{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 0: モニター用のサンプルMLモデルを学習する"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "このノートブックを実行する時のヒント：   \n",
    "- このノートブックは大容量のRawデータを読み込むため、<span style=\"color: orange; \">メモリー8GB以上のインスタンス</span>で実行してください\n",
    "- KernelはPython3（Data Science）で動作確認をしています。\n",
    "- デフォルトではSageMakerのデフォルトBucketを利用します。必要に応じて変更することも可能です。\n",
    "- 実際に動かさなくても出力を確認できるようにセルのアウトプットを残しています。きれいな状態から実行したい場合は、右クリックメニューから \"Clear All Outputs\"を選択して出力をクリアしてから始めてください。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 必要なライブラリーのインストールとインポート"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "!pip install xgboost==1.5.1 optuna scikit-learn==1.0.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import io\n",
    "import boto3\n",
    "import time\n",
    "from datetime import datetime\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import sagemaker\n",
    "from xgboost import XGBRegressor\n",
    "from sklearn import metrics\n",
    "import optuna\n",
    "\n",
    "import model_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SageMaker Default Bucketをセット\n",
    "# 他のバケットを利用する場合はここを変更する\n",
    "bucket = sagemaker.Session().default_bucket()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### トレーニング用のデータをオープンデータのS3バケットから取得"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<span style=\"color: orange; font-size: 120% \">RAWデータ読み込み時に、メモリー4GBのインスタンスではメモリー不足によりカーネルが終了します</span>  \n",
    "<span style=\"color: orange; font-size: 120% \">メモリーを8GB以上搭載したml.m5.largeなどのインスタンスを使用してください</span>  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019 7\n",
      "2019 8\n",
      "2019 9\n",
      "2019 10\n",
      "2019 11\n",
      "2019 12\n",
      "2020 1\n",
      "2020 2\n",
      "CPU times: user 2min 46s, sys: 32.7 s, total: 3min 19s\n",
      "Wall time: 4min 32s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "start = '2019-07-01'\n",
    "end = '2020-02-29'\n",
    "sampling_rate = 20\n",
    "\n",
    "df_features = pd.DataFrame()\n",
    "for target in pd.date_range(start, end, freq='M'):\n",
    "    print(target.year, target.month)\n",
    "    \n",
    "    # Get raw data with 20% sampling\n",
    "    previous_year, previous_month = model_utils.get_previous_year_month(target.year, target.month)\n",
    "    df_previous_month = model_utils.get_raw_data(previous_year, previous_month, sampling_rate)\n",
    "    df_current_month = model_utils.get_raw_data(target.year, target.month, sampling_rate)\n",
    "    df_data = pd.concat([df_previous_month, df_current_month]).reset_index(drop=True)\n",
    "    del df_previous_month\n",
    "    del df_current_month\n",
    "\n",
    "    # Extract features\n",
    "    df_features_current_month = model_utils.extract_features(df_data)\n",
    "    df_features_current_month = model_utils.filter_current_month(df_features_current_month, target.year, target.month)\n",
    "    \n",
    "    df_features = pd.concat([df_features, df_features_current_month])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### データを期間で学習、検証、テストに分割し、ハイパーパラメーターチューニングを行う\n",
    "ハイパーパラメーターチューニングはSageMakerでのトレーニングに組み込むことも可能ですが、今回はモデル作成をシンプルに実行するためにノートブック内で動かしています"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split data for training\n",
    "df_train = df_features[('2019-07-01'<=df_features.index) & (df_features.index <= '2019-12-31')].copy()\n",
    "df_validation = df_features[('2020-01-01'<=df_features.index) & (df_features.index <= '2020-01-31')].copy()\n",
    "df_test = df_features[('2020-02-01'<=df_features.index) & (df_features.index <= '2020-02-28')].copy()\n",
    "\n",
    "y_train = df_train['pickup_count'].values\n",
    "X_train = df_train[df_train.columns[1:]].values\n",
    "y_validation = df_validation['pickup_count'].values\n",
    "X_validation = df_validation[df_validation.columns[1:]].values\n",
    "y_test = df_test['pickup_count'].values\n",
    "X_test = df_test[df_test.columns[1:]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\u001b[32m[I 2022-12-15 10:37:31,273]\u001b[0m A new study created in memory with name: no-name-df606950-889f-4535-a9f0-e4d1d7a52b19\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:37:49,796]\u001b[0m Trial 0 finished with value: 77.77208361524062 and parameters: {'max_depth': 5, 'alpha': 595.7300746704884, 'min_child_weight': 120, 'subsample': 0.7158474569125317, 'eta': 0.3801220778920714}. Best is trial 0 with value: 77.77208361524062.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:38:08,899]\u001b[0m Trial 1 finished with value: 77.02380578750139 and parameters: {'max_depth': 5, 'alpha': 975.5350306481461, 'min_child_weight': 70, 'subsample': 0.7601596156492616, 'eta': 0.2363846460940136}. Best is trial 1 with value: 77.02380578750139.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:38:25,763]\u001b[0m Trial 2 finished with value: 81.88596838991234 and parameters: {'max_depth': 5, 'alpha': 209.82960645759752, 'min_child_weight': 90, 'subsample': 0.5929469916694439, 'eta': 0.489450686239459}. Best is trial 1 with value: 77.02380578750139.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:38:49,537]\u001b[0m Trial 3 finished with value: 75.84568397248532 and parameters: {'max_depth': 8, 'alpha': 71.27087140564048, 'min_child_weight': 100, 'subsample': 0.5114553701914726, 'eta': 0.10532813405553175}. Best is trial 3 with value: 75.84568397248532.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:39:00,688]\u001b[0m Trial 4 finished with value: 79.24528251039771 and parameters: {'max_depth': 3, 'alpha': 569.4373647459664, 'min_child_weight': 89, 'subsample': 0.7049259419901959, 'eta': 0.1991279931446049}. Best is trial 3 with value: 75.84568397248532.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:39:27,348]\u001b[0m Trial 5 finished with value: 72.87626544251876 and parameters: {'max_depth': 7, 'alpha': 17.446370432440684, 'min_child_weight': 70, 'subsample': 0.8197475403827663, 'eta': 0.11950101013136272}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:40:03,156]\u001b[0m Trial 6 finished with value: 79.67777782906306 and parameters: {'max_depth': 8, 'alpha': 93.95774599445939, 'min_child_weight': 12, 'subsample': 0.8856977253181799, 'eta': 0.3677019348005638}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:40:10,388]\u001b[0m Trial 7 finished with value: 79.83207904514698 and parameters: {'max_depth': 2, 'alpha': 921.3524155540516, 'min_child_weight': 18, 'subsample': 0.6071649012352914, 'eta': 0.1428285881574027}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:40:32,526]\u001b[0m Trial 8 finished with value: 76.11333836402889 and parameters: {'max_depth': 6, 'alpha': 158.46003290587495, 'min_child_weight': 30, 'subsample': 0.6630682352765657, 'eta': 0.18087601086155877}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:41:04,670]\u001b[0m Trial 9 finished with value: 78.71398548817686 and parameters: {'max_depth': 8, 'alpha': 281.3364244988845, 'min_child_weight': 76, 'subsample': 0.8354604589739707, 'eta': 0.29429450448439476}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:41:46,078]\u001b[0m Trial 10 finished with value: 75.38634314536843 and parameters: {'max_depth': 9, 'alpha': 405.2634566881888, 'min_child_weight': 42, 'subsample': 0.9807998055993875, 'eta': 0.27250960263292057}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:42:28,247]\u001b[0m Trial 11 finished with value: 76.97887819901742 and parameters: {'max_depth': 9, 'alpha': 385.05684079071, 'min_child_weight': 44, 'subsample': 0.9902858603660764, 'eta': 0.2741003569734054}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:42:59,947]\u001b[0m Trial 12 finished with value: 79.00590977248038 and parameters: {'max_depth': 7, 'alpha': 771.693293432469, 'min_child_weight': 50, 'subsample': 0.9833736593112152, 'eta': 0.3324708964642379}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:43:34,551]\u001b[0m Trial 13 finished with value: 80.3679712952508 and parameters: {'max_depth': 9, 'alpha': 1.6240307004530337, 'min_child_weight': 59, 'subsample': 0.8878182263994833, 'eta': 0.4565976582960169}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:44:02,830]\u001b[0m Trial 14 finished with value: 75.2419466359473 and parameters: {'max_depth': 7, 'alpha': 414.05936668619256, 'min_child_weight': 36, 'subsample': 0.7956405970152522, 'eta': 0.10721894996527502}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:44:28,865]\u001b[0m Trial 15 finished with value: 75.9878905915093 and parameters: {'max_depth': 6, 'alpha': 720.0681429449196, 'min_child_weight': 0, 'subsample': 0.8142085064321046, 'eta': 0.10205035571523037}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:44:43,840]\u001b[0m Trial 16 finished with value: 75.02692274686075 and parameters: {'max_depth': 4, 'alpha': 335.039022052757, 'min_child_weight': 66, 'subsample': 0.7892541388459663, 'eta': 0.16651605093687322}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:44:55,206]\u001b[0m Trial 17 finished with value: 78.78332304426065 and parameters: {'max_depth': 3, 'alpha': 267.65419982803854, 'min_child_weight': 76, 'subsample': 0.8525717676305501, 'eta': 0.18074039077525406}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:44:59,604]\u001b[0m Trial 18 finished with value: 84.86921367458474 and parameters: {'max_depth': 1, 'alpha': 314.7698321231883, 'min_child_weight': 59, 'subsample': 0.9110096172534815, 'eta': 0.22652031476556614}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:45:14,707]\u001b[0m Trial 19 finished with value: 79.49312262346432 and parameters: {'max_depth': 4, 'alpha': 524.3202611896247, 'min_child_weight': 98, 'subsample': 0.764089704421335, 'eta': 0.16098542745193378}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:45:28,466]\u001b[0m Trial 20 finished with value: 79.57043176781805 and parameters: {'max_depth': 4, 'alpha': 7.992322395294423, 'min_child_weight': 116, 'subsample': 0.6725249120169093, 'eta': 0.2168084162276126}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:45:56,990]\u001b[0m Trial 21 finished with value: 75.77042364098418 and parameters: {'max_depth': 7, 'alpha': 426.7812655177545, 'min_child_weight': 35, 'subsample': 0.7914744501585645, 'eta': 0.1326514754763159}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:46:20,959]\u001b[0m Trial 22 finished with value: 74.71888785625812 and parameters: {'max_depth': 6, 'alpha': 682.7553432388506, 'min_child_weight': 67, 'subsample': 0.7942830128814948, 'eta': 0.12441495376871681}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:46:45,810]\u001b[0m Trial 23 finished with value: 75.9255318000287 and parameters: {'max_depth': 6, 'alpha': 671.4925002263429, 'min_child_weight': 69, 'subsample': 0.9229107105169898, 'eta': 0.14893757813182745}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:47:01,264]\u001b[0m Trial 24 finished with value: 78.65270214212134 and parameters: {'max_depth': 4, 'alpha': 801.4226733305587, 'min_child_weight': 81, 'subsample': 0.8466236452828909, 'eta': 0.13999119678237934}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:47:24,513]\u001b[0m Trial 25 finished with value: 76.44402467401008 and parameters: {'max_depth': 6, 'alpha': 868.1061629286465, 'min_child_weight': 63, 'subsample': 0.7235846042581046, 'eta': 0.18093512240514656}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:47:43,706]\u001b[0m Trial 26 finished with value: 76.81182653068953 and parameters: {'max_depth': 5, 'alpha': 658.4940270296295, 'min_child_weight': 53, 'subsample': 0.7710663436145959, 'eta': 0.12549252971711278}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:47:54,938]\u001b[0m Trial 27 finished with value: 79.14518838608227 and parameters: {'max_depth': 3, 'alpha': 495.04317574647087, 'min_child_weight': 85, 'subsample': 0.8231637577625006, 'eta': 0.2583378910534704}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:48:22,795]\u001b[0m Trial 28 finished with value: 75.76168225553381 and parameters: {'max_depth': 7, 'alpha': 185.46536334443476, 'min_child_weight': 102, 'subsample': 0.9337371439712899, 'eta': 0.16480662926287554}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:48:37,463]\u001b[0m Trial 29 finished with value: 76.35434082092893 and parameters: {'max_depth': 4, 'alpha': 615.7267187397515, 'min_child_weight': 67, 'subsample': 0.7260118646579098, 'eta': 0.20148799910311282}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:49:00,335]\u001b[0m Trial 30 finished with value: 78.4644613428213 and parameters: {'max_depth': 6, 'alpha': 494.53074327361975, 'min_child_weight': 52, 'subsample': 0.6848127335136737, 'eta': 0.33001440154189743}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:49:29,650]\u001b[0m Trial 31 finished with value: 74.62188337883865 and parameters: {'max_depth': 7, 'alpha': 377.90497014312723, 'min_child_weight': 32, 'subsample': 0.8048765831738828, 'eta': 0.10181569642365346}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:49:49,230]\u001b[0m Trial 32 finished with value: 75.79970228735438 and parameters: {'max_depth': 5, 'alpha': 327.88606371357383, 'min_child_weight': 75, 'subsample': 0.8662060524965635, 'eta': 0.12589347616640623}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:50:16,733]\u001b[0m Trial 33 finished with value: 77.08416914023665 and parameters: {'max_depth': 7, 'alpha': 119.79213019037157, 'min_child_weight': 28, 'subsample': 0.7549953548618707, 'eta': 0.12123628290578631}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:50:47,808]\u001b[0m Trial 34 finished with value: 73.8551575631542 and parameters: {'max_depth': 8, 'alpha': 206.15031206517529, 'min_child_weight': 60, 'subsample': 0.7914570912260337, 'eta': 0.1002366586383201}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:51:19,861]\u001b[0m Trial 35 finished with value: 75.09818160789118 and parameters: {'max_depth': 8, 'alpha': 232.51665731171983, 'min_child_weight': 44, 'subsample': 0.8082275508562556, 'eta': 0.10714056911328979}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:51:52,917]\u001b[0m Trial 36 finished with value: 82.75594469195075 and parameters: {'max_depth': 8, 'alpha': 51.83845271824586, 'min_child_weight': 13, 'subsample': 0.7457254081991068, 'eta': 0.44899115259255096}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:52:19,470]\u001b[0m Trial 37 finished with value: 75.2698072489552 and parameters: {'max_depth': 8, 'alpha': 139.59332781175615, 'min_child_weight': 94, 'subsample': 0.6173581926468027, 'eta': 0.1018788907763682}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:52:49,998]\u001b[0m Trial 38 finished with value: 77.25927940702049 and parameters: {'max_depth': 7, 'alpha': 217.71850543354248, 'min_child_weight': 23, 'subsample': 0.8621485786929561, 'eta': 0.20247284636847981}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:53:17,565]\u001b[0m Trial 39 finished with value: 77.78330077844033 and parameters: {'max_depth': 9, 'alpha': 70.82091170012853, 'min_child_weight': 58, 'subsample': 0.501853306757283, 'eta': 0.15084210738850345}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:53:41,713]\u001b[0m Trial 40 finished with value: 77.47778191457628 and parameters: {'max_depth': 6, 'alpha': 561.161276699925, 'min_child_weight': 108, 'subsample': 0.8895420652969035, 'eta': 0.24892863004586316}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:54:00,743]\u001b[0m Trial 41 finished with value: 75.83273990725189 and parameters: {'max_depth': 5, 'alpha': 346.4717007723859, 'min_child_weight': 68, 'subsample': 0.7937461524193514, 'eta': 0.17394834454685995}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:54:27,116]\u001b[0m Trial 42 finished with value: 74.82902125097327 and parameters: {'max_depth': 7, 'alpha': 447.7316670886733, 'min_child_weight': 83, 'subsample': 0.7739922428610406, 'eta': 0.12402984169678255}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:54:53,515]\u001b[0m Trial 43 finished with value: 75.82671540998987 and parameters: {'max_depth': 7, 'alpha': 993.6508635301852, 'min_child_weight': 85, 'subsample': 0.734868908704065, 'eta': 0.12122511226639646}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:55:24,657]\u001b[0m Trial 44 finished with value: 77.23259387459402 and parameters: {'max_depth': 8, 'alpha': 448.57017473721663, 'min_child_weight': 80, 'subsample': 0.8306406840416405, 'eta': 0.1424551313659464}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:55:47,389]\u001b[0m Trial 45 finished with value: 76.52796480472506 and parameters: {'max_depth': 6, 'alpha': 267.5576046327119, 'min_child_weight': 91, 'subsample': 0.7755836652680191, 'eta': 0.11970199388189023}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:56:13,168]\u001b[0m Trial 46 finished with value: 79.94465238072888 and parameters: {'max_depth': 7, 'alpha': 465.56276396640436, 'min_child_weight': 74, 'subsample': 0.6421041852233894, 'eta': 0.39729537142853155}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:56:45,747]\u001b[0m Trial 47 finished with value: 74.30726433007189 and parameters: {'max_depth': 8, 'alpha': 376.26908896101327, 'min_child_weight': 48, 'subsample': 0.8117033908399881, 'eta': 0.10112911773224174}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:57:17,663]\u001b[0m Trial 48 finished with value: 74.78163715525162 and parameters: {'max_depth': 8, 'alpha': 376.13860681138357, 'min_child_weight': 49, 'subsample': 0.812920710051217, 'eta': 0.10057496160804144}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n",
      "\u001b[32m[I 2022-12-15 10:57:49,184]\u001b[0m Trial 49 finished with value: 75.03167647867211 and parameters: {'max_depth': 9, 'alpha': 187.88131284150344, 'min_child_weight': 35, 'subsample': 0.5611342416569123, 'eta': 0.15294051734904007}. Best is trial 5 with value: 72.87626544251876.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "def objective(trial):\n",
    "    \n",
    "    params = {\n",
    "        'objective': 'reg:squarederror',\n",
    "        'max_depth': trial.suggest_int('max_depth', 1, 9),\n",
    "        'alpha': trial.suggest_float('alpha', 0, 1000),\n",
    "        'min_child_weight': trial.suggest_int('min_child_weight', 0, 120),\n",
    "        'subsample': trial.suggest_float('subsample', 0.5, 1),\n",
    "        'eta': trial.suggest_float('eta', 0.1, 0.5),\n",
    "    }\n",
    "    \n",
    "    # Fit model\n",
    "    bst = XGBRegressor(**params)\n",
    "    bst.fit(X_train, y_train)\n",
    "    \n",
    "    # make predictions\n",
    "    preds = bst.predict(X_validation)\n",
    "    \n",
    "    # Return target metric\n",
    "    return np.sqrt(metrics.mean_squared_error(y_validation, preds))\n",
    "\n",
    "# 最適なパラメーターを探すため、実行に20分ほどかかります。\n",
    "study = optuna.create_study()\n",
    "study.optimize(objective, n_trials=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation data\n",
      "RMSE: 72.87626544251876\n",
      "MAE: 46.227257232512194\n",
      "R2: 0.8969308192107929\n",
      "Test data\n",
      "RMSE: 50.24950549434309\n",
      "MAE: 35.37940113033567\n",
      "R2: 0.9549393007439243\n"
     ]
    }
   ],
   "source": [
    "bst = XGBRegressor(**study.best_params)\n",
    "bst.fit(X_train, y_train)\n",
    "\n",
    "print('Validation data')\n",
    "validation_preds = bst.predict(X_validation)\n",
    "model_utils.calc_accuracy(y_validation, validation_preds)\n",
    "\n",
    "print('Test data')\n",
    "test_preds = bst.predict(X_test)\n",
    "model_utils.calc_accuracy(y_test, test_preds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'max_depth': '7',\n",
       " 'alpha': '17.446370432440684',\n",
       " 'min_child_weight': '70',\n",
       " 'subsample': '0.8197475403827663',\n",
       " 'eta': '0.11950101013136272'}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "best_params_str = {k: str(v) for k, v in study.best_params.items()}\n",
    "best_params_str"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 得られたハイパーパラメーターを利用してモデルのトレーニングを行う"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_data_prefix = 'model_monitor/data/nyctaxi/model_training'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "s3://sagemaker-ap-northeast-1-370828233696/model_monitor/data/nyctaxi/model_training/data.train\n",
      "s3://sagemaker-ap-northeast-1-370828233696/model_monitor/data/nyctaxi/model_training/data.validate\n"
     ]
    }
   ],
   "source": [
    "# Split data to train, validation and test, and save the data in S3\n",
    "data_path = f's3://{bucket}/{model_data_prefix}'\n",
    "train_data_file = 'data.train'\n",
    "validation_data_file = 'data.validate'\n",
    "\n",
    "# Upload train and validate data to s3\n",
    "df_train.to_csv(f'./{train_data_file}', index=False, header=False)\n",
    "resp = sagemaker.s3.S3Uploader.upload(f'./{train_data_file}', data_path)\n",
    "print(resp)\n",
    "\n",
    "df_validation.to_csv(f'./{validation_data_file}', index=False, header=False)\n",
    "resp = sagemaker.s3.S3Uploader.upload(f'./{validation_data_file}', data_path)\n",
    "print(resp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training job nyctaxi-xgboost-regression-2022-12-15-10-58-19\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "InProgress\n",
      "Completed\n",
      "arn:aws:sagemaker:ap-northeast-1:370828233696:model/nyctaxi-xgboost-regression-2022-12-15-10-58-19-model\n",
      "Model creation completed.\n",
      "\n",
      "Endpoint deployment started.\n",
      "Endpoint name: nyctaxi-testing-endpoint-2022-12-15-10-58-19\n",
      "Status: Creating\n",
      "Status: Creating\n",
      "Status: Creating\n",
      "Status: Creating\n",
      "Status: Creating\n",
      "Endpoint deployment completed.\n",
      "Endpoint arn: arn:aws:sagemaker:ap-northeast-1:370828233696:endpoint/nyctaxi-testing-endpoint-2022-12-15-10-58-19\n",
      "CPU times: user 265 ms, sys: 20.4 ms, total: 286 ms\n",
      "Wall time: 14min 3s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# モデルの学習とエンドポイントのデプロイをまとめて行うので、実行に15分程度かかります\n",
    "\n",
    "# Set environments for model training\n",
    "role = sagemaker.get_execution_role()\n",
    "region = boto3.Session().region_name\n",
    "# container = get_image_uri(region, 'xgboost', '1.0-1')\n",
    "container = sagemaker.image_uris.retrieve('xgboost', region, '1.5-1')\n",
    "\n",
    "training_start_time = datetime.now().strftime('%Y-%m-%d-%H-%M-%S')\n",
    "\n",
    "job_name = 'nyctaxi-xgboost-regression-' + training_start_time\n",
    "model_prefix = 'model/nyctaxi-xgboost-regression'\n",
    "print(\"Training job\", job_name)\n",
    "\n",
    "# Define model training parameters\n",
    "create_training_params = \\\n",
    "{\n",
    "    \"AlgorithmSpecification\": {\n",
    "        \"TrainingImage\": container,\n",
    "        \"TrainingInputMode\": \"File\"\n",
    "    },\n",
    "    \"RoleArn\": role,\n",
    "    \"OutputDataConfig\": {\n",
    "        \"S3OutputPath\": f's3://{bucket}/{model_prefix}'\n",
    "    },\n",
    "    \"ResourceConfig\": {\n",
    "        \"InstanceCount\": 1,\n",
    "        \"InstanceType\": \"ml.m5.large\",\n",
    "        \"VolumeSizeInGB\": 5\n",
    "    },\n",
    "    \"TrainingJobName\": job_name,\n",
    "    \"HyperParameters\": {\n",
    "        **best_params_str,\n",
    "        \"num_round\":\"1000\"\n",
    "    },\n",
    "    \"StoppingCondition\": {\n",
    "        \"MaxRuntimeInSeconds\": 3600\n",
    "    },\n",
    "    \"InputDataConfig\": [\n",
    "        {\n",
    "            \"ChannelName\": \"train\",\n",
    "            \"DataSource\": {\n",
    "                \"S3DataSource\": {\n",
    "                    \"S3DataType\": \"S3Prefix\",\n",
    "                    \"S3Uri\": f'{data_path}/{train_data_file}',\n",
    "                    \"S3DataDistributionType\": \"FullyReplicated\"\n",
    "                }\n",
    "            },\n",
    "            \"ContentType\": \"csv\",\n",
    "            \"CompressionType\": \"None\"\n",
    "        },\n",
    "        {\n",
    "            \"ChannelName\": \"validation\",\n",
    "            \"DataSource\": {\n",
    "                \"S3DataSource\": {\n",
    "                    \"S3DataType\": \"S3Prefix\",\n",
    "                    \"S3Uri\": f'{data_path}/{validation_data_file}',\n",
    "                    \"S3DataDistributionType\": \"FullyReplicated\"\n",
    "                }\n",
    "            },\n",
    "            \"ContentType\": \"csv\",\n",
    "            \"CompressionType\": \"None\"\n",
    "        }\n",
    "    ]\n",
    "}\n",
    "\n",
    "# Start model training\n",
    "client = boto3.client('sagemaker', region_name=region)\n",
    "client.create_training_job(**create_training_params)\n",
    "\n",
    "# Wait for model training completion\n",
    "status = client.describe_training_job(TrainingJobName=job_name)['TrainingJobStatus']\n",
    "print(status)\n",
    "while status !='Completed' and status!='Failed':\n",
    "    time.sleep(60)\n",
    "    status = client.describe_training_job(TrainingJobName=job_name)['TrainingJobStatus']\n",
    "    print(status)\n",
    "\n",
    "# Create model\n",
    "model_name=job_name + '-model'\n",
    "info = client.describe_training_job(TrainingJobName=job_name)\n",
    "model_data = info['ModelArtifacts']['S3ModelArtifacts']\n",
    "primary_container = {\n",
    "    'Image': container,\n",
    "    'ModelDataUrl': model_data\n",
    "}\n",
    "\n",
    "create_model_response = client.create_model(\n",
    "    ModelName = model_name,\n",
    "    ExecutionRoleArn = role,\n",
    "    PrimaryContainer = primary_container)\n",
    "\n",
    "print(create_model_response['ModelArn'])\n",
    "print('Model creation completed.')\n",
    "print('')\n",
    "\n",
    "# Deploy model to endpoint\n",
    "endpoint_name = 'nyctaxi-testing-endpoint-' + training_start_time\n",
    "endpoint_config_name = 'nyctaxi-testing-endpoint-config-' + training_start_time\n",
    "print('Endpoint deployment started.')\n",
    "\n",
    "create_endpoint_config_response = client.create_endpoint_config(\n",
    "    EndpointConfigName = endpoint_config_name,\n",
    "    ProductionVariants=[{\n",
    "        'InstanceType':'ml.t2.medium',\n",
    "        'InitialVariantWeight':1,\n",
    "        'InitialInstanceCount':1,\n",
    "        'ModelName':model_name,\n",
    "        'VariantName':'AllTraffic'}])\n",
    "\n",
    "print('Endpoint name:', endpoint_name)\n",
    "create_endpoint_response = client.create_endpoint(\n",
    "    EndpointName=endpoint_name,\n",
    "    EndpointConfigName=endpoint_config_name)\n",
    "\n",
    "# Check endpoint creation status\n",
    "resp = client.describe_endpoint(EndpointName=endpoint_name)\n",
    "status = resp['EndpointStatus']\n",
    "while status=='Creating':\n",
    "    print(\"Status: \" + status)\n",
    "    time.sleep(60)\n",
    "    resp = client.describe_endpoint(EndpointName=endpoint_name)\n",
    "    status = resp['EndpointStatus']\n",
    "\n",
    "print('Endpoint deployment completed.')\n",
    "print('Endpoint arn:', resp['EndpointArn'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "学習されたモデルの名前\n",
      "nyctaxi-xgboost-regression-2022-12-15-10-58-19-model\n"
     ]
    }
   ],
   "source": [
    "print('学習されたモデルの名前')\n",
    "print(model_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- <span style=\"color: orange; \">ここで作成したモデルの名前を、データ品質やモデル品質のモニタリング時に設定してください。</span>\n",
    "- エンドポイントは学習時のテスト用なので、このノートブック以降では使用しません  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### デプロイした推論エンドポイントを使ってテストする"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
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       "      <td>652.0</td>\n",
       "      <td>594.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>641.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.245378</td>\n",
       "      <td>0.193127</td>\n",
       "      <td>0.239437</td>\n",
       "      <td>0.787042</td>\n",
       "      <td>0.313423</td>\n",
       "      <td>0.223082</td>\n",
       "      <td>0.138045</td>\n",
       "      <td>0.257931</td>\n",
       "      <td>0.290571</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28 22:45:00</th>\n",
       "      <td>727</td>\n",
       "      <td>789.0</td>\n",
       "      <td>899.0</td>\n",
       "      <td>879.0</td>\n",
       "      <td>646.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>661.0</td>\n",
       "      <td>589.0</td>\n",
       "      <td>626.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.174195</td>\n",
       "      <td>0.190456</td>\n",
       "      <td>0.258225</td>\n",
       "      <td>0.405913</td>\n",
       "      <td>0.353292</td>\n",
       "      <td>0.312892</td>\n",
       "      <td>0.296960</td>\n",
       "      <td>0.198254</td>\n",
       "      <td>0.237768</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28 23:00:00</th>\n",
       "      <td>732</td>\n",
       "      <td>677.0</td>\n",
       "      <td>911.0</td>\n",
       "      <td>857.0</td>\n",
       "      <td>739.0</td>\n",
       "      <td>708.0</td>\n",
       "      <td>673.0</td>\n",
       "      <td>657.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>610.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.273648</td>\n",
       "      <td>0.261844</td>\n",
       "      <td>0.218833</td>\n",
       "      <td>0.360368</td>\n",
       "      <td>0.347987</td>\n",
       "      <td>0.210449</td>\n",
       "      <td>0.227228</td>\n",
       "      <td>0.206366</td>\n",
       "      <td>0.269820</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28 23:15:00</th>\n",
       "      <td>651</td>\n",
       "      <td>629.0</td>\n",
       "      <td>879.0</td>\n",
       "      <td>882.0</td>\n",
       "      <td>763.0</td>\n",
       "      <td>636.0</td>\n",
       "      <td>713.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>571.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.297361</td>\n",
       "      <td>0.158965</td>\n",
       "      <td>0.251508</td>\n",
       "      <td>0.376248</td>\n",
       "      <td>0.401356</td>\n",
       "      <td>0.303953</td>\n",
       "      <td>0.166909</td>\n",
       "      <td>0.228785</td>\n",
       "      <td>0.255742</td>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28 23:30:00</th>\n",
       "      <td>660</td>\n",
       "      <td>582.0</td>\n",
       "      <td>869.0</td>\n",
       "      <td>889.0</td>\n",
       "      <td>856.0</td>\n",
       "      <td>648.0</td>\n",
       "      <td>684.0</td>\n",
       "      <td>737.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>540.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209467</td>\n",
       "      <td>0.190713</td>\n",
       "      <td>0.206524</td>\n",
       "      <td>0.331530</td>\n",
       "      <td>0.293599</td>\n",
       "      <td>0.311977</td>\n",
       "      <td>0.306903</td>\n",
       "      <td>0.255863</td>\n",
       "      <td>0.183760</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-28 23:45:00</th>\n",
       "      <td>606</td>\n",
       "      <td>631.0</td>\n",
       "      <td>789.0</td>\n",
       "      <td>899.0</td>\n",
       "      <td>879.0</td>\n",
       "      <td>646.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>661.0</td>\n",
       "      <td>589.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.295404</td>\n",
       "      <td>0.174195</td>\n",
       "      <td>0.190456</td>\n",
       "      <td>0.451774</td>\n",
       "      <td>0.405913</td>\n",
       "      <td>0.353292</td>\n",
       "      <td>0.330726</td>\n",
       "      <td>0.296960</td>\n",
       "      <td>0.198254</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2688 rows × 143 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     pickup_count  history_12slots  history_16slots  \\\n",
       "timestamp                                                             \n",
       "2020-02-01 00:00:00           537            758.0            639.0   \n",
       "2020-02-01 00:15:00           467            686.0            635.0   \n",
       "2020-02-01 00:30:00           461            613.0            636.0   \n",
       "2020-02-01 00:45:00           435            653.0            770.0   \n",
       "2020-02-01 01:00:00           444            608.0            758.0   \n",
       "...                           ...              ...              ...   \n",
       "2020-02-28 22:45:00           727            789.0            899.0   \n",
       "2020-02-28 23:00:00           732            677.0            911.0   \n",
       "2020-02-28 23:15:00           651            629.0            879.0   \n",
       "2020-02-28 23:30:00           660            582.0            869.0   \n",
       "2020-02-28 23:45:00           606            631.0            789.0   \n",
       "\n",
       "                     history_20slots  history_24slots  history_28slots  \\\n",
       "timestamp                                                                \n",
       "2020-02-01 00:00:00            773.0            837.0            652.0   \n",
       "2020-02-01 00:15:00            773.0            803.0            712.0   \n",
       "2020-02-01 00:30:00            733.0            850.0            720.0   \n",
       "2020-02-01 00:45:00            656.0            822.0            827.0   \n",
       "2020-02-01 01:00:00            639.0            773.0            837.0   \n",
       "...                              ...              ...              ...   \n",
       "2020-02-28 22:45:00            879.0            646.0            650.0   \n",
       "2020-02-28 23:00:00            857.0            739.0            708.0   \n",
       "2020-02-28 23:15:00            882.0            763.0            636.0   \n",
       "2020-02-28 23:30:00            889.0            856.0            648.0   \n",
       "2020-02-28 23:45:00            899.0            879.0            646.0   \n",
       "\n",
       "                     history_32slots  history_36slots  history_40slots  \\\n",
       "timestamp                                                                \n",
       "2020-02-01 00:00:00            594.0            689.0            641.0   \n",
       "2020-02-01 00:15:00            636.0            664.0            589.0   \n",
       "2020-02-01 00:30:00            621.0            618.0            686.0   \n",
       "2020-02-01 00:45:00            605.0            628.0            654.0   \n",
       "2020-02-01 01:00:00            652.0            594.0            689.0   \n",
       "...                              ...              ...              ...   \n",
       "2020-02-28 22:45:00            700.0            661.0            589.0   \n",
       "2020-02-28 23:00:00            673.0            657.0            590.0   \n",
       "2020-02-28 23:15:00            713.0            603.0            618.0   \n",
       "2020-02-28 23:30:00            684.0            737.0            618.0   \n",
       "2020-02-28 23:45:00            650.0            700.0            661.0   \n",
       "\n",
       "                     history_44slots  ...  tolls_amount_mean_12slot  \\\n",
       "timestamp                             ...                             \n",
       "2020-02-01 00:00:00            569.0  ...                  0.193127   \n",
       "2020-02-01 00:15:00            592.0  ...                  0.318950   \n",
       "2020-02-01 00:30:00            611.0  ...                  0.219462   \n",
       "2020-02-01 00:45:00            614.0  ...                  0.212894   \n",
       "2020-02-01 01:00:00            641.0  ...                  0.245378   \n",
       "...                              ...  ...                       ...   \n",
       "2020-02-28 22:45:00            626.0  ...                  0.174195   \n",
       "2020-02-28 23:00:00            610.0  ...                  0.273648   \n",
       "2020-02-28 23:15:00            571.0  ...                  0.297361   \n",
       "2020-02-28 23:30:00            540.0  ...                  0.209467   \n",
       "2020-02-28 23:45:00            589.0  ...                  0.295404   \n",
       "\n",
       "                     tolls_amount_mean_16slot  tolls_amount_mean_20slot  \\\n",
       "timestamp                                                                 \n",
       "2020-02-01 00:00:00                  0.239437                  0.351979   \n",
       "2020-02-01 00:15:00                  0.240945                  0.199884   \n",
       "2020-02-01 00:30:00                  0.253349                  0.195689   \n",
       "2020-02-01 00:45:00                  0.288740                  0.179558   \n",
       "2020-02-01 01:00:00                  0.193127                  0.239437   \n",
       "...                                       ...                       ...   \n",
       "2020-02-28 22:45:00                  0.190456                  0.258225   \n",
       "2020-02-28 23:00:00                  0.261844                  0.218833   \n",
       "2020-02-28 23:15:00                  0.158965                  0.251508   \n",
       "2020-02-28 23:30:00                  0.190713                  0.206524   \n",
       "2020-02-28 23:45:00                  0.174195                  0.190456   \n",
       "\n",
       "                     tolls_amount_mean_96slot  tolls_amount_mean_100slot  \\\n",
       "timestamp                                                                  \n",
       "2020-02-01 00:00:00                  0.313423                   0.223082   \n",
       "2020-02-01 00:15:00                  0.232559                   0.315537   \n",
       "2020-02-01 00:30:00                  0.479963                   0.247932   \n",
       "2020-02-01 00:45:00                  0.528936                   0.148938   \n",
       "2020-02-01 01:00:00                  0.787042                   0.313423   \n",
       "...                                       ...                        ...   \n",
       "2020-02-28 22:45:00                  0.405913                   0.353292   \n",
       "2020-02-28 23:00:00                  0.360368                   0.347987   \n",
       "2020-02-28 23:15:00                  0.376248                   0.401356   \n",
       "2020-02-28 23:30:00                  0.331530                   0.293599   \n",
       "2020-02-28 23:45:00                  0.451774                   0.405913   \n",
       "\n",
       "                     tolls_amount_mean_104slot  tolls_amount_mean_192slot  \\\n",
       "timestamp                                                                   \n",
       "2020-02-01 00:00:00                   0.242169                   0.257931   \n",
       "2020-02-01 00:15:00                   0.273710                   0.561222   \n",
       "2020-02-01 00:30:00                   0.345783                   0.175694   \n",
       "2020-02-01 00:45:00                   0.314701                   0.267750   \n",
       "2020-02-01 01:00:00                   0.223082                   0.138045   \n",
       "...                                        ...                        ...   \n",
       "2020-02-28 22:45:00                   0.312892                   0.296960   \n",
       "2020-02-28 23:00:00                   0.210449                   0.227228   \n",
       "2020-02-28 23:15:00                   0.303953                   0.166909   \n",
       "2020-02-28 23:30:00                   0.311977                   0.306903   \n",
       "2020-02-28 23:45:00                   0.353292                   0.330726   \n",
       "\n",
       "                     tolls_amount_mean_196slot  tolls_amount_mean_200slot  \\\n",
       "timestamp                                                                   \n",
       "2020-02-01 00:00:00                   0.290571                   0.242643   \n",
       "2020-02-01 00:15:00                   0.251507                   0.276241   \n",
       "2020-02-01 00:30:00                   0.209829                   0.268718   \n",
       "2020-02-01 00:45:00                   0.362395                   0.206045   \n",
       "2020-02-01 01:00:00                   0.257931                   0.290571   \n",
       "...                                        ...                        ...   \n",
       "2020-02-28 22:45:00                   0.198254                   0.237768   \n",
       "2020-02-28 23:00:00                   0.206366                   0.269820   \n",
       "2020-02-28 23:15:00                   0.228785                   0.255742   \n",
       "2020-02-28 23:30:00                   0.255863                   0.183760   \n",
       "2020-02-28 23:45:00                   0.296960                   0.198254   \n",
       "\n",
       "                     time_slot  \n",
       "timestamp                       \n",
       "2020-02-01 00:00:00          0  \n",
       "2020-02-01 00:15:00          1  \n",
       "2020-02-01 00:30:00          2  \n",
       "2020-02-01 00:45:00          3  \n",
       "2020-02-01 01:00:00          4  \n",
       "...                        ...  \n",
       "2020-02-28 22:45:00         91  \n",
       "2020-02-28 23:00:00         92  \n",
       "2020-02-28 23:15:00         93  \n",
       "2020-02-28 23:30:00         94  \n",
       "2020-02-28 23:45:00         95  \n",
       "\n",
       "[2688 rows x 143 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test['timestamp'] = df_test.apply(lambda x: x.name + pd.offsets.Minute(x.time_slot*15), axis=1)\n",
    "df_test = df_test.set_index('timestamp')\n",
    "df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE: 52.072790599634025\n",
      "MAE: 37.37686011904762\n",
      "R2: 0.9516099526556806\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f3822a6d450>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "# Exec prediction\n",
    "df_test[['pred', 'inference_id']] = model_utils.exec_prediction(endpoint_name, df_test)\n",
    "model_utils.calc_accuracy(df_test.pickup_count, df_test.pred)\n",
    "df_graph = df_test[:24*7*4]\n",
    "\n",
    "# plot\n",
    "pd.DataFrame({'y': df_graph.pickup_count, 'pred': df_graph.pred}).plot(ylim=(0,1000), figsize=(12,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### データ品質のためのベースライン・データセットをアップロードする\n",
    "このデータセットには推論結果は含めません。推論結果を含めてしまうと、推論リクエスト時に渡す特徴量の数と食い違うので、エラーが発生します。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'s3://sagemaker-ap-northeast-1-370828233696/model_monitor/data_quality_baseline_input/features-2019.csv'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Upload feature data for baseline job\n",
    "df_features.to_csv(f'./features-2019.csv', index=False)\n",
    "sagemaker.s3.S3Uploader.upload(f'./features-2019.csv', f's3://{bucket}/model_monitor/data_quality_baseline_input')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### モデル品質のためのベースライン・データセットをアップロードする\n",
    "モデル品質のためのデータセットには推論結果が必要なので、推論結果を保持したDataFrameの内容をアップロードします。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'s3://sagemaker-ap-northeast-1-370828233696/model_monitor/model_quality_baseline_input/test.csv'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Upload feature data for baseline job\n",
    "df_test.to_csv(f'./test.csv', index=False)\n",
    "sagemaker.s3.S3Uploader.upload(f'./test.csv', f's3://{bucket}/model_monitor/model_quality_baseline_input')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 対話的データ分析の参考コード"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import boto3\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "import model_utils\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2021年8月のデータを取得して傾向を調査"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VendorID</th>\n",
       "      <th>tpep_pickup_datetime</th>\n",
       "      <th>tpep_dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>RatecodeID</th>\n",
       "      <th>store_and_fwd_flag</th>\n",
       "      <th>PULocationID</th>\n",
       "      <th>DOLocationID</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>...</th>\n",
       "      <th>extra</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>improvement_surcharge</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "      <th>airport_fee</th>\n",
       "      <th>pickup_date_hour</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>118021</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-02 16:51:58</td>\n",
       "      <td>2021-08-02 16:57:30</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>229</td>\n",
       "      <td>137</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.06</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>12.36</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2021-08-02 16:00:00</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1873676</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-22 19:22:17</td>\n",
       "      <td>2021-08-22 19:50:23</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>2.0</td>\n",
       "      <td>N</td>\n",
       "      <td>132</td>\n",
       "      <td>230</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>12.35</td>\n",
       "      <td>6.55</td>\n",
       "      <td>0.3</td>\n",
       "      <td>74.20</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2021-08-22 19:00:00</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>948739</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-12 04:27:49</td>\n",
       "      <td>2021-08-12 04:36:36</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.20</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>74</td>\n",
       "      <td>126</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>12.30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2021-08-12 04:00:00</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060902</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-25 09:16:46</td>\n",
       "      <td>2021-08-25 09:42:36</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.33</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>151</td>\n",
       "      <td>164</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>4.96</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>29.76</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2021-08-25 09:00:00</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658824</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-08 18:39:17</td>\n",
       "      <td>2021-08-08 18:42:05</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.40</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>236</td>\n",
       "      <td>236</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.45</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>8.75</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2021-08-08 18:00:00</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
       "118021          1  2021-08-02 16:51:58   2021-08-02 16:57:30              1.0   \n",
       "1873676         1  2021-08-22 19:22:17   2021-08-22 19:50:23              1.0   \n",
       "948739          1  2021-08-12 04:27:49   2021-08-12 04:36:36              1.0   \n",
       "2060902         2  2021-08-25 09:16:46   2021-08-25 09:42:36              1.0   \n",
       "658824          1  2021-08-08 18:39:17   2021-08-08 18:42:05              2.0   \n",
       "\n",
       "         trip_distance  RatecodeID store_and_fwd_flag  PULocationID  \\\n",
       "118021            1.10         1.0                  N           229   \n",
       "1873676          18.10         2.0                  N           132   \n",
       "948739            3.20         1.0                  N            74   \n",
       "2060902           5.33         1.0                  N           151   \n",
       "658824            0.40         1.0                  N           236   \n",
       "\n",
       "         DOLocationID  payment_type  ...  extra  mta_tax  tip_amount  \\\n",
       "118021            137             1  ...    3.5      0.5        2.06   \n",
       "1873676           230             1  ...    2.5      0.5       12.35   \n",
       "948739            126             2  ...    0.5      0.5        0.00   \n",
       "2060902           164             1  ...    0.0      0.5        4.96   \n",
       "658824            236             1  ...    2.5      0.5        1.45   \n",
       "\n",
       "         tolls_amount  improvement_surcharge  total_amount  \\\n",
       "118021           0.00                    0.3         12.36   \n",
       "1873676          6.55                    0.3         74.20   \n",
       "948739           0.00                    0.3         12.30   \n",
       "2060902          0.00                    0.3         29.76   \n",
       "658824           0.00                    0.3          8.75   \n",
       "\n",
       "         congestion_surcharge  airport_fee    pickup_date_hour hour  \n",
       "118021                    2.5          0.0 2021-08-02 16:00:00   16  \n",
       "1873676                   2.5          0.0 2021-08-22 19:00:00   19  \n",
       "948739                    0.0          0.0 2021-08-12 04:00:00    4  \n",
       "2060902                   2.5          0.0 2021-08-25 09:00:00    9  \n",
       "658824                    2.5          0.0 2021-08-08 18:00:00   18  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw = model_utils.get_raw_data(2021, 8, sampling_rate=20)\n",
    "\n",
    "# Remove abnormal records\n",
    "df_raw = df_raw[0<df_raw.fare_amount]\n",
    "df_raw = df_raw[(0<df_raw.trip_distance) & (df_raw.trip_distance<100)].copy()\n",
    "\n",
    "df_raw['pickup_date_hour'] = pd.to_datetime(df_raw.tpep_pickup_datetime.dt.strftime('%Y-%m-%d-%H:00:00'))\n",
    "df_raw['hour'] = df_raw['pickup_date_hour'].dt.hour\n",
    "df_raw.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 平日3日間の乗車数推移"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d5546c990>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_3days = df_raw[('2021-8-02' <= df_raw.tpep_pickup_datetime) & (df_raw.tpep_pickup_datetime < '2021-08-05')].sort_values(by='pickup_date_hour').copy()\n",
    "df_3days.groupby(by='pickup_date_hour')['VendorID'].count().plot(figsize=(12,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 時間帯ごとの乗車料金の推移をプロット"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_data = df_raw[df_raw.fare_amount<100]\n",
    "fig, axes = plt.subplots(2,1, figsize=(14, 12))\n",
    "\n",
    "for ax, start, end in zip(axes, [0,13], [13,24]):\n",
    "    df_plot = df_data[(start<=df_data.hour) & (df_data.hour<end)]\n",
    "    sns.violinplot(data=df_plot, x='hour', y='fare_amount', ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特定の1日に絞って乗車料金とタクシー乗車数の連動をプロット"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VendorID</th>\n",
       "      <th>tpep_pickup_datetime</th>\n",
       "      <th>tpep_dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>RatecodeID</th>\n",
       "      <th>store_and_fwd_flag</th>\n",
       "      <th>PULocationID</th>\n",
       "      <th>DOLocationID</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>...</th>\n",
       "      <th>extra</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>improvement_surcharge</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "      <th>airport_fee</th>\n",
       "      <th>pickup_date_hour</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>147820</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-02 23:56:53</td>\n",
       "      <td>2021-08-03 00:24:30</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>138</td>\n",
       "      <td>48</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>4.25</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.00</td>\n",
       "      <td>6.55</td>\n",
       "      <td>0.3</td>\n",
       "      <td>46.60</td>\n",
       "      <td>2.5</td>\n",
       "      <td>1.25</td>\n",
       "      <td>2021-08-02 23:00:00</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2660769</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-02 23:01:33</td>\n",
       "      <td>2021-08-02 23:24:18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>132</td>\n",
       "      <td>145</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.5</td>\n",
       "      <td>8.71</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>52.26</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-08-02 23:00:00</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2660798</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 23:28:23</td>\n",
       "      <td>2021-08-02 23:48:50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>265</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>34.23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-08-02 23:00:00</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147845</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 23:49:04</td>\n",
       "      <td>2021-08-02 23:53:29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.42</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>68</td>\n",
       "      <td>48</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.96</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>11.76</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02 23:00:00</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147486</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 23:38:17</td>\n",
       "      <td>2021-08-02 23:44:20</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.71</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>237</td>\n",
       "      <td>140</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>9.80</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02 23:00:00</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
       "147820          1  2021-08-02 23:56:53   2021-08-03 00:24:30              1.0   \n",
       "2660769         1  2021-08-02 23:01:33   2021-08-02 23:24:18              NaN   \n",
       "2660798         2  2021-08-02 23:28:23   2021-08-02 23:48:50              NaN   \n",
       "147845          2  2021-08-02 23:49:04   2021-08-02 23:53:29              1.0   \n",
       "147486          2  2021-08-02 23:38:17   2021-08-02 23:44:20              1.0   \n",
       "\n",
       "         trip_distance  RatecodeID store_and_fwd_flag  PULocationID  \\\n",
       "147820           11.50         1.0                  N           138   \n",
       "2660769          15.10         NaN               None           132   \n",
       "2660798           5.49         NaN               None             4   \n",
       "147845            1.42         1.0                  N            68   \n",
       "147486            0.71         1.0                  N           237   \n",
       "\n",
       "         DOLocationID  payment_type  ...  extra  mta_tax  tip_amount  \\\n",
       "147820             48             1  ...   4.25      0.5        1.00   \n",
       "2660769           145             0  ...   1.75      0.5        8.71   \n",
       "2660798           265             0  ...   0.00      0.5        5.68   \n",
       "147845             48             1  ...   0.50      0.5        1.96   \n",
       "147486            140             2  ...   0.50      0.5        0.00   \n",
       "\n",
       "         tolls_amount  improvement_surcharge  total_amount  \\\n",
       "147820           6.55                    0.3         46.60   \n",
       "2660769          0.00                    0.3         52.26   \n",
       "2660798          0.00                    0.3         34.23   \n",
       "147845           0.00                    0.3         11.76   \n",
       "147486           0.00                    0.3          9.80   \n",
       "\n",
       "         congestion_surcharge  airport_fee    pickup_date_hour hour  \n",
       "147820                    2.5         1.25 2021-08-02 23:00:00   23  \n",
       "2660769                   NaN          NaN 2021-08-02 23:00:00   23  \n",
       "2660798                   NaN          NaN 2021-08-02 23:00:00   23  \n",
       "147845                    2.5         0.00 2021-08-02 23:00:00   23  \n",
       "147486                    2.5         0.00 2021-08-02 23:00:00   23  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_1day = df_raw[('2021-8-02' <= df_raw.tpep_pickup_datetime) & (df_raw.tpep_pickup_datetime < '2021-08-03')].sort_values(by='pickup_date_hour').copy()\n",
    "df_1day.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d52fee150>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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T16/Iod9Ixg7KkJxYaScyL+4GQGRusb2bOD1efrGfubFV92w2qkq70N/fj1//+tfYvn07vF7vkBGQV199NSXBUer09/cNeZ6Xl5emaGisRJJe7FRR32eNW/5AcorvHs/dAIjMJDYJYKWdyHzik3Z2j5ddfNLOSjuQZNJ+1113YceOHfjHf/xHlJeXc+qfBPr74yvtfX19cLvL0xQNjZWYOVHi1D/IBl9fkk9sos6kXX6x34tcjye/SISVdiIzY5JHmS6ppP2tt97CunXrsGzZslTHQ+Okp6cn7nlvb2+aIqFU6OvTZ06U5+pfTH6/D5FIBFarNZ1h0RjEVvJYJZBfbM8QDmzLj3sGE5kbk/bMxYFvXVJr2gsLC1FcXJzqWGgc9fbGJ+09PV1pioRSQVzP8pyBL6a+Pg7EyCx+uxom7fIbyOyY5MlP05gEEMmCA6WZhddTl1TS/h//8R/42c9+xuZXEuns7Ih73tXFpF1m3d3dAPQ17Xk2Ne4YySl2T9JIhEm77CyW2OnxaQyEiCgLcHZTplFO8zh7JTU9fsOGDTh16hSWL1+Oqqoq2Gzxv+b5559PSXCUOh0d8Ul7e7s3TZFQKnR3dwIACh0aCh0a+sNAd3cXgGnpDYySFj+1j1me/HiTkUliB144CENkPrHLA63WpNIbMpHYcZfYQfBsltS/6quuuirVcdA483rbAACR/HJY+9rg9XrSHBElKxKJGFX1QoeKQoeK5n4rOjra0xwZjQXX42UaZnaZhdeTyMxik/bYqjvJKX62BJN2IMmk/dvf/naq4zitlpYWPPjgg9i6dSv8fj9mzpyJ1atXY9GiRQD05gSPPvooNm/ejO7ubixZsgT33HMP5s6dO2ExyqClpQUAoBZUwtrXhtbWljRHRMnq6GiHqqqwKhqKHBpKnfrNJAdi5Ba7ZpZJu/xiZ0twpqb84vdpZwKfCXgdM0tsdd1mY1Ne2cUm7fwO1Zl6KKqrqwvXXXcd7HY71q9fj5dffhm33347CgsLjXPWr1+PDRs24J577sEzzzwDt9uNG264gd3RY/T29kSnTgPhYn36dGNjQzpDojHwePRZEyVOFRYFKIs2o2tra0tnWDRG8TeQvJmUXXySl8ZAKOXYlC4zcN1zZrFaB1IaVtozC79DdUlV2hcsWDDsh11NTU3SAcVav349Jk2ahDVr1hjHqqqqjMeapmHjxo24+eabcfXVVwMA1q5di+XLl+Oll17Cl770pZTEIbu6ulMAANWeBzVf35u9o6MdPT09KCgoSGdolITm5mYAQEV0u7fyXL2BWWtrc9piorGLTfJiO8mTnGK38GOSJz9W2jNP7HVUVZWJnuRir5/Fwkq77OI/c/kdCiSZtD/66KNxz8PhMGpqavD888/jlltuSUlgAPDaa69hxYoV+M53voPq6mpUVlbiy1/+Mr7whS8AAOrr69HW1oYVK1YYP+NwOHDhhRdi9+7dTNqjjh07CgBQ88sAmwOqswCWQA+OHz+KxYvPS3N0NFrNzY0ABpL2yuifzc1NaYuJxi52mzcm7fILhcIxj0PDnEkyiH1/xu70QJkhFArC6cxJdxg0BorCSnsmib0P4j2RLmWN6D7xiU9gzpw52LJlCz7/+c+POTAAqKurw5NPPokbbrgBN998M/bu3YtVq1bB4XDgn/7pn4zpwGVlZXE/53a70djYmJIYMsHhw4cAAGq+2/jTEujB4cOHmLRLSCxtmJyvf4hNzhtI2iORSFwzFpJHbGWW+7TLLxgMxDwOpjESSoX4G0i+PzNBbKXd7w8waZdcbIdxLn2QX+xgNwe+dSkdilqyZAnefffdlP0+TdNwzjnn4NZbb8XChQvxpS99CV/4whfw5JNPxp03+M3JqWvxamr2AwAiBZOif1bGHSe51NfXAQAm56rQNKA0R4XToiEcDqOlhVPkZRWb2AUC/jRGQqkQm7T7/byeshs8E4bNIuUX+znr8/WnMRJKBd76Z5bY96Tf70tjJOaRsqTd7/dj06ZNqKysTNWvRHl5OWbPnh13bNasWUYVvbxcX5/t8cR3zfZ6vXC73SmLQ2ZNTY3weNqgKRaorgoAgFowGQBQU3OAo1eSiUQiaGjQk/bnjufg/vcLoACY4tKrQKdOnUhfcJS0UCgUl7T7fPyCkl1sos5BGPnFzoTRn7PaLrvYhsV9fWxeLLvYgh2Ld/KLfU+yubguqenxF154YVx1W9M09PX1IScnBw8++GDKgjv//PNx/PjxuGMnTpzA1KlTAehN6crLy7Ft2zYsXLgQgF6tqq6uxn/+53+mLA6Z7dmzCwCguioBq11/nFcKzZYDv9+HQ4dqsGjR4nSGSKPQ2NiAcDgMh0XDiR797RtQgar8CI5323Dq1El85COXpjlKGq3e3p645z09Pac5k2TR19dnPO7vZxVPdoOXOIRCQTgcjjRFQ6kQmwjwM1d+8X0nOKgmu46OjpjH7WmMxDySStrvuOOOuOeKoqC0tBRLlixBUVFRSgIDgK997Wu47rrr8Nhjj+GTn/wk9u7di6effhr33Xef8fdef/31WLduHWbOnIkZM2Zg3bp1yMnJwWc+85mUxSGznTurAQCR4oGu+1AUhIurYPccwc6d1UzaJSIq6VPzIzjeM/D2nR6ttJ84cSwdYdEYiS8kzaJBURX09vYgGGRSIDNWCTJLIBCIe+73+5Gf70pTNDRWPp8P/f0DA2vt7d40RkOpwD4imaWpaaA3GRst65JK2q+55ppUx5HQ4sWL8eijj+Lhhx/GL37xC1RVVeGOO+7AZz/7WeOcm266CYFAAPfeey+6urqwZMkSPPHEE3C5+GXq8/nw4Yd7AADh4ulxr0WKp8PuOYLq6u342tf+NR3hURJOnNBnnkxzxSft0wr0pP3kyZNpiYvGxuhFUAxo3RqUsILW1mZUVU0f/gfJtDo7OxI+JjkNng3T19eLsjIuw5NVW1tL3PPW1pbTnEmy6OrqinncmcZIKBXq6gbuZ5ubmxEI+LO+WWRSSTsAdHd345lnnsHRo0ehKArmzJmDa6+9NuX7fq9cuRIrV6487euKouCWW25J6VZzmWLPnl0Ih8NQnYXQcovjXosUVUFTLGhqakR9fR2qqqalKUoajZMn9aS9yhW//YWotLe0NMHv9yMnJ7s/2GQjmgtqBRoUTQE6EH1fMmmXldfriXnclsZIKBVip2qK59Onz0xPMDRmJ0+eGPY5ySd2IKatrTWNkdBYaZqGgwdrYp6rqK09hHPPXZLGqNIvqUZ0H374IT72sY/ht7/9Lbq6utDR0YENGzbgqquuwv797EhuFtXV2wEAkZLpwODtL2wORAqnAAB27Ehdx38aX6dO6SOPVfnxSXuhQ0ORQ4WmaaivP5WO0GgMjh49oj8oBrRiLf4YSUkMxABAZ2cnG11JrrGxftDzhjRFQqlQW6tvheuy61ukHj58iM3LJCe2Nx78mORz/Pgx9PR0w2KxoKJCb6L9wQe70xxV+iWVtK9ZswZXXHEFXnvtNTz66KP4xS9+gVdffRUrV67Ef//3f6c6RkpCJBLBrl3vAwDCJTMSn1OiV/HEeWRuPp/PGD2eMihpB/R17sBAYk9y0DQNhw8f1B+XakCpfpw3HfLSNM1YyiIcP85+EzIT/UJy7fpswuPHj6YzHBqj3bv1+55ZhfmwKnpfETGTjeTT1dWFY8cG3pMffLCb2zJKbPv2bQCAsrIyY6ew9957J+sH1pJK2vft24cbb7wRNtvA7HqbzYYbb7wR+/btS1lwlLyjRw+jp6cbmtWhd44H9E0sY/7BR4r1KfEHD9YMWa9H5tPUpFd2Cu0qXI6hH1wiaW9oqB/yGplXY2MDOjs7oVk0oATQ3Pq1PXToILdklFRjYwO6u7tgA7AgeuzgwQPpDInGoL+/H4cP1wIAzp5yMQDgww8/SGdINAanTp1EU1MjFADluQ6UOvWGn9u3v5PewChpb7/9JiKRCKa4KpBny4HX6+F7VFKapuHtt98EoG/tXVZWBovFgsbGhqwfLE0qaXe5XGhqGtrJr6mpCfn5+WMOisZu3769AIBI4WTAYgE0DTkHXkTOgZeMxF1zFkDNKYKmqaip4Q2l2YlOmpPyEo8ei+OxHTfJ/Pbv/1B/UArACqAA0JwagsEAjhypTWdolCRxTasAzIkeE5/JJB9RtXM5izGj7BxYFAtaW1u4FElSb775KgA9YbdZLJiUr/eAeeut17O+kiejSCSCP//5RQDAR6ddgAsnnwsAxjGSy6FDNWhpaYbVakV5eTlsNhvcbr3p5+uvv5rm6NIrqaT9U5/6FO68805s2bIFTU1NaG5uxssvv4y77roLn/70p1MdIyWhpkbvLRApnKwfUMOw9rbC2tsCqAP7V4rXxflkXqLDeEXu0KnxAFCeqyftg7vikrmJBE+riN4sKoBWrsW9RnLZs2cXAGA2gFnRYzU1++H3+9MWEyXvvff0CuzUkrmwWx2oKNSXnLEyKx9VVfH2228BACZHk/WKXCesioKWlmbU1h5MZ3iUhB073kVTUyPybDm4ZMoSXDHjYihQUF39HpcLSuitt14HoFfZrVa958SkSZMAAO+88xYikcT3wNkgqaT9Bz/4AT72sY/hBz/4Aa644gqsXLkSt99+Oz7+8Y/jtttuS3WMlASxnlLNLx/2PPH64PWXZD5iH9mSnMSV9rLoce43KxdxkyimxQMA3PGvkTw0TTMGW2ZDv5RFAMLhMK+nhPT+MNUAgKnFcwEAVSXzAAA7d1anLS5KTm3tQXg8bbAqCspznQAAm0VBRa4+RX7btq3pDI+S8PLLLwAAVk6/CDk2Jyblu3Fehb4w6c9/fimdodEoqapqDIZWVlYax0tLS2Gz2dDZ2ZnVRcakknaHw4G77roL1dXV+OMf/4jnn38eO3bswB133AGHw5HqGGmU+vr6jMRNzS0Z9lzxeux+iGROYq/n4gTr2QGgyKEn7V1dXVk9EimTvr7egf2BSweOa6X6NWbzMvk0NNSjt7cHdgBTAChQIDbu47p2+Rw5Uou+vj44rDkodekz0yYVnQVAbxbZ08N+MDIRAy0VuQ5YY3bVmZSXE/c6yaGu7hRqavbDoljw0WkXGMdXzrgIgF619fn60xUejVJ9fR26ujphsVhQUjKQv1gsFpSVlQHI7hmISSXtQm5uLubPn48FCxYgNzc3VTHRGHV0tAMANKsDsA0/iKI59R4EnZ0d7LRpcn19fQCAfHvipF0c1zQNfr9vwuKi5IneIFqOBthjXtAbVKO93csp1ZIRjSArAFihJwVToq9xmzD5iOm1pa7JsCj6LVOeowB5jkJomoaGhrrhfpxMRuwCUOy0xx0Xz5ubG5nkSUQ0mzu7bBaKcwqN4/NKZqI0pwh+vw9HjhxOV3g0SqKPT2FhISyW+BS1qKgIAIymoNnIduZThgoEAti0aRPee+89eL3eIY07nn/++ZQER8np6ekGAGi2nDOeK85RVRV9fX0oKCgY19goeT6fnojnWhMn7XYLYFM0hDUFPp8P+fmuiQyPktDd3aU/GPxWdQCaRYOiKuju7kZOzpnfy2QOYkZM7CepeCwGVEkeYpvNfEdR3PF8ZxH6g91oa2vFggUL0xEaJaG5WR8ozbfH3/46rBbYLQpCqoaWlmbMnDkr0Y+TyYhmkNMKJsUdVxQF0womod3fhbq6Uzj33CXpCI9GSdwTJbrnEceM+6YslFTSfscdd2Dbtm34+Mc/jsWLF0OJmWJE6WdUzEdyXZSBkSxNY6XdzMJhvYGgzXL67rY2CxCODJxL5hYMBvQH1gQvWgGoMeeQVPitmBnE1rYa4r8fxfelzWYf8jNkXk6nvo49UZd4NXrI4XBOZEg0BmJbVJtlaDpjs+rHwmFunSoLce+aKK8Ux7J5K9ykkvY33ngDv/71r7Fs2bJUx0MpILotYiRJeMw5xs+RKYmbxOHGYsRLXOogB3EDicFjLNrAMVbZ5eJy6XX1vphj/YNeI3kUF+vrKvsD3XHH+4P6WnYxZZPkIN6Dvkj8d2RIVRGJJvKccSiPyZP1xUctfZ4hr7X0eqLnTJ3QmCh5JSV6c59AYGixQhwTa9uzUVJr2isrK7kfu4kVFOjrepTQmdfCKiF9yrXVarjnH7oAACAASURBVEVubt64xkVjIwZVIsNsIyte4wCMHAoLozf8g9+qIUDR9CEY3kDKRdxEtgHQoL8hWwe9RvKYM0fvGO/pbYQaHTjtC3ShP9gNq9WKs87iNGqZzJ9/NgCg3R+MO97u16t3U6ZUGfdQZH5z584HAOz3HEEoMlCBbetvR31vCxRFwezZc9IVHo3S1KlVAICenp4hs2FE089sHoRJKmn/r//6L/zkJz9BQwOb6phRaak+UqWoISAcHPZcJajXg0pKSoc0fSBzsdv1poKhSOJSu6YBIVWcyymbMpg0SU/ilIACxM74ijakLi0tg9PJSrtMpk2bDpvNBh+AzuixxuifZ501O01RUbJmzDgLLlcBwmoQ3l79nqepS98idc6ceRzslszixUsBAF5/EGpMUtDmC0RfPy8tcVFyFi5chLIyN/rDfnzQdsg4vr1Rb1C3ePF5KC3N3sqsbGbPnguHw4lQKGQ0XxY6OvR+MYsWnZuO0EwhqSzt3HPPRSAQwFVXXYWlS5fioosuivuP0is3N8+YYmLxdw57rsWnv84KkPmJadL+0yTtQRXQohPkuZuDHPLz8wduKGJ6qyid+nWcNm16gp8iM7Pb7UYTqzoAIWhojr4mqkIkD6vVigsu0O9r6jv0LtQNHXr34osu+kja4qLkLFhwNoqLixFSNXii1faIpqGlX0/aly9fkc7waJSsVisuv/xKAMDb9bsAABE1gm0NuwEAK1delbbYaPTsdruRlHs8A0se+vv70d/fD6vVikWLFqcrvLRLak37rbfeitbWVnzve9+D2+1mIzoTmj59Bjo62mHpb4fqqjjteRafPnI1bdqMiQqNkiS6wfeHE7/fxHGLxcLqrERmzZqN9nYvlHYFmjta+ekQr3Fan4zmzVuAI0dqUQ+gGIAKfW10eXl5miOjZFx88SV4441X0dR5FIumrkBbj77N20UXXZLmyGi0rFYrli//KLZseQHNfX5U5Drh9QUR1jSUlpbh7LPPSXeINEpXXfUJPPfc06jxHoPH14HmXg86/N0oKCjERz5yabrDo1G66KJLsGvX+/B4PJg5cyaAgQT+nHPOzeqdkZJK2nfv3o3NmzdjwYIFqY6HUmTWrDn44IPdsPS2ARWnv06WXn215ezZcycqNEqSy6V/UPWGEift4nh+votLHSQye/ZcvP/+DiNRBwClQzFeI/mIdc4tAMpjjnGAW07nnrsEVqsVvYFOHG/bC1VTMWnSZEyZkr1rK2X2kY9cii1bXkBbdIp8a3Rq/MUXX8LvTglVVFRg4cJF2L//Q3zYWovGvjYA+qwJLhWUz7JlFwIAuru7EQwG4XA4jKT9ggsuTmdoaZfUp9OsWbPg95+5yRmlz9y58wAA1t7W05+kRmDp88adT+YlmuOcLmnvCVriziM5zJmjv/dEog4VxlR5NtCRU1XVNACAN/ofMNBgh+STm5tnDKAdbtWn4J5zTvauq5TdggVnR/sUaOgOhuGNTpO/8EIud5DV+efrid4B71HUeI4CGEj+SC6lpWWYOfMsAPo69kgkgq4u/aZo6dLs3rUsqaT9+9//Ph544AG899576OjoQG9vb9x/lH7z5unVdcXXcdpmdJZ+LxQtApergBUDCYhO493BxG9bkcwXFjJpl4n4ckIvgAiAbr1zfH5+PsrLT7+0hcyruFjvKdILo6cgSkrYDElmok9BX6Ar7jnJx2q1Yt48vb9Emy8Af0SFoijGMZKPGOBu6GmBJ7rskzPV5LVggb5Mpbu7G729vdA0DUVFxVnffyup6fE33ngjAOBf/uVf4o5rmgZFUVBTUzPmwGhsSkpKUVFRidbWFlj6WqG6KoecY+nRq/Dz5y/gtE0JiGT8tJV2I2nnvsEyKSkpRV5ePvr7++KyvKqqaXxfSqqgQF/KEoF+SYGB5S0kp8rKScM+J7mcddZs7Nr1PpqjDegmT57CnQAkJt6PXr8+qOZ0OlFUVJzOkGgMZs3Sd1rp6+szushziVmSSfvGjRtTHQeNg3nzFqC1tQXW3raESbu1r9U4j8zP5dL36z7z9Hju6y0TRVEwadIkHDt2FOgDlD79+ort4Eg+NtvAOkoxz4lrK+VWXByfADAhkJvbrXeb6A9HAABlZe50hkNjNHjHnJyc3KxP8GQ2adJkAIDP54PP54s7ls2SStq5rZsc5s6dj7ffflNvRpeApddjnEfmJyp1faHE0+P7wgON6EguZWVuHDt2FIpPAXwDx0hOsTeLaoJjJJ/BO3KILThJToOXkXGGmtwGNxBkQ0G5iUHRUCiEUCgEQN+BJdsllbQLPp8PjY2Nxv9DBXaVNwfRwdjS3z70xUgQlkB33HlkbiPd8i0/P3/CYqLUMKp2geh/YCVPZpFIxHgsvmRVVU18Mklh8EwJm21Mt0+UZrGzYQDOhJFdMBjfu2lwXkJyycvTl6pEIhGEw2EAQ2dTZKOkvnXa29vxwx/+EG+99VbC17mm3RxmzJgJALAEe4FI/AeaxdcJQB+54gizHJxOJwAgoAKaNvT1QERP2lkBko8xOyIEKNHlD+JLi+QTm7SLVEDceJCcBk+UYCVPbpz5klkCgcCg59zhSmbi81WLudm1WKzpCsc0kvrWWb16Nbq6urB582bk5OTg8ccfxwMPPIAZM2bgV7/6VapjpCS5XAXGFDBLIL6rv+LXq+zsGi8Ph0NP2lVNSZi0h6OFPLvdMYFRUSqIARmEo/+Bgy8yi63yOBIcI/kM/szlzAm5hUKszGYSsQ21RdHTmlAoFDd4SnLREtzkJjqWbZKqtL/33nv45S9/icWLF0NRFEyZMgWXXnopXC4X1q1bh8svvzzFYVKyKiomobu7G0qgL+64SOIrKoY2qCNziq3sRBJ8doljVitHI2VjTM1UYSyC5vRbeYXDegJgxUClnUmB3FQ1Mug5k3aZDZ5OHQwGTnMmyUBU1gsd+egM6Fuw+P1+LheUlJiZZrFYjFkxkQhnqyVVae/v70dpqb4PbXFxMdrb9TXT8+bNw4EDB1IXHY1ZSYneuEEJ9ccdV0K+6OulEx4TJUfTBm4SLQlm9olDvJmUT6KpmorC6beyEgm6FQMj4yKRJzkNXt7AKp7c+vv7Bj3vP82ZJAMxCJNrcxrH+JkrL/EdqiiKUbAaPNCWjZK6KzzrrLNw/PhxAHrTuc2bN6OlpQVPPfUUysvLUxogjY1Yr66E49f3iOeDO6iSecXeJCZK2q2WoeeRHIyBFiXBMZKOuLmwYSBpZ6VdboOvH6+n3ESS7ox+cQ5O4kkuYlDNarHCGh3wZh8ReYmZL1ar1Zg9OrhvQTZKKmn/2te+hrY2fRuxb3/729i6dSsuv/xybNq0CbfeemtKA4y1bt06zJ8/H6tXrzaOBYNB3H///bj44otx3nnn4eabb0Zzc/O4xSCbnJxot0V10IdX9LnxOpmeWLPltGhDmiIBQI5Vnx/PBizyMRIAC/TyLHjDITNR4YlN2lklkNvgG0ZOp5ZbT48+hTrPpn/g9vb2Dnc6SUKJ/h/ANdAyE9+XFouFlfYYSS2a/OxnP2s8XrhwIV577TUcO3YMkydPNqbNp9revXuxefNmzJ8fv6f46tWr8frrr+ORRx5BcXExHnjgAXzzm9/Ec889x7W9AOx2/RIrg6t20fV5DgeblslCVAJybIm/iHKjx/v6WDGQjTHQYoWRtHPwRV6JKu2cqim3we9HMYhKcurtHUjaOwIhI4knOYklZho0qNDijpF8xCBpbKWdSXuSlfbBcnNzcc455wxJ2M8//3zU1dWN+ff39fXhtttuw6pVq1BUNLA9WU9PD5599lncfvvtWL58ORYuXIgHH3wQtbW1eOedd8b892aG031oaWd4ncymq6sLAFDoSDxtutCuX9Pu7q4Ji4lSw1hPaQe06HXkdE15xa5pF0PHvOGQm8/nG/Sca6Bl1tOj76CTZ9ffoX6/j0seJCYSu4iqQo32/2HhTl6JKu2Dd3zIRuPa6ShVU1Puu+8+XHbZZVi+fHnc8X379iEUCuHSSy81jlVWVmLu3LnYvXt3Sv5u2Q1cg8HJuf58cEdcMq+ODr3hY5Ej8fuqyKl/UbW3eycsJkoNo8rjgLFHGCs/8hI3//GVdi53kFlfX++g5xxUk5kY3M6zWY27Iw54y0vswBKIDCR23IFFXuL7MrYRHQfVkpweP5FefvllHDhwAM8888yQ1zweD+x2e1z1HQDcbjc8Hs9EhWhq4h+5NrhzmcUa9zqZn8ej95Eoy0lcaRfHxXkkD+Nm0Rn9D0BXV2fa4qGxiV3Tbh10jOQ0eBBNVGpJTt3d+vVzWCywWxQEVQ09Pd0oK3OnOTJKhljq2R/yxRxznu50Mjlu+ZaYqZP2pqYmrF69Gk888QSczpG/+dh8YoDfH/0Aswy61NHn7MYoj5YWvcGi+zRJe3n0eGtrCzRN43ouiYhZFFqOBiWoX7fOzo50hkRjIHZwiOkriFCINxwyE4NoTlsuAmGfsVyJ5CQGXRxWCxxWC4JqhNdUYjabXmn3x1TaRfWd5CMSdEVRjHtZzlYb5+nxY7V//354vV587nOfw8KFC7Fw4ULs2LEDmzZtwsKFC+F2uxEKhYZ80Hq9XrjdHC0FBtbdadb4hnPiOdfNyqOxsQEAMDkv8ZKG8lwVCjT4/X5OkZeIpmkD1ysX0HL1QUdeQ3kZ2w9hIGnnVoxyE4NoxXkVAAYG2kg+kUjE6BavV9r1W2HRnI7kMzhBt1qtLFxILFGlPRzmd+i4VtrH+ob5yEc+ghdffDHu2A9/+EPMmjULN910EyZPngy73Y5t27bhU5/6FACgtbUVhw8fxm233TamvztTiC8mzRY/U0Gz6Un74HV6ZE6apqG+/hQAYHJ+4kq7zQJU5qlo7reivr6O0/wk0dPTPdCkLBdAdDCZS3zklagRHZciyU0MopXkTUJL90kOqkksNjm3WRQ4okm7mDJP8hHrnk/3nOSSaE07p8ePc9I+1mnqLpcL8+bNizuWl5eH4uJi4/i1116LtWvXoqSkBEVFRVi7di3mzZs3pGldtjK+hGyDKu22nPjXydTa273o6+uDRdEwOS+CxGk7UJUfQXO/FXV1J7FkydIJjZGSI5JzzanpGV6efryrqxPBYJDbMkpILDtyABD1H+7rLa9AwG98V7oLpgLN7B0iMzE13qYosCgK7FYl7jjJZ3C+wWWychOD3PHd4znwPaahqGAwiGPHjp12ncH69etRWVk5lr/ijO644w5cddVV+O53v4vrrrsOubm5eOyxx7jVQ5RYh6fZc+OOa/acuNfJ3E6cOA4AmJynwjHMP+1prkjc+WR+Hk+r/iCarMMOaFYt+hoTAxmJZUkOGH0FB7b1I+m0turvUbvVYUyP93jauORBUmIGokjWxfR47tghr8EJXTgcZuIusUDADyB+n3ajR1cWS6rS7vP5cP/99+OPf/wjAOCvf/0rpk2bhlWrVqGiogLf+MY3AAAXXHBB6iKN2rRpU9xzp9OJu+++G3fffXfK/y7ZRSIRoyu1ZhuctOsZQkcHm13J4PjxowCA6a7hbxJnFETizifzMxJzkbQr0cc9gNfrwZQpU9MUGSVL9FnJw8Bl5XZS8hJNQPOdxci1u2BRrFDVCDyeNlRWTkpzdDRaIjkXybo9ursOlwvKSyR0+fZc9EU7yAcCAeTk5KQzLEqS2FLTZrMZW/dxm80kK+0PPfQQDh48iI0bN8Z1db/kkkuwZcuWlAVHY9PV1QlVVaFBMSrrwkDSznV5Mjh27AgA4KzC4df0zIy+Xld3amCdNJma16u/B0UDOgD62vaY10guomlZAQBX9FhXVycrs5Jqbm4CALicxVAUBS5ncdxxkouYBj+QtFvijpN8xKBoaU4RbIo17hjJR1w7u91uNBnkct4kk/ZXX30V99xzz5BK+pw5c3Dq1KmUBEZj5/VG18racwEl/lJrjnwA+siVz8cpJ2Z39KietM8sGP6mv8ypodCuIhKJ4MSJYxMRGo2RsbVbzGQYkcBzUE1Ora0tAIBiAIXQv2jD4TA7jkuqubkRAIxk3ZWj/9nU1Ji2mCh5A53j46fHi+MkHzFrtNDpQqFTHyrltqnyEo0+HQ6H0dfH7/dl/TKzpJL29vZ2lJWVDTnu8/m4xYKJtLXp6/A0p2voizaHse0b182aW2dnBzyeNijQzlhpVxTgrEI9sT9y5PBEhEdjZPSViJ0M4xSvsVIgI5HklQKwQEFJ9DiTPDkZ0+OjyXp+NHkXgzMkl6GVdjaik5243y3LKUJpThEAvj9lJq5nTk5O3BT5bL+mSSXt5557Lt54440hx59++mmcd955Y42JUkQ0z9GcBQlfV6PJfLa/CcxOJN+T81XkjqALxaxoYn/0KJN2GYgpX5ojZnq8U7zGpF02PT3dxjUVQ9viz4aG+rTERGMjviNdDj0ZyI/+KZJ5kovRiC6arDtYaZdea6v+XizLLYE7j8tXZBaJRIzP1tzc3Lg/s33gO6lGdLfeeituvPFGHDlyBJFIBBs3bsSRI0ewZ8+eIY3iKH1aWvQPLPU0SbvmLAD6243zyJyOHKkFMJCMn8kso9JeO24xUeoYewbH7uzmEK/xJlI2jY0NAIAiAA7oSYEbQG3MayQPTdOM2Wh5zmjS7iwEwFlqsjIq7dZopT3aRb63tweqqnKPbwk1NOifrZX5ZVA1fVPcbE/wZNXU1IhwOAyLxWI0EszPz0dPTw/q608BuDS9AaZRUp9M559/Pp566in4/X5Mnz4d27ZtQ1lZGZ566iksWrQo1TFSksQHlpZTmPB1NXqcH2zmJirms86wnl0QyX1DQ72x9RSZl3GN7DEHo4+5xYl8xOdp7AIy8VhMmyd59Pf3we/Xtx/Kteuz03Id+kC4WHdJchEDpYMb0Wmaxg7VEtI0DY2N+iymyvwyVObrn7gNDXXpDIuSdPLkCQCAy+Uylly7XK7oa9m9nfGoK+3hcBgvvvgiVqxYgbVr145HTJQiYiqmGl3fM5gWXZ/HKZvmpWnaiDvHC0VODaVOFe0BC44dO4ZzzuFAmpmJhCD201izadHXmLTLRkylLok5Vmq81jrh8dDYiOaBdqsTNqs+miaS987ODkQiEWMfYZLDwJp2PSGwKAqsioKIpqGnpxsFBYlnJ5I5tbd74fP5YFEUVOSVGscbGuqhaRp7bUlGNFF2uVzQNM14DADHj2d30j7qSrvNZsOPfvQjbidlcn19fUYVQM0tTniOOF5Xx47/ZtXR0Y7Ozk4o0DB9hJV2AJhZoCf43K/d3DRNG/gsjb3vjz4OBkMTHhONjdi1I3aotNB4jdOpZdPZqTeKzLHnG8ec0S1TVVUdWN5C0hA9JxzWgVtgB5vRSUsUnspzS2Gz2FCeVwoFCvr7+9lBXkLivtXlcmHXrl3YtWsX8vP1z9/m5sasng2T1PT4xYsXo6amJtWxUArV1Z0EAKiOfMDmTHiOmqvXgtrbvbzxMKnjx/URx8n5KpzRRC4QAdbtH7iBXLc/H4FB+fyMaILPbd/MLRyOmT0R+2kcfRwKcXBUNmLrodhanXjc39/PAW/JiN0dcqKJOgBYFAscNr0xkkjqSQ5atJoODDSgAwbWt7P5p3xErxAxLd5usaEsWpRqbOSSJJlommZscZyXl4euri50dXXBZrPB6dRzmRMnsrfanlTS/uUvfxkPPPAAfv/732P37t04ePBg3H+UfiLZU2OmCg1hc0B16FNOsvlNYGanTp0AAEx3DWTl6w/ko7p1oGtZdasD6w/kx/2cqMqLnydzOlPSHvc6SUEkBHkxx3IwMJGCSYFcRFLutMV/xubY9CtsbNlIUvD5fAiF9BlMsUm7M/qY22zKR/QRKY+53xXT5Jua2PxTJu3tXnR3d0FRFGNKvCCWrRw7lr07IyXVPf573/seAGDVqlXGMUVRjLUjrMKnn1gHreaVDXueml8GS7AXx44dwaJFiyciNBoFsXRhWjRpD0aAnW32IeftbLMjGAEc0cxAnF9XV8duuCYWl5THTo9n0i6tREm7AgW50NALvQmW212eltho9MT02thKu/48H91+L5N2yYjraVUUWC0Da53FVHleT/mIPiKxSXt5XingPcptGSUjCo55eXlDeoUUFBTA4/EY52SjpJL2V199NdVxUIqJvb3VfPew56n55UDHSeN8MhexVmtKvp6EdwUtCKlDm6qEVAVdQQvKc/WtTspzVNgUDcFgAB6PBxUVFRMXNI1YOKxXfDRE92jXACjg9HiJiW36cgcdzwXQC6Cnh0uRZDKQtA+qtEefi+UQJAdxPZ1Wi9HkSlEUI2kXjQdJHm1teoPPspimy2J6vMfD5p8yiW1CN9hAM7rs7dWUVNI+derUVMdBKeTz9Q+saXcNn6xFXHrF5/DhQ+MeF42Ovo2JPrVrUt7Im9ABgNUCVOapaOizorGxnkm7SQUCAf2BBbC8rt80qitVo+oupnGSHCKRCPr69KQ9b9Br4jkbXclFJOWnT9q57ZtMRFLusCjY0dIJKMBFFcVwRpP29nYm7bIRzT9LYpL2kuiWxh6PJy0xUXJEFT3RDg7iWENDPUKhEOz2obNOM11SSbtw5MgRNDY2DrmxvPLKK8cUFI1Nbe0haJoG1eGC5hh86xhPzS+HBgWtrS1ob/eitHT46fQ0cXp6utHfr3fJrIxW0EejIjeChj5rdG/o81McHaWCkbTbAMUbnUERgfHJHAwGuaWURPr6eqGq+nt1cKVdfBJzTbtcRFIu9mYXcqP9YJjkycXr1a+nw2pBq0+fyRTRgBxW2qUUCoWMz9SSnIH3aLFTf8zrKRfRXytRpd3pdMJmsyEcDqOu7hRmzZo90eGlXVJJe11dHb71rW+htrbWWMsOwNgLkWva0+vAgX0AALVg0plPtjmg5pXC2u9FTc1+XHrpR8c5OhopY79np2qsVR+Nimiiz72hzcvn69cf2ADEzoSP+WT2+33Izx/6BUbmI6be5gGwQTGWPShQ4DLO4ZpZmYitU3MHVdrFXu1MCuQirqfTGt/nxRkdGBWvkxxEwm5RFOTZB4ZKCx36+5U9CuTh8/VHi0yJk3bRnK6zsxMnThzLyqQ9qe5Uq1evRlVVFd555x3k5OTg5Zdfxu9//3ssWrQImzZtSnWMNEoiaY8URpP2SBjOo28arzuPvglEBhpcqdHz9u//cOKCpDNqa9P3dHbnjL7KHvtzIvkn8zHWNzsGvWAFNKsWfw6ZnphK7YLep+BxAI9HH7uMc5jkyUKv4unLGUSSLuREn4vKLclBJOU5g2YvOWMq7WK2DJmfSMpd9nxYlIGUpsCpvz+5zaY8RJXd6XTC4Rh8U6QTU+SztRldUkn77t278Z3vfAelpaWwWCxQFAUXXHABbr311riO8jTxAoEAamv1bfcihZMBAM5jb8HWccI4x9ZxAs5jbxnPIwX6efv27Z24QOmMRAOVsiSTdvFzYr0XmY9RBUj0/eQcdA6ZnnivFQIIATgV/S8UPaafwyRPFmKAxaJY4bDlQtM0Y2ahmB7f0eE1jpH5nb7Srj+PRCJcwiIRsUWfqKwLebYcI4nn9ZSDSMQTVdmFbG9Gl1TSrqoq8vP1N0hJSYkx/Xbq1Kk4fpz7fafTwYMHEA6HodrzoDkLATUMa8fJIedZO04Cql5tjxROhga9uQMTPPMQN/elzrEl7R5PW8piotQSSYGWm+CmPzrTj2tm5RGbtA9WNOgcMr+BqfH6jeJrB/+A1w8+CU3TjGOBQMBoPkjmJz5zByftFkUx9m3nZ648xKB2gTM+aVcUxUjkuSRJDiIRT9SEThCvnThxLCtnxCSVtM+dOxeHDundxpcsWYLHH38cO3fuxC9+8QtMmzYtpQHS6HzwwW4AQKRoKqAoUEI+KNrQzuOKFoES8ulPbE5967eYn6f0E8l2aZKVdvFznZ0diERG132eJoYxoDK4axkGEnmvl4MushDXsyjBa0WDziHzEwOnuQ4XImoI3t5GeHobEFFDsFntcFhzAHAdtCw0TRuotFuG3v6KZnQcWJOH6CNS6HDFzYQBgAIjaee2jDI4duwIgOGT9ry8PFgsFvh8PjQ3N01UaKYx4qT94MGDxqjGv/3bvxlvjO9+97tobGzEV77yFbz55pu48847xydSGpHdu3cCiCbtoyDO37NnV8pjouSIG4dkK+1FDg1WRYOqqlxHa1ItLc36g0SbPOQPOodMT+wXXJzgNXGsv7+PlVlJiCVKgzvHC+K46D9C5tbT022sb3bahnZ3ddqYtMtGXKsipwsP7ngCD+54wshPiqPbvnFQzfwCgQDq6k4BGD5pt1gsxhR5keRnkxEn7ddcc43RZOdHP/oRLrjgAgDAtGnTsGXLFmzfvh3vvvsuLrnkkvGJlM7I42nDqVMnoAGIFFWN6mcjxfr5H3ywi1VZkxAN5MqT2O4NACzKQLVdJBNkLk1NeqdUzZVgerwr/hwyP2PHhwSvOaCIcRg2h5SEuE4uZ6JhGCDfWRR3HpmbmOXisCiwRHc7iiWa0/H7Uh5iH/ZCpwtHO+twtLMOwYi+DXVpdN92Xk/zO3nyOCKRCOx2O5xO57DniqT+yJHDExGaqYw4aS8sLER9fT0AoKGhYUjjleLiYmPLN0qPnTurAQCqqwKw54zqZ1VXBTSrE729vTh0iFv2pVsg4DemdCXbPR4AyqM/y2qt+fj9/oGp0gn6rmgF+mdsfX3dBEZFyQqHw0byVnqac8TxbJzWJ6PGxgYAQP5pknaRzDc21k9YTJQ88b7LS1Bljz3e0sL3pyzENXXnDB0qdefq70/e/5hfba2+5LqwsPCMuWRhoT6D4vDhQ+Mel9mMeJ/2q6++Gv/8z/+M8vJyKIqCa6+9FpYEa4IA4NVXX01ZgDRy1dXbAQCRkhmj/2HFgkjxNNi8R1BdvR0LFy5KcXQ0GqK66rKrKHAk35l4Up6KAx0DN59kHnV1eoNIzakZa5T0YQAAIABJREFUneLjRLuZtbW1wufrR25uojn0ZBYtLc16pQBAAYBwgnPKANRBb/pJ5nfq1AkAQFGuO+Hr4vipU0ObvZL5iAHQPHviW998uzV6Ht+fMtA0zRhgKcsbOrBWkacPk3KQ1PzErlciIR9OUZE+g+Lo0cMIhUKw2+3jGpuZjDhpv//++/Gxj30Mp06dwqpVq/D5z3/e6CBP6dfX14u9ez8AAIRLpif1O8KlM2DzHsH27e/g+uv/lTMn0kjcBE7OG1t3zCn5kbjfR+Zh7DOauIgHOPVmdIpPwYkTx3H22edMWGw0eqLzbSUACxQAQwfbJkX/PHYsO7erkYnH04bOzk4oUFCUW5bwnOK8CgD69VRV9bSFDDIH8ZlbcJqkXRxvqK9DIOCH0zm6GYs0sbxeDwKBACyKxaiqx6rM1wfVGhvroWka72lNStM01NTsB6DP2j6T3Nxc2O12hEIhHD16GAsWLBzvEE1jxEk7AHz0ox8FAOzfvx/XX3/9sHvp0cTasWM7IpEw1NwSaLmJVlSeWaRoGjSLDa2tLTh69DDmzJmX4ihppMTNxYyCRPW6kZvu0pP2EyeOjTkmSi0xtUsrGWYmRQkAn34uk3ZzO3y4FgAwZZhzJkf/PHKkljeRJieWiRXnVcBmdSAcCQ45pyivHFaLHf39faivP4Xp02dOcJQ0UqqqGte0yJH41tdptcBhsSCoqjh8uBaLFi2eyBBplMRstYq8UliVoUseyvNKYFH0TuNerwdud/lEh0gj0NBQj/Z2LywWy4gq7YqioLi4GG1tbdi7d09WJe1JDQuvWbOGCbvJvPXW6wCAcOlZyf8Sqw2RaJX+rbfeSEFUlCwxVeiswrE1BZxZGIYCDW1treygajIHDuwDAGju0yft4rX9+z+ckJgoefv26TOdhlucVAXACr1CxAaD5rZ37x4AgLvg9E1dLYoFbteUuPPJnE6ePI6urk5YFQVFzsTTaRVFQVmO/hq3vzW/EyeOAwCqCioTvm6z2DA5Wm03ZraR6eze/T4Afdq71Zq438RgpaWl0Z/dOW5xmZHp53KtW7cO1157LZYuXYpLLrkE//7v/45jx+LffMFgEPfffz8uvvhinHfeebj55pvR3Jw9jSe8Xg8+/DA6Nd49d0y/S/z81q1vIBQKjTk2Gj2/348jR/Sq3fzisVXa82wD1XYmfubR2NiA5uYmaIoGJF4uCwDQKvSkfd++D42tish8vF6PcQM5a5jzHFAwLfp41673xz0uSo6macbN4KTCmcOeO6lIHyjftSu7bh5l8+672wAApTn2hJ3jBXeu3mBk+/ZtQxouk7mI2U3TCiaf9pxphZOj52Zf0zJZiPem2z3MzdAg4tza2oNZtUWj6ZP2HTt24Ctf+QqefvppbNiwAZFIBP/6r/+K/v5+45zVq1fj73//Ox555BH84Q9/QH9/P775zW9mzdZlf//7X6BpGiIFk6DlnH5/w5GIFE2Fas9Dd3cXduzYnqIIaTQ+/PADhMNhuHMiqExyu7dYi8r0xD/bRiTNbPt2/UsKFQCG66FSrK9r9/t9+OCDXRMRGiXhnXe2AtCr7C4MP+VdLHLYtu2t8Q2Kknb06GF4vR7YLHaUF04b9twpxbMBAPv27UVfX+9EhEejFIlE8PrrrwAApuQPv069ItcBq6KgsbEBBw8emIjwKAmqqhqz1eaWnn5+09zo7FEWLcypqanRWLZSUVEx4p9zOp1GQzox0zgbmD5p/81vfoPPfe5zmDt3LhYsWIA1a9agsbER+/frTQt6enrw7LPP4vbbb8fy5cuxcOFCPPjgg6itrcU777yT5ujHXygUwiuv/FV/XHn22H+hYkG4Yj4A4C9/eWnsv49GbceOdwEA57lDSMWS16VufcbEzp07OHvCBFRVNd6z2rQzVHKUgXP+/ve/jndolARVVfH3v/8FAHDuCM4/B/oXb23tQaM6T+by9tv6gMqkolmwWYbvTFyQU4rCXDcikbBRMSJz2br1DbS3e2G3KKjIHX4PaJvFgkl5+jnPP//MRIRHSaipOYCenm7k2JyYWXj6TiILSvW5T7WHDqKjo32iwqMR+utftwAAysrKzrg/+2CTJ082fke2FGlNn7QP1tPTA2Cg5f++ffsQCoVw6aWXGudUVlZi7ty52L0789ckbd36Bjo62qHa8xApmZmS3xmuWABNseDAgX3G2mqaGMFg0KjCfqQyNQn2vOIwih0qent7sWcPq+3p9t5776ClpRmaXTtz0g5Am6Wfs2tXNU6ePDHO0dFo7d69Ew0N9XACWDKC8wugQLTNefHF58cxMkpGOBw2Kjcz3SNrcDSjTD/vtdf+Pm5xUXJCoRA2b/5fAMDMwrxhp8YLZxXmQYE+0M1quzm98YY+c2JZ5UJYLadfB+3OK8FZRVVQNRVbt74xQdHRSHR2duBvf/szAGDq1Kmj/vnKykrY7Xa0tbXizTdfS3V4piRV0q5pGtasWYNly5Zh3jy9s7nH44HdbjeSeMHtdsPjyex1DpFIxBgJDk9aBAzzwTUamiMf4TJ9yt9zzz2dkt9JI/Puu2+jv78fZTkRzBvjenbBogCXTNLXQ7/66t9S8jspOaFQCP/7v78DAGhztZHt31EAaFUaNE3Dpk0buM7SRCKRCH7/+w0AgAsA5JxharywPPrnm2++xmq7yWzd+ga6ujqRY8/HpKLhOhQMmFl2DhTFgkOHarh21mSefvoPaG1tgcNiwXRX3oh+Jt9uM6bRP/bYo5yhZjJNTY1GkrZ86tIznn9p9Jw//elZ+Hy+cY2NRm7z5v9FIOBHYWEhysoSb6s5HKvVihkzZhi/KxuurVRJ+3333Yfa2lo8/PDDZzw3G25s33zzNX3/SZsToYoFKf3doSlLoEFBdfV7rLZPoL/85WUAwBVTg7CkcDeolVMDAICd71ejtbUldb+YRuXJJzehqakRmlODNm/kn1HqIhWw6F1WxdpMSr8///lFnDp1ErkAPjqKn5sGBedA/556/PFfZc3UPrMLh8PGQPW8ygtgUUZ2i5TrcGFGqb487f/+76lxi49G59ChGjz//P8BABaWumAbxZfqvGIXHBYFdXUn8Yc/bByvEGmUNE3Db3+7HpFIBIvcczAnumZ9OJdMXYKKvFJ0dnbimWf4/jSDvXv3GFX22bNnJ7396dSpU5GTkwOPpw0bNz6RyhBNSZqk/f7778drr72G3/3ud5g0aZJx3O12IxQKoaurK+58r9c7qk6EsgkE/MaUr+CUJYDNkdLfr+UWI+yeAwCs7k2Qmpr9qK09CJui4bIpgZT+7in5KhaVhqBqKl566U8p/d00MtXV2/HCC88BANRl6vAN6AYrANSFelPC3/zmMZw4we1r0u3IkcPYuFGvsl8FIG+EVXbh4wAc0N/3Tz/9h5THR6P34ovPo7GxAU5bLmZXjGSxw4AFky+Goliwc+cOVFe/N04R0ki1trZg7dpV0DQNk/OcqMwbvgHdYA6rBeeU6ntGv/DCc3jjjVfHI0wapRdeeA7vv78DVsWKz8372Ih+xmax4drouX/84zN4//0d4xkinYHX68HPf/4QAD3pLikpGXJOJBLBgQMDS1MOHDiQcHDbarViwQK9aPm3v23Btm1bxylqczB90q5pGu677z787W9/w+9+9ztMmxbfyXXRokWw2+3Ytm2gAUxraysOHz6MpUvPPG1GVs8993/weNqgOlwIV45s3d1ohaqWQbNYceDAPqM7Mo0fURH4hylBFDtTP0jy6Rl+AMArr/xlyCAXja+DBw/g4YfXQtM0qLNVYPTLt6At0KBVaPD7/Vi16v9xxkQaNTc34cc/XoVIJIyzAVyYxO8ogYJ/jD5+9tnNWbMmz6yOHTuKzZv1wZMl01bCbh1dU6TC3DLMr7wAAPDrXz/Kpldp1N3dhdWrf4Surk4U2G1YWJrcrjoVeU6cVahPqf/lL/+He7en2TvvbMWmTb8FAHxxwScw9TT7sydyXuXZuHya/kn9s58+yBmkaeLz+bBmzX1ob29HXl4eZs+enfC8mpoatLW1Gc/b2tpQU1OT8NzS0lJMn67PuPj5zx8yutFnItMn7ffeey9eeOEFPPTQQ8jPz0dbWxva2trg9+sJSEFBAa699lqsXbsW7777Lg4cOIDbbrsN8+bNw/Lly8/w2+XU2NiAP/3pWQBAcMbFgGUkC2NHT3O6EJqsVxt++9v16OvrG5e/h4AjR2qxc2c1FGhGcp1qi0rDOKsg/P/ZO+/wKM5zb9+zXaveu0AVIYQEAtGbMdjGJS6J7ZNj++RLLyc9OY6Pux3jEjtuiWMnsWM7sYPxMbgAovcqEAIJSQgJVdS1WrXtbb4/BgQSAtS1wN7XtRf27O7su5qdmff3Ps/ze7BarXz11ZpR+QwPF1NQcIxnn30Cm82GGCkiThvigowArrkuRD+R9nY9jz/+MLW1NSM7WA9XpLm5iaee+l/a2nSEAHcDwiCj7OfIQGAO0uL0n/706nXVusadaG/X8+KLz2K324jwj+8xlhssaVHz8NUEodfreeml32O1jmzGlIcr09am44knfkddXS1quYysUH8UsqFPdZP9vYnQqnE6HbzwwjM93V08jC3btm3m1Vf/gCi6mB89nUWxMwe9j3tTbyY5cAIms4lnnn6MwsLjozBSD5fCaDTy3HNPUlVVgVKpJDMzE4XiYv3idDr79STT6XSXLCVLTEzsybx+7rmnrlnh7vaifdWqVXR3d/PQQw+xYMGCnkdOTk7Pax599FGWLVvGL3/5S775zW/i5eXFO++8g1w+MsZs7oTL5eIvf3kDu92Owz9mxBzjL4U9KgOX2g+9Xt9juORh5PnkE6nUYX6kjQjt8Huz94cgwD0J0oLAxo3r6ehoH5XP8SAhiiLbtm1m5cqnsFotiGEirjmui6+6DhAOnxd9wmEBLuVBqALXIheir0hbm47HH3/YE/0ZQwoLj/PI736FTtdKCPAdwGuIgv0cK5BM7ERR5I03XmHVqn95atzHkJaWZp588hHa2nT4aoKYk3D7kOsrFXIlC5LvQSXXUF5exsqVT3kWu8eQurpaHn/8YerqzqCRy5gZFoBGcfE80OkSOdHW1fP/J9q6cLr6X0wVBIGpwX6Eeamx2+28/PLzHkPXMcRut/PBB+/y9ttvIoouFsbM4MEpdwzpHFXIFPw06z9JDYrHYrWwcuVTrF//paf8cwzo6GjnmWceo7S0BIVCQWZmJl5eXv2+1maz4XJdPA92uVzYbLZ+3yMIAmlpafj7+2MyGXn22SeuybmR24v2U6dO9fu45557el6jVqt54oknyM3NpaCggHfeeaenf9+1xqZN6zl5shhRpsAWP58RaeR9OWQKrAkLANiyZeM1eRKMNydPFnPsWB4yQeSu+NGJsp9jWoidRD8p2r527f+N6mddz1gsFv70p1d5++03cTqduGJduBa4+nWLF/IEZPXnL8WyehlC3mXOay9wLXUhBosYjQZ+//snPEJvlHE6naxd+ynPPvs4Xd1dRADfRmrf1h82RC7MZVlzdlt/yBC4A5hz9v8/++wTnn/+ac+i2hhQWVnBY4/9loaGerQqPxYm34NKMbja5774agKZn3w3CpmK4uITPPWUtCDgYXTZv38vDz/8K1pamtEq5MwKD8RH2X8WYpG+ixbz+SyIFrOVIn1Xv68FkAkCmSF+RHlregInf/3rWx5X+VGmsbGBxx77bU9rzFviF/BA2u0DNojsD41CzU9nPMCM8DQcDgfvv/83XnjhWbq6PCWDo0VlZQW/+92vqKgoR6lUMn36dPz8/Eb8cxQKBdOmTSMwMBCLxcxzzz1JTs66a2pRRv70008/Pd6DcBdMpv5XcNyFurozvPzyC7hcTmxxc3AFxFzxPYLThrKpuN/n7BHpoLhy3Z6o9kWwm5EbdRQVFbJ06XJUqpE1vrteEUWRN9/8I62tLSyJtrEo6vK/QZNDYPOZ/ieVt8RZ8VZe/uIkCBCqcbGvSU1VVQVLltyIt7f3kMfv4WIKC4+zcuVTFBefkFLap7oQM8X+l0idIDsiQxD7iD8DiJMu8R4AOYhxIlhBaBcoKSni+PGjJCenEhAQMNJf6bqmsvI0L774bE/qehbwTS5vPPcZcOFVtxXQA+mXeI+AQAoCQcBpoKGpke3bN+Pr68fEiQlDjvx66B+Xy8W6dV/w2msvYTQa8fMKYUnq/Xir/ft9vcNp53DVRrosbQB0W9qJ9E9Edok2q95qPyL846lvL0enb2HHjm1EREQRG3tlp2sPg8NqtfDhh+/xz3++h9PpIEitJOsSEXYApyhSpO+6aAnN5HBeto+7IAiEealAEGi32qmoKOf48XymTJmKr+/IC5DrGZvNxpo1q3nj9ZfR6VrxVnrx/cxvsCRu1iWvhU6Xk41VkvfSioSFKC7TAlkuyMgKT8NHqaVUX0V9Qx07dmzF29uH+HjP9XakEEWRnTu38fLLK+nu7kar1TJt2jR8fHwu+z6Hw0FdXV2/z8XGxqJUXtrFVyaTERYWhtVqpbu7m2PH8mhpaSYjY9pl3zfeCAJotVfWYx7RfgHuLNodDgfPP/8MOl0rTr9obBPnDijKPhKiHcDpF4mirQpLdzs6nY45c+YPavwe+qew8DifffYJSpnIzzMMaK9gTzBc0Q4Q6uWitENBi0nAYrGQnT17KEP30IfOzg7ee++ds/4PBkQvEdd8F0yAS+o7M8jKLlbmgiggxouSvfilkAFRgC/QAvpWPdu2bcZut5OcPKnfWjEPA6e7u4t///tD/vKXN2hv16MB7gBuAOSXEex2RD4H+ib36YH5V3hvBAKTgDpAb7eTl5dLUVEhEyfGExgYNMxv5AEkT5jXXvsDW7bk4HK5iApIYkHy3WiUl168zK3Koa79fP/1LksbBmsHsUGTLvkeL5UPMYEp6AwNdJn0HDiwl5aWZiZNSkWj6T8t1MPgKCoqZOXKpzh27CgA8X5a0oP9UF6mht3qdFHdfXE/ZxGI8fG67HsFQSBIo8JfpaDVYkPX1sa2bZtQKBQkJ09CNozaeQ+SyMvLy+XFF58lN/cgTpeT1KB4fjHzQSb6XzpIZXPa+ODE5zQapYyWZqOOjLAU5JcR7oIgEB8QQ0boJE531NJm0JOXd5hjx44yYcJEgoOv3e5TY4HRaOStt15nzZrVOJ1OgoKCyMzMRKO5cibTcEQ7SMI9JCQEhUKBXq+nurqKQ4f2k5o62W3vox7RPgTcWbR/8slH7N+/B1GuxpJ6y4BbvI2UaEcmx+UdiqK1jNraaqKiopkwYeIAR++hP6Qo+yu0tem4KcbKnIgrp9qNhGgXBIjQOtndoKampppFi2644sqnh0tjt9tZt+5zXnnlBcrLpYm9K8mFOE+UBPVl3wyy8v4nemLyFUT7OfxBnCAiGATELpGTJ4vZtWs7fn5+xMVN9EQNBonFYuGLLz7j1T++SHFJEQDpwIPARIQrms51Afv72e4CZnDlGngfBLIADVADNOta2bp1E/X1dUyYEO+J6g0Ro9HIqlX/5E9/epWmpkbkMgXT424kM3YJCvmlJ4FOl4MjVZsQ+yzDGC0dTIrIvmyqrkqhIT4kHRcudIZ6qqur2LpVEnkJCUnXpO/OWNDerueDD/7OP/7xVwwGAxq5jIwQP+J8tVe83jlcIjX9iHaACb7ay4r2c3grFURqNRjsTgw2O4WFx8nPP0Js7ARCQkKH9J2uZ0RR5Nixo7z55it89dXnGI0GAtS+PDjla9yTshwv5eWF3j9OrOVo8/n2YI1GHa0mPTMiplzxs/3VPiyMyUKr9KKy4wwtbS1s376FiorTREZGExQUPOzvd71x/Hg+K1c+RWlpCYIgkJCQwKRJkwZ8vRuuaAdpUcbf35+AgADa29vp6Ghnx45tiKLIpEmT3W6BzSPah4C7ivbS0hLeeusNQMSauBjXINpcjJhoB0S1FImQdzdSWFjA4sU3oNVqB/x+D705caKANWs+RSkT+VmGEa8BBEYvFO133HEHTz75JHa7nfLycmaHWQnWDKx2J1gjUtahoNkkYLPZmDnTE20fLE6nk927d/DKKy9w8OA+HA47YqCIa64LEoGB3J9GQrQDKEGMFRH9RQS9gKXLzOHDBzl69DDBwSFERkZ5xPsVMJtNbNy4nldffYm8vFzsDjsRwD3AIgTUAzScswCX8peey8CM62QIxCGQCRiBFqD2TA2bN29Ap2slOjrWI94HiMlkYt26z3n99ZcpLDwu9e32T2B+8l1E+sdf8bww27o51Xzkou0iLhJCM65YAy8IMsL9JhDuP5EOUyvd5nYKCo6xb99u1Go1sbETPOJ9gFgsFtau/ZRXX32pZ4E0xkfD9FB/fFUDS30dCdEOoJTJiNSq8VLI0VvttOn17NixlZqaauLjEz3n5wBwuVzk5x/hzTdf5YsvPkOvb0MpU3DTxHl8P/NeJvhf+b5ld9r5sOhLXGLvRbVWUzvLJ869bLT9HDJBRkJALPOip2GwmanvbqahsZ5t2zZRUXGa8PAIT+R9ABgM3bz77jt88MG7mEwmNBoNmZmZREREDGr+MRKi/RxeXl5ERkZiNpsxGAwUF58gLy+X5OQUt4q6e0T7EHBH0W6xWPj975/EYOjCEZyEPWZwvecvFO19RZ4jKB5RPbgIq8s3HHlHHU5TBzU11SxevNQjBobI3//+Nk1NDdwYPbAoO/QW7U8++SRxcXHExsaydu1a0oPsxPoM3Hk+RONiT6OaM2dqWL58xYDSljxIYn3//j388Y8vsn37FoxGI6JGRJwuPRiMRcBIiXaQUvD9QEwUJcM7PXS0tbN37y4KCvIJCQkjPHxwN8/rga6uTtau/T9ef+1ljhw5hMViIRC4HbgNCBmkO/xIiPZzaBCYgkAq0AnoRJGqqgo2bVpPbW0NERGRbjXxcCe6u7tYu/ZTXn/9Dxw9egSr1YqvJojZCbcxJXoeasXAUtTtTivlzUf7fS4lfMaAjeu0Kj8SQjPwVvujNzTQ0dVOXl4uu3ZtRy6XERc3wVPScgmsVgtbtuTwxz++SF7eYZxOB34qBZnBUnT9UnXo/TFSoh2kaJ6fSkm0twa7S6Tb7qC+/gxbtuSg1+uJjY3zZLH1g9lsYuvWjbz55h/ZuHF9j1i/ccJsfpB5H9PCU1EMsJVxu7WLrdUXX3Fdoov5ZyPoA0WjUDMtPJXsyKmYHRbqu1toaKxn+/YtHDuWh1qtISoq2rPI1gdRFNm9ewcvvPAspaVSxkNMTAxTp069pEP85RhJ0Q4gl8sJCwtDq9XS0dGBXt/Gtm1b6O7uYtKkyW7h0eUR7UPAHUX7xx9/wNGjR3CpvLFMumnQPdkvFO19RZ7TLxpRO8gJnyDg9I1A0XqKlqZGQkPDiI9PHNw+PNDQUM8//vFXBER+nG7CZwBp7dBbtNvtdmJjY1m9ejXl5eWsiLMMONIOEKxxcVynpM0M3t7epKWlD+m7XC84HA527drO66+/zNatm+ju7kZUiYhTRMRZIgRx6dr1SzGSov0cMiAExAQRRBA6BNpadezevYOCgnwCAgI9kXek9lCrVn3EW2+9xokTBdjsNoKBm4A7gagBpML3x0iK9nP4IpCJQCJS5F13dvxbt27i5MlivL19PMf0LKdPl/Hvf/+Tt956g6KiAux2O36aYKbF3kDWxOX4aQZ3zxsp0Q6SyAvUhpEYNg2VQkunuZUuQwfHjh1l8+YcOjs7CQsL90Rpz2IwdPPVV5/z2msvcejQASwWM15yGWlBvqQG+uB1CXf4yzGSov0cCpmMMK2acC81ZocTo91BRUU5Gzeup7GxnsjIaI9BKFBbW8PatZ/y5pt/5PDhQxgM3WgUam6Im8X3M+8lKzwN9QBLP89hcljYUZPb73M3TpgzKNF+Dh+Vlunhk8mOTMfisNFkaEXXpuPQoQNs374Fi8VCeHgEWq3HxLeqqoJXX32JDRu+xGq1otVqmTp1KtHR0UNOQR9p0Q7StdfHx4fIyEgsFgtGo4Hy8jJ27tyKv3/AuJcSDlS0C+K15IU/THS6btzpr1FVVcHDD/8Sl8uFZdLNOANiB70PwdqN9vhqQIq033///axevZr169djmnz7oFLtL0TRWIi69jA+Pr68+eZf8ffv33XXQ/+sWvUvPvvsEzKD7fzPdMOA39dqlvGr/dLfWhAERFHs+fe1+Z2Eeg2ux/ueBhV/K/EmKiqGN998xzPp7wer1crOnVv54os1tLa2ACAqRcQUURLWwzEkNYI85xIux7c6Bxe1vxRmEEoFZJWyHne0+PgE7r77PubMmXddRQ1cLhfHjh1lw4avKCjI79keBSwE0pBS04dDOyKvXuK5XwOBw9w/QBMie4EizhveRUREsmLF7SxdetN1V7ZkNps5cGAvmzfnUFFR3rM9UBvO5MjZRAemDPnaZrR2sqHwb/0+d1vGDy7pOD8QnC4HVboiTjUdxmg933IqMzOLm29eQVZWtls7Ho8WDQ31bN68gW3btmCxSALbSy5jop+WGB+vQUXW+2J2ONnT0Nbvc4uigvG6hOv8YNBbbFR2mWiznA8EZWXN5NZb7yAzM8vt6mlHE6PRyP79e9ixYwvl5WU928O9g1kaN5s5UZloBlGm2ReduZ3H9rzR73MrF/2CEK/AIe/7HF1WA3vrjrKr9ghdNmm+JggCmZnTWbp0OdnZc9wiWjuWtLfr+fe//8nOnVKduEwmIz4+ntjY2GH/vs1mMwcP9r/0PXfu3CFF7/ui1+spKyvDZDIBkJiYzLe//X0mT76yD8JoIAgQEnIlEySPaO+Fu4n2Z555jMLC4ziC4rEm3zikfVwo2vuKPNO0+xHVV/6R9IvLhab4C+QmPbfddiff+c4Phraf65T//u/v09TUwE/SDcwbYGo89BbtfRmKaDc54L/3BGB3CbzyypuerIkLMBqNbN68gfXrv6SzswMAUX1WrCdLrkgKAAAgAElEQVQOU6z3fMgYiPZzWEAoExAqBASHNOmNjIzirru+weLFS69pcdDd3c3OnVvZvDmHpqZGQEqKSEWKfk+EIUXV+2MsRPs5OhDJBfKQIvwAGo0XixffwC233EZc3MQR+yx3w+VyUVRUyK5d2zl0aD9Wq9R3WybIiQ2aRGLYNIK9h599MJqi/Rwu0UVzZzWnW47R2FnZs93Pz48FCxazZMmNJCQkXdOLqk6nk/z8I2zcuKHXgpqPUkGCn5ZwrXpYYv0cYyHaz9Fls1PVZaLJdL4nfEREFDfffCtLly7Dx2eI8y83x+l0Ulh4nD17dnDo4AFsdmnxQibIyAhNYWHMDNJCEofVb/0cYyHaz+FwOchvKmFvXT5l7dU92318fFiwYAmLFi0hJSX1mj5PzWYz69Z9zpdfru1ZUAsLCyMpKWnESizHQrSDdA85c+YM1dXVOJ1OAGbPnscDD3yL6Ogrt9QeSQYq2j0FVG5KcXGRZJojyLDFzRqRfZ5bnxmRdRqZDFvcbLxKN7JlSw533nmPx6hjgLS0tNDU1IBMEJkWMnDBPhpoFTAlyM5xnYrCwuMe0Y5UC7t+/ZdsyPkK89lVWFErIk4SpTZsV2tgWgNihoiYKiKUCwinBRobG3j77TdZvfpj7rrrGyxbdjNq9dCjHu5GRUU5mzZtYN/e3T0TRw1Sr/U5jKyAHg8CELgZuAGR48AhoNViZvPmHDZvzmHy5CmsWHE7s2bNvWYWZWpra9i7dxd79uxEp2vt2e6jDiQ+dCrxIVPRKK+uTAOZICMyIIHIgAQM1g4qWgqoaSumq6uLnJx15OSsIyYmjiVLlrJgwWJCQ8PGe8gjhuTqvJUtWzb2ZDIBhGpUxPl6EaxRXbUiyE+lJDPEnyS7gzMGM/UGC01NDXz44busWvVPFi5cwk033UpSUvJ4D3XYiKJIWVkpe/fuYv/+vXR1nc8cifQOZX7MdGZHZuA3SB8ld0IhUzArKoNZURm0mvQcqD/OwYbjtBu62LRpPZs2rScsLJyFC5ewcOESYmPjxnvII4bD4WDbtk18+umqniCGn58fycnJV22mrUwmY8KECURGRlJZWUlDQwO5uQc4cuQQy5bdzH33/afbecZ4RLubsnHjOgAcoSlDj4aPMi6/KJy+4dDdzLZtm7n//gfGe0hXBadOSUYd8b7OK/ZlHwvSAh0c16k4ebKEO+/8+ngPZ9zo7u7iq68+JydnXc8KsugniVwxVpRqxa8FVEh1+JNEhEoBoUxAr2/jH//4K2vXrubOO7/BzTffetWKd7vdzqFD+8nJWUdZWWnP9ghgNpABqK5ysd4XFQKzgGxEqoBcoBQ4ebKYkyeLCQwM4qabVrB8+S1uNwkZCG1tOvbu3c3evTuprq7q2a6Uq4kLSmVCyJQRiaq7Az7qADJjFzM1ZiHNndVUtxXT0H6aurpaPvroAz766APS0tJZuHAJc+cuwNfXPecHl0MURYqLT7B5c47Uj9vpAEApE4j29iLW1wvtCEa8xxtvpYLUQF+S/H1oNFmo7TZjsNnYvn0L27dvITExmZtuWsGCBYuvOkPYurpa9uzZxd69u2hpae7Z7qPUMjNiCnOiMpnoH31NnJsXEqoN4s7kpdyRtISTbZXkNhRyvOUkLS3NrFmzmjVrVjNxYjwLF97AwoWLr9qgliiKHDp0gI8//oDGxgZAcmRPSEggLCzsmjiuKpWK1NRUYmJiqKysRKfTsWXLRnbv3sEdd9zNXXd9HS8v91gIdgPJ4KEvZrOZo0elFjOOsNRxHs1lEAQcoanIu5vZt28P9933n9fECTzanLvwxfg4x3kkEufG0dzcOM4jGR/sdjubN2/g00//jdFoBED0F3GluSCawZvLXS0o6En1F6oFhFKBjo4OPvzwXTZs+JKHHvo28+cvumrO6c7OTjZtWs+WLRvp6GgHpKSIKUhiPZaRS4F3VwQEEoAEoAuRI0ip8+3telav/pjPPlvNvHkLuOOOu0hMdO/ontVq4eDB/ezYsZWSkqKeDDGZICPCP4EJwWlEBSQiH6Q569XChdF3m8NKXfspatpKaO0+Q0lJESUlRbz77jvMmJHN0qXLycqa6fb+FDabjV27trN+/RfU1583mvJXKYj18SJCq0Euu3bPUYVMINbHixhvDR1WO2cMZppMVioqynn77XI+/PA9li5dzh133OXW/d7b2/Xs27ebPXt2UllZ0bNdLVcxPTyV7IipTA5OGFC7tasdmSBjSkgSU0KSsDltFLSUcaTxBEW601RXV1FdXcVHH71PenoGCxcuYc6c+Xh7Xx0GdmVlpXzwwbucOnUSAKVSSXx8PFFRUWPmy9DXi8tqtY5YenxffHx8yMjIoKOjg9OnT9PV1cVnn33C1q2buP/+B1i27OZxv8Zem3e7q5yyslJsNisulQ8ubfB4D+eyOAInoEKgoaGO9nY9QUHuPV53oL1dD0CQenD156NF8Nlx6PX6cR7J2FNcfIJ33vkTDQ31wFmxnu6CSMZcrPe9OWFmZGvaL4VcahMnxosINQJCsYBO18prr/2BnJyv+MlPfklMzOBNMMeK9nY9X321ls2bc3rqmn2BbGAmkvP6eNH3mHaLIiNXYXl5/BC4EViMSAlS6vwZp4O9e6WoWFbWTO6995ukpLjPwrAoipSXn2LHjq3s27cbs/m8y3eobwxxQWnEBKUMuF3btYJKoSYhNIOE0AxM1i5q9aXUtpXQYW7l8OGDHD58kICAQJYsuZGlS5ePeT3mlTAajWzZksP69V/Q0SGl1soFgUhvNbE+XvgNsMf6SHORIHA6R7Sm/VIIgkCgRkWgRkWq00W90cwZgwWTycj69V+wceM6Fi26gbvu+joxMe6RYu1yuTh+PJ+cnK8oOH6spy+6TJCRHpLErMgMMsNSUMmvL0O2C1HJVWRHppMdmY7RZuJocwmHG09Q3l7DiRMFnDhRwN///hdmz57H7bffSXLypPEecr+YTCY+/vhDNm/e0GMyFxcXR1xc3Ji3pbz//vuJi4vj/vvvZ926dVgsliu/aZgEBAQwY8YMWltbqaiooLOzg7/97S127tzKj3/8CyZMmDjqY7gUHtHuhjQ3NwHg0gZK7gTujEKFqPZGsBpobm7yiPYBcD5iNM4DOcv5n5gbuTCOMqIosmHDV3z44bu4XC7JYC79bM36OB2XvjcnTGM8ABmI8SJinIhwSoq8nzpVyiOP/Iqf//w3zJo1d4wHdHnMZjOffPIRWzbn9NSrRwELkFzg5W4QVe97TDuAsZ6CKxDIQCoLqEfkIHACyM/PIz8/j8zM6XzrW98b14mIKIocO3aUVav+2Sty5632Jz5kKhOCp+CtHv82aH1FntlmGBEjusGgVfuRGjmL1MhZdJpaqdIVUdNWQkdHO1988RlffPEZmZlZPPDAf417NoXL5eKrr9ay5rPVmMzSBU0jlzHRV0u0jwbFOLuo9z0/zQ4XAWNcFaSSy4j382airxadxUZ1lwm91c7OndvYuXMbc+fO5/vf/+9xqxu2Wi3s2rWDDRu+7JUdkRAQw+zIDGZGTMFH5R6R477nZ6e1e0SN6AaDt0rLotiZLIqdSZu5g8ONJ8htKKDRqGPfvt3s27ebSZMmc/vtdzJ7tvt0cSkuLuKNN16mrU0HQEREBImJieNWLrd69eqeYyoIwpiVjwiCQFhYGCEhIdTX11NZWUl5eRn/8z8/5777/pOvf/3+cclC9Ih2N8RolFpKiMNogzGWiAoNWA0YDANvXXY9o1ZLFx2jY/xFBUi93+H8uK4H/v3vf7J27acAuOJciFkj5AY/DPrenBivEio5iGnSAobskAyzzsxLLz3Hz372a5YsGVoXi5GmtraaV155oWcSGQssAZJxrxT4vsc0YJzbk0Qj8A0k47o9wHGgoOAYv/vdr/jBD37C0qXLx3xMpaUlfPzxh5SUFAEgFxTEBKUQHzKVUN9YtyrP6CvyTLYupBqa8cFfG8q0uBuYGrOIxs4KqlqLaOqspKAgn4KCfObOnc83v/lf4xJ57+7u4o03/sixY3kAeCvlxPtqifTWjIgL/EjQ9/z0UozfIoIgCIR6qQn1UtNhlVznW8xWDh7cz6lTpfzmN4+Qmpo2pmM6fPggf/nLm3R3dwGgkauYH5PFkthswrzdL0DT9/xsM3eSGDDeo4JgrwBWJCzklvgF1HY1sqM2lyONRZw6dZJTp04SFhbOb3/7v+O+yFZUVMjKlU9hs9nQaDSkpqYSFDS+Hijr169n3bp1PV2vxnrxQCaTERsbS1hYGKdOnUKn07Fq1b8wmUw89NC3x/z+5BHtbkhgoHQxlNnGOtQ2NISz4xzvk/tqITIyCoAmk3s4mzUapRXec+O61mlsbODLL9cA4Mp0Sb3W3WAO2ffmxHhnAHuBa7EL4ZjU4/1f//oHs2fPG7V6soFy7Fgef/jDSmw2G37AXUAS7iXWz9H3mLqLZVgwAncDSxBZB5Tbbbz11utUVVXw3e/+aMzGsXfvLl5//WVAatWWFDadyZGzUbup+3tfkadVjX/0H0AukxMTmEJMYAoGawfF9fupaSvh4MH95OUd5ve/f2lMU3FbWpp54onfodO1IhNgcqAv0d4at1qAgX4EgZtEOwPUSqaH+tNls1Oo60Kvb+PJJx/hpz/9FYsW3TAmY9i4cT3vvfdXRNFFiFcAN8TNZn7MdLwU7ru43/f8DPZyL1dzQRCY4B/Ft6fezT0py9hde4TdZ/JoaWnmySce4Te//V+ysmaOy9gaGxt4/vlnsNlsBAcHk56e7hbR/xHtejUM1Go1U6dOpb6+nrKyMr78cg0hISHceuvXxnQc7qEaPPQiOlpauZcZWsE5vi3BroRg7kBmNyGTyQgPjxjv4VwVJCRIbdXKOhQ4BlnW7q9yoZRdfPFSykT8VUOrkS9pl9burpd2b7t2bcfpdCKGST3X3UXrucvNqRcyEKeLiFqRjo4O8vJyx3tEfPbZamw2G4nAT4BkBLcU7OCmx/QCAhF4EFiGdBrk5KxDr++/h/VI096u5+9/fxuA2KBUbp36PabF3eC2gh0kkffggw+yfv16RFHES+V+7at81AHMTriNm6b8P0J9Y7Db7fz5z69jt4/dXCI/Pw+drhW1XMbs8EBifLzcTrCD+5+ffiolcyICCfVS4XQ62bZt85h87o4dW3n33bcRRRcLorN4dsHPWDZxrlsLdrj4/PR3085LAP5qX76WvJTnFv2cycEJWKwWXnjhGUpLS8ZlPMeOHcVqteDr6+s2gt3dEASBmJgY4uPjAThwYN+Yj8Ej2t2QxMRkwsMjEFx2FPqqK7/hMohKL0Th4pNPFOSIyuFHzBStZQBMnz4THx/3vUC6E4mJyfj5+WFyyDjZPrhkF5UcZoRePPmaEWpHNYRrrN0Fx3VSXviMGdmD38FVSE/LKyvgHgb+7o0DkErG3cKzoqlJ6r6wAPB2U7F+NSFDYB7nqzGamsami8SmTRswGg0o5Wqy429B6wY161fC3UXehQRoQ5k58RZAasuVm3tgzD5bpZLMyLzkMnyUnoTO4aCQyQhUS/foc3/X0eZcj3UfpZb/SLv1qnGBv5rOz3N4KTT815SvISB5QIxXmanJJHXOkcvlY+YMf7WiVErno8k09tnQniPjhshkMpYtuxkA5Zk8cNiGsTMFzsAJF212Bk6AYbbKESydKJuKAVi27KZh7et6Qi6XM2/eIgC2nBl8fc7304xkh53/TWSH2fh+mnFIY8ltVtFtlxEUFMzkyVOGtI+rjfnzF6JUqhA6BWQ7ZTC0P931gR5kW2UIDoHw8Ai3+I1oNJK8XAUcRUS8jgwUR4MmRP7K+dNgrIx+ZszIRqlUYndaya3cgMHaMSafe73Qbmomt3IDAP7+AWNaD32uJ3WHzcGBRj1tlmHMYa5jLA4nBbpOyjqks3Osen3ffPOtBAQEYrCbeCX3HxyoP4bN6TmGI43BZmJb9UFey/snIpCcPGnc0uOnTs1EEGR0dHRQVFSEw+EYl3GAtDjV38KBTCYbs4Wr/hBFsSc9HiAzc/qYj0H+9NNPPz3mn+qmmEzuc1FKSEhi//49GLvaERyWfoX3QHEGxCIzdyCzSJMiR+BErImLYTiraS4XmvLtyKzdZGZO55vf/C+3TH9zVyIjo9i4cR3NJhkzQu0EqAcuPBQymBZi56tqKVPi2VldaIawEO50wdvF3nTbZdxzz31MmTJ18Du5ClGr1SQkJJGfn4e9y45QJYAd8GPszejkSE7tYu9zR5RJbvbjtqzaBcIJAflxOYJNEuwPP/zY+SyFcSQ7ew7V1ZU0tbZQCpwELEht3rzcIPKuAPYDfYtVFMCNuIervQWRImA7sAXoRhJ2v/7178bsOhAcHEJ8fCIHDuyj06SjvDmflu4zCEgp3jI3ie7JZQrKmvIQ+xxRuaAgPWYBMsF9Yh9Wu4lKXSFHa7ZS0nAAs92Aj48vzzzzAlFRY2eYFx4eQVhYOKWlJzGYzTQYLXRapQwxjUKGfBznCjJBoLrbdNFSn0yApACfcTfJc4ki7VY71V0mivXddNsdCIKMFStu46GHvtMT5RtNlEolERER5B46iN7SSUHLKXbVHqbd0oW/2gc/lY/bzPeUMgVbqw/2tKC7cPudSUvdLkvA6XJS3l7Dl+U7+FfRVxTpyjHazXh7e/PrX/9uzBZm+hISEkpc3AQOHz6IwWCgvr4eh8OBt7f3mLd5k8lkGAwGjMbeEZXQ0FAiIsa+DNflctHU1ERJSQmNjVIm2tKly/nOd344YlkJggBa7ZWDeB7RfgHuJNoVCgWxsXHs2bMTmVGHqFDh8gkb2s5kMpwBsagaCgAwp98J8mFc+EURVfV+FO01qNUaHn30aXx9Panxg8HX14/6+jpqz9TSZJKxINI2qO5+DpEe0f61eAtDMb3dUa9ib6MaX19ffvazX6NSXR3dCkaCyMgo5s9fTHn5KfStbQhtArJyGRiQDOA0jE2tuwxJIHf1Ee0x4tj3BhOBFpAdlyE7LkPoEECEOXPm89hjzxAWFj7GA+ofb29vFi26AY3Gi5KSE3S5XFQi9SE/hdTe3gfpMI5HrbscgWagpc/2NCBjHAW7+Wy/9u3AOqAY0CEd9uzsOTz++DM9fhtjRVRUNJMnT6G9XU9LSzNGayf1Hacpbz5Gp1mHzWlBKVehlI+fiZlMkNFp1tFl1vXaHhOUQlzw5HEZ0zlEUaTTrKNWX8rJxlzya7bS2FmJxW5EoVAwe/Y8fvazX495Oz9BEIiPT2D58puxWq2cPn0ak8NBi9lKdZeJdqsdp0tEo5CNeds3mSBgsDsw2HvXRoVr1UR6j0/NtlMU0VlsVJ0V6mcMFjptDkQgNTWNRx55nBtvvGlMBPs5YmJiWbbsZnx9/Whpaaaju5Pqrgb21h1lV+0RKjvO0GUzoJDJ8VV5j9v5KZfJqTc002Bo7bU9K3wy2ZHjH4iwuxxUddRxqLGAnIo9rDqZw766fOoNLbgQSUhI5L77HuAnP/nluPtCxcTEkZqaRllZKZ2dnXR2dlJXV4fZbEYul6NWq8fsOAcHB2MymXpS0ENDQ0lLSxvT1H2j0Uh9fT0nT56kqakJu92Ol5cX3/jGf/Ctb31vRMcyUNEuiFdT8ccoo9N1425/jS++WMO//vUPACxJN+AMHuKkymnHO+9DAIwzvzV00S6KKOuPoarPRxBk/O53j5OdPXto+7rOaWlp4ec//wF2u50fpBlZFDXwRSOLE763U+o/+u4N7YOOtOstAo8c8sfkEPjud3/ErbfeMbgdXCO4XC6OHj3CV1+t7Wk5BSD6iIixUs9yRrvU1gHCYQFZvXQDcEW7EGeJY9PbQwT0INQKCHUCgkW6IQuCwKxZc/ja1+4Z8zZDg6Grq5Pc3IMcOLCXoqJCXK7z0RY/YOIFjxDGTsTbEFkDnLMUSgO+DqjGULQbEakBqs8+mqBXdDEqKoZ58xYwb97Cce3Rfo7W1hZ2797Bzp3bLqqr16r8CPWNJcwvjjDf2DHvje5w2jlclUNdu5QWGROYwqz4W1EMZ/F7CIiiSJeljZauWlq7z9DafQarw9zrNQkJidxww3IWLlyMr697+ATU1dWyd+9uDh06QF1dba/nAlQKgjQqgjQqAlRK5LLRP0ecLpHCti5azFYAwrzUZAT7jclng3QcDXYneqsNvcVOm8WG84LJp4+PL9nZs5k7dz5ZWdnjHtV2uVycOFHA1q2bOHr0CDabtdfzGoWapIA4kgMnkBQYR5xfJKoxPDdsThvvF35OfstJALLCJvPtjLtRycc+ldpst1DdVU95ey3l+hqqOuuwu3qnmnt7ezNv3kKWL79l3Nu89YfL5SIvL5cvv1zbyxhPqVQSEhJCWFgYgYGBoy6gnU4nu3fvBmDx4sVjYo5nNBppaWmhpaWlV6Q/MDCI22+/k+XLV+Dt7T3inysIEBJy5eCnR7RfgDuKdlEU+dvf3mLLlo2AgDVhIY7QlMHvaCREuyiirMvridh/5zs/5LbbxrbdwbXG2rWf8vHHH6JViDw/p5MQzcB+gMMR7S4RXjnuQ2GbkuTkFFaufMXjFAqcPl3G+vVfkpt7AJvt/AKK6C8ixoiI0WcF/GjMnxwg/1w6Bs67naMr2EWgDYSGs0LdeP4L+fj4sGDBEm677Wtjmk47EnR2dpKbe4CDB/dRUlyEw9l7ouQDTADikZIYwpFM2EYLGyK/P/vfTzD6gr2rj0jvG+kHiI6OYe5cSajHxU0YdzHQH6IoUlpawvHj+RQVFVJeXoazz7HUqvwI9omSHt5RBGjDRj0N1uG0sTb/DQDuyfoFijEQBA6nDb2xmTZjA20G6WF19DY/UqvVpKZOIT19KllZ2UycGD/q4xoODQ315OYeIDf3AOXlZb2eEwB/tZIgtXLURbzDJbK9TorO3hgTimIUBXtfkd5utWF39b7XBweHMHv2XGbNmktamvu6d9vtdiorT1NSUkRxcRGlpcWYzb0XjmSCQJRPGBP9opngH8VE/yiifcJH9Ry1Omz8fPvzALx546OoFaN/ftqcNs50NVHd1UB1Zz01nQ00my7uvuHvH0Ba2hTS0tJJS5tKXNyEq8bsrbS0hJ07t3H48EG6urp6tisUCoKDg3seo5EFMhai3eVy0dnZSVtbGzqdrpe5nFwuJyNjOgsWLGL+/EWjmuniEe1DwB1FO0g/qr/+9c897T6sE+bgiEgf3E6GK9pFF6qaQyibpVW3b33re3zta3cPbh8eLsLpdPLYY/9Defkpkv0dPDaje0Cp7sMR7eur1XxyWotSqeSVV94kJmas87DdG7PZTF5eLnv37ub48aM4nefTKEVvSbyLUeK50O3IMNqi3Qm0gFAvSGLden7gao2G2bPmsGDBYjIypo9pCuZoYbVaOHWqlJKSIkpKiigrK72o5ZUaiEES8HFn/1szgsJ6NEW7E5FmoPaCR2c/r4uJiWPKlPSzk8V0t3D/HywWi4XS0hKKigopKiqkoqK8V0YFSPXlgd7hBHlHEuITRbBP9Ii3Yxtt0S6KIgZrhyTOz4r0TlPrRUaLKpWKSZMmk56eQXp6BomJyVftOdvWpuPYsaMUF5+guPgEbW29SxAuFPGBahUBauWIievRFO2iKNJtd/QI9Har/SKRrtFoSE1NY8qUqWRkTCMxMdktF9GuhNPppKam6uwxLKK8vJSOjotNJRUyObG+EUzwj2aiXxQJATGEaYNH7DuPtmh3upw0GFqp6qyjprOB6q56GgwtuPoRDaGhYaSmpvVcd6OjY67KY3shTqeT4uITHDy4j0OHDvR0GDiHv78/wcHBhISE4O09MuUSoyXabTYbbW1ttLW1odfre5nuyeUKpk2bzty5C8jOnj1mXbE8on0IuKtoB0m4v//+38jJWQeAPSIdW9xsBlwIPRzR7rSjPr0TRUctgiDwve/9iFtuuX2wX8HDJWhqauR//ucXmExGbomz8GCK+YrvGapoL21X8Hy+Dy5R4Ic//Ck33bRiOEO/5unu7iY39wCHDx+isPBYL+EnqiTxLkaLUth2OPeT0RDtNhAaJZFOIwjO89cKrdabGTOymTVrDjNmZKNWu3f/3eFis9k4fbqsl4jvGx0SgDAkAT8BSAB8hyG0R1K02xA5A1QBZ4A6errw9SATZEyYGM/kyVOYMiWdyZPT8fcf2zTyscBsNlFeXkZZWSllZaWcOlWKwdB90eu8Vf4E+0QR4htDiE80/l4hw5pIjrRod7qcdJia0Rnq0XXXozPUXxRFB6nN4qRJqaSkTCYlZRIJCUnj6qA8WoiiSHNzU4+ALy4+gU7Xu05ZAPzOptMHqpUEqpVDrokfSdEuiiJddgftFjt6q412ix2H2FekezF5siTSp0yZSkJC0pgbfI0FoijS1qbj9OkyKipOn/23/CJTMQBvpRfx/jEkBEiPif7RQ+4FP9KivctqoKqzjsqOOqo666jurMfqvLjdbkBAIElJySQlpZCYmExiYvI1ed29EKfTSWnpSfLzD3P0aB5nztT0el6tVhMSEkJISAgBAQFDFtsjJdpFUcRgMKDT6Whra+uVMQDg5+fH9OkzmTEjm2nTsvD2HtkF34HgEe1DwJ1FO0g/vC+/XMO//vU+AI7ACVgTlwxMgA9RtAs2E+qyLciNOpRKJb/4xW+ZO3fBUL+Ch0uQm3uQP/zhOQB+NMXIgsjL17cPRbTrLAJP5vrRZZexcOESfvGL3171q79jidlspqAgnyNHcsnLy+3VT1WUS8JdjD4r4gcb+Bop0W4+G02vF6CVXq70QUHBzJo1l1mz5pCWln7VRudGAqfTyZkzNZSWnuTUqZOUlpbQ0tJ80etCkdLpE87+qx2E8B6OaHcgUgdUcl6oO/u8Rqv1ZtKkVCZNmkxqahpJSSl4eXkN+DOuFURRpLGxoUfAl5WdpKamBrGvm7RcLYl4n2jCfGMJ8okalCiaLdwAACAASURBVPP7cEW70+U4W4deh85Qj97YiLNPratCoSAxMalHoE+aNHnc3KTHG1EUaWlppqiokJKSIoqKCi8p4kO81IR5qfBVKgZ8TxuuaLc4nLRabLSarf2KdC8vr56yhbS09GtWpA+Ec+doRUU5p0+XU15+isrK0xdlPwlApE8oCf6xJAXGkRaSiL96YJHO4Yr2VpOeYt1pKjrOUNlRh87cftFrvLy8SE6eRFJSSo9QDwoauWyBq5WWlhby84+Qn5/HiRMFvTwP5HI5gYGBhISEEBoaOqh5x3BEu8vlor29HZ1Oh06nw2rt7cOQkJBIVlY2M2Zkk5iYPO7lKB7RPgTcXbSfY9++3fzpT6/icDhwaoOxTroJUXUFYwRRRFOyHgBL2u0DitDLjG2oy7Ygsxnx9fXjkUeecGtTqqudf//7n6xZsxqlTOTxGd0k+vedpp9HFOH3edIJ/sTM7iseTosTnsvzpbpbQXx8AitXvnzNR1dHE4fDwcmTxRw+fIgjRw7R2nq+gliUiRABYpyIGDlAQzkRqWc84LrBNbi0extSbXqtgNDa+41xcROYNWsu2dlzSExMuu4nF5ejvV1/VsCfpLi4kKqqSi68PQpICRVJQDoQxeWN7QYr2rvPtmErA2qQuhBeSHBwCOnpGaSmppGamkZMTOxVUxc51pjNJsrKTlFaWkJpaQllZaVYLJZer1HJNYT7TyTSP54I/3g0ysvfQ0VRZGfpKgBuSP3mgM4lg7WDxo5KmjqraOmuvUik+/r6kZo6ueeYXqtR9JGipaW5VyS+70KbWi4j1EtFqJeaYLXqsvXwoihyuEVK454VFnDF43kumt5qloR6l62Pz4JWezbLRYqkx8cnjrsQcGfsdjs1NVVnM2ZOcerUyX4XTuP8IpkSkkR6SDLx/tGXrIsfrGi3O+2UtddQ1FpOka6cFpO+1/OCIBATE0dKyiRSUlJJSUklOjrGc0yvgNVqpaiogLy8w+TlHUavP1/jLwgCQUFBhIeHExIScsVFLFEUyc/PByArK2tA52hnZyfNzc20tLT0WhRSqdRkZk5j5szZZGXNdLtSsetOtH/88ce89957tLa2kpyczKOPPsrMmTMHtY+rRbSDZA7x4ku/p7urC5dSi3XSzbi8r/AjPPflBjDZkHecQV2+A8FlJzo6hkcffZqIiMgRGLmHS+FyuXjxxd9z9OhhAlQunp3VRdBljOkGejhdIvz5hDeHW1T4+fnx0kuvu037rmsBURSprq4kN/cgBw/u7+WOLMrPmtglihDE5cX4uUM9EF0tAk0gq5AhNAm9bMFTUlKZO3c+2dlziIyMGvwX8gBIpRFShK+AEycKL0oBDAKmnn2E93PQBiLaTYgUAyeQzOMuPNv9/PyZOjWT9PQMpk7NJCIi0rPoMkTO1d2ePFnCyZPFnDhxvFemDECgNoKogAQmhkzFW92/6/q56dLljkOnqZUqXRGNnZV0W3oLgaCgYDIypjF58hRSU9OuiVrX8aS1tYWCgmMcPXqEgoL8XtE0mQAhGjVxvl4EqZX9/p0HcjzNDie13WYaTRaszt7ZG8nJKcycOZtp02YQH5/gEXTDpKOjnfLyU5SWnuTEieNUVJzu9bxWoWFySCKzI6cyNTSlV6bMQES73eXgSOMJjjaVcEpf1cvVXS6Xk5qaRnp6BpMmTSYpKWVUXMKvJ0RRpKqqkqNHD5Obe4Cqqsqe52QyGSEhIcTExODv73/Jc3Ag56jFYqG+vp6mpqZe1wA/P3/mzJnHzJmzSE/PRK1237bG15Voz8nJ4eGHH+app54iKyuLTz75hM8++4wNGzYQFTXwSevVJNpBqoV+/vmnqa+vQ5QrsSbdiDMgZtj7VbSUoqraj4DI1KmZ/Pa3/ztmZgzXOyaTiUcf/S1nztQQ7+fgiRndqIY5D/i8UsOaSi8UcjlPPf08aWmDNDH0MGBEUaSmppr9+/ewb9/uXpEDMVBETJJayQ25/t0GQrWAcLq36/vEifHMny85nI53r9drlY6OdoqKCnuyKy7sMBAGLAAyOe9IfznR3oDITqSo+oUyYNKkycydO5/MzOnExrqnu/u1gNPp5PTpMvLz88jPP0JlZUXPcwICUQGJJIZNJ9xvYMfA6XJS315OResxWrvrerbLZDImT57C9OkzyMrKdlvH/msBm81GUVEhR49KEb4LU+l9lHLifLVEaTUDcqMXRZF2q52abhMt5vPnuUajISNjOjNnziIrayaBgUGj8l08SHR0tHP8eD75+XkUFOT3WmgL0wZx44Q5zI2ahlqhuqxo77YZ2XMmj121h+myna+tDwoKJitrJtOnzyAjYzparXbsvtx1SF3dGfbt283evbtpamro2e7n50dcXByhoaGDuj4aDAZqa2tpbm7uEfdarZbZs+exYMFipk7NvGoW0q4r0X7vvfeSlpbGM88807NtxYoVLFu2jN/85jcD3s/VJtoBDIZu/vCHlRQXn0AUZFgTFw+9l7soomw4jqruKABLltzIj370s+u69nU8aGpq5JFHfkV3dzfzIqz8eIppwH6DfTnSouSNQslU48c//jnLlt08giP1cDlEUaSsrJQtWzayf/+enlQtUSMipouIE8WBp8E7QCgXEEoFBIf0Jq3Wm6VLl7Ns2c3Exno6AIwlZrOZo0cPs2/fbo7lH+1pLxcO3AQkI6W39xXt7YhsAwov2Fd8fCILFixi3ryFngyYcaK9Xc+xY0fZvXsHRUXnj46POpCM2EXEBPbfZlUURU63HONk4yEsdkkMyGQysrPnsHDhEjIypnmidePAueynbds2s3PndqxWqTRCIRNI9PNmgq/XJcVBu9VOib4bg/18FDYzczq33HIb06bN8JQvjBPnFtoOHTrA9u2be4zttAoNyyfO44a4Wfxyx4vAedFuddhYW7aV/fXHeqLqQUHB3HzzrWRnz/Esoo0ToihSUVHOtm2b2bVre8/cSKvVkpKSQlDQ5RfDrFYrZWVltLaeX5ibMmUqK1bcwYwZ2VflOXrdiHabzca0adN44403WL58ec/25557jtLSUj766KMB7+tqFO0g1Qb9+c+vsW+fZNhgjV+AIyx1cDsRRZRnDqNqPAHAvfd+k/vvf8BzQRsniooKefbZx3E6nTyQbGLFBOuV39SHeqOMpw77YXEK3HbbnXznOz8YhZF6GAhdXZ1s376FTZs29ESARH8R1zSXFKa9FCJSrfoJAcEsnYtxcRO59dY7WLhwCRqNx5dgvDEYutm2bTNr1nyKySRNJFOBu4AXz77mCeAYsJHzhnILFy7hG9+439Ny0c2oq6tl8+Ycdu3a3tOzd2JIOtPjlqKUn0+vNNm6OVyVQ0uXVA4TEBDI8uW3sHz5LdeteZw7YjQa2L59Kxs3ruvJfArRqEgP9kMtP59eLYoiVV0mTncaEZEcsBcvvpFbb73DsyjqZpjNZnbu3MaGDV/S1NQIwJSQJIp1Ujr9mzc+itFu5i/HVnGmuwmAxMQk7rjjbubOXXDdGgK6Ix0d7eTkrGPTpvU9CzHR0dEkJiZedJykDhPNlJWV4XA4EASB2bPnceed95CSMkjN42ZcN6K9ubmZRYsWsWrVKrKysnq2v/POO3z++eds3rx5wPu6WkU7SPXQf//7X9iyZSMA1oRFOEL7jw70h7L2MKpGKcLw7W9/n9tvv2tUxulh4OTkfMV77/0VmSDyaJaB1EDHld90FrMDnjrsR4NJTnp6Bk8++dxVkyZ0LWO329m0aT3/99knGM+m+rnSXYip/UTdnSDkC8iqpYllaGgYDzzwLebPX+QxIHNDuru7WLv2U3Jy1uFwOEhAirYLwBQkwQ6QkTGNhx76NgkJSeM2Vg9Xxmw2s2bNar744jNEUcRb7c/S1P/ES+VDu7GZXadWY3daUalUPPTQd7jpphUeMeDGOJ1Otm3bzPvv/x273YZKJmNmWAC+KgUuUSS/tZM2i5QKv3DhEr773R/h6+spC3RnJHfxHfz9b3/BZrehkimI8g3nv6Z8jdfz/kmXzYi/fwA///lvyMyc7glCuTFms4mPPvqATZs2AFLUPSsrqydqLooi5eXl1NVJ5UeJicn89Ke/JC5u4ngNeUQZqGiXP/3000+P/nBGD6PRyPvvv8+9995LZOR5o7QjR45w6tQpHnzwwQHvy2S6fJstd0YQBGbMyMZkMlJWdgp5ey0ubRCiV8AV36tsKEBVfwyAH/7wp6xYccdoD9fDAEhKSqGpqYHqmhqK9EoWRNpQD1B3/+OkluJ2JUFBwTz11Eq8vDy1Wu6AXC5n0qTJLFt2C93dXVRVVSC0CNANRHNeuNtBtluGrFGGIAjcf/8D/OpXvyMhIdEz8XBT1Go106ZlMWXKVA4e2Eer00EsMAP44uxr7rnnPn7601+5nXOth4tRKpVkZExj6tRMTpwooKNLT4ephaiAJPaU/R8Wu5HExGSeemolWVkzPQtpbo5MJiMpKZlZs+ZQUlJMe2cHequNaB8vKjqNNBgtqNVqfvSjn/Ef//GgW5tWeZCQyWTExycybVrW/2/vzuNqyv8/gL9utz1KqaZuKZQulVTk0sZkNNmJSb6UbRbKIIPwGFuDZoR8B2OYMWMdwxg8xtQwY5n5DSMGTSE7SZY2tEhanN8fjfuVdi333no9Hw+Px72f8/l87vs43XvO+5zP+RycO/c38vKfoLOJHeLuJeD+kwxYW7fDokWRfHKKCtDQ0EDXrm7o1MkB58//g5ycHDx+/BimpqZQU1NDcnIyUlJSIBKJMGpUEKZMCWtSc0qIRICubvW/OSqftGtqamLjxo3o1asXbGz+dy/3oUOHkJ+fD39//xr3pcpJO1CauDs7uyIzMwPJt25A/Pg2SlpZQdCsPGETP0yG1q3jAIDg4AkYMGBwY4VL1RCJROjSxRVxcSeQ/jgP6flqkL1RVO397ScfaGDPTV2oiUSYO28hh/YpIS0tLbi59YCRUWvEx58DHgulM5K9gdLHv8WpQZQugp5eC4SHz0efPr4cKaEiTExM0bGjA37//QjSAVz8t7x//0EIDp7Ig0cVY2JiCmfnrjh27Dfk5D/E5QenUVhSABMTUyxdGsWh8CrGwKAV3N098ccfR5Cb/xSPnxXhfn7p7WcffTQXXl69+B1VMUZGrWFj0wHHjh1GSs59PCzIhqaGJiIjV8LEpKr7z0jZvPGGGVxd3XD8+B/Izc1FcXExxGIxLl26BAB4770QDB7s3+ROktY0aVf5tdbU1ISDgwNOnDhRpvyvv/6Ci4uLgqJSHJFIhEmTPoSLS1eInpdA69oRoLjikxGigmxo3Sy9D75//8EYMmR4Y4ZKNaCjo4OwsNkQi8X4O0MTp9OrnhQwp1CELVdKT9IMHxHImeKVXN++fvjwwzAAgNplNSANEN0QQXRPBA0NDcyfHwFnZ9dqeiFl4+DgCJnMXf5eR0cHgYFjmAyoKEvLNggMDCpT9sEHU/hUFRWlr2+A998PBQA8fFY6CZaHhzdksp6KDIvqwMGhM7p0+d8xf1/ffjA2NlFgRPS6LC3bYMaMcADAvXv35Al7375+8PMboMjQFE7lk3YAGD9+PPbs2YM9e/bgxo0bWLZsGe7fv4/AwEBFh6YQYrEY06bNhLGxCdSe5UAzJa58JUGA1o0/ICopQseO9hg7dmLjB0o10r69Lfz9AwAAW67oIr+KW9u/u6qDvCI1WFu3w/DhIxspQqoLL6/e8PXtDwBQu6AG0aXSxC44eAI6dJAqMjSqg969feSv3dx6QE+vhQKjobry8uolf21g0ApOTs4KjIbqqls3WZmTLn36+CowGqoPL38nu3Th91OVdeniAgeHzhAEAQUFBRCL1fHOO6MUHZbCNYmkvX///pg7dy6++OILDBkyBGfOnMHGjRthYWGh6NAUpmVLfUyfPgsAoJFxFWr/zqD5gnrGFYjz0qGtXXollxPoKLfhw0dCIrFETqEafrqlU2GdG9liHH+gBZFIhJCQqXxUnwoZMWIkxGJ1iB6KICoQwcioNfr27afosKgOXp5ozsrKWoGRUH0wNDTC2LET4eDQGRMnTuLtKipOLBajR4/S0TAGBq04Kq0JaNPGusLXpJo8PLzlr+3tHXgrEoAmk6mNHj0ao0ePVnQYSqVTJwf06eOLI0d+hWbKaRTYDyq9ceJ5MTT+fRZ7YOBoDiFSARoaGhg3biKWLVuMgyla8G1TACPtso862HW9NJnv1csHtrY1f3IAKV7r1sawt3fA+fMJAIAePTx40kXFtWplKH+trV3xiTZSLYMH+2Pw4JrPk0PKbcKED+Du7gULC0v+3jYBLz+fmzP/qz5nZ1eIxWKUlJSga1c3RYejFJrElXaq3KhRQVBXV4c4Lx1quaXPKFXPuAa1oqcwNjbhTPEqxNXVDfb2jigWRIhNKft87quPxUh6pAF1sTpGjQqqpAdSZt2793zpdQ8FRkL14eUrsSr+ZFWiJklLSwtdurjwwkUTpKWlXX0lUmpvvGGGVavWIiLiU/Tvz0mygSZ0pZ0qZmhohN69++Dw4UPQSE/CM30zqKeXTuowaNAwDotXISKRCP7+AUhKuoBjd7UwvP1T6Py7+Q7+m8R793qTByAqys9vAGxtO0BTUxNt27ZXdDhUjzgBHRFRw3r5eLapzS7eXFlaWsHSUtFRKA/+VTcDLyZYET9KgdqTTIjzH0IsFqNXL59qWpKycXZ2hURiiWclIsSllQ4FyykU4WxG6dC+AQOGKDI8qgM1NTXY2XVkwt6EvDiBxgkFiYgalp1dR0ilndC7dx9Fh0LUIHiZtRno0EEKExNTZGSkQ/P2KQCls2zynh/VIxKJ0KePL7Zt+wYnH2jiTYtC/J2ugRJBBBsbW7Rt207RIRLRvxYuXIq0tAewte2g6FCIiJo0sViMZctWKDoMogbDK+3NgEgkQufOXQAA4tz7AMDH1aiwFzPeXn6sjtxCEc5klF5x79nTU5FhEdErJBILuLh0VXQYREREpOKYtDcTUmmnMu/t7DoqKBKqKzMzc1haWuG5IMKFh+q4/Kh0wEzXrt0VHBkREREREdU3Ju3NRJs2Vq+85zMsVZmDQ+kzZQ+maKPouQj6+gbltjEREREREak+Ju3NRJs21vLnkEokltDT01NwRFQXdnalIydu5JReZe/QQcoZqomIiIiImiBORNdM6Orq4rPPViM5+SY6dXJUdDhUR23btn3lPSegIyIiIiJqipi0NyPW1m1hbd1W0WFQPTA3tyjzXiLhgyyJiIiIiJoiDo8nUkFaWlryZ0ADgEQiUWA0RERERETUUHilnUhFTZr0IU6c+D+YmZmjQweposMhIiIiIqIGIBIEQVB0EMoiMzMX/N8gIiIiIiKihiYSAcbGLautx+HxREREREREREqKSTsRERERERGRkmLSTkRERERERKSkmLQTERERERERKSkm7URERERERERKikk7ERERERERkZJi0k5ERERERESkpNQVHYAyEYkUHQERERERERE1BzXNP0WCIAgNGwoRERERERERvQ4OjyciIiIiIiJSUkzaiYiIiIiIiJQUk3YiIiIiIiIiJcWknYiIiIiIiEhJMWknIiIiIiIiUlJM2omIiIiIiIiUFJN2IiIiIiIiIiXFpJ2IiIiIiIhISTFpJyIiIiIiIlJSTNqJiIiIiIiIlBST9iZmx44d8PHxQefOneHv748zZ85UWjc1NRXz5s2Dj48PnJyc8NZbb+Hzzz9HYWFhI0ZMFfnuu+8waNAguLq6wtXVFSNHjsQff/xRZRsfHx9IpdIy/1asWNFIEVN10tLSMHPmTMhkMnTp0gVDhgzBhQsXqmyTkZGBWbNmwcPDA87Ozhg2bBgOHjzYSBHTy/Ly8rB06VK8+eabcHJyQmBgIBITE6tss2vXLgQFBcHV1RVSqRQ5OTnl6qxfvx6BgYHo0qULunXr1lDhN2t///03Jk2aBE9PT0ilUhw+fFi+rKioCFFRURg0aBCcnZ3h6emJ2bNnIy0trdp+lyxZAn9/fzg6OmLIkCFV1r19+zZcXFy4jetJVdsUAObMmVNufxgQEFBtv9V9H/fu3Vuu3xf/srKy6m39mpvqtueTJ08QEREBb29vODk5oV+/fvjuu++q7LOmx7hXrlzBmDFj4OTkBC8vL6xduxaCINT7OjYnGzZswPDhw+Hi4oKePXsiJCQEN2/eLFOnJvvHV12+fBkzZsxAr1695H8HW7ZsKVPnzJkzCAwMhEwmg5OTE/z8/LB58+b6XD2FUVd0AFR/YmNjERkZiYULF8LV1RXff/893nvvPcTExEAikZSrf/PmTQiCgIiICFhbW+Pq1auYP38+nj59ivDwcAWsAb1gZmaGmTNnwsrKCgCwf/9+hIaGYt++fejQoUOl7aZOnVrmwERXV7fBY6XqZWdnY9SoUZDJZPjqq69gZGSEO3fuQF9fv8p2s2fPRm5uLtavXw9DQ0McOHAAYWFhsLKygr29fSNFTwDw8ccf49q1a1i+fDlMTU3x008/Yfz48YiNjcUbb7xRYZunT5/Cy8sLXl5eWLlyZYV1ioqK4OfnB2dnZ+zZs6chV6HZys/Ph1Qqhb+/Pz788MMyywoKCpCUlITJkyejY8eOyMnJwbJlyzB58mTs3bu32r6HDx+OhIQEXLlypdI6RUVFmDFjBrp164b4+Pg6rw9VvU1f8PLyQmRkpPy9hoZGtf1W933s378/vLy8ypTNmTMHhYWFaN26dS3Xgl6obntGRkbi1KlTiIqKgoWFBU6cOIHFixfD1NQUb731VoV91uQYNy8vDxMmTIBMJsOePXuQnJyMOXPmQFdXFxMmTGjQdW7KTp8+jdGjR6Nz584oKSlBdHQ0Jk6ciJiYGPlxaU32j6+6cOECjIyMEBUVBXNzc5w7dw4LFiyAWCzGmDFjAJQe944ZMwZSqRQ6Ojo4e/YsFi5cCB0dHYwcObLB1rlRCNRkjBgxQliwYEGZMj8/P2HFihU17uOrr74SfHx86js0qgdubm7C7t27K13+5ptvCt9++23jBUQ1FhUVJYwaNarW7ZydnYV9+/aVKevevXuVfwdU/54+fSp06tRJOHbsWJnywYMHC6tWraq2fVxcnGBnZydkZ2dXWufHH38UunbtWtdQqRp2dnbCb7/9VmWdhIQEwc7OTrh7926N+vz888+FwYMHV7p8+fLlwsyZM7mNG0hF2zQ8PFyYPHnya/dZ022VlZUlODg4lPudptdX0fYcMGCAsHbt2jJlw4YNE6Kjo2vV96vHuDt27BC6du0qPHv2TF62YcMGwdPTU3j+/PlrRE8VycrKEuzs7ITTp0+XW1aT/WNVFi1aJAQFBVVZJzQ0VJg5c+Zr9a9MODy+iSgsLMTFixfh6elZptzDw6NWZ/Zzc3NhYGBQ3+FRHZSUlCAmJgb5+flwcXGpsu7XX38NmUyGIUOGYP369bzVQUkcPXoUjo6OmDp1Knr27ImhQ4di9+7d1bZzdXXFL7/8gsePH+P58+eIiYlBYWEhZDJZI0RNLxQXF6OkpARaWlplyrW1tXHu3DkFRUUNJS8vDyKRqNqRMDVx8uRJHDx4EAsXLqyHyKg2Tp8+jZ49e+Ltt9/Gxx9/3CDD1/fv3w9tbW34+fnVe9/0P66urjh69CjS0tIgCALi4uJw69atcse81Xn1GPeff/6Bm5sbNDU15WWenp5IT09HampqvcXf3OXm5gJAg+QXubm5aNWqVaXLk5KSEB8fj+7du9f7Zzc2Do9vIh49eoSSkpJyw7OMjY2RkZFRoz5SUlKwfft2zJkzpyFCpFq6cuUKAgMD8ezZM+jq6mLdunWwtbWttH5wcDDs7e2hr6+P8+fPY+XKlUhNTcXSpUsbMWqqyJ07d7Bz506MHz8ekyZNQmJiIpYsWQJNTU0MHTq00narV6/G9OnTIZPJoK6uDm1tbaxdu1Z+2wQ1jhYtWsDFxQVffPEF2rdvD2NjY/z8889ISEiAtbW1osOjevTs2TOsWLECAwcORIsWLerU16NHjzB37lxERUXVuS+qHW9vb/j5+UEikSA1NRX//e9/MXbsWOzdu7dMglZXP/74IwYOHAhtbe1665PK+/jjjzF//nx4e3tDXV0dIpEIS5YsqdUcERUd42ZmZsLCwqJMvRfH0ZmZmWjTpk39rEAzJggCIiMj0bVrV9jZ2dVr3/Hx8Th48CA2bNhQbpm3tzcePnyIkpISTJkyBe+88069frYiMGlvYkQiUZn3giBAJBJhwYIFOHDggLz81avvaWlpePfdd+Hn59ck/rCbgnbt2mH//v3IycnBr7/+ivDwcGzfvh1bt26tcFuOGzdOXtaxY0fo6+tj6tSpmDlzJgwNDRs7fHqJIAhwdHTEjBkzAAD29va4fv06du7ciaFDh+LLL78ss9N5MQ/F6tWrkZOTg82bN8PQ0BCHDx/GtGnTsGPHDkilUkWtTrO0fPlyzJs3D97e3hCLxbC3t8fAgQORlJRU6fYj1VJUVISwsDAIgoBFixbJy999912cPXsWACCRSBATE1Oj/ubPn4+BAwfCzc2tIcKlKvTv31/+2s7ODo6OjvDx8cHvv/8OX1/fao+JaiI+Ph7Xr1/HZ599Vi8xU+W2bduGf/75B+vXr4dEIsGZM2fk97S7u7vX6Rj31ePm6sqpdiIiInD16tVqJw58VXW/u9euXUNISAhCQkLg4eFRrv2OHTuQn5+PhIQErFy5EtbW1hg4cODrr4gSYNLeRBgaGkIsFiMzM7NMeVZWFoyNjTFt2jRMnDixwrZpaWkIDg6Gs7MzPvnkk8YIl2pAU1NTfhWvc+fOOH/+PLZu3VrltnyZs7MzgNKzy0zaFcvExAQ2NjZlytq3b49Dhw4BAAIDA9GvXz/5MlNTU/lVgZ9//lk++WDHjh1x5swZ7NixAxEREY23AgQrKyts374d+fn5yMvLg6mpKaZPnw5LS8sKRdOMhwAAC9dJREFUtx+plqKiIkyfPh2pqanYsmVLmSvjS5cuRUFBAQBAXb3mh01xcXE4evQovvnmGwClJ++eP38Oe3t7REREYMSIEfW7ElQpU1NTSCQSJCcnA0CN96NV+eGHH9CpUyc4OjrWQ4RUmYKCAkRHR2Pt2rXo3bs3gNJ94aVLl7Bp0ya4u7u/9jFuRaNRX9xGwYkF6+6TTz7B0aNHsX37dpiZmdWqbVW/u9evX8fYsWMREBCAkJCQCtu/GCUhlUqRmZmJNWvWMGkn5aCpqQkHBwecOHECffv2lZf/9ddf6NOnD1q3bl3hD9CLHzMHBwdERkZCTY3THCgrQRDkM9TWZGeSlJQEoDRhJMVydXXFrVu3ypQlJyfLh+W1atWq3D1ZT58+BYBy30mxWMzH0SiQrq4udHV1kZ2djePHj2PWrFkVbj9SHS8S9tu3b2Pr1q3lTnJW9nSA6uzatQslJSXy90eOHMFXX32F77///rX7pNfz6NEj3L9/X35Crab70co8efIEv/zyCz766KP6CpEqUVxcjKKionJXvl/eF77uMa6zszOio6NRWFgov23i+PHjMDU1haWlZQOtUdMnCAI++eQT/Pbbb9i2bdtr3WZQ2W/ktWvXMHbsWAwdOhRhYWE1jqeoqKjWMSgbJu1NyPjx4zF79mw4OjrCxcUFu3btwv379xEYGFhh/bS0NAQFBcHc3Bzh4eF4+PChfBkTPcVatWoVvL29YWZmhidPniA2NhanT5/G119/XWH9+Ph4JCQkQCaToUWLFjh//jwiIyPh4+PDYbpKYOzYsRg1ahS+/PJL9OvXD4mJidi9e3eVV8vbt28Pa2trLFiwAOHh4WjVqhUOHz6MEydOVHj/FjWsP//8E4IgoF27dkhJScHy5cvRrl07+Pv7V9omIyMDmZmZSElJAQBcvXoVenp6MDc3lyf59+7dQ3Z2Nu7du4eSkhJcunQJQOmVfT09vYZfsWbgyZMn8m0AlD6/+dKlSzAwMICpqSmmTp2KpKQkbNiwASUlJfIrbwYGBlXe/3z79m3k5+cjIyMDBQUF8m1nY2MDTU3NcqNrLly4ADU1tXq/r7M5qmqbGhgYYO3atfD19YWJiQnu3r2L6OhoGBoaVvp4sBdq+n2MjY1FSUkJBg0a1DAr2MxUtT0lEgm6d++OqKgoaGtrQyKR4O+//8b+/furnIOpJse4gwYNwrp16zB37lx88MEHuH37NjZs2IDQ0FAOj6+DxYsX4+eff8YXX3wBPT09+W9qy5Yt5fM/1GT/+Kpr164hODgYHh4eGD9+vLxfsVgMIyMjAKXD4s3NzdG+fXsAwNmzZ/HNN9/IHwmnykQCL9k0KTt27MCmTZuQnp4OOzs7zJ07t9L76fbu3Yu5c+dWuKyqZ85Sw5s3bx7i4uKQnp6Oli1bQiqV4r333qvwvh0AuHjxIhYvXoybN2+isLAQEokEAwYMwLvvvgsdHZ1Gjp4qcuzYMaxatQrJycmwtLTE+PHjERAQUGWb5ORkrFy5EmfPnkV+fj6srKwwYcKEKievo4YRGxuLVatW4cGDB2jVqhV8fX0RFhaGli1bVtpmzZo1WLt2bbnyyMhIebI/Z84c7Nu3r1ydrVu38ikB9eTUqVMIDg4uVz5s2DBMmTIFffr0qbBdddsgKCgIp0+fLld+5MiRCq/S7d27F8uWLcOZM2dqET1VpKptumjRIoSGhiIpKQm5ubkwMTGBTCbDtGnTYG5uXmW/Nf0+BgYGwsLCosbPl6aqVbU9P/30U2RkZGDVqlU4fvw4srOzIZFIMHLkSIwbN67S5Lqmx7hXrlxBREQEEhMTYWBggMDAQCbtdVTZnDsv7/tqsn98VWVtLCwscPToUQCl8x/s2rULqampEIvFsLKywjvvvIPAwECVH03MpJ2IiIiIiIhISan2KQciIiIiIiKiJoxJOxEREREREZGSYtJOREREREREpKSYtBMREREREREpKSbtREREREREREqKSTsRERERERGRkmLSTkRERERERKSkmLQTERGpgKCgICxdulTRYRAREVEjY9JOREREREREpKSYtBMREVGFCgsLa92mqKioASIhIiJqvpi0ExERqQhBELB8+XJ0794dHh4eWLNmjXzZvXv3MHnyZLi4uMDV1RXTpk1DZmamfPmcOXMQEhJSpr+lS5ciKChI/j4oKAgRERGIjIyETCbDhAkTqo1JKpVi586dmDx5MpydnbF+/XqUlJRg3rx58PHxgZOTE95++21s2bKlTLsX8WzatAmenp6QyWRYvHhxmaQ/PT0d77//PpycnODj44MDBw7Ax8cHmzdvltfJzc3F/Pnz0bNnT7i6uiI4OBiXL1+u8f8pERGRsmPSTkREpCL27dsHXV1d7N69G7NmzcK6detw4sQJCIKA0NBQZGdnY9u2bfj2229x584dhIWFvdZniMVi7Ny5E4sXL65RmzVr1qBPnz44cOAAhg8fjufPn8PMzAyrV69GTEwMQkNDER0djdjY2DLtTp06hZSUFGzZsgWffvop9u3bh3379smXh4eHIz09Hdu2bcOaNWuwe/duZGVlyZcLgoD3338fGRkZ2LhxI/bu3QsHBweMHTsWjx8/rvW6ExERKSN1RQdARERENSOVSjFlyhQAQNu2bbF9+3acPHkSAHDlyhUcOXIE5ubmAIDly5djwIABSExMhJOTU40/w9raGrNnz65VXAMHDsSIESPKlE2dOlX+uk2bNoiPj8fBgwfRv39/ebmBgQEWLFgAsVgMGxsb9OrVCydPnkRAQABu3LiBv/76C3v27EHnzp0BAEuWLIGvr6+8fVxcHK5evYqTJ09CU1MTQGmif/jwYRw6dAgjR46s1XoQEREpIybtREREKkIqlZZ5b2JigqysLNy4cQNmZmbyhB0AbG1toa+vj5s3b9YqaXd0dKx1XBW12blzJ3744Qfcu3cPz549Q1FRETp27Fimjq2tLcRicZn1uXr1KgDg1q1bUFdXh4ODg3y5tbU1DAwM5O8vXryI/Px8yGSyMv0WFBQgJSWl1utBRESkjJi0ExERqQh19bK7bZFIBEEQIAgCRCJRufqCIJSr+7Li4uJybXR0dGodl66ubpn3sbGxiIyMRHh4OFxcXKCnp4dNmzYhISGhRutTlZeXP3/+HCYmJti2bVu5ei1btqztahARESklJu1EREQqztbWFvfv38f9+/flV9uvX7+O3Nxc2NjYAACMjIxw7dq1Mu0uXboEDQ2Neo/n7NmzcHFxwejRo+Vltb3y3a5dOxQXFyMpKUl+Jf/27dvIycmR13FwcEBmZibEYjEsLS3rJ3giIiIlw4noiIiIVJy7uzukUilmzpyJixcvIjExEbNnz0b37t3l94P36NEDFy5cwP79+5GcnIzPP/+8XBJfX6ysrHDhwgX8+eefuHXrFlavXo3z58/Xqg8bGxu4u7tjwYIFSExMRFJSEubPnw9tbW35qAJ3d3c4OzsjNDQUf/75J1JTU3Hu3DlER0fX+vOIiIiUFZN2IiIiFScSibBu3Tro6+tjzJgxGDduHNq0aYPo6Gh5HS8vL4SEhCAqKgojRozAkydPMHTo0AaJZ9SoUfD19UVYWBgCAgLw+PFj/Oc//6l1P5999hlat26N0aNHY8qUKQgICICenh60tLQAlK73xo0b4ebmhnnz5sHPzw8zZszA3bt3YWxsXN+rRUREpBAiobqbx4iIiIiUwIMHD9CrVy9s3rwZPXv2VHQ4REREjYL3tBMREZFSOnnyJPLz82FnZ4eMjAxERUXBwsIC3bp1U3RoREREjYZJOxEREVXop59+wsKFCytcJpFIEBMT06CfX1xcjOjoaNy5cwd6enpwcXHBihUrGmTyPCIiImXF4fFERERUoby8PGRlZVW4TF1dHRYWFo0cERERUfPDpJ2IiIiIiIhISXH2eCIiIiIiIiIlxaSdiIiIiIiISEkxaSciIiIiIiJSUkzaiYiIiIiIiJQUk3YiIiIiIiIiJcWknYiIiIiIiEhJMWknIiIiIiIiUlJM2omIiIiIiIiU1P8DMkGzqzuOaK0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_fare = df_1day[df_1day.fare_amount<100].copy()\n",
    "\n",
    "def hour_range(hour):\n",
    "    for i in range(3,25,3):\n",
    "        if hour<i:\n",
    "            return '{}-{}'.format(i-3, i-1)\n",
    "\n",
    "df_fare['hour_range'] = df_fare.hour.apply(hour_range)\n",
    "plt.figure(figsize=(12, 3))\n",
    "sns.set_style('dark')\n",
    "sns.violinplot(data=df_fare, x='hour_range', y='fare_amount')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d52d9f0d0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_fare.groupby(by='pickup_date_hour')['VendorID'].count().plot(figsize=(12,3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特定の2日間に絞って乗車料金とタクシー乗車数の連動をプロット"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>VendorID</th>\n",
       "      <th>tpep_pickup_datetime</th>\n",
       "      <th>tpep_dropoff_datetime</th>\n",
       "      <th>passenger_count</th>\n",
       "      <th>trip_distance</th>\n",
       "      <th>RatecodeID</th>\n",
       "      <th>store_and_fwd_flag</th>\n",
       "      <th>PULocationID</th>\n",
       "      <th>DOLocationID</th>\n",
       "      <th>payment_type</th>\n",
       "      <th>...</th>\n",
       "      <th>extra</th>\n",
       "      <th>mta_tax</th>\n",
       "      <th>tip_amount</th>\n",
       "      <th>tolls_amount</th>\n",
       "      <th>improvement_surcharge</th>\n",
       "      <th>total_amount</th>\n",
       "      <th>congestion_surcharge</th>\n",
       "      <th>airport_fee</th>\n",
       "      <th>pickup_date_hour</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>68575</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 00:07:51</td>\n",
       "      <td>2021-08-02 00:28:53</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.22</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>234</td>\n",
       "      <td>49</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>24.30</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70087</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 00:09:40</td>\n",
       "      <td>2021-08-02 00:42:29</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.50</td>\n",
       "      <td>2.0</td>\n",
       "      <td>N</td>\n",
       "      <td>132</td>\n",
       "      <td>238</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>12.12</td>\n",
       "      <td>6.55</td>\n",
       "      <td>0.3</td>\n",
       "      <td>72.72</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.25</td>\n",
       "      <td>2021-08-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70270</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 00:29:32</td>\n",
       "      <td>2021-08-02 00:38:14</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.62</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>114</td>\n",
       "      <td>246</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>11.80</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69723</th>\n",
       "      <td>2</td>\n",
       "      <td>2021-08-02 00:09:47</td>\n",
       "      <td>2021-08-02 00:16:51</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.99</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>170</td>\n",
       "      <td>263</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>5.32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>18.62</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69539</th>\n",
       "      <td>1</td>\n",
       "      <td>2021-08-02 00:31:53</td>\n",
       "      <td>2021-08-02 00:42:49</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>N</td>\n",
       "      <td>186</td>\n",
       "      <td>143</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.85</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.3</td>\n",
       "      <td>17.15</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2021-08-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
       "68575         2  2021-08-02 00:07:51   2021-08-02 00:28:53              1.0   \n",
       "70087         2  2021-08-02 00:09:40   2021-08-02 00:42:29              1.0   \n",
       "70270         2  2021-08-02 00:29:32   2021-08-02 00:38:14              1.0   \n",
       "69723         2  2021-08-02 00:09:47   2021-08-02 00:16:51              1.0   \n",
       "69539         1  2021-08-02 00:31:53   2021-08-02 00:42:49              1.0   \n",
       "\n",
       "       trip_distance  RatecodeID store_and_fwd_flag  PULocationID  \\\n",
       "68575           6.22         1.0                  N           234   \n",
       "70087          20.50         2.0                  N           132   \n",
       "70270           1.62         1.0                  N           114   \n",
       "69723           2.99         1.0                  N           170   \n",
       "69539           2.50         1.0                  N           186   \n",
       "\n",
       "       DOLocationID  payment_type  ...  extra  mta_tax  tip_amount  \\\n",
       "68575            49             2  ...    0.5      0.5        0.00   \n",
       "70087           238             1  ...    0.0      0.5       12.12   \n",
       "70270           246             2  ...    0.5      0.5        0.00   \n",
       "69723           263             1  ...    0.5      0.5        5.32   \n",
       "69539           143             1  ...    3.0      0.5        2.85   \n",
       "\n",
       "       tolls_amount  improvement_surcharge  total_amount  \\\n",
       "68575          0.00                    0.3         24.30   \n",
       "70087          6.55                    0.3         72.72   \n",
       "70270          0.00                    0.3         11.80   \n",
       "69723          0.00                    0.3         18.62   \n",
       "69539          0.00                    0.3         17.15   \n",
       "\n",
       "       congestion_surcharge  airport_fee  pickup_date_hour hour  \n",
       "68575                   2.5         0.00        2021-08-02    0  \n",
       "70087                   0.0         1.25        2021-08-02    0  \n",
       "70270                   2.5         0.00        2021-08-02    0  \n",
       "69723                   2.5         0.00        2021-08-02    0  \n",
       "69539                   2.5         0.00        2021-08-02    0  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2days = df_raw[('2021-8-02' <= df_raw.tpep_pickup_datetime) & (df_raw.tpep_pickup_datetime < '2021-08-04')].sort_values(by='pickup_date_hour').copy()\n",
    "df_2days.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d55634cd0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_fare = df_2days[df_2days.fare_amount<100].copy()\n",
    "\n",
    "def hour_range(hour):\n",
    "    for i in range(3,25,3):\n",
    "        if hour<i:\n",
    "            return '{}-{}'.format(i-3, i-1)\n",
    "\n",
    "df_fare['hour_range'] = df_fare.hour.apply(hour_range)\n",
    "df_fare['date'] = df_fare.pickup_date_hour.dt.date\n",
    "plt.figure(figsize=(12, 3))\n",
    "sns.set_style('dark')\n",
    "sns.violinplot(data=df_fare, x='hour_range', y='fare_amount', hue='date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f4d2856a690>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_count = pd.DataFrame()\n",
    "g = df_fare.groupby(by='pickup_date_hour')\n",
    "df_count['pickup_count'] = g['VendorID'].count()\n",
    "df_count['hour'] = df_count.index.hour\n",
    "df_count['date'] = df_count.index.date\n",
    "\n",
    "plt.figure(figsize=(12, 4))\n",
    "sns.lineplot(data=df_count, x='hour', y='pickup_count', hue='date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "instance_type": "ml.m5.large",
  "kernelspec": {
   "display_name": "Python 3 (Data Science)",
   "language": "python",
   "name": "python3__SAGEMAKER_INTERNAL__arn:aws:sagemaker:ap-northeast-1:102112518831:image/datascience-1.0"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}