \"2016-04-19 19:00:00 CEST\"\n",
       " [625] \"2016-04-19 19:15:00 CEST\" \"2016-04-19 19:30:00 CEST\"\n",
       " [627] \"2016-04-19 19:45:00 CEST\" \"2016-04-20 13:45:00 CEST\"\n",
       " [629] \"2016-04-20 14:15:00 CEST\" \"2016-04-20 14:45:00 CEST\"\n",
       " [631] \"2016-04-20 15:30:00 CEST\" \"2016-04-20 15:45:00 CEST\"\n",
       " [633] \"2016-04-20 16:15:00 CEST\" \"2016-04-20 16:30:00 CEST\"\n",
       " [635] \"2016-04-20 16:45:00 CEST\" \"2016-04-20 17:00:00 CEST\"\n",
       " [637] \"2016-04-20 17:45:00 CEST\" \"2016-04-20 18:00:00 CEST\"\n",
       " [639] \"2016-04-20 18:15:00 CEST\" \"2016-04-20 18:45:00 CEST\"\n",
       " [641] \"2016-04-20 19:00:00 CEST\" \"2016-04-20 19:15:00 CEST\"\n",
       " [643] \"2016-04-20 19:30:00 CEST\" \"2016-04-21 13:45:00 CEST\"\n",
       " [645] \"2016-04-21 14:00:00 CEST\" \"2016-04-21 14:15:00 CEST\"\n",
       " [647] \"2016-04-21 14:30:00 CEST\" \"2016-04-21 15:30:00 CEST\"\n",
       " [649] \"2016-04-21 15:45:00 CEST\" \"2016-04-21 16:00:00 CEST\"\n",
       " [651] \"2016-04-21 16:15:00 CEST\" \"2016-04-21 16:30:00 CEST\"\n",
       " [653] \"2016-04-21 16:45:00 CEST\" \"2016-04-21 17:00:00 CEST\"\n",
       " [655] \"2016-04-21 17:15:00 CEST\" \"2016-04-21 17:30:00 CEST\"\n",
       " [657] \"2016-04-21 17:45:00 CEST\" \"2016-04-21 18:15:00 CEST\"\n",
       " [659] \"2016-04-21 18:30:00 CEST\" \"2016-04-21 18:45:00 CEST\"\n",
       " [661] \"2016-04-21 19:00:00 CEST\" \"2016-04-21 19:15:00 CEST\"\n",
       " [663] \"2016-04-21 19:30:00 CEST\" \"2016-04-21 19:45:00 CEST\"\n",
       " [665] \"2016-04-22 13:45:00 CEST\" \"2016-04-22 14:15:00 CEST\"\n",
       " [667] \"2016-04-22 14:45:00 CEST\" \"2016-04-22 15:00:00 CEST\"\n",
       " [669] \"2016-04-22 15:15:00 CEST\" \"2016-04-22 15:30:00 CEST\"\n",
       " [671] \"2016-04-22 16:00:00 CEST\" \"2016-04-22 16:15:00 CEST\"\n",
       " [673] \"2016-04-22 16:30:00 CEST\" \"2016-04-22 17:30:00 CEST\"\n",
       " [675] \"2016-04-22 18:00:00 CEST\" \"2016-04-22 18:15:00 CEST\"\n",
       " [677] \"2016-04-22 18:30:00 CEST\" \"2016-04-22 18:45:00 CEST\"\n",
       " [679] \"2016-04-22 19:15:00 CEST\" \"2016-04-22 19:45:00 CEST\"\n",
       " [681] \"2016-04-25 13:45:00 CEST\" \"2016-04-25 14:00:00 CEST\"\n",
       " [683] \"2016-04-25 14:15:00 CEST\" \"2016-04-25 14:30:00 CEST\"\n",
       " [685] \"2016-04-25 14:45:00 CEST\" \"2016-04-25 15:00:00 CEST\"\n",
       " [687] \"2016-04-25 15:15:00 CEST\" \"2016-04-25 15:30:00 CEST\"\n",
       " [689] \"2016-04-25 16:00:00 CEST\" \"2016-04-25 16:15:00 CEST\"\n",
       " [691] \"2016-04-25 16:45:00 CEST\" \"2016-04-25 17:00:00 CEST\"\n",
       " [693] \"2016-04-25 17:15:00 CEST\" \"2016-04-25 18:00:00 CEST\"\n",
       " [695] \"2016-04-25 18:15:00 CEST\" \"2016-04-25 18:30:00 CEST\"\n",
       " [697] \"2016-04-25 18:45:00 CEST\" \"2016-04-25 19:00:00 CEST\"\n",
       " [699] \"2016-04-25 19:30:00 CEST\" \"2016-04-26 13:45:00 CEST\"\n",
       " [701] \"2016-04-26 14:00:00 CEST\" \"2016-04-26 14:15:00 CEST\"\n",
       " [703] \"2016-04-26 14:30:00 CEST\" \"2016-04-26 14:45:00 CEST\"\n",
       " [705] \"2016-04-26 15:00:00 CEST\" \"2016-04-26 15:15:00 CEST\"\n",
       " [707] \"2016-04-26 15:30:00 CEST\" \"2016-04-26 16:00:00 CEST\"\n",
       " [709] \"2016-04-26 16:15:00 CEST\" \"2016-04-26 16:30:00 CEST\"\n",
       " [711] \"2016-04-26 16:45:00 CEST\" \"2016-04-26 17:15:00 CEST\"\n",
       " [713] \"2016-04-26 17:30:00 CEST\" \"2016-04-26 17:45:00 CEST\"\n",
       " [715] \"2016-04-26 18:00:00 CEST\" \"2016-04-26 18:15:00 CEST\"\n",
       " [717] \"2016-04-26 18:30:00 CEST\" \"2016-04-26 18:45:00 CEST\"\n",
       " [719] \"2016-04-26 19:00:00 CEST\" \"2016-04-26 19:15:00 CEST\"\n",
       " [721] \"2016-04-26 19:30:00 CEST\" \"2016-04-27 13:45:00 CEST\"\n",
       " [723] \"2016-04-27 14:00:00 CEST\" \"2016-04-27 14:15:00 CEST\"\n",
       " [725] \"2016-04-27 14:30:00 CEST\" \"2016-04-27 14:45:00 CEST\"\n",
       " [727] \"2016-04-27 15:15:00 CEST\" \"2016-04-27 15:30:00 CEST\"\n",
       " [729] \"2016-04-27 15:45:00 CEST\" \"2016-04-27 16:00:00 CEST\"\n",
       " [731] \"2016-04-27 16:15:00 CEST\" \"2016-04-27 16:30:00 CEST\"\n",
       " [733] \"2016-04-27 16:45:00 CEST\" \"2016-04-27 17:00:00 CEST\"\n",
       " [735] \"2016-04-27 17:15:00 CEST\" \"2016-04-27 18:30:00 CEST\"\n",
       " [737] \"2016-04-27 19:15:00 CEST\" \"2016-04-27 19:30:00 CEST\"\n",
       " [739] \"2016-04-27 19:45:00 CEST\" \"2016-04-28 13:45:00 CEST\"\n",
       " [741] \"2016-04-28 14:00:00 CEST\" \"2016-04-28 14:15:00 CEST\"\n",
       " [743] \"2016-04-28 14:30:00 CEST\" \"2016-04-28 14:45:00 CEST\"\n",
       " [745] \"2016-04-28 15:00:00 CEST\" \"2016-04-28 15:15:00 CEST\"\n",
       " [747] \"2016-04-28 15:30:00 CEST\" \"2016-04-28 15:45:00 CEST\"\n",
       " [749] \"2016-04-28 16:00:00 CEST\" \"2016-04-28 16:15:00 CEST\"\n",
       " [751] \"2016-04-28 16:30:00 CEST\" \"2016-04-28 17:00:00 CEST\"\n",
       " [753] \"2016-04-28 17:15:00 CEST\" \"2016-04-28 17:30:00 CEST\"\n",
       " [755] \"2016-04-28 17:45:00 CEST\" \"2016-04-28 18:00:00 CEST\"\n",
       " [757] \"2016-04-28 18:15:00 CEST\" \"2016-04-28 18:30:00 CEST\"\n",
       " [759] \"2016-04-28 18:45:00 CEST\" \"2016-04-28 19:00:00 CEST\"\n",
       " [761] \"2016-04-28 19:15:00 CEST\" \"2016-04-28 19:45:00 CEST\"\n",
       " [763] \"2016-04-29 13:45:00 CEST\" \"2016-04-29 14:00:00 CEST\"\n",
       " [765] \"2016-04-29 14:15:00 CEST\" \"2016-04-29 14:30:00 CEST\"\n",
       " [767] \"2016-04-29 14:45:00 CEST\" \"2016-04-29 15:00:00 CEST\"\n",
       " [769] \"2016-04-29 15:15:00 CEST\" \"2016-04-29 15:30:00 CEST\"\n",
       " [771] \"2016-04-29 15:45:00 CEST\" \"2016-04-29 16:00:00 CEST\"\n",
       " [773] \"2016-04-29 16:15:00 CEST\" \"2016-04-29 16:30:00 CEST\"\n",
       " [775] \"2016-04-29 16:45:00 CEST\" \"2016-04-29 17:00:00 CEST\"\n",
       " [777] \"2016-04-29 17:15:00 CEST\" \"2016-04-29 17:30:00 CEST\"\n",
       " [779] \"2016-04-29 17:45:00 CEST\" \"2016-04-29 18:00:00 CEST\"\n",
       " [781] \"2016-04-29 18:15:00 CEST\" \"2016-04-29 18:30:00 CEST\"\n",
       " [783] \"2016-04-29 18:45:00 CEST\" \"2016-04-29 19:00:00 CEST\"\n",
       " [785] \"2016-04-29 19:15:00 CEST\" \"2016-04-29 19:30:00 CEST\"\n",
       " [787] \"2016-04-29 19:45:00 CEST\" \"2016-05-02 13:45:00 CEST\"\n",
       " [789] \"2016-05-02 14:15:00 CEST\" \"2016-05-02 14:30:00 CEST\"\n",
       " [791] \"2016-05-02 15:00:00 CEST\" \"2016-05-02 15:30:00 CEST\"\n",
       " [793] \"2016-05-02 15:45:00 CEST\" \"2016-05-02 16:30:00 CEST\"\n",
       " [795] \"2016-05-02 16:45:00 CEST\" \"2016-05-02 17:00:00 CEST\"\n",
       " [797] \"2016-05-02 17:30:00 CEST\" \"2016-05-02 17:45:00 CEST\"\n",
       " [799] \"2016-05-02 18:00:00 CEST\" \"2016-05-02 18:30:00 CEST\"\n",
       " [801] \"2016-05-02 18:45:00 CEST\" \"2016-05-02 19:00:00 CEST\"\n",
       " [803] \"2016-05-02 19:15:00 CEST\" \"2016-05-02 19:30:00 CEST\"\n",
       " [805] \"2016-05-02 19:45:00 CEST\" \"2016-05-03 13:45:00 CEST\"\n",
       " [807] \"2016-05-03 14:00:00 CEST\" \"2016-05-03 14:15:00 CEST\"\n",
       " [809] \"2016-05-03 14:30:00 CEST\" \"2016-05-03 14:45:00 CEST\"\n",
       " [811] \"2016-05-03 15:00:00 CEST\" \"2016-05-03 15:15:00 CEST\"\n",
       " [813] \"2016-05-03 15:30:00 CEST\" \"2016-05-03 15:45:00 CEST\"\n",
       " [815] \"2016-05-03 16:00:00 CEST\" \"2016-05-03 16:15:00 CEST\"\n",
       " [817] \"2016-05-03 16:30:00 CEST\" \"2016-05-03 16:45:00 CEST\"\n",
       " [819] \"2016-05-03 17:00:00 CEST\" \"2016-05-03 17:15:00 CEST\"\n",
       " [821] \"2016-05-03 17:30:00 CEST\" \"2016-05-03 17:45:00 CEST\"\n",
       " [823] \"2016-05-03 18:00:00 CEST\" \"2016-05-03 18:30:00 CEST\"\n",
       " [825] \"2016-05-03 18:45:00 CEST\" \"2016-05-03 19:00:00 CEST\"\n",
       " [827] \"2016-05-03 19:45:00 CEST\" \"2016-05-04 13:45:00 CEST\"\n",
       " [829] \"2016-05-04 14:15:00 CEST\" \"2016-05-04 14:30:00 CEST\"\n",
       " [831] \"2016-05-04 14:45:00 CEST\" \"2016-05-04 15:15:00 CEST\"\n",
       " [833] \"2016-05-04 15:30:00 CEST\" \"2016-05-04 15:45:00 CEST\"\n",
       " [835] \"2016-05-04 16:00:00 CEST\" \"2016-05-04 16:15:00 CEST\"\n",
       " [837] \"2016-05-04 16:30:00 CEST\" \"2016-05-04 16:45:00 CEST\"\n",
       " [839] \"2016-05-04 17:00:00 CEST\" \"2016-05-04 17:30:00 CEST\"\n",
       " [841] \"2016-05-04 17:45:00 CEST\" \"2016-05-04 18:00:00 CEST\"\n",
       " [843] \"2016-05-04 18:15:00 CEST\" \"2016-05-04 18:30:00 CEST\"\n",
       " [845] \"2016-05-04 18:45:00 CEST\" \"2016-05-04 19:00:00 CEST\"\n",
       " [847] \"2016-05-04 19:15:00 CEST\" \"2016-05-04 19:30:00 CEST\"\n",
       " [849] \"2016-05-04 19:45:00 CEST\" \"2016-05-05 13:45:00 CEST\"\n",
       " [851] \"2016-05-05 14:15:00 CEST\" \"2016-05-05 14:30:00 CEST\"\n",
       " [853] \"2016-05-05 14:45:00 CEST\" \"2016-05-05 15:15:00 CEST\"\n",
       " [855] \"2016-05-05 15:30:00 CEST\" \"2016-05-05 15:45:00 CEST\"\n",
       " [857] \"2016-05-05 16:00:00 CEST\" \"2016-05-05 16:15:00 CEST\"\n",
       " [859] \"2016-05-05 16:45:00 CEST\" \"2016-05-05 17:00:00 CEST\"\n",
       " [861] \"2016-05-05 17:15:00 CEST\" \"2016-05-05 17:30:00 CEST\"\n",
       " [863] \"2016-05-05 17:45:00 CEST\" \"2016-05-05 18:00:00 CEST\"\n",
       " [865] \"2016-05-05 18:15:00 CEST\" \"2016-05-05 18:30:00 CEST\"\n",
       " [867] \"2016-05-05 18:45:00 CEST\" \"2016-05-05 19:00:00 CEST\"\n",
       " [869] \"2016-05-05 19:15:00 CEST\" \"2016-05-05 19:30:00 CEST\"\n",
       " [871] \"2016-05-05 19:45:00 CEST\" \"2016-05-06 13:45:00 CEST\"\n",
       " [873] \"2016-05-06 14:00:00 CEST\" \"2016-05-06 14:15:00 CEST\"\n",
       " [875] \"2016-05-06 14:45:00 CEST\" \"2016-05-06 15:00:00 CEST\"\n",
       " [877] \"2016-05-06 15:15:00 CEST\" \"2016-05-06 15:30:00 CEST\"\n",
       " [879] \"2016-05-06 15:45:00 CEST\" \"2016-05-06 16:00:00 CEST\"\n",
       " [881] \"2016-05-06 16:15:00 CEST\" \"2016-05-06 16:30:00 CEST\"\n",
       " [883] \"2016-05-06 16:45:00 CEST\" \"2016-05-06 17:00:00 CEST\"\n",
       " [885] \"2016-05-06 17:15:00 CEST\" \"2016-05-06 17:45:00 CEST\"\n",
       " [887] \"2016-05-06 18:00:00 CEST\" \"2016-05-06 18:15:00 CEST\"\n",
       " [889] \"2016-05-06 18:30:00 CEST\" \"2016-05-06 18:45:00 CEST\"\n",
       " [891] \"2016-05-06 19:00:00 CEST\" \"2016-05-06 19:15:00 CEST\"\n",
       " [893] \"2016-05-06 19:30:00 CEST\" \"2016-05-06 19:45:00 CEST\"\n",
       " [895] \"2016-05-09 13:45:00 CEST\" \"2016-05-09 14:15:00 CEST\"\n",
       " [897] \"2016-05-09 14:30:00 CEST\" \"2016-05-09 14:45:00 CEST\"\n",
       " [899] \"2016-05-09 15:00:00 CEST\" \"2016-05-09 15:15:00 CEST\"\n",
       " [901] \"2016-05-09 15:30:00 CEST\" \"2016-05-09 15:45:00 CEST\"\n",
       " [903] \"2016-05-09 16:15:00 CEST\" \"2016-05-09 17:00:00 CEST\"\n",
       " [905] \"2016-05-09 17:15:00 CEST\" \"2016-05-09 17:30:00 CEST\"\n",
       " [907] \"2016-05-09 17:45:00 CEST\" \"2016-05-09 18:00:00 CEST\"\n",
       " [909] \"2016-05-09 18:15:00 CEST\" \"2016-05-09 18:30:00 CEST\"\n",
       " [911] \"2016-05-09 18:45:00 CEST\" \"2016-05-09 19:00:00 CEST\"\n",
       " [913] \"2016-05-09 19:15:00 CEST\" \"2016-05-09 19:30:00 CEST\"\n",
       " [915] \"2016-05-10 13:45:00 CEST\" \"2016-05-10 14:00:00 CEST\"\n",
       " [917] \"2016-05-10 14:15:00 CEST\" \"2016-05-10 14:30:00 CEST\"\n",
       " [919] \"2016-05-10 14:45:00 CEST\" \"2016-05-10 15:00:00 CEST\"\n",
       " [921] \"2016-05-10 15:30:00 CEST\" \"2016-05-10 15:45:00 CEST\"\n",
       " [923] \"2016-05-10 16:00:00 CEST\" \"2016-05-10 16:15:00 CEST\"\n",
       " [925] \"2016-05-10 16:30:00 CEST\" \"2016-05-10 16:45:00 CEST\"\n",
       " [927] \"2016-05-10 17:30:00 CEST\" \"2016-05-10 17:45:00 CEST\"\n",
       " [929] \"2016-05-10 18:00:00 CEST\" \"2016-05-10 18:15:00 CEST\"\n",
       " [931] \"2016-05-10 18:30:00 CEST\" \"2016-05-10 18:45:00 CEST\"\n",
       " [933] \"2016-05-10 19:00:00 CEST\" \"2016-05-10 19:15:00 CEST\"\n",
       " [935] \"2016-05-10 19:30:00 CEST\" \"2016-05-10 19:45:00 CEST\"\n",
       " [937] \"2016-05-11 13:45:00 CEST\" \"2016-05-11 14:00:00 CEST\"\n",
       " [939] \"2016-05-11 14:15:00 CEST\" \"2016-05-11 14:30:00 CEST\"\n",
       " [941] \"2016-05-11 14:45:00 CEST\" \"2016-05-11 15:00:00 CEST\"\n",
       " [943] \"2016-05-11 15:15:00 CEST\" \"2016-05-11 15:30:00 CEST\"\n",
       " [945] \"2016-05-11 15:45:00 CEST\" \"2016-05-11 16:00:00 CEST\"\n",
       " [947] \"2016-05-11 16:15:00 CEST\" \"2016-05-11 16:30:00 CEST\"\n",
       " [949] \"2016-05-11 16:45:00 CEST\" \"2016-05-11 17:00:00 CEST\"\n",
       " [951] \"2016-05-11 17:45:00 CEST\" \"2016-05-11 18:00:00 CEST\"\n",
       " [953] \"2016-05-11 18:15:00 CEST\" \"2016-05-11 18:30:00 CEST\"\n",
       " [955] \"2016-05-11 18:45:00 CEST\" \"2016-05-11 19:00:00 CEST\"\n",
       " [957] \"2016-05-11 19:15:00 CEST\" \"2016-05-11 19:30:00 CEST\"\n",
       " [959] \"2016-05-11 19:45:00 CEST\" \"2016-05-12 14:00:00 CEST\"\n",
       " [961] \"2016-05-12 14:15:00 CEST\" \"2016-05-12 14:30:00 CEST\"\n",
       " [963] \"2016-05-12 14:45:00 CEST\" \"2016-05-12 15:00:00 CEST\"\n",
       " [965] \"2016-05-12 15:15:00 CEST\" \"2016-05-12 15:30:00 CEST\"\n",
       " [967] \"2016-05-12 15:45:00 CEST\" \"2016-05-12 16:00:00 CEST\"\n",
       " [969] \"2016-05-12 16:30:00 CEST\" \"2016-05-12 16:45:00 CEST\"\n",
       " [971] \"2016-05-12 17:00:00 CEST\" \"2016-05-12 17:15:00 CEST\"\n",
       " [973] \"2016-05-12 17:30:00 CEST\" \"2016-05-12 17:45:00 CEST\"\n",
       " [975] \"2016-05-12 18:00:00 CEST\" \"2016-05-12 18:45:00 CEST\"\n",
       " [977] \"2016-05-12 19:00:00 CEST\" \"2016-05-12 19:30:00 CEST\"\n",
       " [979] \"2016-05-12 19:45:00 CEST\" \"2016-05-13 14:00:00 CEST\"\n",
       " [981] \"2016-05-13 14:15:00 CEST\" \"2016-05-13 14:45:00 CEST\"\n",
       " [983] \"2016-05-13 15:00:00 CEST\" \"2016-05-13 15:15:00 CEST\"\n",
       " [985] \"2016-05-13 15:30:00 CEST\" \"2016-05-13 16:00:00 CEST\"\n",
       " [987] \"2016-05-13 16:15:00 CEST\" \"2016-05-13 16:30:00 CEST\"\n",
       " [989] \"2016-05-13 16:45:00 CEST\" \"2016-05-13 17:00:00 CEST\"\n",
       " [991] \"2016-05-13 17:15:00 CEST\" \"2016-05-13 17:30:00 CEST\"\n",
       " [993] \"2016-05-13 17:45:00 CEST\" \"2016-05-13 18:00:00 CEST\"\n",
       " [995] \"2016-05-13 18:15:00 CEST\" \"2016-05-13 18:30:00 CEST\"\n",
       " [997] \"2016-05-13 18:45:00 CEST\" \"2016-05-13 19:00:00 CEST\"\n",
       " [999] \"2016-05-13 19:15:00 CEST\" \"2016-05-13 19:30:00 CEST\"\n",
       "[1001] \"2016-05-13 19:45:00 CEST\" \"2016-05-16 13:45:00 CEST\"\n",
       "[1003] \"2016-05-16 14:30:00 CEST\" \"2016-05-16 14:45:00 CEST\"\n",
       "[1005] \"2016-05-16 15:00:00 CEST\" \"2016-05-16 15:15:00 CEST\"\n",
       "[1007] \"2016-05-16 15:30:00 CEST\" \"2016-05-16 15:45:00 CEST\"\n",
       "[1009] \"2016-05-16 16:15:00 CEST\" \"2016-05-16 16:30:00 CEST\"\n",
       "[1011] \"2016-05-16 16:45:00 CEST\" \"2016-05-16 17:00:00 CEST\"\n",
       "[1013] \"2016-05-16 17:15:00 CEST\" \"2016-05-16 17:30:00 CEST\"\n",
       "[1015] \"2016-05-16 17:45:00 CEST\" \"2016-05-16 18:00:00 CEST\"\n",
       "[1017] \"2016-05-16 18:15:00 CEST\" \"2016-05-16 18:30:00 CEST\"\n",
       "[1019] \"2016-05-16 19:00:00 CEST\" \"2016-05-16 19:15:00 CEST\"\n",
       "[1021] \"2016-05-17 13:45:00 CEST\" \"2016-05-17 14:00:00 CEST\"\n",
       "[1023] \"2016-05-17 14:15:00 CEST\" \"2016-05-17 14:30:00 CEST\"\n",
       "[1025] \"2016-05-17 14:45:00 CEST\" \"2016-05-17 15:00:00 CEST\"\n",
       "[1027] \"2016-05-17 15:15:00 CEST\" \"2016-05-17 15:30:00 CEST\"\n",
       "[1029] \"2016-05-17 16:00:00 CEST\" \"2016-05-17 16:15:00 CEST\"\n",
       "[1031] \"2016-05-17 16:30:00 CEST\" \"2016-05-17 16:45:00 CEST\"\n",
       "[1033] \"2016-05-17 17:00:00 CEST\" \"2016-05-17 17:15:00 CEST\"\n",
       "[1035] \"2016-05-17 17:30:00 CEST\" \"2016-05-17 17:45:00 CEST\"\n",
       "[1037] \"2016-05-17 18:00:00 CEST\" \"2016-05-17 18:15:00 CEST\"\n",
       "[1039] \"2016-05-17 18:30:00 CEST\" \"2016-05-17 18:45:00 CEST\"\n",
       "[1041] \"2016-05-17 19:00:00 CEST\" \"2016-05-17 19:15:00 CEST\"\n",
       "[1043] \"2016-05-17 19:30:00 CEST\" \"2016-05-18 13:45:00 CEST\"\n",
       "[1045] \"2016-05-18 14:00:00 CEST\" \"2016-05-18 14:15:00 CEST\"\n",
       "[1047] \"2016-05-18 14:30:00 CEST\" \"2016-05-18 14:45:00 CEST\"\n",
       "[1049] \"2016-05-18 15:30:00 CEST\" \"2016-05-18 15:45:00 CEST\"\n",
       "[1051] \"2016-05-18 16:00:00 CEST\" \"2016-05-18 16:15:00 CEST\"\n",
       "[1053] \"2016-05-18 16:30:00 CEST\" \"2016-05-18 16:45:00 CEST\"\n",
       "[1055] \"2016-05-18 17:15:00 CEST\" \"2016-05-18 17:30:00 CEST\"\n",
       "[1057] \"2016-05-18 17:45:00 CEST\" \"2016-05-18 18:00:00 CEST\"\n",
       "[1059] \"2016-05-18 18:15:00 CEST\" \"2016-05-18 19:00:00 CEST\"\n",
       "[1061] \"2016-05-18 19:30:00 CEST\" \"2016-05-18 19:45:00 CEST\"\n",
       "[1063] \"2016-05-19 13:45:00 CEST\" \"2016-05-19 14:00:00 CEST\"\n",
       "[1065] \"2016-05-19 14:15:00 CEST\" \"2016-05-19 14:30:00 CEST\"\n",
       "[1067] \"2016-05-19 15:00:00 CEST\" \"2016-05-19 15:15:00 CEST\"\n",
       "[1069] \"2016-05-19 15:30:00 CEST\" \"2016-05-19 15:45:00 CEST\"\n",
       "[1071] \"2016-05-19 16:00:00 CEST\" \"2016-05-19 16:15:00 CEST\"\n",
       "[1073] \"2016-05-19 16:30:00 CEST\" \"2016-05-19 17:00:00 CEST\"\n",
       "[1075] \"2016-05-19 17:30:00 CEST\" \"2016-05-19 17:45:00 CEST\"\n",
       "[1077] \"2016-05-19 18:00:00 CEST\" \"2016-05-19 18:15:00 CEST\"\n",
       "[1079] \"2016-05-19 18:30:00 CEST\" \"2016-05-19 18:45:00 CEST\"\n",
       "[1081] \"2016-05-19 19:00:00 CEST\" \"2016-05-19 19:15:00 CEST\"\n",
       "[1083] \"2016-05-19 19:30:00 CEST\" \"2016-05-19 19:45:00 CEST\"\n",
       "[1085] \"2016-05-20 13:45:00 CEST\" \"2016-05-20 14:00:00 CEST\"\n",
       "[1087] \"2016-05-20 14:30:00 CEST\" \"2016-05-20 15:00:00 CEST\"\n",
       "[1089] \"2016-05-20 15:15:00 CEST\" \"2016-05-20 15:30:00 CEST\"\n",
       "[1091] \"2016-05-20 15:45:00 CEST\" \"2016-05-20 16:00:00 CEST\"\n",
       "[1093] \"2016-05-20 16:15:00 CEST\" \"2016-05-20 16:45:00 CEST\"\n",
       "[1095] \"2016-05-20 17:15:00 CEST\" \"2016-05-20 17:30:00 CEST\"\n",
       "[1097] \"2016-05-20 17:45:00 CEST\" \"2016-05-20 18:15:00 CEST\"\n",
       "[1099] \"2016-05-20 18:30:00 CEST\" \"2016-05-20 18:45:00 CEST\"\n",
       "[1101] \"2016-05-20 19:00:00 CEST\" \"2016-05-20 19:30:00 CEST\"\n",
       "[1103] \"2016-05-20 19:45:00 CEST\" \"2016-05-23 13:45:00 CEST\"\n",
       "[1105] \"2016-05-23 14:15:00 CEST\" \"2016-05-23 15:15:00 CEST\"\n",
       "[1107] \"2016-05-23 15:30:00 CEST\" \"2016-05-23 15:45:00 CEST\"\n",
       "[1109] \"2016-05-23 16:00:00 CEST\" \"2016-05-23 16:15:00 CEST\"\n",
       "[1111] \"2016-05-23 16:30:00 CEST\" \"2016-05-23 16:45:00 CEST\"\n",
       "[1113] \"2016-05-23 17:45:00 CEST\" \"2016-05-23 18:15:00 CEST\"\n",
       "[1115] \"2016-05-23 18:30:00 CEST\" \"2016-05-23 18:45:00 CEST\"\n",
       "[1117] \"2016-05-23 19:30:00 CEST\" \"2016-05-23 19:45:00 CEST\"\n",
       "[1119] \"2016-05-24 13:45:00 CEST\" \"2016-05-24 14:00:00 CEST\"\n",
       "[1121] \"2016-05-24 14:30:00 CEST\" \"2016-05-24 14:45:00 CEST\"\n",
       "[1123] \"2016-05-24 15:00:00 CEST\" \"2016-05-24 15:30:00 CEST\"\n",
       "[1125] \"2016-05-24 15:45:00 CEST\" \"2016-05-24 16:00:00 CEST\"\n",
       "[1127] \"2016-05-24 16:15:00 CEST\" \"2016-05-24 16:30:00 CEST\"\n",
       "[1129] \"2016-05-24 16:45:00 CEST\" \"2016-05-24 17:00:00 CEST\"\n",
       "[1131] \"2016-05-24 17:15:00 CEST\" \"2016-05-24 17:30:00 CEST\"\n",
       "[1133] \"2016-05-24 17:45:00 CEST\" \"2016-05-24 18:15:00 CEST\"\n",
       "[1135] \"2016-05-24 18:30:00 CEST\" \"2016-05-24 18:45:00 CEST\"\n",
       "[1137] \"2016-05-24 19:30:00 CEST\" \"2016-05-24 19:45:00 CEST\"\n",
       "[1139] \"2016-05-25 14:00:00 CEST\" \"2016-05-25 14:15:00 CEST\"\n",
       "[1141] \"2016-05-25 15:00:00 CEST\" \"2016-05-25 15:15:00 CEST\"\n",
       "[1143] \"2016-05-25 15:30:00 CEST\" \"2016-05-25 15:45:00 CEST\"\n",
       "[1145] \"2016-05-25 16:00:00 CEST\" \"2016-05-25 16:15:00 CEST\"\n",
       "[1147] \"2016-05-25 16:30:00 CEST\" \"2016-05-25 16:45:00 CEST\"\n",
       "[1149] \"2016-05-25 17:15:00 CEST\" \"2016-05-25 17:30:00 CEST\"\n",
       "[1151] \"2016-05-25 17:45:00 CEST\" \"2016-05-25 18:00:00 CEST\"\n",
       "[1153] \"2016-05-25 18:30:00 CEST\" \"2016-05-25 18:45:00 CEST\"\n",
       "[1155] \"2016-05-25 19:00:00 CEST\" \"2016-05-25 19:30:00 CEST\"\n",
       "[1157] \"2016-05-25 19:45:00 CEST\" \"2016-05-26 13:45:00 CEST\"\n",
       "[1159] \"2016-05-26 14:00:00 CEST\" \"2016-05-26 14:15:00 CEST\"\n",
       "[1161] \"2016-05-26 14:30:00 CEST\" \"2016-05-26 14:45:00 CEST\"\n",
       "[1163] \"2016-05-26 15:15:00 CEST\" \"2016-05-26 15:30:00 CEST\"\n",
       "[1165] \"2016-05-26 15:45:00 CEST\" \"2016-05-26 16:00:00 CEST\"\n",
       "[1167] \"2016-05-26 16:30:00 CEST\" \"2016-05-26 16:45:00 CEST\"\n",
       "[1169] \"2016-05-26 17:00:00 CEST\" \"2016-05-26 17:15:00 CEST\"\n",
       "[1171] \"2016-05-26 17:45:00 CEST\" \"2016-05-26 18:00:00 CEST\"\n",
       "[1173] \"2016-05-26 18:45:00 CEST\" \"2016-05-26 19:15:00 CEST\"\n",
       "[1175] \"2016-05-26 19:30:00 CEST\" \"2016-05-26 19:45:00 CEST\"\n",
       "[1177] \"2016-05-27 13:45:00 CEST\" \"2016-05-27 14:30:00 CEST\"\n",
       "[1179] \"2016-05-27 14:45:00 CEST\" \"2016-05-27 15:00:00 CEST\"\n",
       "[1181] \"2016-05-27 15:15:00 CEST\" \"2016-05-27 15:30:00 CEST\"\n",
       "[1183] \"2016-05-27 15:45:00 CEST\" \"2016-05-27 16:00:00 CEST\"\n",
       "[1185] \"2016-05-27 16:15:00 CEST\" \"2016-05-27 16:45:00 CEST\"\n",
       "[1187] \"2016-05-27 17:15:00 CEST\" \"2016-05-27 17:30:00 CEST\"\n",
       "[1189] \"2016-05-27 18:15:00 CEST\" \"2016-05-27 18:30:00 CEST\"\n",
       "[1191] \"2016-05-27 18:45:00 CEST\" \"2016-05-27 19:30:00 CEST\"\n",
       "[1193] \"2016-05-31 14:15:00 CEST\" \"2016-05-31 14:45:00 CEST\"\n",
       "[1195] \"2016-05-31 15:00:00 CEST\" \"2016-05-31 15:15:00 CEST\"\n",
       "[1197] \"2016-05-31 15:30:00 CEST\" \"2016-05-31 15:45:00 CEST\"\n",
       "[1199] \"2016-05-31 16:15:00 CEST\" \"2016-05-31 16:30:00 CEST\"\n",
       "[1201] \"2016-05-31 17:00:00 CEST\" \"2016-05-31 17:15:00 CEST\"\n",
       "[1203] \"2016-05-31 17:30:00 CEST\" \"2016-05-31 18:00:00 CEST\"\n",
       "[1205] \"2016-05-31 18:15:00 CEST\" \"2016-05-31 18:30:00 CEST\"\n",
       "[1207] \"2016-05-31 18:45:00 CEST\" \"2016-05-31 19:00:00 CEST\"\n",
       "[1209] \"2016-05-31 19:15:00 CEST\" \"2016-05-31 19:30:00 CEST\"\n",
       "[1211] \"2016-06-01 13:45:00 CEST\" \"2016-06-01 14:00:00 CEST\"\n",
       "[1213] \"2016-06-01 14:15:00 CEST\" \"2016-06-01 14:30:00 CEST\"\n",
       "[1215] \"2016-06-01 14:45:00 CEST\" \"2016-06-01 15:00:00 CEST\"\n",
       "[1217] \"2016-06-01 15:15:00 CEST\" \"2016-06-01 15:30:00 CEST\"\n",
       "[1219] \"2016-06-01 15:45:00 CEST\" \"2016-06-01 16:00:00 CEST\"\n",
       "[1221] \"2016-06-01 16:15:00 CEST\" \"2016-06-01 16:30:00 CEST\"\n",
       "[1223] \"2016-06-01 16:45:00 CEST\" \"2016-06-01 17:00:00 CEST\"\n",
       "[1225] \"2016-06-01 17:15:00 CEST\" \"2016-06-01 17:30:00 CEST\"\n",
       "[1227] \"2016-06-01 17:45:00 CEST\" \"2016-06-01 18:00:00 CEST\"\n",
       "[1229] \"2016-06-01 18:15:00 CEST\" \"2016-06-01 18:30:00 CEST\"\n",
       "[1231] \"2016-06-01 18:45:00 CEST\" \"2016-06-01 19:00:00 CEST\"\n",
       "[1233] \"2016-06-01 19:30:00 CEST\" \"2016-06-02 14:00:00 CEST\"\n",
       "[1235] \"2016-06-02 14:30:00 CEST\" \"2016-06-02 14:45:00 CEST\"\n",
       "[1237] \"2016-06-02 15:00:00 CEST\" \"2016-06-02 15:15:00 CEST\"\n",
       "[1239] \"2016-06-02 15:30:00 CEST\" \"2016-06-02 16:15:00 CEST\"\n",
       "[1241] \"2016-06-02 16:30:00 CEST\" \"2016-06-02 17:15:00 CEST\"\n",
       "[1243] \"2016-06-02 18:00:00 CEST\" \"2016-06-02 18:15:00 CEST\"\n",
       "[1245] \"2016-06-02 18:30:00 CEST\" \"2016-06-02 19:00:00 CEST\"\n",
       "[1247] \"2016-06-02 19:15:00 CEST\" \"2016-06-02 19:30:00 CEST\"\n",
       "[1249] \"2016-06-02 19:45:00 CEST\" \"2016-06-03 14:15:00 CEST\"\n",
       "[1251] \"2016-06-03 15:00:00 CEST\" \"2016-06-03 15:15:00 CEST\"\n",
       "[1253] \"2016-06-03 15:30:00 CEST\" \"2016-06-03 15:45:00 CEST\"\n",
       "[1255] \"2016-06-03 16:15:00 CEST\" \"2016-06-03 16:45:00 CEST\"\n",
       "[1257] \"2016-06-03 17:00:00 CEST\" \"2016-06-03 17:30:00 CEST\"\n",
       "[1259] \"2016-06-03 17:45:00 CEST\" \"2016-06-03 18:00:00 CEST\"\n",
       "[1261] \"2016-06-03 18:15:00 CEST\" \"2016-06-03 18:30:00 CEST\"\n",
       "[1263] \"2016-06-03 18:45:00 CEST\" \"2016-06-03 19:30:00 CEST\"\n",
       "[1265] \"2016-06-03 19:45:00 CEST\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.data$date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " [1] \"2016-06-02 16:15:00 CEST\" \"2016-06-02 16:30:00 CEST\"\n",
       " [3] \"2016-06-02 17:15:00 CEST\" \"2016-06-02 18:00:00 CEST\"\n",
       " [5] \"2016-06-02 18:15:00 CEST\" \"2016-06-02 18:30:00 CEST\"\n",
       " [7] \"2016-06-02 19:00:00 CEST\" \"2016-06-02 19:15:00 CEST\"\n",
       " [9] \"2016-06-02 19:30:00 CEST\" \"2016-06-02 19:45:00 CEST\"\n",
       "[11] \"2016-06-03 14:15:00 CEST\" \"2016-06-03 15:00:00 CEST\"\n",
       "[13] \"2016-06-03 15:15:00 CEST\" \"2016-06-03 15:30:00 CEST\"\n",
       "[15] \"2016-06-03 15:45:00 CEST\" \"2016-06-03 16:15:00 CEST\"\n",
       "[17] \"2016-06-03 16:45:00 CEST\" \"2016-06-03 17:00:00 CEST\"\n",
       "[19] \"2016-06-03 17:30:00 CEST\" \"2016-06-03 17:45:00 CEST\"\n",
       "[21] \"2016-06-03 18:00:00 CEST\" \"2016-06-03 18:15:00 CEST\"\n",
       "[23] \"2016-06-03 18:30:00 CEST\" \"2016-06-03 18:45:00 CEST\"\n",
       "[25] \"2016-06-03 19:30:00 CEST\" \"2016-06-03 19:45:00 CEST\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tail(exp.data$date,26)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       " [1] \"2016-05-23 16:30:00 CEST\" \"2016-05-23 16:45:00 CEST\"\n",
       " [3] \"2016-05-23 17:45:00 CEST\" \"2016-05-23 18:15:00 CEST\"\n",
       " [5] \"2016-05-23 18:30:00 CEST\" \"2016-05-23 18:45:00 CEST\"\n",
       " [7] \"2016-05-23 19:30:00 CEST\" \"2016-05-23 19:45:00 CEST\"\n",
       " [9] \"2016-05-24 13:45:00 CEST\" \"2016-05-24 14:00:00 CEST\"\n",
       "[11] \"2016-05-24 14:30:00 CEST\" \"2016-05-24 14:45:00 CEST\"\n",
       "[13] \"2016-05-24 15:00:00 CEST\" \"2016-05-24 15:30:00 CEST\"\n",
       "[15] \"2016-05-24 15:45:00 CEST\" \"2016-05-24 16:00:00 CEST\"\n",
       "[17] \"2016-05-24 16:15:00 CEST\" \"2016-05-24 16:30:00 CEST\"\n",
       "[19] \"2016-05-24 16:45:00 CEST\" \"2016-05-24 17:00:00 CEST\"\n",
       "[21] \"2016-05-24 17:15:00 CEST\" \"2016-05-24 17:30:00 CEST\"\n",
       "[23] \"2016-05-24 17:45:00 CEST\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "exp.data$date[1211:1233]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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WTuXDuPCz5B0Wvb1lupkvDVV/zNmzibAQAg2EGhmjNHc+YMM3iwOyFBMb3jQdFo\nmiQnu71eas0arLQDAECwg8Jz6hS7cKG2VClxwgQ0roPg6dvXbTBIqalqrxdbdQAg0iHYQeEQ\nRTJ2rM7nI7Nn200mZVxcFcKDXi89/7zn1i160yZM/wNApEOwg8KxYoUmM5Pr0MHbrp1iLkIP\nYWPoUBdNk8WLsYUCACIdgh0UguvX6ffe0xoM0owZdrlrgUhUpYrQurX3+HE2M5OTuxYAADkh\n2EEhGD9eb7VSkyc7YmNx9TCQx7BhbkLI0qXYQgEAEQ3BDh7Wli2qbdv4Ro38Awbg6mEgmyef\n9D7yiLB1q+rKFZzWACBy4QwID8VmoyZN0vE8+eADG41XE8iHosiQIS6/n6xahZV2ABC58FYM\nD+Wdd3TXrtGjRjlr1MDVw0BmPXt6oqOl1avVLhf6ngBAhEKwg4I7epRds0ZdtarwyisuuWsB\nIBqN1Lu3Ozub+vJLldy1AADIA8EOCsjrJWPGGCSJzJljV6nQuA5CQnKyi2XJkiUaCS9JAIhI\nCHZQQPPna3/7jend2/3447h6GISK8uXFpCTvb78x+/ej7wkARCIEOyiIM2eY99/XlCghTp2K\nq4dBaBk+3EUIeestnQ+fOAAg8iDYQb5JEhk/Xu/1Uu++64iKwowXhJamTX09enhOnGBTUrRy\n1wIAEGwIdpBva9eqf/yRe+opb5cuHrlrAcjBzJn2smXFDz/UHj3Kyl0LAEBQIdhB/ty8Sb/z\njk6jkWbPxiQshCijUfrwQ5sgkFGjDG43Wp8AQARBsIP8mThRZzZTEyc6K1RA4zoIXS1b+gYM\ncJ85w0yfjglZAIggCHaQD3v28Js2qRo08A8disZ1EOrefttRpYqwbJkmPR07ZAEgUiDYQV45\nndTrr+tYlqSk2BlG7moAHkSrlT76yE5RZNQovc2GCVkAiAgIdpBXM2Zo//yTeeEFV716frlr\nAciT+HjfiBGuS5eYKVN0ctcCABAMCHaQJ//7H5uaqilfXnztNafctQDkw8SJzpo1/WvXqnft\n4uWuBQCgyCHYwYP5/WTsWL0gkJQUm1aLxnWgJDwvLVxo53nyyiv6rCxMyAJAmEOwgwf7+GPN\niRPsc895WrVCL39Qnrp1/WPGOG/coCdM0MtdCwBA0UKwgwe4dIlJSdHGxEhvv43GdaBUr7zi\nbNjQ//XXqm++UcldCwBAEUKwgwd49VW900m9/ba9eHFR7loACohlyUcf2dRqaUX/bIsAACAA\nSURBVPx4/Y0bOO8BQNjCCQ5y89lnqr17uRYtfM8/j6uHgbLFxQkTJzqzsqhRowwSVooCQJhC\nsIP7ysqipk7VqdXS++/bKSw6B+UbPtzVvLnv+++59evVctcCAFAkEOzgviZP1t+6Rb/2mrNy\nZVw9DMIBTZMFC+x6vTRxou7CBXTZBoAwhGAHOdu/n/viC1XNmv4XX8TVwyB8VKggvP22w+Gg\nRo7Ui1g1CgBhB8EOcuB2U6+8oqcokpJi53CZTQgv/fu727TxHjrELV+ukbsWAIBChmAHOZgz\nR3vhApOc7IqPx9XDIAy9/749Olp65x3tb79hQhYAwgqCHdzr1Cl20SJN2bLixIm4ehiEp9Kl\nxffes3s81MiRBh+6bgNAGGHlLgBCgtVKnT/PnDvHnD/PfPmlyucjs2bZ9Xr0hICw1a2b59tv\n+S1bVB99pH3lFXyGAYAwgWAXcez2vzPc2bP0uXPMuXPMrVv/Grvt2tXTtq1XrgoBgmPuXMfB\ng9zcudqnn/bWqYNVBwAQDhDswpnTSd0NcIEwd+4cc/PmvzIcTZOyZcUnnvBVqSJUrixUqSJU\nqSJUq4b+JhD+YmLEefPs/foZX3pJv2uXhecxRA0AiodgFya8XnLtGnPhAn36NHv6NHPxInPh\nAn3pEnNPQ4eoKKl+fX/16kL16v5KlcSKFYW4OEGrxfsZRKikJG/Pnu4NG9SzZ2vffBNXQwYA\nxUOwU6q//qI++4ycPKk9e5Y6d465evXefTBlyojNmvkCg3CVKwtVq4qVKwtqNTIcwL/MmOHY\nv5//6CNN27YebAMHAKVDsFOqqVPZFSsIITwhpFSpvzNcIMBVroxxOIA8MRqlDz+0de9uGjnS\nsHevWaPBHw4AKBiCnVLt3Uvr9eTbb20VK3p1OrwVARTcE0/4kpNdy5dr3nlH9957drnLAQAo\nOPSxU6SrV+lz56gWLUi9egJSHcDDmzLFWbWqkJqq/u47Xu5aAAAKDsFOkTIyOEJIy5Zy1wEQ\nLjQa6aOPbDRNxozRm82U3OUAABQQgp0iIdgBFLrGjf2jRrmuXaMnT9bLXQsAQAEh2ClSRgan\n1ZLGjeWuAyC8jBvnqF3bv2GDautWldy1AAAUBIKd8ty8SZ89yzRpIvJYCwRQqHieLF5sU6mk\n117T/fUXTo8AoDw4cylPYB728cfFB94TAPKrRg3htddct2/TY8diQhYAlAfBTnkQ7ACK1OjR\nziZNfNu38xs3YkIWABQGwU55MjI4npcaN0awAygSNE0++siu00njx+uvXMFJEgCUBOcshbl9\nm/79d6ZxY79aLXcpAOGrUiVh0iSn1UqNGWOQ0CkSAJQDwU5hDhzgJIk0b+6TuxCAMDdkiKtV\nK+/evdyaNfgUBQCKgWCnMOnpLCEIdgBFjqLIBx/Yo6KkKVN0584xcpcDAJAnCHYKk5HB8Txp\n3NgvdyEA4S82VnznHYfTSY0cqRcEuasBAMgDBDslyc6mfvuNbdDAp9Fg1Q9AMPTq5e7QwZuZ\nyS1ZopG7FgCAB0OwU5KDBzlRxDwsQFDNnWsvXlycMUP7yy84YQJAqMN5SkkCHewQ7ACCqVgx\nMSXF7vVSI0ZofPjjA4DQhmCnJAcOcBxHEhKwwA4gqNq183bt6jl+nJk1i5W7FgCA3CDYKYbV\nSp08ydar59fpsMAOINhmzrSXKSO99x67YAEW2wFA6EKwU4xDhzhBwDwsgDyio6UNG5wlS0rv\nvKMbPVrv9cpdEABAThDsFCOwwK5FCwQ7AHk0aCCkp3vr1/evX6/u0sV06xbOnwAQcnBiUoyM\nDI5hSHw8gh2AbGJjpc2bLe3aeTMzuaQk0+nTaFwMAKEFwU4ZHA7qxAm2bl2/0YgFdgBy0mql\nVaus48Y5L15kkpKi0tJ4uSsCAPgbgp0yHD7M+XxYYAcQEiiKvP66c8kSm89H+vc3zp+P7RQA\nECoQ7JQBHewAQk3Xrp6vv7ZGR4vTpunGjtWjxR0AhAIEO2VIT2dpmiQk4K0DIITEx/t27LBU\nry6sWaPu3dtksVByVwQAkQ7BTgFcLurnn7latfzR0VhgBxBaKlYUduwwJyZ69+7lEhOj/vgD\n2ykAQE4IdgqQmcl6vZiHBQhRer20Zo119GjXuXNMu3ZR+/dzclcEAJELwU4BsMAOIMQxDJk8\n2ZGSYrfbqR49TCtXquWuCAAiFIKdAqSncxRFmjTBJWIBQlr//u716y06nfT66/qJE3WiKHdB\nABB5EOxCncdD/e9/bI0aQvHieJcACHUtW/p27TJXqyYsW6bp3dtos2E7BQAEFYJdqDtyhPV4\nKMzDAihF5crCtm3mxx7z7dnDt29vunQJp1kACB6ccUIdFtgBKE50tPTFF5bBg92nTrFt2kQd\nPIjtFAAQJAh2oS4jg6Mo0qwZgh2AkrAsmTXLPmOGw2Khu3UzfvGFSu6KACAiINiFNK+XHD3K\nVqsmlCiBBXYAyjNsmGvdOqtKRV56yTBtGrZTAECRQ7ALaf/7H+dyYYEdgIK1bu399ltLuXLC\n/PmaIUMMLhe2UwBAEUKwC2lYYAcQBmrW9O/ebWna1Ldli6pdO9OVKzjxAkBRYYPzNJIkrV27\ndt++fYIgNG/efPDgwQxz74V37nef+91ut9tXr16dmZnpdrtr1aqVnJxctmzZwI/at2/f5s2b\nL126VL169REjRty9XXECwQ4L7ACULiZG/PJL6yuv6D//XJWUFLV2rbV+fXSmBIDCF6QPjhs2\nbNi+ffvgwYNfeOGF/fv3p6am5v0+97v9448//vnnn0eOHDllyhRBECZNmuRwOAgh6enpCxYs\nSExMnDhxot/vnz59uqjMhS1+PzlyhK1cWShTRpH1A8A/8bz00Ue2yZMdN2/SnTqZtm3j5a4I\nAMJQMIKdIAjbtm3r169f8+bNExIShgwZsmfPHo/Hk5f73O92h8Oxf//+oUOHNm7cuFatWhMm\nTHA4HJmZmYSQL7/8smfPnm3btm3QoMGoUaOMRuO1a9eC8GsWumPHWLsdC+wAwgdFkdGjXcuX\n2ySJDBxonD1bK3dFABBugjEVe+HCBYvF0qhRo8C3jRo1crlcv//+e926dR94H61Wm+PtUVFR\n1apVq1GjRuB2tVqtUqmys7Nv3Ljxxx9/vP7664HbY2NjZ82aFYTfsShggR1AWOrY0VOunNCv\nn3HOHO2lS3RKip2PpME7t5tyOimbjbLbKaeTOJ2UxUI7ncTlolwurmZNqlUruUsEULJgBLvs\n7GxCSLFixQLfarVatVptNpvzcp/AwN5/b69bt+68efPuPjw9Pd1qtdasWfOvv/4ihFy4cGH2\n7NnXr1+vVq3akCFDKlSocPeeLpfL57sTlSiKoijq7td3/xsiDhzgCCEtWvhzqeqfv0KIC8Ej\nnBc4wkVNQQVT/+/hf1TDhsKuXZY+fQwbNqgvXGBWr7YVKyY9/I+9R9G9JOx26vZt2uEgTifl\ncFBWK+VyUU4nZbVSDgflclF2O7Fa78S1wI1OJ+V0UhYLJT3oF33vPc3Qoe5Cr7noROZrOJgU\nVHBwjnDuPz8Ywc5ut3Mc98/dElqt1maz5eU+giDk/lhBELZs2bJq1arExMQaNWr8+OOPhJBV\nq1b179/fZDJ9/fXXb7755qJFi3Q6XeD+M2bM2LFjR+Dr6OjoXbt2/bOMuwlSdoJADh8mlSqR\n+vWjc7mbyWQKWkmFInSOcB5FRUXJXUL+qFQKa4QbExMjdwn5U1hHuFgxcuAA6duXfPMN98wz\nMRMnkubNSY0apNDfEQrrj+7KFbJvH/nhB/LDD+TUqXw8kGGI0UiMRlKmDKlalURHE52OaLXE\nYCBG452vo6KITkdEkYwdSyZO1BUrphs6tFCqDgbFnda0WoWtAVDcEb4bOYpI7jsHghHs9Hq9\nz+cTBOFuPnM6nXq9Pi/30Wq1uTz24sWLKSkp169fT05O7tChAyGEZVlCyMiRI+vUqUMIqVKl\nSv/+/Q8dOtS6devAQ+rUqeP339mMptPp7i71oyiK4ziv11tkhyF/jh6lrFa+UyfB48l56xzL\nsgzDeL1e6YGff0MDRVEsy94dLg19ijvCNE0zDKOgI8xxHE3TyjrCNE3fPYE8PJYl69aRKVPY\nuXOZIUMIISQmhjRpIjZpIjZrJjVuLD7ku0PgCN+zoDlfzp+n0tPpffuo9HT63Lk7kVOjIU88\nIZYqRYxGyWAgWi3RaqVAMtNoJKORGAxEq5W0WhIVJWm1JO9JmGGYOnXoNm3oESMIy/p79xYK\nXHlw8DxPUdTDHOEgC7yTCkKoH9i7eJ4nhITOW/MDsSwrSVIQjnAunzCDEeyio6MJIdnZ2cWL\nFyeEuN1ut9sduPGB9wl8sMjxsSdOnJg6deqjjz769ttv3/1pgS8qVqwY+Faj0ZQoUSIwPxvQ\ns2fPnj173v321q1bgS9omjYajfeMI8po924NIXxCgstmy3lKQq/XMwzjdDoL8W2mSDEMo9Pp\nQucIP5DBYGAYxuFwKOUkyHGcWq1W0BE2Go08z9tsNqUEO57neZ632+2F+2PHjycdOrDp6Vxm\nJnv4MLd9O719O00IYVlSq5Y/IcHfuLEvIcFXvny+d8ebTCaapvP7kjhzhjlwgDtwgMvI4K5e\nvbPBTq+XWrXyNm/ub97c16CBL++LAr1ekvc3ZZVKVaMGu2GDp3t309ChrCi6OncO6cwUHR1d\ngCMsI7VaTVGUy+WSu5C8CozoK+gIa7VaURTd7qJdS8AwjMzBrlKlSiaT6dixY23atCGE/Pzz\nz2q1Oi4uLi/34Tgux9t9Pt+cOXMSExOHDRv2z8nmihUrqtXqM2fONGzYkBDicDhu3rypxD52\ngQV22DkBEAlq1/bXru0fNowQQq5coTMzucOH2SNHuJMn2ePH2eXL1YSQ0qXF+HhfIOfVq+cv\nxP0WokhOn2bT09lAnvvrrzthLipKatvW27y5r2lTX716fjZIbU/Jo4/6N2yw9uhhfOEFA89L\nzzwTuqM1Dge5eZNotRTPK+PDCUSCYPylMgyTlJS0du3a2NhYmqZTU1MTExPVajUhZOfOnR6P\np1OnTrncJ8fbjxw5Yjab4+Lijhw5cveJKlSoUKpUqaeffnrhwoVDhgwxmUzr168vXrx4QkJC\nEH7NQiSK5OBBrmxZsWJFZYwVAUBhKVtWLFvW06WLhxDiclHHjrGHDrFHjnCZmeyWLaotW1SE\nEJVKatDAn5Dgj4/3xcf7ixfP92CeIJATJ9iDB7n0dO7QIS47+87H4+LFxQ4dPIGRuZo1/bRM\n18iIj/etXWvt1cs4ZIjhk09srVuHYrb75Re2b1/m8mVCSLESJcQyZcTYWLFcOaFMGbFMGbF8\neTHwBTIfBFmQPoL17t1bEISUlBRRFFu0aDFo0KDA7QcOHLBarZ06dcrlPjnefuXKFULIBx98\n8M9nGT58ePv27QOXpkhNTXU6nXXr1p0+fTqvtF4Cv/7Kms1UmzaheC4DgKDRaKRmzXzNmvkI\ncRFC/viDOXKE+/+cxx06xBGiIYRUriwERvKaNPFXr37fNObzkWPHuIwM9uBB7tAhzma7E+ZK\nlxa7dvUGnuiRR4QQ2YD42GO+NWtsffsaBgwwrFtnffzx0Jq+2LWLHzbM4HCQdu3I7du+q1fp\n335jjx/P4Z4lS4qxsWKZMmK5csL/fyHGxoqlSglKe2sCZaCUsrqliNyzxu6eJixyWbpUM2mS\n7v337X373neeXq/XBzq/KGuNndVqlbuQvDIYDIHmiFhjV0QCa+xu376tlLNQEa2xKxi7nfrl\nF/bQIfbQIe7wYc5svhPHdDqpdm1/06b+hARfmzaaYsW4ffvM+/Zxhw5xBw9yVuudu5UqJTZp\n4mvZ0peQ4KtePVTCnEqlYlk2cA2hgO++4/v1MzAM2bDBGjpLU9asUY8fr6dpadkyqV8/6vbt\n24HbzWbq+nX6xg364kXm7hcXLtBXrzI5bmqKipJKlRJLlxYrVhTuflGpkhgbK3BckVSu0DV2\nWVlZcheSV0FbY3fPRoV/CtaiCcgPXCIWAHKn10tNmviaNPER4hIEcurUnRnbw4fZw4e5w4c5\nQjQ0TViWeL13WvZUqyZ07uxr1szXvLmvbFllXKiwdWvv4sX2YcMMffsaN260NGwo8+dYQSCT\nJ+uWLdPExIhr1tiSkvSE/B2Ko6KkqCihRg2BkH+dvUWR3LxJX7lCX7vGXL1KX75MX7tGX71K\nX7nCnD3LnD7NEPKvHEfTpGxZcfFiW0IC3gUg3xDsQo4kkQMH2FKlxKpVlTFQBADyYhhSp46/\nTh1/crKbEHLjBh3YYHvsmNrloho1cgemWUuWVEaYu0fHjp7588nIkYbnnzd9/bWlTh3Zsp3D\nQQ0dati1i69WTVi/3lqpUl5P0TRNSpcWS5cWCbm3eEEgN2/Sly/T16/fyXyBwHf0KDtvnmbD\nBgQ7yDcEu5Dz229MVhb97LMhvckfAEJWqVJihw7eDh28JhPLcdytWyExd/wwevTwCAL18sv6\nbt2M33xjqVlThg+916/TffoYjx9nExJ8n3xii4kpnJTMMCSwx+KezJeYGPXdd/zZsww+4UN+\nybTlCe4Pl4gFALhHz57ulBR7djbdtavp99+ZBz+gUP36K5uUFHX8ONuzp/vrry2FlepyMXiw\nW5LI6tXqon4iCD8IdiEHwQ4A4L/69nVPm+a4dYvu3t108WLwst133/Ht25uuXqXHjXMuWGAP\nzlbWrl09xYuL69apnc7Q2NgCyoFgF1okiRw4wBUrJsbFYfgdAOBfhg93vfGG89o1uksX06VL\nwch2S5dqevc2er1k0SLb6687g/CMATwv9e7tsViojRsVdvVnkB2CXWj54w/mr7/o5s19IdJ9\nAAAgpLz6qvOVV5yXL9PduhmvXy/CtzBBIG+8oZ80SWcySV9+ae3WLdjrngcNcjEMWbZME+Tn\nBaVDsAst6emYhwUAyM3Eic7Ro13nzzNduphu3iySdzGHg+rf37h8ubpKFWH7dnPTpjKck8uV\nExMTvb/9xhw8WDRN7SBMIdiFlsACuxYtlNFzGABAFm++6Rg82H32LNOjhzErq5AnOK5dozt2\nNKWl8S1b+tLSzFWqyLYwZvBgFyEkNRVbKCAfEOxCy4EDXHS0VL06gh0AwH1RFJk50z5ggPvX\nX9lu3Ux3L7zx8E6eZJOSok6cYHv3dq9fbzGZ5LwsSsuWvrg4YetW1bVreLOGvMJrJYScO8dc\nv043a+aT68LbAABKQVFk9mx7jx6ekyfZXr1MdnshZLutW/l27UzXrtHjxjk//NBeRNf1yjuK\nIoMGuf1+8sknGLSDvEKCCCFodAIAkHc0TRYssD37rOfIEfb5540P2Rlk6VJNcrJRFMmSJUHd\nAJu7Xr3cBoO0Zo3a65W7FFAIBLsQgmAHAJAvDEMWLrQlJXkPH+b69zd6PAXJdn4/GT9eP2mS\nrnhxccsWS0hd+Eevl7p399y4QW/bhr4nkCcIdiHkwAHOaJRq1cICOwCAvOI4kppqbdPGu28f\n17+/wevNX7az26m+fY0rVqhr1hR27DA/+mjInYGTk10UhS0UkFcIdqHizz+Zy5fppk19TLAv\nlgMAoGw8T1autD32mO+77/hhwwz+PGezP/9kkpKi9uzhn3zSt3WruXz5Ir9WWAFUry60aOE7\neJA7fhyXd4cHQ7ALFZiHBQAoMLVaWrfO2qyZ79tv+eHDDUIeWpQcOcImJZlOn2b69XOvW2cx\nGuXcAJu75GQ3IWTVKgzawYMh2IWK9HSWINgBABSURiN9+qn10Uf9mzerxozRi7mOvm3Zonr2\nWdOtW/S4cc558+TfAJu7pCRPbKz4xReq7GxclQgeAMEuVGRkcDqdVLduyC3vAABQCoNB+uIL\nS716/g0b1K++qpfuMwa3dKlmyBADTZPVq62hswE2FyxLBgxwu93Uhg0YtIMHQLALCVev0n/+\nyTRp4mOxggIA4CGYTNLnn1tr1BA+/VT95pu6e/7V7yevvaafNElXooS4ebPlmWcU00RkwAC3\nSiWtWKHOfSQSAMEuJOASsQAAhaVYMfGrryxxccLSpZq33vo725nNVI8eptWr1TVr+nfsMNev\nr6QZkmLFxI4dvRcuMN9/z8tdC4Q0BLuQgJ0TBUaZzbo33uDT0uQuBABCSIkS4saNlgoVhI8/\n1sybpyWEXLzItGsXtX8/16qV99tvLeXKKW/gC5eOhbxAsAsJBw5wWq3UoIGSPj6GAvbkyag2\nbTTLlxv791d/8onc5QBACImNFb/6yhobK773nnbCBH1iounMGWboUNf69VaDIXQ3wOYiPt5f\nv75/zx7+wgW0xYL7QrCT340b9NmzTHy8P8S3ZYUa9YYNpmeeYf78092rl2Qw6MeO1XzwgdxF\nAUAIqVhR+OorS8mSYmqq2mKh33vP/u67DkX3Ck1OdosiWbkSg3ZwXwh28sM8bH5RXq9u4kT9\nqFGEZW3Ll9vnzzdv3SqWKaObMUP3xhsES4sB4P9VrSp8+aWlZUvfp59ahwxxy13Ow3r2WU9M\njLRundrlQt8TyBmCnfwQ7PKFvnLF1KmTZtkyoVo18/btnk6dCCFC9eqWrVuFqlU1y5cbRo4k\nPhxMALijRg1h40bLU08pZgNsLtRqqU8ft9lMffklLh0LOUOwk19GBqdSSSF4gcIQxO3fH9Wm\nDXv0qKdrV/Pu3UKNGnf/SShf3rJli79uXdUXXxgHDqTciv9oDgDwX4MGuRiGLF+O2VjIGYKd\nzG7fps+cYeLj/SqVIhfzBo8kaebPN3XvTpvNjsmTbUuWSLp7O1SJJUpYtmzxtWzJp6WZnn2W\nysqSpVIAgKJTvrzYpo33l1/Yw4exLhtygGAns4wMTpIwD/sAlNVqHDhQN22aWLKkZdMm1+jR\n97unpNNZ163zdOzIHjkS1bkzfe1aMOsEAAiCwKVj0fcEcoRgJzMssHsg9sSJqNat+W3bfM2a\nmXfv9iUk5H5/iedty5a5+/ZlfvvN1KEDc/58cOoEAAiOJ5/0VqsmbNmiunYNb+JwL7wmZJae\nzvI8adgQC+xypvrsM1P79syff7qGDrV8+aVYsmSeHsYw9nnzXKNGMX/+aerQgT15sojLBAAI\nHooigwa5fT7y6acYtIN7IdjJKTubOn2abdjQp9Fggd29KK9XP3asYeRIwjC21FTHu++SfDX6\noyjHlCmOGTPov/4ydenCHTpUZJUCAARb795uvV5atUqNHgBwDwQ7OR04wIki5mFzQF++bOrY\nUb1mjRAXZ96xw9OxY8F+jmvYMNuCBZTDYezald+6tXCLBACQi14vde/uuXGD3rYNfU/gXxDs\n5IQFdjnid++Obt2a/eknT7du5t27herVH+aneZ5/3rpyJaFp45Ah6nXrCqtIAAB5DRnioihs\noYB7IdjJKSOD4zgSH48Fdv9PkjTz5xv79KFsNsfkybbFiyWt9uF/qjcpyfrZZ5JOpx8zRrNw\n4cP/QAAA2VWvLjRr5jtwgPv1V1buWiCEINjJxmqlfv2VbdDAr9VigR0hhFBZWcaePXXTpoml\nSpk3b86lp0kB+Jo3t3z9tVismG7qVN20aUTCMQcAxQv0PVmxAoN28DcEO9kcOMAJAuZh72CP\nH496+mn+u+98zZubd+/2x8cX+lP469Wz7NghVKqkmT9fP3o08WOgFACUrV07T2ys+Pnnquxs\nXDoW7kCwkw0W2N11p6fJpUv562mSf0LFipatW/21aqk3bDAmJ1MeTxE9EQBAELAs6d/f7XJR\nn3+OQTu4A8FONhkZHMuS+PiIDnaUx6N/5RXDyJGE42wrVjjefZewRbtYRCxVyrJpky8hgd+2\nzdizJ2WzFenTAQAUqQED3DwvpaaqRVHuUiA0INjJw26nTp5k69b1GwyRu9jrTk+TtWv9tWub\nv/vO06FDcJ5Xioqybtzofeopbv9+U9eu9O3bwXleAIBCV7y42LGj9/x5Zu9eXu5aICQg2Mnj\n0CHO74/oeVh+167oVq3Y//3P06OHZft2oVKlYD67pNFY16519+zJHjtm6tiRvnw5mM8OAFCI\ncOlY+CcEO3lE9AI7QdDOnm3s25c4nY4ZM2wffyxpNDKUwbL2+fNdL7zAnDkTlZTEnjolQw0A\nAA8tPt5Xv75/927+4kVG7lpAfgh28sjI4GiaNGkSccGOzsoy9eqlnTNHLF3asmmTa9gwOauh\nKMc77zgmT6Zv3DB17sxmZspZDABAQQ0a5BZFsmoVBu0AwU4OLhd1/Dhbu7bfZIqsBXbUTz+Z\n2rThvv/e99hj5t27/Y0by10RIYS4Ro+2z5pFWSym7t3577+XuxwAgHzr1s0TEyOtXat2udD3\nJNIh2Mng0CHW6424eVhu2zauZUvm8mXn2LGWjRvFEiXkruhv7sGDbYsXU36/oW9f1ebNcpcD\nAJA/arXUq5fbbKa+/hqXjo10CHYyiMwFdvxnnxGv17pihXPCBMKE3EIQz7PPWteuJSxrGDZM\nvXq13OUAAORPcrKLYciyZZiNjXQIdjLIyOAoijRtGllXPmDOnSMqlbddO7kLuS9vq1aWb74R\nTSb9a6/ppk2TuxwAgHwoX1586invyZNsZiYndy0gJwS7YPN4qGPH2Bo1/DExkdRNUpLo8+el\nqlUJHdIvOf+jj1q2bBHLltXMn8++8gpBx08AUA70PQGCYBd8mZmsx0O1aBFZw3X0jRuU0ylV\nqSJ3IQ8mPPKIecsWoWpVZtEiMmAA8UXWjDkAKFerVt6qVYUtW1Q3b+LNPXLh/32wReYCO+b8\neUKIVK2a3IXkiVi+vGXrVqlhQ7J2rf6553DZMQBQBIoiAwe6vV7yyScYtItcCHbB9v8L7CIs\n2J07RwiRqlaVu5C8EosX96alkfbtuX37otq3x6UpAEARevVya7XSqlVqTDZELAS7oPJ6qaNH\n2bg4oUSJyFq8xVy4QAghChmxu0OvJ5s2eQYNYk6dikpKYk+ckLsgAIAHL0sq5QAAIABJREFU\nMJmk7t0916/TO3ag70mEQrALqp9+Yt1uKtLmYQkh9NmzRDlTsX9jGGdKimPGDPqvv0wdO/K7\nd8tdEADAAwwd6qIobKGIXAh2QRWZC+xIYI2dSiWVLSt3IQXhGjbMtmwZ8fuN/fqhxR0AhLga\nNYQmTXzp6dyvv7Jy1wIyQLALqkCwa9Ys8oLdhQtCxYoh2Jc4jzydOlk3bJB0ujst7qTIuhYc\nAChLoO/JypUYtItECHbB4/ORzEy2alWhdOnIWmBH37xJ2e2iEnqd5ML32GPmrVvF8uU18+cb\nRo1CGxQACFkdOnjKlBE/+0xlNuPSsREHwS54jh1jnc5IXGAX2BIrKDzYEUKEGjXM27f769dX\nffaZqWdPymqVuyIAgBywLOnXz+1yUZ9/jkG7iINgFzwRvcCOELFyZbkLKQRiqVKWTZu8Tz/N\n/fBDVIcOaIMCAKFpwAA3z5Ply9W4gE6kQbALnkCwi7QOdoQQ+tw5QoionCZ2uZN0Ousnn7gH\nDkQbFAAIWSVLiu3be86fZ/btw6VjIwuCXZD4/SQzk6tYUShXLuI+PQVG7ISwGLG7g2Hsc+ag\nDQoAhLLAFooVKzRyFwJBhWAXJCdOsDZbJC6wI4Fgx/NiuXJyF1LI0AYFAEJZkya+evX8aWn8\nn38qtSMBFACCXZBE7AI7Euh1UqGCcnud5OJfbVAmTkQbFAAIKQMHukWRrF6NLRQRBMEuSALB\nrkULv9yFBBv911+U1RoGW2Lv5+82KMuWGUaNIl6v3BUBANzRo4cnOlpas0btcqHvSaRAsAsG\nUSSHDnFly4rlywty1xJsYbjA7j/QBgUAQpNaLfXq5TabqW++waVjIwWCXTD88gtrsVAtWkTi\nPGxgS2x4BzvyzzYoP/6INigAEDoGDXLTNFm2DLOxkQLBLhjS0yN4gV2giV34TsXehTYoABCC\nKlUSWrf2njjBHjmCS8dGBAS7YIjonRMRMBX7N7RBAYDQg74nEQXBrshJEjl0iCtVSqxcOeIW\n2JHA9cQ4TihbVu5CggdtUAAgpDz1lLdqVWHTJtXNm9hCEf4Q7IrcqVNsVlaELrAjhDDnzwsV\nKhAuslqfow0KAIQOiiL9+7u9XrJ6dWSdiiMTZtyLXEYGSwhp1iwSgx19+zZltQoJCXIXIoNA\nGxRT796aZctoq9U2bx7hebmLAoAI1bu3e+ZM7YoV3KuvBvXNyOGgfD5isdB+P7HbKbebcruJ\nzUYJAmWxUF4vcTopp5Py+SiLhfL7ic1GeTyU203Z7YFv6ZIlSf36uvh4f3y8LzY24i7dVAAI\ndkUukhfYRciW2PsJtEEx9umj+uwz+upV66pVktEod1EAEImioqRu3Txr16q3bWOffvref7XZ\nKEEgDgfl91NOJ/F6KY+HcrmIz0c5nVQgk4kisVopQojFQhNCrFZKFEkgfrlclNd754FW651A\n5vGQh2yep9VKKhW5eJEcPKhZsoQQQmJjxfh4X3y8v1EjX716fnxYzhGCXdGSJHLgAFeihBgX\nF6kL7CJjS+z9BNqgGIYO5XftiurQwbJuXfhdWg0AFCE52b12rfqll3ijMVoUic1GE0IsFqoQ\nl4qoVJJGQ/R6KSpKNJkkjiM6naTRSDwvGY0SyxKjUeJ5SaORdDqJ40hUlMQwkl4vaTREpZIM\nhsB9RJ4nWq1ECImJibHZyJ49tiNHuMxM9uhRbtMm1aZNqsBz1avnD4zkNW7sL10ag3l3INgV\nLYoiaWmWP/+kqYhcscpcuEAieMQuINAGRf/GG+qVK6OSkqzr1vnr1ZO7KACIOHXq+Lt08e/Z\nw1gstFYrmUyiRkMqVpR4XtJqCctKOp1E08RolAghUVESIcRgEGma6PUSyxKtVuJ5olZLKpWk\nUhGN5k5uo+k7gUyvL5LFxAYDeeIJ3xNP+AghkkT++IMJhLwjR7ijR7nMTI4QDSGkfHkxkPAa\nN/bVqeOPsHXd/4JgV+TKlxci8IITAYERuzC+nlheMYx99myhWjXd5MmmTp1sy5d727SRuyYA\niDiffOKmKMrlcsldSAFRFImLE+LihF69CCHE4aBOnmQPHWIPHeKOHOG++kr11VcqQgjHkVq1\n/AkJvvr1/c2b+8qXj6zBPAQ7KELM+fOEZQVMPhJCCHENGyZGRxvGjDH27+8aONDboYOvSRPC\nMHLXBQCgSDqd1KSJr0kTHyEuQsjFi8zBg+zPP7OHD3MnTrA//3wn4ZQqJTZp4mvSxF+/vv/R\nR/08H+ZtChDsoAgx588L5ctHWq+TXHh69BDLlDEmJ2uWLdMsWybGxHjbtvW2a+d78klJjQv+\nAAAUXMWKQsWKwvPPewghdjv1yy93BvMyM7nNm1WbN6sIIRqNVLeuv359f9Om/ubNfcWLh+Fg\nHoIdFBUqK4sym4WGDeUuJLT4Hnss6/hx9uBBfudO1ebN6vXr1evXS2q174knAiFPLF5c7hoB\nAJRNr89hMO/wYS4waXv4MLdsGSH3Dub5wmObLYIdFBUssLsfSaXytWzpa9nSMX06e+IEv3On\n6uuv+bQ0Pi2NvP66r1Ejb+fOnvbtxUi6XAfA/7F35+FNVAsbwM+s2duk7EsBFaSsZelCiyxe\nsUXBCpddtJ9aBBVu/RTBBesFudxPWbzK4oaIIigUlAoKtLIVQegCUkAB0bbsRdomXdKsM/P9\nkd6CCCWFJJOk7+/h8UmHSfJ2hPTlzJwzAN5z9WBeVRV16BCbk8O5TtrWDeap1VL37rWDef37\nO5o0CdTBPBQ78BbXXWLFxj0l9iZo2hkZ6YyMrJk5kzlxgs/K4jMzubw8LjdXM2uW0LmzLSnJ\nnpjojIyUOygAQJDQ6aRBgxyDBjkIIYJATp1iXA3PddL2r4N5sbGOHj2cdODcqAvFDrzFVeww\nYucmISLCEhFhSU2lz57ld+3iMzP5XbvUCxaoFywQ2rWzJybaExMd/fsTFn9nAQA8g2FIRIQQ\nEVE7mFdZSf30U+1gXk7OlcE8jUbq1s3Zr58zJsYRHe0MC/PrwTz8kABvqS12GLFrIDE83Jqc\nbE1OpoxG1/lZfseOuskWjiFDbElJjnvvlYLjYhAAAL8REnKTwTzXmnnt2wuuy/L8czAPxQ68\nhSksJAwjhIfLHSRQSQaDbdw427hxlNXKZWfzWVn8li2K9HRFerqkUjkGDLAlJdkfeAC3KQMA\n8LhrBvMuX6YPHapdSyU3l01PV6SnKwghWq3UtWvtYF5MjEOtljs3ih14D1NUJLRtSzCwdNsk\npdJ1KpbMn8/l5/PffKPYsqV2sgXLOvr0sT/8sC0piaBDAwB4R7NmYmKiPTHRTghxOMjRo+zB\ng1x+vqvn1Q7m0TSJiBC3b7fIu8YXJXnwLnEByOl01j1mGEYQAuYWETRN0zQtCIKf/h80Gtnm\nzaX77xe2bHFtoCjKFVjeXO5jGIaiKD89wpJEHTpEZWRQ33xDHT9OCCE0LcXGkgkThMmTA2XR\nY9cRvvrvoJ+jKIqiKFH068trroYj7G0Bd4RpmiaEBNARZlmW/PkntR8qKSH5+dShQ9SPP1Kn\nT1MnT4rePsKSJHE3Lo+NvdgZjUbXA5qmNRpNVVWVvHncp1arFQpFZWWlf1Yl9tAh3ZAhtpSU\nmgULXFsYhlGpVNXV1fIGc59Go+F5vqKiws8/BOnff+e/+4777jv24EEiio5Bg8zLl0uBsBie\nVqvlOM5kMgXKpxDHcRzH1dTUyB3EXTqdjmXZuk85/8fzPMMwAXTDq5CQEJqmTSaT3EHcpVAo\nKIqyWq1yB3FXaGgoIaSiokLuIO7ieSVFSTabzavvQtO068hcV2M/FVvXilw/WvyzJF2XK7Ao\niv6Zmf3tN0KI8447ro4nSZJ/pr0uPz/CdYQOHRxTp5KpUxWlpZrnnuOyskLuvbfy44+dUVFy\nR7uJur90gVLsGIYJxD/DARRYFMXAGtd3CaDAoii6TkTIHaRhAigwRUmy/9Tws7kcECxqVyfG\nlFgfElu1cnzzjTktjb54Uf/QQ6rFi+VOBAAAvoZiB16BtU7kQVGW1NTKL76QdDrN3Lm6p5+m\nAue8IQAA3D4UO/AKpqiI0LTYvr3cQRoj+333GXftcvbtq/jqK/2QIczJk3InAgAAH0GxA6+g\nCwuFtm2xiK5cxDZtKjZtsjz1FHPqlH7oUMWmTXInAgAAX0CxA8+jKiro8nIRNxOTlcTz5n//\nu2rZMiIIukmTNK++ShwOuUMBAIB3odiB52HmhP+wjR1bsWWL0L69avny0FGj6EuX5E4EAABe\nhGIHnoeZE37F2b27aedO+/Dh3P79+sGDuR9+kDsRAAB4C4odeB6Knb+RdLrKTz4xp6XRRmPo\n2LGqxYtJgCwdBwAADYJiB55XW+xwjZ1foShLamrFV1+JBoNm7tyQ//kfqrJS7kwAAOBhKHbg\neXRhIdY68U+O/v1N27c7o6P5rVv1CQmM6z6zAAAQLFDswPOYwkKxTRtJoZA7CFyH2Lq1adMm\nS2oq8/vv+gceUGRkyJ0IAAA8BsUOPIyqqqLLynCBnV9jWXNaWtUHHxBJ0j31lHb6dGK3y50J\nAAA8AMUOPKx2rRNcYOf3bKNGmbZvFzp3Vq5aFTpyJF1SInciAAC4XSh24GG1Myc6dJA7CNyc\n0KmTads220MPcbm5+sGDuexsuRMBAMBtQbEDD8OIXWCRtNqqFSvM8+bRlZWh48ap588noih3\nKAAAuEUoduBhNBaxCzgUZZk8ueKrr8SmTdULFoQkJ1MVFXJnAgCAW4FiBx7GFBYSihJxKjbQ\nOOLiTLt3OwYM4DMz9QkJ7C+/yJ0IAAAaDMUOPIwpKhJbt5aUSrmDQIOJTZtWpKdbUlOZoqLQ\nhATlF1/InQgAABoGxQ48iTKb6cuXcYFdAGNZc1pa5aefEoVC+9xzWAkFACCwoNiBJ9XOnMAF\ndgHO/uCDpsxMoUsX5apV+gcfZM6elTsRAAC4BcUOPInBzIlgIXTsaNqyxfbww2xBQej99ys/\n+wz3lgUA8H8oduBJNEbsgoik1VZ9/LH5X/+iKyu1L74Y1q2b7plnuD17sB4KAIDfQrEDT3KN\n2Im4xi6IWKZMKc/JqZkxQ2zWTLFhQ+ioUWFRUeq33mJOn5Y7GgAAXAvFDjzJtdYJbjsRZMTw\n8JqZM435+RXffmtNTqbKytQLFxqiovRDhihXraLMZrkDAgBALRQ78CSmqEhs1UpSqeQOAl5A\n047Y2OpFi8qPHatautQxaBB75Ih2+vSwHj10U6dy2dlEkuSOCADQ2Llb7J599tkff/xRwgc3\n3BhlNtN//IEL7IKepNPZxo2r2LDB+OOPNTNmSHq9Ij09dPRoQ1ycev58TKEFAJCRu8Xuo48+\n6t+//1133ZWWlnbixAmvZoIAxRQVEUnCInaNh9CxY83MmeX5+RUbNtjGjqXPn1cvWGCIigod\nPVqxbh1lscgdEACg0XG32F28ePG9994LDw+fN29ely5doqKi3nnnnYsXL3o1HASW2rVOcIFd\nY0PTjkGDqpYtKz92rHrRImePHlx2tm7atLAePbTTp3M5OXLnAwBoRNwtds2aNXvmmWeys7PP\nnj379ttvMwzz/PPPt23bNjEx8fPPP6+qqvJqSggItWudYMSusZJCQ63Jyabt240//GBJTZVY\nVrlqVejw4YZ77lEtXkyXlsodEAAg+DV48kSbNm2ef/75nJycnJyciIiIrKys5OTkFi1aTJgw\nYf/+/d6ICIECa52AixARYU5LKz9ypHL1altSElNYqJk7N6x799DRoxWbNhGHQ+6AAABBi23o\nE86cOZORkbFx48Y9e/aIonjHHXeMGjWqsrJy3bp1a9euXbZs2bPPPuuNoOD/mKIirHUCV/C8\nPTHRnphovnRJ8c03ijVruOxsLjtb07y57eGHbRMnkrg4uSMCAAQbys2JrsePH9+4cePGjRvz\n8/MJIXfffffo0aNHjRrVu3dviqIIISaTKSEhoaio6PLly96N7FGl/z09RNN0SEiIyWSSN4/7\ntFqtUqk0mUxOp1PuLLXCevYkklR+9Oh1f5dhGI1GUxk4t6XS6XQKhcJoNAqCIHcWt3Acp1Qq\n/fm6CC4vT/Hll4qMDKqqihAixcZSU6aUDRsm0YGx7hLP8zzPV1dXyx3EXaGhoRzHlQbOSXCF\nQsGyrDlwVkY0GAw0TZeVlckdxF1KpZKiKEvgTGwKCwsjhJSXl8sdxF1qtVoURavV6tV3YRjG\nYDDc6HfdHbHr2rUrIaRbt27//Oc/R48e3a1bN1efq6PX6+Pi4kpKSm4nKwQuymKhS0oc/frJ\nHQT8lyM62hEdbZ43j9+8Wfnll9yPP5KcnNBevaoXLnRGRsqdDgAgGLj7D+V//etfJ06cOHbs\n2OzZs7t3735Nq3N5++23CwsLPRoPAgZTXEwkCYvYwU1JKpVt7NiKjRsdv/xCxoxhDx/WJyZq\nX3mFCpzRXAAAv+VusTt69Oh1T0jt3LlzypQprscMw7Bsgy/ag+BA//47wZRYaAjpjjtIenpl\nRoZw553Kjz82xMUp1q3D7SsAAG7HTYpdTU1NaWlpaWnpunXrTp06Vfpnf/zxx5YtW1avXu2b\nrODPmMJCgimx0HCOe+4x7t5tTkujKip006aFjhjBnDwpdygAgEB1kwG2+fPnz5kzx/V4xIgR\n191nyJAhHg4FAYgpLiaE4FQs3Aqet6Sm2pOSNDNn8rt2Ge691/L44zWvvSap1XInAwAIMDcp\ndkOHDtXr9YSQ559/furUqR07drxmB4VCkZSU5K10EDhcI3ZY6wRumdChQ2V6Op+ZqX3pJdXy\n5XxWlvnNN+34dyMAQEPcpNj169evX79+hJCMjIxJkyb16tXLJ6kg8DBFRWKLFpJWK3cQCGz2\nxERjXJz6zTdVn3wSMmGCPSGh+q23xLZt5c4FABAY3J08sXv3brQ6uBHKaqVLSnAeFjxCCgkx\n//vfpu3bnVFRfFaWIT5ePX8+sdvlzgUAEADqG7GjKCo0NNS1Zm9UVFQ9e7pWLYZGiy4qIqKI\nYgce5Oze3bRliyI9Xfv66+oFC/jvvjMvXOiIjpY7FwCAX6uv2LVo0SIkJMT1uGnTpj7JAwEJ\nU2LBKyjKNm6c429/08yerVi/PnTYMNuYMea5c8WwMLmTAQD4qfqK3dW3kdi2bZv3w0CgYoqK\nCKbEgneIzZpVLVtmffRR7YwZivR0/vvva1580TJpEgmQG5EBAPgSPhnBA2qLHUbswGsccXHG\nXbvM8+YRu10za1ZoUhJz/LjcoQAA/E59I3b33HOPm6+yd+9eT4SBQFVb7LDWCXgVx1kmT7YP\nHap56SV++3bD3/5meeKJmldfxVxsAIA69Y3YsW7zWVzwT0xRkdismaTTyR0Egp/Qrl3ll19W\nrl4ttmqlWr7cEB+vWLdO7lAAAP6ivk62e/duX8WAAEbZ7fSFC456500DeJY9MdE4cKBqyRL1\nu+/qpk1TbNpkfvNNITxc7lwAADLDNXZwu+jCQiKKuMAOfExSqWpmzjR9/70jJobPytLHx6vn\nz6ew3B0ANG5Yxw5ul+sCOxFTYkEOzq5dK779VpGervnnP9ULFii+/rr6rbccgwbJnQsAQB5Y\nxw5uF9Y6AZm5lru7/3717NnKtWtDx4yxjRtnnjMHy90BQCOEdezgdqHYgT8Qw8KqFy+2TZyo\nnTFDsXYtt3Nn9X/+Y09IkDsXAIBPuXuN3fjx43/55Ze/bt+5c+eUKVM8GgkCDBaxA//hiI01\n7thR88ortNEYMnGi9oUXKLNZ7lAAAL5zk2JXU1NTWlpaWlq6bt26U6dOlf7ZH3/8sWXLltWr\nV/smK/gnprBQbNJE+u9ZewCZcVzNCy+Yduxwduum/Pxz/YAB3P79cmcCAPCRmyxBN3/+/Dlz\n5rgejxgx4rr7DBkyxMOhIHDUrnXSp4/cQQD+xNmlS0Vmpnr+fNXSpaEjRlhSUmpmz5Z4Xu5c\nAADedZNiN3ToUL1eTwh5/vnnp06d2rFjx2t2UCgUSUlJ3koHfo8uLiaCIOI8LPgfSaEwp6XZ\nExO1zz6rWr6c37u36r33nN27y50LAMCLblLs+vXr169fP0JIRkbGpEmTevXq5ZNUEDAwcwL8\nnCMmxrRrl2b2bOWqVaFDh9bMnGmZOpUwjNy5AAC8wt3JE7t3775uq3v//ffHjRvn0UgQSJjC\nQoJiB/5N0umqFy2qWrlS0mg0c+eGPvQQU1wsdygAAK9w9zavkiStXr16586dFoulbqMoijt2\n7NDiDtyNmOsHJIod+D/b8OGO2Fjt88/zmZn6v/3NPHu2NTlZ7lAAAB7mbrFbtmzZP/7xD61W\nK4piTU1NeHh4TU1NWVlZu3btVq5c6dWI4M8wYgcBRGzWrHL1asW6ddqXXtJOn85v3Vr9zjti\nixZy5wIA8Bh3T8V++OGHPXr0uHz58unTpxUKxXfffXf58uUvvviiqqrqrzMqoPGgCwvFsDBJ\nr5c7CIC7bOPGmfbscfTrx2/frh88mN+6Ve5EAAAe426xKywsHDp0qFKpbNq0aXx8fG5uLkVR\nEyZMiIuLe+WVV7waEfyX3c6cP48psRBwhHbtKjIyzGlpdGVlSHKybupUqrpa7lAAAB7gbrFj\nWVb/31GZvn377tu3z/U4Kiqq7jE0NsyZM0QQcB4WAhLDWFJTTdu3O7t1U6Sn6wcOxDrGABAE\n3C12d999d0ZGhtVqJYT06tVr69atoigSQoqLi41GoxcDgh/DBXYQ6FzrGFtSU5nz50NHjNC8\n+iplt8sdCgDg1rlb7J577rm8vLw777yzvLw8Li6utLR0ypQpixYt2rhxo2uhO2iEsIgdBAHX\nOsYVmzcL7dqpli/XDxnCHjsmdygAgFvkbrF79NFH169fHxsbK4rinXfe+Z///GfVqlUvvvhi\naGjowoULvRoR/FZtscM1dhD4HDExpp07rcnJzPHjoYmJqsWLiSDIHQoAoMHcLXaEkNGjR2/c\nuLFp06aEkGnTppWXlx85cuS3337r0aOH1+KBX6NxKhaCyJV1jLXa2nWMi4rkDgUA0DANKHbX\n0Gg0PXr0UCgUHkwDgYUpKpL0eslgkDsIgMfYhg837d1rHzqUy8vT33efctUquRMBADRAfQsU\n33PPPW6+yt69ez0RBgKKw8GcP+/EeC0EHbFZs8rPP7+yjvGWLdXvvot1jAEgINQ3Yse6zWdx\nwX8wZ84QhwMX2EGwql3HOC6O37ED6xgDQKCor5Pt3r3bVzEg8GBKLAQ9oV27io0bVcuWad56\nKyQ52TF+vLB4MaEouXMBANxQw66xE0WxqKho+/bt27Zt+/333wXMGmvEaotdhw5yBwHwJtc6\nxtu2CRER3Nq1ipgYfudOuTMBANxQA4pdZmZmZGTknXfeef/99z/wwAMdO3bs2bNnZmam98KB\nP8OUWGg8nD16mLZvt0+bRp09GzJunG7yZPqPP+QOBQBwHe4Wu9zc3OHDh5eXl7/xxhtfffXV\nxo0b33jjjfLy8uHDh+fn53s1Ivgn14ideNddcgcB8AVJobDOm2f/8Udnnz6KjRsNcXGqjz7C\nWncA4G/cLXZpaWlt2rQpKChIS0v7+9//PmLEiLS0tMOHDzdv3jwtLc2rEcE/MYWFUmioGBYm\ndxAA3xF79jRt3Vq9aBERRc2sWfrERLagQO5QAABXuFvsDh8+/Mgjj7hWJ67TokWLCRMm/PTT\nT14IBv7N6WTOncOUWGiMaNqanGzcv9/20ENsQYF+6FDNq69SZrPcsQAACHG/2EmSdN3tFCaI\nNUrM2bPE4cAFdtBoiS1bVn3ySeXq1WLLlqrly/UDB/I7dsgdCgDA7WLXu3fvL774orS09OqN\nly9fXrt2be/evb0QDPwa1joBIITYExONP/5oSU1lzp8PGT8+ZOJE+sIFuUMBQKPm7trCc+fO\n7d+/f2Rk5LPPPtutWzdCyM8///zee+/98ccfX3/9tTcTgj9iMCUWgBBCiKRSmdPSbCNHaqdP\n57OyDAcO1Lz0kiUlhTCM3NEAoDFyd8QuJibm22+/NRgMr7322siRI0eOHPnaa6+FhoZu3rw5\nOjraqxHBD9GuKbG4xg6AEEKIs3t3TKoAAH9QX7EbO3bs+vXrzf+9KDgxMbGgoOC3337btm3b\ntm3bfv3116NHjw4dOtQnOcG/1I7YodgB1MGkCgDwA/UVu/Xr148dO7ZZs2ZjxoxJT0+vrq5m\nGOauu+5KTExMTEzs1KkTg3MNjRVTVCTpdGKTJnIHAfAvmFQBAPKq7xq748ePZ2RkZGRkbNiw\nYcOGDSqV6sEHHxwzZsywYcO0Wm2D3kaSpNWrV2dnZwuCEB8f/+STT/61FN5onxttr66u/uyz\nz/Ly8qxWa9euXVNSUtq0aXP1C544ceKll1769NNPDQZDg9LCTQgCc/ass0sXuXMA+Cl7YqJx\n4ED1woWqZctCxo+3JyRUL1ggtm4tdy4ACH71jdhFRES8/PLLBw4cuHDhwgcffDBo0KBNmzaN\nHz++WbNmf//737/88suqqio332bt2rVbt2598sknn3nmmb17965YscL9fW60/b333isoKJg2\nbdrrr78uCMKsWbPMV531sFqtb7/99o1WaYHbwZw7R+x2zJwAqIdrUoVp+3Znnz58VpZhwADc\nqQIAfMCtyROtWrWaMmXK1q1bS0tL165dO3LkyB07djzyyCPNmjUbOXLkF198Uf/TBUHYsmXL\nY489Fh8fHxMTM2nSpB07dthsNnf2udF2s9m8d+/ep556KioqqmvXri+//LLZbM7Ly6t7wRUr\nVigUils4InBTuMAOwE2YVAEAPuburFiXkJCQcePGffHFF5cvX87MzOzTp09GRsbEiRPrf1Zx\ncXFFRUXfvn1dX/bt29disfz666/u7HOj7eXl5R07doyIiHBtVyqVCoXCaDS6vszNzc3Pz09J\nSWnQdwduogsLCSEiRuwA3IFJFQDgQ+6uY1dHkqRDhw6lp6evX79jYoI8AAAgAElEQVS+qKiI\nEBIZGVn/U1x9q8l/L7RXq9VKpdJkMrmzj2tg76/be/To8fbbb9c9fd++fZWVlV26dCGEVFRU\nLFmy5Pnnn7/uhYDHjh0rKSlxPeZ5vm51ZYqiKIoKoEE+14WGPM/7fgoLf+YMIYTu3LlBh4um\naZqmA+gI0zRNCOF5XhRFubO4hWGYQDzCCoUiUC6ZYFmWYZhbPMLt29vXrBG3blVMn65avlyR\nlWV7+23n/fd7OuOf1B1hr76LB93WEZaD695LARSYZdnA+klHUZQkSQEU2Defw/Xf9MvdYidJ\n0sGDB9evX1/X5zp37vzPf/5z3LhxXW52EX11dTXHcVf3D7Vafc31eTfaRxCE+p8rCMLmzZs/\n/fTThISEiIgISZKWLFkSHx/fp0+f33777a9h1q5du23bNtdjg8Hw/fffX/27Op3upofCr6jV\nahne9cwZQoi6Z0/S8MMVcEdYo9HIHaFhOI6TO0LDNHQmluxu6wiPHUuGDydvvEEvXKgaNYoM\nH07ef5+0beu5dNcRcH/peJ6XO0LDBNwRDqCeRAihKCrgjrBSqfTq69c/3HCTYidJUn5+vqvP\nFRcXE0Lat2//0ksvjR8/PjIy0s0bxWq1WofDIQhCXT+rqam55tP8Rvuo1ep6nnv69OlFixaV\nlJSkpKQMHz6cELJz584zZ868+OKLNwqTkJDQqVMn12OlUlk334KiKKVSabFY3PmO/AHP8xzH\nWSwW348nqX79ldJoarRa0pDTSTRN8zxvtVq9F8yzFAoFy7KyHOFbwzAMy7LXXL3qz5RKJcMw\nNTU1gTVi54EjnJZGP/ywIjWV/vZbac8ex2uvOaZM8cadKlxH2Bw4p31ZlqVp2m63yx3EXSqV\niqKompoauYO4y/XPEofDIXcQd7kGLwLoCPM8L0mSt48wRVH1DOvUV+xmzJixfv3606dPE0Ja\ntWr13HPPjR8/PjY21s0+V8e12ojRaGzatCkhxGq1Wq3Wa5YgudE+rujXfe7Ro0dnz57du3fv\nOXPm1L3ayZMnS0pKxo8fTwhx/bR4/PHH77vvvtTUVNcOAwcOHDhwYN371t391lU7AqjYMQzD\ncZzNZnM6nT59Y0FQFxcLnTs39FgxDMMwTAAdYZZlWZa1Wq1CgMxk5DiOoqgAOsKuwXiLxRI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7dua0tPIjR8zz5klKpfqddww9e2qnT6fP\nn5c7GgQAFDu4PteUWCxiBwD+TwwLs6SmGg8dqlq6VGjXTpGebhg4sHZ2xVUos1k9f74hNlaR\nnu7s0aPim28q16zx208515QRY16ea0awctWqsJgY3yz4AgENxQ6uzzVzQsSIHQAECMk1u2Lf\nvsrVq53R0bWzK/72N9fsCsW6dYboaPWCBZLBUL1okSkryxEfL3fkm5PU6iszgsPDryz4UlAg\ndzTwUyh2cH2YEgsAAYmm7YmJpi1bKjIy7EOGsMeO6aZNa9Kxo27aNKq62rXgsDU5mTCM3EEb\nwtVZ9+6tWrZM6NSJz8rS339/SHIye+iQ3MnA76DYwfVhETsACGiO/v0rv/zSmJ1tHT+eSJJt\n3DjjgQM1M2dKarXc0W4Vy9rGjjXu2VO5cqWzZ09+61Z9YmLomDHcvn1yJwM/gmIH18cUFhKG\nwVonABDQhC5dqpcsKTt7tmrpUrF1a7njeAJN24cPN23fXvHtt/aEBG737tARI/T33afYtMlT\nyzVDQEOxg+urXeuE5+UOAgAA1+GIja1cs6biu+/sCQns0aO6lJTa5ZoFQe5oICcUu0BFb9tG\nXn2VOXXKGy9OGY2U0Yi7xAIA+DlHTEzlmjWm7dttw4e7lms23HOPcu1a4nDIHQ3kgWIXeNhD\nh0JHjOBHjiT/93+6fv1CkpO53FzPvkXtBXYodgAAgcDZs2fVypXGH36wjRvHFBdr//GPsNhY\n5YoVlNUqdzTwNRS7QMIUFupSUvRDh3L79on33Uc++EDo3p3fujV02LDQBx/kt24louiZN8LM\nCQCAQCPcfXfV0qW1d+P44w/tyy8b+vRRLVlCVVfLHQ18B8UuMNDl5Zq5c/UDBig2bRI6d65c\ns8b+7bdkypSq7Oza62fz80OSkw2xsaqPPrr9f6IxWJ0YACAwCe3aVc+fbzx8uGbGDMpm07zx\nRljPnpq5c6nycrmjgS+g2Pm72qXS+/RRLV4stmxZ9cEHxuxse0JC3Q6u62dNO3faRo1izp3T\nzJpl6NtX9e67VEXFLb8pU1xMUOwAAAKW2LRpzcyZ5Xl5NS++SBhGtXhxWJ8+ilmz6BMnKJtN\n7nTgRZTUuGdHl5aWuh7QNB0SEmIymeTN8ycOh/Lzz9ULF9KXL4thYZbp0y2PP143TVWr1SqV\nSpPJ5HQ6655Bnz2rev995RdfUGazpNVaH3vMMmWK2KZNQ99Z/+CD7KFDZWfOSJ6bFcswjEaj\nqays9NQLeptOp1MoFEajUQiQKWYcxymVyqqqKrmDuCskJITn+bKyskD5FOJ5nuf56sA5qxUa\nGspxXN2nnP9TKBQsy5rNZrmDuMtgMNA0XVZWJneQm6Cqq5UrV6ref5++fNm1RWzeXAwPF9q2\nFcPDhTZtxHbthPBwsW1bSaeTN+o1wsLCCCHlgTPWqFarRVG0evnSRoZhDAbDjX4Xxc4vi50k\nKTZvVs+bxxQWSiqV5emnLf/4xzV/365b7Fwoo1G1cqVy+XK6tJRwnG3kSMu0ac4uXdx//7DO\nnSWNxujRNc1R7LwNxc7bUOy8DcXOqyirVbthA5OTIxUVMefO0SUlf10YRdLra9te27Ziu3ZC\n27Zi27ZieLjYpIksmVHsrqv+Ysd69b3hFnB5eeo5c7icHELTtrFjzWlpYsuWDXoFyWCoeeEF\ny7Rp/MaN6nffVaSnK9LTHTExltRUe2LiTZ9OVVTQ5eWOnj1v9TsAAAC/IymVjkmTnE89ZbFY\nCCHE4aDLyuhLl5jTp+niYub0abqkhL50iTl1ij127Nrn8rzYqpXYoYPQvr3YooXYsqXQvr3Y\noYPQtm2A3ZytEUCx8yPs8ePqN97gt28nhNgffND82mtCp063/Gqu+2HbxoxRbNmiWrqUy83l\nHn3U2auX5R//sA0bVs9fRax1AgAQ/DhObNlSbNnSGRn5p+2SRF+6xJw9S589S587x5w7R589\n6/qSOX2au+ZFeF5o3VoMDxfat7clJTkGDyYU5btvAa4Hxc4v0OfOad56S5GeTkTRERNTM3u2\nIzraQy9N24YPtw0fzu3fr1q6lP/+e11KirpDB8szz9gmTJBUqr8+A8UOAKDxoihX4SN/+TFE\nl5dfaXtnztR2vnPnmOJi7ocflKtXC3feaX38ceuECZJeL0t2ICh2sqOMRvW77yo//piy2YS7\n7za/9pr9gQe88UaOuDhHXBxz4oRq2TLl119rX3pJPX++NSXFmpIihoVdvSfWOgEAgL8Sw8LE\nsDByzQgfIVR1NXvkiPKzzxTffqt5/XX1v/9t+/vfrU884ezVS5acjRyWO5GP3a5ctcoQF6da\ntkwKC6tetMiYne2lVldHiIioXrKk3LW+kSCo58839OihmzqV+f33un2wOjEAALhP0mod8fFV\nH35YXlBgTksTmzdXfvGF/v779UOGKFetolyX9IGvoNjJQRQVmzYZ4uK006dTVqslNdX444/W\n5GTC+mgAVWzWrGbmzPKffjLPmyc1bapITzfEx4dMnMgePEgIoQsLCU2L7dv7JgwAAAQHsWlT\nS2qqMS+vYsMGW1ISe+yYdvr0sO7dtdOnMydPyp2usUCx8zX+++8NgwfrUlLokhLL00+XHzpk\nTkuTtFrfJ5G0WsvkyeV5edWLFwudOvFZWfqhQ0NHjWJ//VVs00ZSKHwfCQAAAh5NOwYNqlqx\nwnjggGXqVMKyylWrDAMHhowdy2/b9tc1VsCzUOx8hz14MPThh0MeeYQ5edI2erTpwAHz3LnS\nn69vkwHPWydMMP7wQ+Xq1Y5+/bg9e6iKClxgBwAAt0no0ME8e3b5kSPVS5Y4e/Xid+0Keeyx\nsKgo9Tvv1C2VDB6HYucLzO+/6558Uv/AA9yPPzruvde0Y0fV++8L4eFy57oKRdkTEys2bzZt\n3WobPdoyaZLcgQAAIBhICoV1/HhTZqZp+3brI49QZWXqefPCevXSTZnCHTggd7oghFmxXqfI\nyNA9+yxxOJyRkea0NMegQXInqo8zKqoqKkruFAAAEGyckZHV775rnjNHuXat8tNPFV9/rfj6\na2eXLtYnn7SNHi3LJUlBCSN2Xue45x7n3XdXffih6fvv/bzVAQAAeJWk11ueftq4f3/F+vX2\nYcPYX3/VzpgR1rOn9uWXmRMn5E4XDDBi53Vi06am3bvlTgEAAOA3KMoxeLBj8GD60iXFunWq\nTz5RrlihXLHCGRlpTU62jRuHCXy3DCN2AAAAIA+xRQtLamr5wYOVq1c7Bg1ijxzRTp9u6N1b\nM3cuffas3OkCEoodAAAAyIph7ImJFRs2GPfssT75JGW1qhYvDouOpkaNor76ij53Tu58gQSn\nYgEAAMAvCBER1W+9ZU5LU2zYoPzkEzYjg2RkhBEiNm3qjIx09url+iW2bCl3Uv+FYgcAAAB+\nRNJqrY8/bn388bDjx6lduxz797OHD/M7dvA7drh2EFu2rC15kZHOXr3Epk3lDexXKEmS5M4g\nJ+GqJbBpmhZFUcYwDULTNEVRoigGyv9BiqJcgeUO4i7XERYCZ5F0HGFvwxH2toA7wgzDkD//\nHPFzFEURQgLlpwa55ghfvEgdPEgdOkQOHqTy88mlS1f2a9VK6tOH9O0r9ekjxcaSZs1kyuuj\nIyxJEnvje5A29mJXWlrqekDTdEhIiMlkkjeP+7RarVKpNJlMTqdT7ixuYRhGo9FUVlbKHcRd\nOp1OoVAYjcZA+dTmOE6pVFZVVckdxF0hISE8z5eVlQXKpxDP8zzPV1dXyx3EXaGhoRzH1X3K\n+T+FQsGyrNlsljuIuwwGA03TZWVlcgdxl1KppCjKYrHIHcRdYWFhhJDy8vK//hZdUsIWFNT+\nOniQvur/gtiihTMy0vXLER3tyzs8qdVqURStVqtX34VhGIPBcKPfxalYAAAACDBiy5b2li3t\niYmuL6/ueVx+Pp+VxWdl1e55dc+LjZX0evlS+wKKHQAAAAS2+npebu6VnscwQseOdT3P2bOn\npFLJmdsLUOwAAAAgqPyp5wkCc+rUlfO2R48qTp5UpKcTQgjLCnfddaXn9eoVBAsjo9gBAABA\n8GIYISJCiIiwjRtHCCFOJ/Pbb1d6XkHBDXte794Sz8ub/Rag2AEAAECjwbL19bzDh6/0PI4T\n7ryz7uI8Z/fuhGHkze4OFDsAAABorK7peQ4H8/vvdRfnsceOMf/teZJG4+zWrW48T7j7bkL7\n4+27UOwAAAAACCGEcNzVPY8ym9ljx66eb8vl5rp2lLRaZ9euV3pe586EomSNXgvFDgAAAOA6\nJI3GERvriI11fUlVVrpO17p+cbm5V3peWJgjMpKKirK9+KK8I3kodgAAAAA3J4WEOAYMcAwY\n4PqSqqxkjx+vG8/jd+2S8vJsr71G7HYZQ6LYAQAAADSYFBJy9XgeffmyuqRE9gvvUOwAAAAA\nbpfYrJnYvj2R+2bH/jihAwAAAABuAYodAAAAQJBAsQMAAAAIEih2AAAAAEECxQ4AAAAgSKDY\nAQAAAAQJFDsAAACAIIFiBwAAABAkUOwAAAAAggSKHQAAAECQQLEDAAAACBIodgAAAABBAsUO\nAAAAIEig2AEAAAAECRQ7AAAAgCCBYgcAAAAQJFDsAAAAAIIEih0AAABAkECxAwAAAAgSKHYA\nAAAAQQLFDgAAACBIoNgBAAAABAkUOwAAAIAggWIHAAAAECRQ7AAAAACCBIodAAAAQJBAsQMA\nAAAIEih2AAAAAEECxQ4AAAAgSKDYAQAAAAQJFDsAAACAIIFiBwAAABAkUOwAAAAAggSKHQAA\nAECQQLEDAAAACBIodgAAAABBAsUOAAAAIEig2AEAAAAECRQ7AAAAgCCBYgcAAAAQJFDsAAAA\nAIIEih0AAABAkECxAwAAAAgSKHYAAAAAQQLFDgAAACBIoKjbgE8AACAASURBVNgBAAAABAkU\nOwAAAIAggWIHAAAAECRQ7AAAAACCBIodAAAAQJBAsQMAAAAIEih2AAAAAEECxQ4AAAAgSKDY\nAQAAAAQJFDsAAACAIIFiBwAAABAkUOwAAAAAggSKHQAAAECQQLEDAAAACBIodgAAAABBAsUO\nAAAAIEig2AEAAAAECRQ7AAAAgCCBYgcAAAAQJFDsAAAAAIIEih0AAABAkECxAwAAAAgSKHYA\nAAAAQQLFDgAAACBIoNgBAAAABAkUOwAAAIAgwfrmbSRJWr16dXZ2tiAI8fHxTz75JMMwbu5z\no+3V1dWfffZZXl6e1Wrt2rVrSkpKmzZt6tkOAAAAENx8NGK3du3arVu3Pvnkk88888zevXtX\nrFjh/j432v7ee+8VFBRMmzbt9ddfFwRh1qxZZrO5nu0AAAAAwc0XxU4QhC1btjz22GPx8fEx\nMTGTJk3asWOHzWZzZ58bbTebzXv37n3qqaeioqK6du368ssvm83mvLy8G233wbcJAAAAIC9f\nFLvi4uKKioq+ffu6vuzbt6/FYvn111/d2edG28vLyzt27BgREeHarlQqFQqF0Wi80XYffJsA\nAAAA8vLFNXauXtWkSRPXl2q1WqlUmkwmd/ZxDez9dXuPHj3efvvtuqfv27evsrKyS5cu4eHh\n191et+Wbb775+eef617t6aefdj2mKIqmaa1W68nv3Js4jiOEqNVqURTlzuIWiqJYlg2gI8yy\nLCFErVZLkiR3FrfQNM0wTMAdYa1WiyPsJa7LkQMrMEVRARSYpunACuw6wn+9xt1vURRFAurP\nMMuykiS5Ptxky+CD96iuruY47uo/SWq1uqqqyp19BEGo/7mCIGzevPnTTz9NSEioG6irZ3te\nXt62bdtcjw0Gw//+7/9eHUOpVN7ud+tbPM/LHaFhAu4IKxQKuSM0TAB9ZLvgCHtbwP2lk/eH\n4i3AEfa2gDvCrpEX76l/QMcX/3e1Wq3D4RAEoe4Dsaam5poCfqN91Gp1Pc89ffr0okWLSkpK\nUlJShg8fXvdqN9pOCHn22WcnTpzoeswwTN3AIU3TGo3mmrrpz1QqlUKhcHVfubO4haZplUoV\nQBNZ1Go1z/OVlZWBMibKsizP8zU1NXIHcZdGo+E4rqKiIlBG7DiO4zgugI6wVqtlWfaa0yP+\njOd5hmEsFovcQdyl0+lomq6oqJA7iLt4nqco6ppr3P1ZSEgIIaSyslLuIO5SKpWiKNrtdq++\nC03TriNzXb4odgaDgRBiNBqbNm1KCLFarVar1bXxpvuo1eobPffo0aOzZ8/u3bv3nDlzrn61\nG213ad26devWreu+LC0tdT2gaVqSJKfT6fnv3ztcPwsFQQiUzAzDBOgRDpTqTFFUIB5hp9MZ\nKMXOdSo2EI+w3EHc5TpRGECBXQIoMMuyOMJeJYqiKIreDlz/eQNfTJ7o0KFDaGjo4cOHXV8W\nFBQolcpOnTq5s8+NtjscjgULFiQkJMyaNevq9naj7QAAAABBzxcjdgzDDB06dPXq1a1bt6Zp\nesWKFQkJCa5T5pmZmTabLSkpqZ59rrs9Pz/fZDJ16tQpPz+/7o3atWt39uzZ625v0aKFD75T\nAAAAABn56ArKRx55RBCERYsWiaLYv3//J554wrV9//79lZWVSUlJ9exz3e3nz58nhLzzzjtX\nv8uUKVNc459/3T5s2DDvf5cAAAAAcqIC5eoWL7n6GruQkJAAuspYq9W6Vn4JlIsPGIbRaDQB\ndA2sTqdzLYIYKNfYcRynVCoDaAJQSEgIz/NlZWWB8inE8zzP89XV1XIHcVdoaCjHcXWfcv5P\noVCwLBtAU6wMBgNN02VlZXIHcZdSqaQoKoCmp4SFhRFCysvL5Q7iLtcaZFar1avvwjBMPReb\n+eiWYgAAAADgbSh2AAAAAEECxQ4AAAAgSKDYAQAAAAQJFDsAAACAIIFiBwAAABAkUOwAAAAA\nggSKHQAAAECQQLEDAAAACBIodgAAAABBAsUOAAAAIEig2AEAAAAECRQ7AAAAgCCBYgcAAAAQ\nJFDsAAAAAIIEih0AAABAkECxAwAAAAgSKHYAAAAAQQLFDgAAACBIoNgBAAAABAkUOwAAAIAg\ngWIHAAAAECRQ7AAAAACCBIodAAAAQJBAsQMAAAAIEih2AAAAAEECxQ4AAAAgSKDYAQAAAAQJ\nFDsAAACAIIFiBwAAABAkUOwAAAAAggSKHQAAAECQQLEDAAAACBIodgAAAABBAsUOAAAAIEig\n2AEAAAAECRQ7AAAAgCCBYgcAAAAQJFDsAAAAAIIEih0AAABAkECxAwAAAAgSKHYAAAAAQQLF\nDgAAACBIoNgBAAAABAkUOwAAAIAggWIHAAAAECRQ7AAAAACCBIodAAAAQJBAsYOAZ6WsckcA\nAADwC6zcAQDcZaWsp+nTZ5mzZ+gz55hzZ+gzrseldGkTsUlfZ98oZ1S0I7q3s7dG0sgdFgAA\nQAYoduB3XAXu6up2ljl7lj57mb58zZ4MYVqLrWMdsaeZ01l8Vhaf5doY4YyIccb0dfSNckbd\nJdwlxzcBAAAgAxQ7kI2dsl+kLxbTxaeZ0yV0ySX60mnmdDFdfJY5KxLxmp31kj7SGdleaN9B\n7NBeaO960EZow/73z3AJXVLAFuRyuQfYAwVswc/szyuVKwkhOknXx9knxhET6YyMdcTqJb2v\nv08AAABfQbEDHymjytbQa05pTtWNw113BK6V2CrWEdtObBcuhNf9t5XQiiNc/a/fUmzZ0t4y\n0Z5ICLFRtiPskXw2P4/Ny+fys7nsbC7b9fqdnZ2jndFRjqi+zr4dhY4Uobz0/QIAAPgeih34\nyP9q/vc79jvXnziGMC3Flv0c/dqL7esKXLgY3lpofdMC5w6FpIh2REc7op8hzxBCztPn87n8\nfDb/IHewgCn4hf3lM+VnhBCDZHCdro1yRPVx9tFJutt/awAAABmh2IEvFDKFW7mt3aXub1S+\n0U5s56kC56Y2Yps2tjYP2x4mhNgpewFTcJA76BrM285v385vJ4TQhO7s7BzljIp2Rvd19O0k\ndPJZPAAAAE9BsQNf+FD1oUjEF4QXBjgGyJuEl/hoZ3S0M/pp8jQh5CJ9MZ/Lz2Pz8tn8I+yR\n4+zxz8nnhBC9pI+VYuNJfG+2d2+xt1JSyhsbAADAHSh24HVGyvil4suWYssx4hgr8a8151qJ\nrR6yPfSQ7SFCiJ3Yj7BHDnIH89n8fC4/k87MJJlER3jC93L0infGxzpiYx2xOGMLAAB+C8UO\nvO4z1WcWyjLDOoNneH8rdlfjCR/ljIpyRk0hUwgh1SHVeXzedtv2vczefC4/l8slKsIQppuz\nWz9HvzhHXJwzronYRO7UAAAAV6DYgXfZif1j5ccqSZVsSyZqudM0RCup1RgyZkjNEEEQqqnq\ng+zBHC4nl8vdz+4/wh75SPURIaS90D7WGRvriB3sGNxOaCd3ZAAAaOxQ7MC7vlZ+fYm+NMky\nKUwKkzvLrdNK2kGOQYMcgwghFspyhD2Sw+bs4ffksDnpivR0RTohpIXYItYR6+p5PZ09sZAK\nAAD4HoodeNeHyg9pQk+2TpY7iMeoJJXrYrtUS6qTOH9mf87hcnLYnB/4HzYpNm1SbCKENBWb\n9nH2iXXEDnIM6uHsQeOmzAAA4BModuBFu7ndx9hjw+3D7xDuIIzcabyAJWykMzLSGTmZTBaI\ncIo5lcvl5nA5+7h9rluczSVzNZImyhkV44iJdcTGOeN4iZc7NQAABC0UO/CiD1QfEEKmWKbI\nHcQXGMJECBERQkSyNZkQ8ivz6wHuwAHuwI/cj3W3vlBL6ihnVD9Hvw5CB4NkMIiGMCmsidgk\nRAqROz4AAAQDFDvwlpPMyZ38zt7O3v0c/eTOIoO7hbvvFu52lbyz9Nn93P793P4D3IE93J49\n3J5rdmYI4yp5rv/qRX2YFBYmhjWRmhhEQ10FNIgGXy7sDAAAAQfFDrzlQ9WHEpGesTwjdxD5\nhYvh4bbwsbaxhJDL9OVcNvcifdFIG42U0Ugby6lyI20so8ou0hd/ZX6t/6V0ks4gGlyFr64C\nuh43o5vdSd3ZirTCJX0AAI0Wih14RSldmq5Ibyu2da39C3Waic2G2Yfd6HcdxOGqeibaVFf4\nyunyqytgOVV+gbngJM7rvoKuiS7KERXljIp2REc5o7CcMgBAo4JiB16xUrnSRtmeqnmKxZ+x\nhuAI11xs3pw0J8JN9qykKsvosqsrYAVbcYY7s0/at4vftYvfRVw3wBU6RzuiXSWvo9DRF98D\nAADIBz90wfPslH2lcqVW0j5qfVTuLEErRAoJEULuIHfUbeE4TkmUVVVVf9B//MT+VMAW5HK5\nOWzOceXxVcpVhBCdpOvj7BPjiIl0RsY54jBjAwAg+KDYgeetU6y7TF9+xvIMqoMsmovNE+2J\nifZEQkjdSnsFbMF+dn/d/FyGMB2FjrGOWFfPixAi5E4NAAAegGIHHiYR6UPVhwxhJlknyZ0F\nrqy05/qyhC5xjeQdYA8cZg+fVJ50DeY1F5v3cvaKdEbGOmL7OfspJIWsqQEA4Bah2IGH7eB3\nnGROjrCNwL1T/VBLsWVLe0vXYJ7r3mgFbEEOe2VFZUIIS9huzm6ukbx4Z3y4EC53agAAcBeK\nHXiYa1Hipy1Pyx0EbqLu3miTyWRCyG/Mb/lsfh6Xl8flHWWPFrAFrt3ChfAYZ8ydwp2txFYt\nxZatxdYtxBZNxaayZgcAgOtDsQNP+oX9JZvLjnHE9HX2lTsLNExHoWNHoeN423hCSBVVlc/m\n53P5eWxePpf/leKra3bmJb6F2KKV2OrqttdGbOPaqJSUcnwHAACAYgce9b7qfUIIFiUOdDpJ\nd6/j3nsd9xJCRCL+zvx+mjl9ib50gb5QQpeU0CUX6AuX6Eu5XO51n26Q/r+9O4+Oqr77B/65\n22xJZpKQZZIQEiELJISQhQQBVxC0aih92kdEoLKI+EhROWJb8dej51EPyqMVbQQepIDFGhcq\nTxEsHqNGBAJMaEIEsoFBCAlb9mS2u/z+uDidZsEJJJnM8H4dDmfune/NfObDkLxzl+8NMcvm\nKCnKPe2pETBcDmeIGdx3AwBwA0Gwg35znj3/N+3f4qS4exz3eLsW6DcssYlSYqKU2P0pBzku\nsBfOcefOs+fr2fp6tv48e/4se/YCe6GWrT3Bnei+iUBCuBweI8VEypFxXFwsxRq1RrNkVsMf\nplMGALhOCHbQb97RveMgx1LbUo44b9cCg0FDmuHy8OHy8B6fbWFaXGlPDX/qDr96tr5EKJFJ\nvjIu8F+b6BV9tBwdIUdEy9HhcniMHBMuh7vW6BX9wL8nAADfhmAH/cPKWN/VvxusBD9oe9Db\ntcCQYFJMJsnU4wx5IokX2YvNQc2XhcuVHZXnmfP1XP155nwD13CePX+SO9njFwxSgtST+cyy\n2fVH3dUXKUdqFM0AvyEAAB+AYAf9433t+41M43Lr8gAlwNu1wFDHEx8lRyUryRrSXLZdVhTF\n/Vk7Y1eP7TawDeoD9e8L7IU6tq6Sq+zxa4bKoZFKZJQUpe7eSxPTJooTcfUuANxoEOygH8gk\nb9BvEEhYZF3k7VrA52kV7QhpRG/zIHYynefYcxfZi3Vs3UX24jn23AX2gvr39+z3XU7sS5QS\nJzonTnROvNl5c6yMCfkAwP8h2EE/2KPZc4o79Uv7L6PlaG/XAn7OoBjUmVl6fLaFaWlgG+q4\nOgtvOSAcKOFL/qL7y190fyGiGDnmZufNas5LkpJwcS4A+CUEO+gHb+vfJqL/sv6XtwuBG516\nYl+ylHyn405yu1XuQf7gt5pvP9Z+/LH2YyIKUoIyxcxbHbfmirkZzgwN4fw8APATN3qwEwRB\nfcCyLMMwrsWhj2VZIuJ5nmG8vOOhlCstFopvEW/JZDKp9/5xHMeyrC92WH0w9PlohwVB6HKO\nXT8SSMim7Gwx+3HxcbJRLVv7Nf91MV+8j9tXJBQVCUVEZFAM4+RxE8WJt4u3T5QmXmV2Zd/t\nsLcL8ZTPdVj99utDBXMc51s/6VQ+VPDgZImr/1RiBu5bqk+w2WzqA/VfwuFweLcezwmCwHGc\nw+GQZfmnRw+kXwu//pD7cLtj+8/kn11lmI922G63+8r/EZZlOY5zOp3eLsRTGo2GZVlvdbie\nqT/AHviS/XI/u7+CqVBIISKe+DQ5bZIyaZI86Q75jhAlxH0TH+2w67vc0KfGDlEUvV2Ip7Ra\nLcMw6PDA0Wq1RGS3271diKd4nlcURZKkgX4hna7XX0Fv9GB36dIl9QHLskajsbm52bv1eC4w\nMFCn0zU3N3v3v+g59lx2aPYIacT+pv0sXe13CI7jAgICWltbB6226xQUFKTVapuamgbhv2i/\nEARBp9O1tbV5uxBPGY1GjUZz+XLXq2IH30X24hH+yCHhUJFQVM6Xq3PsccQlSAm5ztwcZ84U\n55QYOUaj0Wg0mvb2du9W6zmTySQIguu73NCn1Wp5nu/o6PB2IZ4KCQlhWfby5cveLsRTOp2O\nYRir1ertQjwVGhpKRI2Njd4uxFMGg0GW5YHO+hzHhYSE9PbsjX4oFq7TRv1GJzmXWpdePdUB\nDGXhcvgMx4wZjhn/j/5fM9N8SDh0QDhwUDhYypdWcpXv6t4logQpYbI8eQpNSePSRkmjvF0y\nAEDPEOzg2rUz7X/R/SVUDn3A/oC3awHoH8FK8HTH9OmO6URkZawW3lIsFBcLxRbespXbupW2\nUgiFyqETxAnZzuwcMSdDzMAtMQBg6ECwg2v3V91fW5iWFdYV+MEGfkmv6G9x3nKL8xYicpLz\nuP54ibZkr7TXIlj2aPbs0ewhIp74VDF1gnNCtpidI+bESpgtDwC8CcEOrpFE0v/q/lejaBbZ\nMCkx+D+BhAnShMni5IXtC4mogW0o48sOCYeK+eJSvrSML3uH3iGiCDlivDg+XUzPdebmirlX\nucYWAGAgINjBNdql3XWaOz3HNidCjvB2LQCDzSybzQ7zDMcMIrIy1qP80TK+7CB/cL+w/3PN\n559rPqcfd+blOHPSxfSbxZt7u5cGAEA/QrCDa7ROv46IHrU96u1CALxMr+hznbm5ztwltISI\nGtgGdU9eGV/2T+GfZXyZOixSjnTtycsQMzQKZkUGgP6HYAfX4rBw2MJb7nDckSKmeLsWgKHF\nLJvz7Hl59jwi6mA6vuO/O8gfPCgctAgW1848gYQUMSXHmTNRnDjJOSlMDvN21QDgJxDs4Fqs\n060josdsj3m7EIAhLUAJUHfmkZVkkqu4KotgOcQfsggW9ejtRtpIRCOlkZliZrqYPl4cnyam\nBSgB3i4cAHwVgh302Q/cD7u1u8dIY2533O7tWgB8BkvsaGn0aGn0XJpLRE1Mk0WwWHjLYeHw\nEf6I6z62HHGJUqIa8tKd6WlSGq7AAADPIdhBn63XrZdIWmpdypCXb1ML4LtClJC7HHfd5bhL\nXTzNnVZPyyvjy8r58gptxQfaD+jHG2Cki+muP8h5AHAVCHbQN21MW4GuIEwO+w/7f3i7FgD/\nESfFxUlx6lzfEknVXLUa8sr4sqP80Upt5YfaD4mIJ36UNMoV8nARBgB0gWAHfbNFt6WNaXvc\n+rhW0Xq7FgD/xBGnHrRVc55IYg1X48p5pXypK+cJJIyURv4r5zkzNIScB3BDQ7CDPnCS88/6\nP+sU3QLbAm/XAnCj4Il3z3lOcp7kTv4r5wmlldy/cp56sa2a8ybQBG/XDgCDDcEO+uDv2r+f\nZc/Ot80PlUO9XQvADUogwT3ndTKd5Xy5uievlC9VH6sjjWQcR+PiAuNGSaNGSaMSpIR4KR67\n9AD8G4Id9MF6/XqGmKXWpd4uBACuMCiGKzOqEBFRG9OmTqRSypce1Rzdx+z7VvetazBHXKwU\nq4Y8Ne2NkkbFyDFeqh0A+h+CHXhqn7CvlC+d7pieKCV6uxYA6FmQEjTZOXmyczIRmUwmRVDK\nm8oruIpKrvI0d/o0d/oEd6JQU1hIha5NNIomSo5KlpJHS6PVazhSpJRwOdx7bwIArh2CHXhq\nvX49ET1mxaTEAD5DQxo1q82gGa6VzUyzGvJcga+KqzrNnf6cPneNCVaC1Q1dgS9ZSsZMKwBD\nH4IdeOQUd+pzzedpYtoU5xRv1wIA1yVYCQ4Wg9PF9DzKU9dIJJ3hzpzkTtZwNSe5k+of9eIM\n11Y88eph3EQpcZQ0KlVMHSuNRdQDGGoQ7MAjG/QbZJJxdh2AX+KIi5fi46X4qTTVtbKT6TzJ\nnTzFnTrJnazmqtW09z33/Rf0hTqAJz5RTEyX0seJ49LF9LHiWINi8NI7AIArEOzgpzUyje9r\n34+So35u/7m3awGAQWJQDGliWpqY5r7yInuxhqup4WqO8keP8kePccdO8CcKtAX0400yxonj\nXDkvSAnyUu0ANy4EO/hpW/VbrYz16c6nMVECwA0uXA4Pl8Nvdt6sLnaZPPk7/rtKbeVH2o/U\nZyPlSNfkyRPECZgmCWAQINjBT3CQY5Nuk17Rz7XN9XYtADC0dJk82XUztCq+qoKrOCwc/lzz\n+eeaK9dkuOe8LDErTA7zau0A/gnBDn7C33R/O8+eX2xdHKrgt20AuBrXzdDIfmVNA9vg2p9n\nESy95bwMMSNCjvBa3QB+BMEOfsI63TqOuCW2Jd4uBAB8j1k2mx3mGY4ZRKSQ8j33fRlfpp6f\nd5Q/6p7zYuSY8fL4dEqP18YnSAkJUoJe0Xu1dgCfhGAHV1MkFB3nj9/ruPcm6SZv1wIAvo0h\nZqQ0cqQ0cpZ9lrrmNHfalfPK+LJd/K5dtIuCrgweLg1PkBMSxcREKTFBSkiSkrBXD+AnIdjB\n1azTryNMSgwAA0OdAznPfmU6vQv6CxVCRbmzvIarqeaqq/nqr7ivvhK+co03KsZEKTFRSkwQ\nE9SoFy/FCyR4qXyAoQjBDnpVyVV+qfkyU8x03YYSAGDgxMqxN0k33Wq91bWmkW2s5qqrueoa\nrqaKq6rmqkv50hK+hLRXBggkxElxSVKSevQ2SUxKkBJMimmgS5VIamParGQNpMCBfi2APkGw\ng16t169XSMHuOgDwllA5NFfOdf/d0sE41DtkuKKe+th9q3A5XI16iVKi+iBGimGJFUlsZ9qt\njNXBOFqYFic5XYutTKuDHO1Mu42x2Rl790UnOduYNnWxjWmTSHK9nDnUnCwlJ4lJyVKy+gCX\nmoEXIdgNEvUbgYNxWBkrETUzzURkZax2ssuM3Ma0EVE70y6S6CBHJ9NJRK1sq0KKjWw2xqaQ\n0sK0EFEn0+lknCKJnVxnAAWk6lMzHZnZYvYIaUT/FnyJvfSR9qNYOfY++339+5UBAK6ZRtGM\nEceMEce4r6xj665EPb5KfbBP2LdP2OcaoFW0DsahkHLNrxuoBGpIEyQHBSvBcUqcujiMH9bI\nNJZTeZFQVCQUuQaHy+GjpdFJUlKymJwkJY2WRg+Th13zSwP0CYLdgDvGH7s9+PYB+uLfar9V\nD0mEyWFZYla2mJ3lzMoQMwKV6z068Gfdn+2M/ZHOR3h8SABgaIuRY2LkmNuct7nWtDPt6ol6\nVVxVDVdTx9XJJAcpQYIiBClBetJrFa1rUUc6naLrYZGEIPnKYo+vGxISwrLs5cbLTUxTJV9Z\nxVVVcpXqg73C3r3CXtfIUDm0S9TDhSAwQPAze8AFKUE5zhw96RlijLKRiAyKQUManng1fgUp\nQazCakmrXttvUkwMMTpFp1W0LLFGxUhEAUqAQAKv8AFKABEZFaMx0CjqxKL2ooPMwRKhpIQv\n2aPZs0ezh4g44pKkpCxnVraYnenMTJaSWWL7VLOdsW/WbQ5SgjApMQD4okAlcLw4frw4fnBe\nLkQJmeicONE50bWmhWmp4qrUkFfBVVTz1fuF/fuF/e6buB+9TZaSo+SowakW/BuC3YAbIY3Y\n1bJrIL5yIAVOFifnirlkJSI6y54tEUosvKWELznKHz2hO7GNthFRkBKUIWZkObOyxCwPZ3v/\nUPvhJfbSUutS3OoRAOAamBTTBHHCBHGCa00b01bNVVfwFWrUq+KqDgmHDgoH3Tf51y49cfR4\ncXyIEuKN2sG3Idj5j+Hy8OH24TPtM4nISc5yvvyIcKSELynhS74RvvlG+EYdFifFZYvZWWJW\npjMzTUzrfvtXhZQN+g088UusmJQYAKB/BClBmWJmppjpWtPBdFRz1er+vAquopKrLOFLDvOH\n1WcZYhKkhCxnVo6Yk+3MvoZjL3BjQrDzTwIJ6neQxbSYiC6zl9WEVyKUHOGPbNdu367dTkQa\nRZMupWc6M7PErGxndqwcS0SFmsJKrnKmfaa6CAAAAyFACbhyvPjHO7DZGJt6ot4J/oSFt5Ty\npdW66gIqIKIgJShbzM52ZqvnUg/ClC7goxDsbgjD5GHTHdOnO6YTkUxyFVd1RDhi4S0W3nKE\nP+L6BTFCjsgSs2rZWsKkxAAAg06n6MaJ48aJ49SoJ5J4jD92mD9sESyH+cNfCVema2aJTZQS\ns53ZOWJOljMrSUpiiPFy6TBkINjdcFhi1bt0z6E5RNTOtJfypRbeoka9zzSfEVGuMzdLzPJ2\npQAANzSe+HQxPV1MX2xbTEQX2AuukFfGl1XqKt+j94jIpJjUPXnZzuwsMQvnRt/gEOxudIFK\n4BTnlCnOKeoVGGe4MyV8SY4zx9t1AQDAv4mQI+513Huv414icpLzKH9UvWDusHC4UFNYqCkk\nIpbYZDFZvW4j25k9ShqFnXk3GgQ7+DexUmyshFPrAACGNIEEdaKDJbSEiM6z50v50jK+7JBw\n6CB/8AR/4l16l368YiPHmZMupuc6c81k9nbhMOAQ7AAAAHxbpBw5wzFjhmMGETkYRxlXViKU\nHOIPWQSL664YHHEpckqanGZmzGbZHCPHRMvRZtnsyRxY4EMQ7AAAAPyHRtGoh2KX0lIiqmPr\nDguHLbzFIljK+fJytrzLT36too2So8yyOVaONcvmzBHrawAAFuBJREFUKDkqRooxy+ZoOTpC\njsAcKz4HwQ4AAMBvxcgxMfaYn9t/TkSko9Pc6e8d3zewDXVcXT1bX8/Wn2XPNrANtUJtMRV3\n2VYgIUKOiJFi1OQ3XB4eJUepyS9CjhBI8ML7gZ+CYAcAAHBD0JFutDw6zhnX/Sk7Y69j6xrY\nhjq27hx7zj35HRYOK6R0Gc8SGy6Hx8gxZtkcLUXHyDGpYiruljEUINgBAADc6LSKdqQ0cqQ0\nsvtTTnI2sA31XP059lw9W1/HXgl8dVzdUf7oETriPjheis8QM8aL4zPEjHHiOPX+5jCYEOwA\nAACgVwIJsXJsj/cikki6yF6sY+vOcmdL+dJ/8v88yh/9RPvJJ9pPiIgjLlFKHC+OT3emZ4gZ\nY6WxWkU76OXfcBDsAAAA4FpwxJlls1k2Z4lZ6p3KiaiBbTgkHCrmi8v4snK+vEJbUaAtICKe\n+FHSKHXK5XQxPUPM0Chdb1YO1w/BDgAAAPqNWTbn2fPy7HlEJJJYw9WU8WXqn1K+tFJb+aH2\nQyISSBgpjcx15qrT7CVJSbgCt18g2AEAAMCA4IlXb2L5gP0BInKS8yR3Ug15h4RD5Xx5JVf5\nru5dIgpUAlPEFNf+vGQpGffMuDYIdgAAADAYBBLcc147036UP/pP/p/q+XmHhEOHhEPqyFA5\nNEPMuJm5OZVSjYIxWoqOlCMxwYonEOwAAADACwKVwEnOSZOck9TFJqapVChVQ14pX1qoKSyk\nQiIiExERQ0yEHOGaSO/KXMpyTJQcFS1H6xSd997H0IJgBwAAAN4XooTc4bjjDscd6mID23Ay\n5ORJOlllq1InWDnHnTvGHyul0u7bhiqhkVLkv6ZQlmPMsjlKioqRY4KUoMF9H16GYAcAAABD\njlk2pygpRNTY0ei+vplpbmAbzrPnT3On3R+c4c6c4E90/zpaRWuWzZFypFk2x8vx6gP171gp\n1v+u2ECwAwAAAJ8RrAQHS8GjpdHk7PqUjbGdZ8/XsrVdkp86A0v3L6UhTYgcYpbNcVKce+CL\nl+NjpBjeNzOSTxYNAAAA0IVO0cVJcXFSD/dMUzOfmvO6JL9yvryML+u+SbAS7Ap87slvhDzC\noBgG/t1cIwQ7AAAA8HNXyXwOxtHINLrv4XMlv2P8sTLqOfN1D3xm2ZzKpAZS4MC/m6tBsAMA\nAIAbl0bRmBWzWTani+ndn21mmruczKfu+TvDnqnkKrtMwMIRd6n90iDV3QsEOwAAAICeBSvB\nwWJwOnXNfAopF9gL9Wx9A9twlj17njt/jj3n4B088SKJXilVhWAHAAAA0DcMMZFyZKQc6b7S\nYDDIJHurJJW/XeULAAAAcMNCsAMAAADwEwh2AAAAAH4CwQ4AAADATyDYAQAAAPgJBDsAAAAA\nP4FgBwAAAOAnEOwAAAAA/ASCHQAAAICfQLADAAAA8BMIdgAAAAB+AsEOAAAAwE8g2AEAAAD4\nCQQ7AAAAAD+BYAcAAADgJxDsAAAAAPwEgh0AAACAn0CwAwAAAPATCHYAAAAAfgLBDgAAAMBP\nINgBAAAA+AkEOwAAAAA/gWAHAAAA4CcQ7AAAAAD8BIIdAAAAgJ/gB+dlFEXZtm1bUVGRJEmT\nJk1auHAhx3EejultfXt7+9atWw8fPmyz2VJSUhYtWhQTE+PhawEAAAD4n0EKdgUFBZ999tmy\nZct4ns/Pz1cUZcmSJR6O6W3922+/XVNTs2zZMoPB8MEHH6xatSo/Pz8gIMCT1wIAAADwP4Nx\nKFaSpN27d8+bN2/SpEk5OTmLFy8uLCy02+2ejOltfUdHx7fffvvII49kZ2enpKT87ne/6+jo\nOHz4sCevBQAAAOCXBiPY1dbWtrS0ZGVlqYtZWVlWq7WqqsqTMb2tb2xsTEhIGD16tLpep9Np\ntdqmpiZPXgsAAADALw3GodimpiYiGjZsmLpoMBh0Ol1zc7MnY9Sdbd3Xp6Wlvf76667N9+3b\n19raOmbMmJ98rddff72oqEh9bDKZNm/erD5mGIZhmJCQkP597wOHZVkiMhqNiqJ4uxaP+G6H\nvV2Ip3y0w8HBwd4uxFNqhwVB8HYhnlI77EMfCbXDGo3G24V4Sj2B2+c6rNPpvF2Ip3zuM8yy\nrKIoer1+QF/l6j/3ByPYtbe3C4LgfgWDwWBoa2vzZIwkSVffVpKknTt3btmyZfr06aNHj/76\n66+vPt5qtboWOY5TPzQqhmHcF4c4hmHox/+l3q7FU77YYR8qmNDhQeFDBaPDgwMFDzTfKngQ\nfi7LsnyVZwcj2AUGBjqdTkmSXHmrs7MzMDDQkzEGg+Eq254+ffq1115raGhYtGjRfffd58lr\nrVq1atWqVa7FS5cuqQ9YljUajV32Iw5lgYGBOp2upaVFFEVv1+IRjuMCAgJaW1u9XYingoKC\ntFptc3OzJEnersUjgiDodLouvzINZUajUaPRNDY2+speZ41Go9Fo2tvbvV2Ip0wmkyAIly9f\n9nYhntJqtTzPd3R0eLsQT4WEhLAs60Md1ul0DMNYrVZvF+Kp0NBQImpsbPR2IZ4yGAyyLNts\ntgF9FY7jrrIXczBSsPry6kFSIrLZbDabrUtNvY25yrbl5eUrVqyIiIjYsGHD/fffrwZkT14L\nAAAAwC8Nxh67+Ph4k8lUWlo6bdo0IiorK9PpdImJiZ6MEQShx/VOp3PNmjXTp09fsmSJ+z5P\nT17LXVhY2FUWh7K1a9f+3//93/r165OSkrxdSx/4UIdffvnlL774Ytu2bdHR0d6upQ+0Wq23\nS/DUs88+W1xcvGPHDh86kZGIfOj8pN/85jfHjh374osvfOtI1kCfn9SPFixYcPHixU8//dTb\nhfRNQECAt0vw1K9+9SuO4woKCrxdSN90OSY5yAYj2HEcd/fdd6s/IFmW3bRp0/Tp09Vvjnv2\n7LHb7Xl5eVcZ0+N6i8XS3NycmJhosVhcLzRixIjIyMjevo6fsdvtra2tvnKU0BdZrdbW1tar\nn8oA16Ozs7O1tdVXjsP6oo6ODh86+cEXdXR0+NDJD76ovb0dtxjoq0GaoHjOnDmSJL322muy\nLE+ePHnBggXq+gMHDrS2tubl5V1lTI/r6+rqiOiNN95wf5VHH3303nvv7e3rAAAAAPi3QQp2\nDMPMnz9//vz5XdY///zzPzmmx/UzZ86cOXNmn14LAAAAwL8NUrCDfpecnDxt2jTfOjnJt6Sm\npjqdToPB4O1C/Nb48eN1Op0PTQvncyZMmBAREeFDMyL5nIkTJ7a0tHi7Cn92yy23+NYZokMB\ngxNcAAAAAPwDgjAAAACAn0CwAwAAAPATOMduaJEkaf78+X/605+6T6pcUVHx29/+dsuWLd2f\nUhRl27ZtRUVFkiRNmjRp4cKF6vXhva2/kXXvsCRJTqfTfUz3+XHQYc/1+BkuKir6+9//fubM\nmeTk5KVLl8bExHTZCh32XJcOd/8AExHLsl3uuIoOe677Z9hqtW7duvXAgQOyLGdnZy9cuDAo\nKKjLVuiw57p3uK2tbfPmzRaLhef57OzsxYsXd79lMDrsIQS7IcThcBQUFPQ4K5LNZnv99dd7\nOyGyoKDgs88+W7ZsGc/z+fn5iqIsWbLkKutvWD12+JNPPnn33XddiyzL7tixo8uG6LCHeuzw\nvn373nrrrUceeSQyMvKDDz548cUX8/Pzu5wQjQ57qHuHi4uLX3nllS7D7rzzzieffNJ9DTrs\noR4/wxs2bDh+/PgTTzzB8/zGjRvXrl373HPPddkQHfZQ9w4rivLSSy85HI6nn37a4XBs2rTp\nzTfffPrpp7tsiA57CMFuqNi5c+fmzZt7u/Hrpk2berujgCRJu3fvnjdv3qRJk4jIbrf/6U9/\n+vWvf83zfI/rfejOBP2rtw7X1dXl5ubOmjWrtw3RYQ/11uHt27fPnj17xowZRBQREbF27dr6\n+nr3nXbosId67HBaWtrq1atdizabbc2aNVOmTHEfgw57qMcOS5L0zTffPPHEE5mZmUT08MMP\nv/DCC1ar1f0OGeiwh3rscEVFxfHjx995552IiAgiMhqNzzzzzMKFC9UbxarQYc/hHLuh4tZb\nb/3jH/+4cuXK7k8dOnTIYrEsWrTIfeXzzz+/YsUKIqqtrW1pacnKylLXZ2VlWa3Wqqqq3tYP\n8PsYunrrcF1dXWpqaoobdT063Fc9dvj8+fM1NTWunBEdHf3KK6+oqQ4d7qseO2w0Gt0/vd9+\n++2MGTOys7MJHe67HjssSZKiKK6Zj9T7canRBB3uqx47fObMGZPJpKY6IkpMTGQYprq6mtDh\na4I9dkOFyWQymUzdz5VpaWl56623nnrqqS73nrv55pvtdjsRNTU1EdGwYcPU9QaDQafTNTc3\nq892Xz/Qb2TI6q3D586d++6773bu3Gmz2caMGbNgwQI1dqDDfdVjhy9evEhEtbW1r776akND\nQ0JCwuLFi0eMGEHocN/19hl2sVgsx44dy8/PVxfR4b7qscMajSYnJ2fHjh3Jyck8z3/88cfj\nxo1Tz7FDh/uqxw6bTKa2tjbXTtDLly9LktTY2Ejo8DVBsBvSFEV56623Jk2alJmZWVNT4/6U\nemCLiNrb2wVBcD9X1GAwtLW1SZLU4/rBqdxXtLW1tba2iqK4fPlyWZY//PDDVatW5efnBwQE\noMP9Qv12vGXLlvnz55tMpk8++eS5555bt24dOtzvJEnavHnzww8/zPNXvrGjw/1l+fLljz76\n6Ny5c4nIYDBs2LBBXY8O94uxY8cGBQVt2LBh0aJF6rFU+nGfKDp8DRDshrQvv/zyhx9+6H4O\nqbvAwECn0ylJkuuT3dnZGRgYaDAYelw/4EX7FIPB8M477wwbNkztUkJCwoIFC4qLi6dOneoa\ngw5fDzVkLFu2bOzYsUQ0cuTI+fPnHzx48M4773SNQYf7xVdffSUIwsSJE7s/hQ5fD7vd/txz\nz6Wmps6aNYtl2U8//fTZZ59dvXq1+4Wx6PD1CAgI+N3vfvfHP/7xoYce4jhu1qxZ1dXV7ifY\nETrcFwh2Q1plZWVDQ8Ps2bOJSL0k9uGHH546dery5ctdY9TLxZuamsLCwojIZrPZbLaQkBD1\njJDu673yRoYsjuNcJ3YQUVBQUERExKVLl9zHoMPXQ21IXFycuqjX68PDw9Xjs13GoMPXQ1GU\nnTt33n333T3eQAwdvh6lpaV1dXVr1qxRf0t58sknFyxYcPDgwWnTprnGoMPXKTU1dePGjZcv\nX1bvk7l9+/bw8HD3Aeiw53DxxJD2wAMPvPXWW2vXrl27dq263+7FF1+cM2eO+5j4+HiTyVRa\nWqoulpWV6XS6xMTE3tYP8lsY4iwWy7Jly1x3e7RarRcvXhw+fLj7GHT4esTFxel0OvU8aCLq\n6Oi4cOFCl3ns0OHrV1lZ+cMPP9x22209PosOXw/1LC7XbFOKoiiKoq50QYevR0tLy+rVq8+c\nORMWFqbRaA4cOBAWFpaQkOA+Bh32HPbYDWnDhg1znROqnm06fPhw9XeRPXv22O32vLw8juPu\nvvvubdu2RUdHsyy7adOm6dOnq1Ps9rYeXFJSUtrb2//nf/5n5syZWq32448/joiIyMnJIXS4\nn+j1+rvuuis/P3/x4sUmk+n9998PCwtDh/tdcXFxUlKS68pNFTrcL8aPH6/X61955ZVf/OIX\nDMN8+umnDocDn+F+ZDQaGxoa3nzzzTlz5rS3t2/YsGHevHnqVJfo8DVAsPNVBw4caG1tzcvL\nI6I5c+ZIkvTaa6/Jsjx58uQFCxaoY3pbDy4Gg+GFF17YtGnTmjVrtFptenr6k08+KQgCocP9\nR50IftOmTZ2dnWlpaS+++KI6pzw63I8sFosaNdyhw/3CaDS++OKLW7dufemll2RZTk5Ofuml\nl9QDhehwv2AY5tlnn3377bdXr15tNpvnzZt3zz33qE+hw9eA6e1mBgAAAADgW3COHQAAAICf\nQLADAAAA8BMIdgAAAAB+AsEOAAAAwE8g2AEAAAD4CQQ7AAAAAD+BYAcAAADgJxDsAAAAAPwE\ngh0AAACAn0CwAwDoasuWLcy/GzZs2H333ffNN994uzQAgKvBvWIBAHr2i1/8YsyYMURkt9vL\nysq++uqrXbt2rV+//tFHH/Vk8+Li4n/84x/PPPOMwWAY4EoBAK5AsAMA6NmDDz74y1/+0rV4\n4sSJ+++/f/ny5ffdd19MTMxPbl5cXPzCCy8sW7YMwQ4ABg0OxQIAeGTMmDEbN250OByvvvqq\nt2sBAOgZgh0AgKduv/32lJSUjz76yLXmr3/9a05OTnBwcGBg4Lhx4/Lz8xVFUUc+9dRTRBQe\nHj579mx18OnTp2fPnh0fHx8UFDRlypQdO3a4vk5ra+vvf//7xMREvV5/0003PfXUU21tbYP7\n5gDAHyDYAQB4imGYcePG1dfX22w2Itq+fftDDz0ky/LKlSsfe+wxIlq2bNl7771HRG+88cbj\njz9ORDt27PjDH/5ARMePH09PT9+7d+/s2bNXrFjR1NQ0a9ast99+W/3Kc+fOffXVV8eOHfv7\n3/8+JSXljTfeWLZsmdfeJwD4LJxjBwDQB8OHDyei2tra0aNHb9u2zWw27927V6/XE9F///d/\nh4eHFxYWzp07d/z48QkJCUQ0efLksLAwIlq5cmVwcPCRI0dCQ0OJaNWqVdOmTVu5cuXcuXNl\nWd65c+dvfvObN998U32V2bNn7927V1EUhmG89lYBwAdhjx0AQB+oSUv9e+PGjceOHVNTHRF1\ndHTIsmy1Wrtv1d7evnv37oceeohl2ebm5ubm5s7OzgULFnR2dh44cIDneYZh9u3bd/bsWXV8\nQUHBqVOnkOoAoK+wxw4AoA/OnDlDRHFxcUQUFhZ26tSpf/zjH6WlpSUlJfv371cP0XZXU1ND\nRC+//PLLL7/c5akLFy4EBgauXr362WefjYuLmzx58q233pqXlzdhwgQEOwDoK+yxAwDwlKIo\n5eXlUVFROp2OiPLz85OTk1esWHHx4sUHH3zw4MGDsbGxPW4oiiIRrVy58qtupk6dSkTPPPNM\nZWXl6tWrtVrta6+9lpubO3PmTHUrAADPYY8dAICnvv7662PHjj3xxBNE1NHRsWLFiocffnjD\nhg0syxKRoiidnZ09bqieb8cwzO233+5aefbs2YqKCpPJ1NjY+MMPP4waNWrlypUrV65sbW39\n7W9/u379+s8+++z+++8fjDcGAP4Ce+wAADxy4sSJRx55RKPRrFy5kohOnTrlcDjGjBmjpjoi\nKigouHz5sizL7lupi8HBwVOmTNm4ceO5c+fU9aIozp8/f+7cuVqttry8PCMjw3WFrNFonDFj\nhmtbAADPYY8dAEDP3n///dLSUiKy2+3l5eV79+7t7Oxct26detuJpKSkmJiY559//ujRo/Hx\n8RaLZf/+/SNGjCgsLFy3bt1jjz2m1WqJaM2aNT/72c/uuOOO119//bbbbktPT583bx7P87t3\n7z527Nh7773H8/yECRNGjhz5hz/84ciRI6mpqZWVlbt27YqPj3ffvQcA4BEFAAD+3ebNm7t8\nqwwODr7nnnu+/vpr92FlZWXTpk0zGo2xsbGzZ8+ura0tLCwcMWLEf/7nfyqKcvbs2alTp+r1\n+iVLlqjjjx8/npeXFx0dbTQap0yZsnv3bteXqqqq+tWvfhUVFaXRaOLi4hYtWlRbWzuYbxkA\n/AOjKIpXAiUAAAAA9C+cYwcAAADgJxDsAAAAAPwEgh0AAACAn0CwAwAAAPATCHYAAAAAfgLB\nDgAAAMBPINgBAAAA+AkEOwAAAAA/gWAHAAAA4CcQ7AAAAAD8BIIdAAAAgJ9AsAMAAADwEwh2\nAAAAAH7i/wPoc5T/plD3WAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = ggplot() + \n",
    "  geom_line(aes(x = exp.data$date[1211:1233], y = exp.data$aptone[1211:1233]), color = \"blue\") +\n",
    "  geom_line(aes(x = exp.data$date[1211:1233], y = exp.data$ap[1211:1233]), color = \"red\") +\n",
    "  geom_line(aes(x = exp.data$date[1211:1233], y = exp.data$ga[1211:1233]), color = \"green\")\n",
    "  geom_line(aes(x = exp.data$date[1211:1233], y = exp.data$ga[1211:1233]), color = \"yellow\")+\n",
    "  xlab('Dates') +\n",
    "  ylab('Volatility')\n",
    "\n",
    "print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "*---------------------------------*\n",
       "*          GARCH Model Fit        *\n",
       "*---------------------------------*\n",
       "\n",
       "Conditional Variance Dynamics \t\n",
       "-----------------------------------\n",
       "GARCH Model\t: fGARCH(1,1)\n",
       "fGARCH Sub-Model\t: APARCH\n",
       "Mean Model\t: ARFIMA(1,0,0)\n",
       "Distribution\t: norm \n",
       "\n",
       "Optimal Parameters\n",
       "------------------------------------\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000045    0.000075 5.9410e-01  0.55245\n",
       "ar1     0.024688    0.028628 8.6239e-01  0.38848\n",
       "omega   0.000000    0.000000 3.1200e-04  0.99975\n",
       "alpha1  0.010168    0.000327 3.1050e+01  0.00000\n",
       "beta1   0.986583    0.000386 2.5585e+03  0.00000\n",
       "eta11   0.968903    0.009189 1.0544e+02  0.00000\n",
       "lambda  1.304024    0.019944 6.5384e+01  0.00000\n",
       "vxreg1  0.000004    0.000000 1.4303e+01  0.00000\n",
       "\n",
       "Robust Standard Errors:\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000045    0.000079 5.6341e-01  0.57315\n",
       "ar1     0.024688    0.037175 6.6410e-01  0.50663\n",
       "omega   0.000000    0.000000 1.8200e-04  0.99986\n",
       "alpha1  0.010168    0.001852 5.4898e+00  0.00000\n",
       "beta1   0.986583    0.000453 2.1801e+03  0.00000\n",
       "eta11   0.968903    0.020401 4.7492e+01  0.00000\n",
       "lambda  1.304024    0.086978 1.4993e+01  0.00000\n",
       "vxreg1  0.000004    0.000001 6.9771e+00  0.00000\n",
       "\n",
       "LogLikelihood : 5678.67 \n",
       "\n",
       "Information Criteria\n",
       "------------------------------------\n",
       "                    \n",
       "Akaike       -8.9655\n",
       "Bayes        -8.9330\n",
       "Shibata      -8.9656\n",
       "Hannan-Quinn -8.9533\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.07332 0.78657\n",
       "Lag[2*(p+q)+(p+q)-1][2]   1.66738 0.35014\n",
       "Lag[4*(p+q)+(p+q)-1][5]   6.60094 0.02758\n",
       "d.o.f=1\n",
       "H0 : No serial correlation\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Squared Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                     0.1031  0.7482\n",
       "Lag[2*(p+q)+(p+q)-1][5]    0.2844  0.9853\n",
       "Lag[4*(p+q)+(p+q)-1][9]    0.7534  0.9943\n",
       "d.o.f=2\n",
       "\n",
       "Weighted ARCH LM Tests\n",
       "------------------------------------\n",
       "            Statistic Shape Scale P-Value\n",
       "ARCH Lag[3]   0.01361 0.500 2.000  0.9071\n",
       "ARCH Lag[5]   0.28156 1.440 1.667  0.9451\n",
       "ARCH Lag[7]   0.50326 2.315 1.543  0.9781\n",
       "\n",
       "Nyblom stability test\n",
       "------------------------------------\n",
       "Joint Statistic:  NaN\n",
       "Individual Statistics:              \n",
       "mu      0.3540\n",
       "ar1     0.4050\n",
       "omega  17.0446\n",
       "alpha1  0.2035\n",
       "beta1   0.2675\n",
       "eta11   0.1847\n",
       "lambda  0.2865\n",
       "vxreg1     NaN\n",
       "\n",
       "Asymptotic Critical Values (10% 5% 1%)\n",
       "Joint Statistic:     \t 1.89 2.11 2.59\n",
       "Individual Statistic:\t 0.35 0.47 0.75\n",
       "\n",
       "Sign Bias Test\n",
       "------------------------------------\n",
       "                   t-value   prob sig\n",
       "Sign Bias          0.33234 0.7397    \n",
       "Negative Sign Bias 0.44200 0.6586    \n",
       "Positive Sign Bias 0.08244 0.9343    \n",
       "Joint Effect       0.24201 0.9705    \n",
       "\n",
       "\n",
       "Adjusted Pearson Goodness-of-Fit Test:\n",
       "------------------------------------\n",
       "  group statistic p-value(g-1)\n",
       "1    20     127.5    4.406e-18\n",
       "2    30     132.7    3.298e-15\n",
       "3    40     146.8    2.113e-14\n",
       "4    50     150.5    2.957e-12\n",
       "\n",
       "\n",
       "Elapsed time : 1.077834 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1), external.regressors = cbind(all.raw$tone)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "#r.garch = ugarchfit(r.garch.spec, all.raw$fin_return,  solver=\"solnp\",  solver.control=list( maxeval=20, rseed=9876 ))\n",
    "r.garch = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "r.garch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "*---------------------------------*\n",
       "*          GARCH Model Fit        *\n",
       "*---------------------------------*\n",
       "\n",
       "Conditional Variance Dynamics \t\n",
       "-----------------------------------\n",
       "GARCH Model\t: fGARCH(1,1)\n",
       "fGARCH Sub-Model\t: APARCH\n",
       "Mean Model\t: ARFIMA(1,0,0)\n",
       "Distribution\t: norm \n",
       "\n",
       "Optimal Parameters\n",
       "------------------------------------\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000089    0.000069 1.2889e+00 0.197437\n",
       "ar1     0.032948    0.027970 1.1780e+00 0.238799\n",
       "omega   0.000000    0.000002 5.9270e-03 0.995271\n",
       "alpha1  0.020430    0.001259 1.6222e+01 0.000000\n",
       "beta1   0.986515    0.000677 1.4581e+03 0.000000\n",
       "eta11   0.830994    0.185929 4.4694e+00 0.000008\n",
       "lambda  0.993887    0.014244 6.9778e+01 0.000000\n",
       "vxreg1  0.000000    0.000000 1.5000e-05 0.999988\n",
       "\n",
       "Robust Standard Errors:\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000089    0.000076 1.1680e+00 0.242812\n",
       "ar1     0.032948    0.033772 9.7560e-01 0.329261\n",
       "omega   0.000000    0.000003 3.2060e-03 0.997442\n",
       "alpha1  0.020430    0.001236 1.6534e+01 0.000000\n",
       "beta1   0.986515    0.000766 1.2872e+03 0.000000\n",
       "eta11   0.830994    0.453155 1.8338e+00 0.066684\n",
       "lambda  0.993887    0.072689 1.3673e+01 0.000000\n",
       "vxreg1  0.000000    0.000000 7.0000e-06 0.999994\n",
       "\n",
       "LogLikelihood : 5659.834 \n",
       "\n",
       "Information Criteria\n",
       "------------------------------------\n",
       "                    \n",
       "Akaike       -8.9357\n",
       "Bayes        -8.9032\n",
       "Shibata      -8.9358\n",
       "Hannan-Quinn -8.9235\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.02187 0.88243\n",
       "Lag[2*(p+q)+(p+q)-1][2]   1.69188 0.33838\n",
       "Lag[4*(p+q)+(p+q)-1][5]   5.60546 0.06497\n",
       "d.o.f=1\n",
       "H0 : No serial correlation\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Squared Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                     0.2146  0.6432\n",
       "Lag[2*(p+q)+(p+q)-1][5]    0.3663  0.9762\n",
       "Lag[4*(p+q)+(p+q)-1][9]    0.7198  0.9950\n",
       "d.o.f=2\n",
       "\n",
       "Weighted ARCH LM Tests\n",
       "------------------------------------\n",
       "            Statistic Shape Scale P-Value\n",
       "ARCH Lag[3]    0.0358 0.500 2.000  0.8499\n",
       "ARCH Lag[5]    0.2332 1.440 1.667  0.9575\n",
       "ARCH Lag[7]    0.3878 2.315 1.543  0.9874\n",
       "\n",
       "Nyblom stability test\n",
       "------------------------------------\n",
       "Joint Statistic:  NaN\n",
       "Individual Statistics:             \n",
       "mu     0.2050\n",
       "ar1    0.4776\n",
       "omega  0.4630\n",
       "alpha1 0.1265\n",
       "beta1  0.1338\n",
       "eta11  0.1818\n",
       "lambda 0.1093\n",
       "vxreg1    NaN\n",
       "\n",
       "Asymptotic Critical Values (10% 5% 1%)\n",
       "Joint Statistic:     \t 1.89 2.11 2.59\n",
       "Individual Statistic:\t 0.35 0.47 0.75\n",
       "\n",
       "Sign Bias Test\n",
       "------------------------------------\n",
       "                   t-value   prob sig\n",
       "Sign Bias          0.35267 0.7244    \n",
       "Negative Sign Bias 0.27429 0.7839    \n",
       "Positive Sign Bias 0.09052 0.9279    \n",
       "Joint Effect       0.19942 0.9777    \n",
       "\n",
       "\n",
       "Adjusted Pearson Goodness-of-Fit Test:\n",
       "------------------------------------\n",
       "  group statistic p-value(g-1)\n",
       "1    20     143.4    4.028e-21\n",
       "2    30     176.4    4.644e-23\n",
       "3    40     178.1    1.139e-19\n",
       "4    50     180.3    6.499e-17\n",
       "\n",
       "\n",
       "Elapsed time : 0.7459812 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1), external.regressors = cbind(all.raw$polarity)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "r.garch = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "\n",
    "r.garch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "*---------------------------------*\n",
       "*          GARCH Model Fit        *\n",
       "*---------------------------------*\n",
       "\n",
       "Conditional Variance Dynamics \t\n",
       "-----------------------------------\n",
       "GARCH Model\t: fGARCH(1,1)\n",
       "fGARCH Sub-Model\t: APARCH\n",
       "Mean Model\t: ARFIMA(1,0,0)\n",
       "Distribution\t: norm \n",
       "\n",
       "Optimal Parameters\n",
       "------------------------------------\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000090    0.000069 1.2976e+00 0.194412\n",
       "ar1     0.031838    0.026605 1.1967e+00 0.231420\n",
       "omega   0.000000    0.000001 1.0933e-02 0.991277\n",
       "alpha1  0.019567    0.000468 4.1809e+01 0.000000\n",
       "beta1   0.986712    0.000266 3.7115e+03 0.000000\n",
       "eta11   0.840306    0.191634 4.3849e+00 0.000012\n",
       "lambda  1.053106    0.014540 7.2428e+01 0.000000\n",
       "vxreg1  0.000000    0.000000 7.1360e-01 0.475477\n",
       "vxreg2  0.000000    0.000000 0.0000e+00 1.000000\n",
       "\n",
       "Robust Standard Errors:\n",
       "        Estimate  Std. Error   t value Pr(>|t|)\n",
       "mu      0.000090    0.000084   1.07214 0.283655\n",
       "ar1     0.031838    0.031244   1.01902 0.308195\n",
       "omega   0.000000    0.000002   0.00464 0.996298\n",
       "alpha1  0.019567    0.004190   4.66931 0.000003\n",
       "beta1   0.986712    0.001960 503.37224 0.000000\n",
       "eta11   0.840306    0.487451   1.72388 0.084730\n",
       "lambda  1.053106    0.107615   9.78584 0.000000\n",
       "vxreg1  0.000000    0.000001   0.19562 0.844904\n",
       "vxreg2  0.000000    0.000000   0.00000 1.000000\n",
       "\n",
       "LogLikelihood : 5660.07 \n",
       "\n",
       "Information Criteria\n",
       "------------------------------------\n",
       "                    \n",
       "Akaike       -8.9345\n",
       "Bayes        -8.8979\n",
       "Shibata      -8.9346\n",
       "Hannan-Quinn -8.9208\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.01342 0.90779\n",
       "Lag[2*(p+q)+(p+q)-1][2]   1.68542 0.34145\n",
       "Lag[4*(p+q)+(p+q)-1][5]   5.61184 0.06463\n",
       "d.o.f=1\n",
       "H0 : No serial correlation\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Squared Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                     0.2207  0.6385\n",
       "Lag[2*(p+q)+(p+q)-1][5]    0.3735  0.9753\n",
       "Lag[4*(p+q)+(p+q)-1][9]    0.7282  0.9948\n",
       "d.o.f=2\n",
       "\n",
       "Weighted ARCH LM Tests\n",
       "------------------------------------\n",
       "            Statistic Shape Scale P-Value\n",
       "ARCH Lag[3]   0.03816 0.500 2.000  0.8451\n",
       "ARCH Lag[5]   0.23828 1.440 1.667  0.9562\n",
       "ARCH Lag[7]   0.39202 2.315 1.543  0.9871\n",
       "\n",
       "Nyblom stability test\n",
       "------------------------------------\n",
       "Joint Statistic:  NaN\n",
       "Individual Statistics:             \n",
       "mu     0.2022\n",
       "ar1    0.4793\n",
       "omega  1.0371\n",
       "alpha1 0.1231\n",
       "beta1  0.1326\n",
       "eta11  0.1139\n",
       "lambda 0.1077\n",
       "vxreg1    NaN\n",
       "vxreg2    NaN\n",
       "\n",
       "Asymptotic Critical Values (10% 5% 1%)\n",
       "Joint Statistic:     \t 2.1 2.32 2.82\n",
       "Individual Statistic:\t 0.35 0.47 0.75\n",
       "\n",
       "Sign Bias Test\n",
       "------------------------------------\n",
       "                   t-value   prob sig\n",
       "Sign Bias          0.34869 0.7274    \n",
       "Negative Sign Bias 0.28399 0.7765    \n",
       "Positive Sign Bias 0.09917 0.9210    \n",
       "Joint Effect       0.20162 0.9773    \n",
       "\n",
       "\n",
       "Adjusted Pearson Goodness-of-Fit Test:\n",
       "------------------------------------\n",
       "  group statistic p-value(g-1)\n",
       "1    20     142.7    5.632e-21\n",
       "2    30     175.1    7.994e-23\n",
       "3    40     177.8    1.260e-19\n",
       "4    50     174.6    5.325e-16\n",
       "\n",
       "\n",
       "Elapsed time : 1.08995 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1), external.regressors = cbind(all.raw$tone, all.raw$polarity)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "r.garch = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "r.garch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "*---------------------------------*\n",
       "*          GARCH Model Fit        *\n",
       "*---------------------------------*\n",
       "\n",
       "Conditional Variance Dynamics \t\n",
       "-----------------------------------\n",
       "GARCH Model\t: fGARCH(1,1)\n",
       "fGARCH Sub-Model\t: APARCH\n",
       "Mean Model\t: ARFIMA(1,0,0)\n",
       "Distribution\t: norm \n",
       "\n",
       "Optimal Parameters\n",
       "------------------------------------\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000082    0.000063   1.306204 0.191483\n",
       "ar1     0.031256    0.027894   1.120525 0.262490\n",
       "omega   0.000000    0.000001   0.000101 0.999920\n",
       "alpha1  0.019029    0.001844  10.321842 0.000000\n",
       "beta1   0.985842    0.001013 972.886380 0.000000\n",
       "eta11   0.844713    0.215509   3.919608 0.000089\n",
       "lambda  1.064100    0.018317  58.094253 0.000000\n",
       "vxreg1  0.000002    0.000000   4.856004 0.000001\n",
       "\n",
       "Robust Standard Errors:\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000082    0.000061 1.3360e+00 0.181540\n",
       "ar1     0.031256    0.033890 9.2227e-01 0.356385\n",
       "omega   0.000000    0.000000 3.8500e-04 0.999693\n",
       "alpha1  0.019029    0.001837 1.0361e+01 0.000000\n",
       "beta1   0.985842    0.000890 1.1077e+03 0.000000\n",
       "eta11   0.844713    0.505093 1.6724e+00 0.094448\n",
       "lambda  1.064100    0.047168 2.2560e+01 0.000000\n",
       "vxreg1  0.000002    0.000000 1.3403e+01 0.000000\n",
       "\n",
       "LogLikelihood : 5660.056 \n",
       "\n",
       "Information Criteria\n",
       "------------------------------------\n",
       "                    \n",
       "Akaike       -8.9361\n",
       "Bayes        -8.9035\n",
       "Shibata      -8.9361\n",
       "Hannan-Quinn -8.9238\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.00699 0.93337\n",
       "Lag[2*(p+q)+(p+q)-1][2]   1.65022 0.35853\n",
       "Lag[4*(p+q)+(p+q)-1][5]   5.54966 0.06806\n",
       "d.o.f=1\n",
       "H0 : No serial correlation\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Squared Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                     0.1873  0.6652\n",
       "Lag[2*(p+q)+(p+q)-1][5]    0.3346  0.9800\n",
       "Lag[4*(p+q)+(p+q)-1][9]    0.6759  0.9959\n",
       "d.o.f=2\n",
       "\n",
       "Weighted ARCH LM Tests\n",
       "------------------------------------\n",
       "            Statistic Shape Scale P-Value\n",
       "ARCH Lag[3]   0.03242 0.500 2.000  0.8571\n",
       "ARCH Lag[5]   0.23021 1.440 1.667  0.9582\n",
       "ARCH Lag[7]   0.37586 2.315 1.543  0.9882\n",
       "\n",
       "Nyblom stability test\n",
       "------------------------------------\n",
       "Joint Statistic:  NaN\n",
       "Individual Statistics:             \n",
       "mu     0.2135\n",
       "ar1    0.4681\n",
       "omega  1.0004\n",
       "alpha1 0.1282\n",
       "beta1  0.1403\n",
       "eta11  0.1071\n",
       "lambda 0.1516\n",
       "vxreg1    NaN\n",
       "\n",
       "Asymptotic Critical Values (10% 5% 1%)\n",
       "Joint Statistic:     \t 1.89 2.11 2.59\n",
       "Individual Statistic:\t 0.35 0.47 0.75\n",
       "\n",
       "Sign Bias Test\n",
       "------------------------------------\n",
       "                   t-value   prob sig\n",
       "Sign Bias           0.2659 0.7904    \n",
       "Negative Sign Bias  0.2640 0.7918    \n",
       "Positive Sign Bias  0.1371 0.8910    \n",
       "Joint Effect        0.1545 0.9846    \n",
       "\n",
       "\n",
       "Adjusted Pearson Goodness-of-Fit Test:\n",
       "------------------------------------\n",
       "  group statistic p-value(g-1)\n",
       "1    20     144.5    2.470e-21\n",
       "2    30     167.6    1.931e-21\n",
       "3    40     179.2    7.244e-20\n",
       "4    50     178.9    1.102e-16\n",
       "\n",
       "\n",
       "Elapsed time : 1.023607 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1), external.regressors = cbind(abs(all.raw$tone))) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "\n",
    "r.garch = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "r.garch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "*---------------------------------*\n",
       "*          GARCH Model Fit        *\n",
       "*---------------------------------*\n",
       "\n",
       "Conditional Variance Dynamics \t\n",
       "-----------------------------------\n",
       "GARCH Model\t: fGARCH(1,1)\n",
       "fGARCH Sub-Model\t: APARCH\n",
       "Mean Model\t: ARFIMA(1,0,0)\n",
       "Distribution\t: norm \n",
       "\n",
       "Optimal Parameters\n",
       "------------------------------------\n",
       "        Estimate  Std. Error    t value Pr(>|t|)\n",
       "mu      0.000223    0.000086   2.600260 0.009315\n",
       "ar1     0.034490    0.035399   0.974319 0.329898\n",
       "omega   0.000000    0.000000   0.009382 0.992515\n",
       "alpha1  0.039397    0.005085   7.748237 0.000000\n",
       "beta1   0.920365    0.005959 154.455384 0.000000\n",
       "eta11   0.147785    0.067017   2.205189 0.027441\n",
       "lambda  2.819884    0.050493  55.847496 0.000000\n",
       "\n",
       "Robust Standard Errors:\n",
       "        Estimate  Std. Error  t value Pr(>|t|)\n",
       "mu      0.000223    0.002594 0.086001  0.93146\n",
       "ar1     0.034490   10.584612 0.003258  0.99740\n",
       "omega   0.000000    0.001010 0.000002  1.00000\n",
       "alpha1  0.039397   14.563903 0.002705  0.99784\n",
       "beta1   0.920365   16.525273 0.055694  0.95559\n",
       "eta11   0.147785   13.432905 0.011002  0.99122\n",
       "lambda  2.819884   91.484555 0.030824  0.97541\n",
       "\n",
       "LogLikelihood : 5593.941 \n",
       "\n",
       "Information Criteria\n",
       "------------------------------------\n",
       "                    \n",
       "Akaike       -8.8331\n",
       "Bayes        -8.8047\n",
       "Shibata      -8.8332\n",
       "Hannan-Quinn -8.8224\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.07577  0.7831\n",
       "Lag[2*(p+q)+(p+q)-1][2]   0.70935  0.8938\n",
       "Lag[4*(p+q)+(p+q)-1][5]   3.76075  0.2661\n",
       "d.o.f=1\n",
       "H0 : No serial correlation\n",
       "\n",
       "Weighted Ljung-Box Test on Standardized Squared Residuals\n",
       "------------------------------------\n",
       "                        statistic p-value\n",
       "Lag[1]                    0.05579  0.8133\n",
       "Lag[2*(p+q)+(p+q)-1][5]   0.30853  0.9828\n",
       "Lag[4*(p+q)+(p+q)-1][9]   0.66539  0.9961\n",
       "d.o.f=2\n",
       "\n",
       "Weighted ARCH LM Tests\n",
       "------------------------------------\n",
       "            Statistic Shape Scale P-Value\n",
       "ARCH Lag[3]   0.09693 0.500 2.000  0.7555\n",
       "ARCH Lag[5]   0.30141 1.440 1.667  0.9399\n",
       "ARCH Lag[7]   0.48254 2.315 1.543  0.9799\n",
       "\n",
       "Nyblom stability test\n",
       "------------------------------------\n",
       "Joint Statistic:  413.5292\n",
       "Individual Statistics:               \n",
       "mu      0.67624\n",
       "ar1     0.07864\n",
       "omega  55.93349\n",
       "alpha1  0.81223\n",
       "beta1   0.04231\n",
       "eta11   0.85759\n",
       "lambda  0.11728\n",
       "\n",
       "Asymptotic Critical Values (10% 5% 1%)\n",
       "Joint Statistic:     \t 1.69 1.9 2.35\n",
       "Individual Statistic:\t 0.35 0.47 0.75\n",
       "\n",
       "Sign Bias Test\n",
       "------------------------------------\n",
       "                   t-value   prob sig\n",
       "Sign Bias          0.55536 0.5787    \n",
       "Negative Sign Bias 0.08792 0.9300    \n",
       "Positive Sign Bias 0.68439 0.4939    \n",
       "Joint Effect       0.55900 0.9058    \n",
       "\n",
       "\n",
       "Adjusted Pearson Goodness-of-Fit Test:\n",
       "------------------------------------\n",
       "  group statistic p-value(g-1)\n",
       "1    20     221.8    1.469e-36\n",
       "2    30     236.3    2.307e-34\n",
       "3    40     251.9    5.938e-33\n",
       "4    50     255.9    8.565e-30\n",
       "\n",
       "\n",
       "Elapsed time : 0.6532965 \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r.garch.spec = ugarchspec(variance.model=list(model=\"fGARCH\", submodel=\"APARCH\",  garchOrder=c(1,1)) , \n",
    "                             mean.model = list(armaOrder=c(1,0), include.mean=TRUE ), distribution.model = \"norm\" )  \n",
    "r.garch = ugarchfit(r.garch.spec, all.raw$fin_return)\n",
    "r.garch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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