case-study-bellabeat-using-python.ipynb

{
 "cells": [
  {
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"
    }
   },
   "cell_type": "markdown",
   "id": "expressed-converter",
   "metadata": {
    "_cell_guid": "feeabaef-2405-4000-912d-19ab6a3018f8",
    "_uuid": "fea909ec-c82f-4971-9070-fcc02961a32c",
    "execution": {
     "iopub.execute_input": "2021-05-22T15:44:51.57837Z",
     "iopub.status.busy": "2021-05-22T15:44:51.577765Z",
     "iopub.status.idle": "2021-05-22T15:44:51.592943Z",
     "shell.execute_reply": "2021-05-22T15:44:51.591483Z",
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    },
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# INTRODUCTION\n",
    "\n",
    "This case study is the Capstone Project of **Google Data Analytics Professional Certificate**. The **6 steps of Data Analysis** is used to present this analysis.\n",
    "\n",
    "\n",
    "Title: **Bellabeat Case Study**\n",
    "\n",
    "Author: Katie Huang\n",
    "\n",
    "Date: 2 June 2021\n",
    "\n",
    "***\n",
    "\n",
    "![Bellabeat.png](attachment:76850c32-b0d0-499d-8d78-7198daeed9b8.png)\n",
    "\n",
    "## Bellabeat: How Can A Wellness Technology Company Play It Smart?\n",
    "\n",
    "# STEP 1: ASK\n",
    "\n",
    "#### 1.0 Background\n",
    "\n",
    "Bellabeat is a high-tech manufacturer of beautifully-designed health-focused smart products for women since 2013. Inspiring and empowering women with knowledge about their own health and habits, Bellabeat has grown rapidly and quickly positioned itself as a tech-driven wellness company for females.\n",
    "\n",
    "The co-founder and Chief Creative Officer, Urška Sršen is confident that an analysis of non-Bellebeat consumer data (ie. FitBit fitness tracker usage data) would reveal more opportunities for growth.\n",
    "\n",
    "#### 1.2 Business Task:\n",
    "\n",
    "```\n",
    "Analyze FitBit Fitness Tracker Data to gain insights into how consumers are using the FitBit app and discover trends and insights for Bellabeat marketing strategy.\n",
    "```\n",
    "\n",
    "\n",
    "#### 1.3 Business Objectives:  \n",
    "1. What are the trends identified?\n",
    "2. How could these trends apply to Bellabeat customers?\n",
    "3. How could these trends help influence Bellabeat marketing strategy?\n",
    "\n",
    "\n",
    "\n",
    "#### 1.4 Deliverables:\n",
    "1. A clear summary of the business task\n",
    "2. A description of all data sources used\n",
    "3. Documentation of any cleaning or manipulation of data\n",
    "4. A summary of analysis\n",
    "5. Supporting visualizations and key findings\n",
    "6. High-level content recommendations based on the analysis\n",
    "\n",
    "\n",
    "#### 1.5 Key Stakeholders:\n",
    "1. Urška Sršen: Bellabeat’s cofounder and Chief Creative Officer\n",
    "2. Sando Mur: Mathematician, Bellabeat’s cofounder and key member of the Bellabeat executive team\n",
    "3. Bellabeat marketing analytics team: A team of data analysts guiding Bellabeat's marketing strategy.\n",
    "\n",
    "\n",
    "***\n",
    "\n",
    "\n",
    "# STEP 2: PREPARE\n",
    "\n",
    "\n",
    "#### 2.1 Information on Data Source:\n",
    "1. The data is publicly available on [Kaggle: FitBit Fitness Tracker Data](https://www.kaggle.com/arashnic/fitbit) and stored in 18 csv files. \n",
    "2. Generated by respondents from a distributed survey via Amazon Mechanical Turk between 12 March 2016 to 12 May 2016.\n",
    "3. 30 FitBit users who consented to the submission of personal tracker data.\n",
    "4. Data collected includes (1) physical activity recorded in minutes, (2) heart rate, (3) sleep monitoring, (4) daily activity and (5) steps.\n",
    "\n",
    "    \n",
    "#### 2.2 Limitations of Data Set:\n",
    "1. Data collected from year 2016. Users' daily activity, fitness and sleeping habits, diet and food consumption may have changed since then, hence data may not be timely or relevant.\n",
    "2. Sample size of 30 female FitBit users is not representative of the entire female population. \n",
    "3. As data is collected in a survey, hence unable to ascertain the integrity or accuracy of data.\n",
    "\n",
    "\n",
    "#### 2.3 Is Data ROCCC?\n",
    "\n",
    "A good data source is ROCCC which stands for **R**eliable, **O**riginal, **C**omprehensive, **C**urrent, and **C**ited.\n",
    "1. Reliable - LOW - Not reliable as it only has 30 respondents\n",
    "2. Original - LOW - Third party provider (Amazon Mechanical Turk)\n",
    "3. Comprehensive - MED - Parameters match most of Bellabeat's products' parameters\n",
    "4. Current - LOW - Data is 5 years old and is not relevant\n",
    "5. Cited - LOW - Data collected from third party, hence unknown\n",
    "\n",
    "Overall, the dataset is considered bad quality data and it is not recommended to produce business recommendations based on this data.\n",
    "\n",
    "\n",
    "#### 2.4 Data Selection:\n",
    "The following file is selected and copied for analysis. \n",
    "```\n",
    "    • dailyActivity_merged.csv\n",
    "```\n",
    "\n",
    "\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "infectious-nicholas",
   "metadata": {
    "_cell_guid": "38859931-1e88-4365-9514-3ba368222cb5",
    "_uuid": "07d219e0-c65f-478c-9734-cb6cdc62a992",
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     "start_time": "2022-10-14T21:40:31.431874",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# STEP 3: PROCESS\n",
    "\n",
    "We are using Python to prepare and process the data.\n",
    "\n",
    "\n",
    "#### 3.1 Preparing the Environment\n",
    "\n",
    "The ```numPy, pandas, matplotlib, datetime``` packages are installed and aliased for easy reading."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "violent-taiwan",
   "metadata": {
    "_cell_guid": "53bedab9-16e6-459a-b3ce-e0c6449b246f",
    "_uuid": "27e4f97b-1e17-462c-9cfe-d044b42cc1a7",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:31.520278Z",
     "iopub.status.busy": "2022-10-14T21:40:31.518474Z",
     "iopub.status.idle": "2022-10-14T21:40:31.527906Z",
     "shell.execute_reply": "2022-10-14T21:40:31.528379Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.624347Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# import packages and alias\n",
    "import numpy as np # data arrays\n",
    "import pandas as pd # data structure and data analysis\n",
    "import matplotlib as plt # data visualization\n",
    "import datetime as dt # date time"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "standard-capital",
   "metadata": {
    "_cell_guid": "41fc2d38-ee2b-4093-af09-c9d5b40b3ad1",
    "_uuid": "ac279df1-646a-43ba-9f30-36fe2b154e66",
    "papermill": {
     "duration": 0.026952,
     "end_time": "2022-10-14T21:40:31.583957",
     "exception": false,
     "start_time": "2022-10-14T21:40:31.557005",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### 3.2 Importing data set"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "imported-recruitment",
   "metadata": {
    "papermill": {
     "duration": 0.027016,
     "end_time": "2022-10-14T21:40:31.638228",
     "exception": false,
     "start_time": "2022-10-14T21:40:31.611212",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Reading in the selected file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "swedish-supervision",
   "metadata": {
    "_cell_guid": "7b95c099-c3e8-46f8-b60b-cbfaac7c3cd2",
    "_uuid": "c67360eb-49d0-4d8c-b436-ae473e3c7623",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:31.697296Z",
     "iopub.status.busy": "2022-10-14T21:40:31.696371Z",
     "iopub.status.idle": "2022-10-14T21:40:31.724364Z",
     "shell.execute_reply": "2022-10-14T21:40:31.724917Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.638259Z"
    },
    "jupyter": {
     "outputs_hidden": false
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     "end_time": "2022-10-14T21:40:31.725106",
     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# read_csv function to read the required CSV file\n",
    "daily_activity = pd.read_csv(\"../input/fitbit/Fitabase Data 4.12.16-5.12.16/dailyActivity_merged.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "compound-acquisition",
   "metadata": {
    "_cell_guid": "7d80d7cf-e7f6-4951-9a8d-ec20258a2f2f",
    "_uuid": "23415393-9f2d-48ff-9cf7-9b56d0b9d2fc",
    "papermill": {
     "duration": 0.027373,
     "end_time": "2022-10-14T21:40:31.780251",
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     "start_time": "2022-10-14T21:40:31.752878",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### 3.3 Data cleaning and manipulation\n",
    "\n",
    "##### Steps\n",
    "\n",
    "1. Observe and familiarize with data\n",
    "\n",
    "2. Check for null or missing values\n",
    "\n",
    "3. Perform sanity check of data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "surprised-bloom",
   "metadata": {
    "papermill": {
     "duration": 0.027187,
     "end_time": "2022-10-14T21:40:31.835367",
     "exception": false,
     "start_time": "2022-10-14T21:40:31.808180",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Previewing using head function to show the first 10 rows of daily_activity to familiarise with the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "freelance-third",
   "metadata": {
    "_cell_guid": "4126117c-5d8d-47f5-be26-ad0ef695ec29",
    "_uuid": "941abfee-ce91-435a-9a7f-22e129b45d30",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:31.893415Z",
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     "shell.execute_reply": "2022-10-14T21:40:31.927662Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.698951Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.065342,
     "end_time": "2022-10-14T21:40:31.928331",
     "exception": false,
     "start_time": "2022-10-14T21:40:31.862989",
     "status": "completed"
    },
    "tags": []
   },
   "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>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>Calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/12/2016</td>\n",
       "      <td>13162</td>\n",
       "      <td>8.50</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0.55</td>\n",
       "      <td>6.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "      <td>13</td>\n",
       "      <td>328</td>\n",
       "      <td>728</td>\n",
       "      <td>1985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/13/2016</td>\n",
       "      <td>10735</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.69</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21</td>\n",
       "      <td>19</td>\n",
       "      <td>217</td>\n",
       "      <td>776</td>\n",
       "      <td>1797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/14/2016</td>\n",
       "      <td>10460</td>\n",
       "      <td>6.74</td>\n",
       "      <td>6.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.44</td>\n",
       "      <td>0.40</td>\n",
       "      <td>3.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "      <td>11</td>\n",
       "      <td>181</td>\n",
       "      <td>1218</td>\n",
       "      <td>1776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/15/2016</td>\n",
       "      <td>9762</td>\n",
       "      <td>6.28</td>\n",
       "      <td>6.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>2.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29</td>\n",
       "      <td>34</td>\n",
       "      <td>209</td>\n",
       "      <td>726</td>\n",
       "      <td>1745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/16/2016</td>\n",
       "      <td>12669</td>\n",
       "      <td>8.16</td>\n",
       "      <td>8.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.41</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10</td>\n",
       "      <td>221</td>\n",
       "      <td>773</td>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/17/2016</td>\n",
       "      <td>9705</td>\n",
       "      <td>6.48</td>\n",
       "      <td>6.48</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.19</td>\n",
       "      <td>0.78</td>\n",
       "      <td>2.51</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38</td>\n",
       "      <td>20</td>\n",
       "      <td>164</td>\n",
       "      <td>539</td>\n",
       "      <td>1728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/18/2016</td>\n",
       "      <td>13019</td>\n",
       "      <td>8.59</td>\n",
       "      <td>8.59</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.25</td>\n",
       "      <td>0.64</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42</td>\n",
       "      <td>16</td>\n",
       "      <td>233</td>\n",
       "      <td>1149</td>\n",
       "      <td>1921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/19/2016</td>\n",
       "      <td>15506</td>\n",
       "      <td>9.88</td>\n",
       "      <td>9.88</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.53</td>\n",
       "      <td>1.32</td>\n",
       "      <td>5.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>50</td>\n",
       "      <td>31</td>\n",
       "      <td>264</td>\n",
       "      <td>775</td>\n",
       "      <td>2035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/20/2016</td>\n",
       "      <td>10544</td>\n",
       "      <td>6.68</td>\n",
       "      <td>6.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.96</td>\n",
       "      <td>0.48</td>\n",
       "      <td>4.24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28</td>\n",
       "      <td>12</td>\n",
       "      <td>205</td>\n",
       "      <td>818</td>\n",
       "      <td>1786</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>4/21/2016</td>\n",
       "      <td>9819</td>\n",
       "      <td>6.34</td>\n",
       "      <td>6.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.34</td>\n",
       "      <td>0.35</td>\n",
       "      <td>4.65</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19</td>\n",
       "      <td>8</td>\n",
       "      <td>211</td>\n",
       "      <td>838</td>\n",
       "      <td>1775</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Id ActivityDate  TotalSteps  TotalDistance  TrackerDistance  \\\n",
       "0  1503960366    4/12/2016       13162           8.50             8.50   \n",
       "1  1503960366    4/13/2016       10735           6.97             6.97   \n",
       "2  1503960366    4/14/2016       10460           6.74             6.74   \n",
       "3  1503960366    4/15/2016        9762           6.28             6.28   \n",
       "4  1503960366    4/16/2016       12669           8.16             8.16   \n",
       "5  1503960366    4/17/2016        9705           6.48             6.48   \n",
       "6  1503960366    4/18/2016       13019           8.59             8.59   \n",
       "7  1503960366    4/19/2016       15506           9.88             9.88   \n",
       "8  1503960366    4/20/2016       10544           6.68             6.68   \n",
       "9  1503960366    4/21/2016        9819           6.34             6.34   \n",
       "\n",
       "   LoggedActivitiesDistance  VeryActiveDistance  ModeratelyActiveDistance  \\\n",
       "0                       0.0                1.88                      0.55   \n",
       "1                       0.0                1.57                      0.69   \n",
       "2                       0.0                2.44                      0.40   \n",
       "3                       0.0                2.14                      1.26   \n",
       "4                       0.0                2.71                      0.41   \n",
       "5                       0.0                3.19                      0.78   \n",
       "6                       0.0                3.25                      0.64   \n",
       "7                       0.0                3.53                      1.32   \n",
       "8                       0.0                1.96                      0.48   \n",
       "9                       0.0                1.34                      0.35   \n",
       "\n",
       "   LightActiveDistance  SedentaryActiveDistance  VeryActiveMinutes  \\\n",
       "0                 6.06                      0.0                 25   \n",
       "1                 4.71                      0.0                 21   \n",
       "2                 3.91                      0.0                 30   \n",
       "3                 2.83                      0.0                 29   \n",
       "4                 5.04                      0.0                 36   \n",
       "5                 2.51                      0.0                 38   \n",
       "6                 4.71                      0.0                 42   \n",
       "7                 5.03                      0.0                 50   \n",
       "8                 4.24                      0.0                 28   \n",
       "9                 4.65                      0.0                 19   \n",
       "\n",
       "   FairlyActiveMinutes  LightlyActiveMinutes  SedentaryMinutes  Calories  \n",
       "0                   13                   328               728      1985  \n",
       "1                   19                   217               776      1797  \n",
       "2                   11                   181              1218      1776  \n",
       "3                   34                   209               726      1745  \n",
       "4                   10                   221               773      1863  \n",
       "5                   20                   164               539      1728  \n",
       "6                   16                   233              1149      1921  \n",
       "7                   31                   264               775      2035  \n",
       "8                   12                   205               818      1786  \n",
       "9                    8                   211               838      1775  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preview first 10 rows with all columns\n",
    "daily_activity.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "turkish-approval",
   "metadata": {
    "papermill": {
     "duration": 0.027689,
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "Then, finding out whether there is any null or missing values in daily_activity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "chief-license",
   "metadata": {
    "_cell_guid": "af5c7249-a592-4e10-bacd-4188ce32fabc",
    "_uuid": "29266e28-766a-41e4-bd3f-1c945baea3bb",
    "collapsed": false,
    "execution": {
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     "status": "completed"
    },
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id                          0\n",
       "ActivityDate                0\n",
       "TotalSteps                  0\n",
       "TotalDistance               0\n",
       "TrackerDistance             0\n",
       "LoggedActivitiesDistance    0\n",
       "VeryActiveDistance          0\n",
       "ModeratelyActiveDistance    0\n",
       "LightActiveDistance         0\n",
       "SedentaryActiveDistance     0\n",
       "VeryActiveMinutes           0\n",
       "FairlyActiveMinutes         0\n",
       "LightlyActiveMinutes        0\n",
       "SedentaryMinutes            0\n",
       "Calories                    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# obtain the # of missing data points per column\n",
    "missing_values_count = daily_activity.isnull().sum()\n",
    "\n",
    "# look at the # of missing points in all columns\n",
    "missing_values_count[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "commercial-pixel",
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    },
    "tags": []
   },
   "source": [
    "Finding out the basic information of daily_activity:\n",
    "* no. of rows and columns\n",
    "* name of columns\n",
    "* type of value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "novel-oliver",
   "metadata": {
    "_cell_guid": "72b6f724-a60c-4e0d-b627-e1bfdc7ed820",
    "_uuid": "a611da02-43f1-4e0c-ab2a-1f1a648a329d",
    "collapsed": false,
    "execution": {
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     "iopub.status.idle": "2022-10-14T21:40:32.187298Z",
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 940 entries, 0 to 939\n",
      "Data columns (total 15 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Id                        940 non-null    int64  \n",
      " 1   ActivityDate              940 non-null    object \n",
      " 2   TotalSteps                940 non-null    int64  \n",
      " 3   TotalDistance             940 non-null    float64\n",
      " 4   TrackerDistance           940 non-null    float64\n",
      " 5   LoggedActivitiesDistance  940 non-null    float64\n",
      " 6   VeryActiveDistance        940 non-null    float64\n",
      " 7   ModeratelyActiveDistance  940 non-null    float64\n",
      " 8   LightActiveDistance       940 non-null    float64\n",
      " 9   SedentaryActiveDistance   940 non-null    float64\n",
      " 10  VeryActiveMinutes         940 non-null    int64  \n",
      " 11  FairlyActiveMinutes       940 non-null    int64  \n",
      " 12  LightlyActiveMinutes      940 non-null    int64  \n",
      " 13  SedentaryMinutes          940 non-null    int64  \n",
      " 14  Calories                  940 non-null    int64  \n",
      "dtypes: float64(7), int64(7), object(1)\n",
      "memory usage: 110.3+ KB\n"
     ]
    }
   ],
   "source": [
    "# show basic information of data\n",
    "daily_activity.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "respiratory-deposit",
   "metadata": {
    "papermill": {
     "duration": 0.028541,
     "end_time": "2022-10-14T21:40:32.245803",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.217262",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Counting the unique ID and to confirm whether data set has 30 IDs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "banner-footage",
   "metadata": {
    "_cell_guid": "8eb47be2-82ac-414f-8366-c998f31a00c6",
    "_uuid": "254b3971-3932-467c-a82f-68f5800c5b7b",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:32.309120Z",
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     "iopub.status.idle": "2022-10-14T21:40:32.316593Z",
     "shell.execute_reply": "2022-10-14T21:40:32.315743Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.781274Z"
    },
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    },
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     "end_time": "2022-10-14T21:40:32.316797",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.275817",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# of unique Id: 33\n"
     ]
    }
   ],
   "source": [
    "# count distinct value of \"Id\"\n",
    "unique_id = len(pd.unique(daily_activity[\"Id\"]))\n",
    "  \n",
    "print(\"# of unique Id: \" + str(unique_id))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "spoken-sailing",
   "metadata": {
    "_cell_guid": "8af44964-74a0-4d17-88e9-ec09bcec6277",
    "_uuid": "ba96fa39-7a49-43d3-a056-9e6d7c4da0be",
    "papermill": {
     "duration": 0.02918,
     "end_time": "2022-10-14T21:40:32.376304",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.347124",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "From the above observation, noted that\n",
    "\n",
    "1. There is no typo, Null or missing values.\n",
    "\n",
    "2. Data frame has 940 rows and 15 columns. \n",
    "\n",
    "3. *ActivityDate* is wrongly classified as ```object``` dtype and has to be converted to ```datetime64``` dtype.\n",
    "\n",
    "4. There are 33 unique IDs, instead of 30 unique IDs as expected from 30 fitness tracker users."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "facial-methodology",
   "metadata": {
    "_cell_guid": "220e6c03-37de-42e4-ac9b-47ade59e2af6",
    "_uuid": "8916b38a-020a-476a-a3b8-dcff57614da0",
    "papermill": {
     "duration": 0.029399,
     "end_time": "2022-10-14T21:40:32.435720",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.406321",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "The following data manipulation is performed:\n",
    "\n",
    "1. Convert *ActivityDate* to ```datatime64``` dtype.\n",
    "\n",
    "2. Convert format of *ActivityDate* to ```yyyy-mm-dd```.\n",
    "\n",
    "3. Create new column *DayOfTheWeek* by separating the date into day of the week for further analysis.\n",
    "\n",
    "4. Create new column *TotalMins* being the sum of *VeryActiveMinutes*, *FairlyActiveMinutes*, *LightlyActiveMinutes* and *SedentaryMinutes*.\n",
    "\n",
    "5. Create new column *TotalHours* by converting new column in #4 to number of hours.\n",
    "\n",
    "6. Rearrange and rename columns."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "recorded-idaho",
   "metadata": {
    "papermill": {
     "duration": 0.029117,
     "end_time": "2022-10-14T21:40:32.494022",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.464905",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Converting *ActivityDate* from ```object``` to ```datatime64``` dtype and converting format of *ActivityDate* to ```yyyy-mm-dd```. Then, printing head to confirm whether it has been updated to ```datatime64``` dtype and dates to ```yyyy-mm-dd```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "welcome-stamp",
   "metadata": {
    "_cell_guid": "10e0ae12-c842-4406-919d-ca947104d771",
    "_uuid": "29173d13-4135-4e6c-a37c-b833567073f7",
    "collapsed": false,
    "execution": {
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     "shell.execute_reply": "2022-10-14T21:40:32.591733Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.78926Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
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     "duration": 0.067846,
     "end_time": "2022-10-14T21:40:32.591999",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.524153",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 940 entries, 0 to 939\n",
      "Data columns (total 15 columns):\n",
      " #   Column                    Non-Null Count  Dtype         \n",
      "---  ------                    --------------  -----         \n",
      " 0   Id                        940 non-null    int64         \n",
      " 1   ActivityDate              940 non-null    datetime64[ns]\n",
      " 2   TotalSteps                940 non-null    int64         \n",
      " 3   TotalDistance             940 non-null    float64       \n",
      " 4   TrackerDistance           940 non-null    float64       \n",
      " 5   LoggedActivitiesDistance  940 non-null    float64       \n",
      " 6   VeryActiveDistance        940 non-null    float64       \n",
      " 7   ModeratelyActiveDistance  940 non-null    float64       \n",
      " 8   LightActiveDistance       940 non-null    float64       \n",
      " 9   SedentaryActiveDistance   940 non-null    float64       \n",
      " 10  VeryActiveMinutes         940 non-null    int64         \n",
      " 11  FairlyActiveMinutes       940 non-null    int64         \n",
      " 12  LightlyActiveMinutes      940 non-null    int64         \n",
      " 13  SedentaryMinutes          940 non-null    int64         \n",
      " 14  Calories                  940 non-null    int64         \n",
      "dtypes: datetime64[ns](1), float64(7), int64(7)\n",
      "memory usage: 110.3 KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0   2016-04-12\n",
       "1   2016-04-13\n",
       "2   2016-04-14\n",
       "3   2016-04-15\n",
       "4   2016-04-16\n",
       "Name: ActivityDate, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert \"ActivityDate\" to datatime64 dtype and format to yyyy-mm-dd\n",
    "daily_activity[\"ActivityDate\"] = pd.to_datetime(daily_activity[\"ActivityDate\"], format=\"%m/%d/%Y\")\n",
    "\n",
    "# re-print information to confirm\n",
    "daily_activity.info()\n",
    "\n",
    "# print the first 5 rows of \"ActivityDate\" to confirm\n",
    "daily_activity[\"ActivityDate\"].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "specialized-vintage",
   "metadata": {
    "papermill": {
     "duration": 0.033334,
     "end_time": "2022-10-14T21:40:32.660857",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.627523",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Creating new list with rearranged column names and renaming ```daily_activity``` to a shorter name ```df_activity```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "entertaining-genius",
   "metadata": {
    "_cell_guid": "24767d8e-4b12-4da5-8534-46e48373a946",
    "_uuid": "4032a725-60b2-4432-a496-8f89ca67e2e7",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:32.726026Z",
     "iopub.status.busy": "2022-10-14T21:40:32.725336Z",
     "iopub.status.idle": "2022-10-14T21:40:32.743317Z",
     "shell.execute_reply": "2022-10-14T21:40:32.743964Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.822647Z"
    },
    "jupyter": {
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    },
    "papermill": {
     "duration": 0.054221,
     "end_time": "2022-10-14T21:40:32.744136",
     "exception": false,
     "start_time": "2022-10-14T21:40:32.689915",
     "status": "completed"
    },
    "tags": []
   },
   "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>Id</th>\n",
       "      <th>ActivityDate</th>\n",
       "      <th>DayOfTheWeek</th>\n",
       "      <th>TotalSteps</th>\n",
       "      <th>TotalDistance</th>\n",
       "      <th>TrackerDistance</th>\n",
       "      <th>LoggedActivitiesDistance</th>\n",
       "      <th>VeryActiveDistance</th>\n",
       "      <th>ModeratelyActiveDistance</th>\n",
       "      <th>LightActiveDistance</th>\n",
       "      <th>SedentaryActiveDistance</th>\n",
       "      <th>VeryActiveMinutes</th>\n",
       "      <th>FairlyActiveMinutes</th>\n",
       "      <th>LightlyActiveMinutes</th>\n",
       "      <th>SedentaryMinutes</th>\n",
       "      <th>TotalExerciseMinutes</th>\n",
       "      <th>TotalExerciseHours</th>\n",
       "      <th>Calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-12</td>\n",
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       "      <td>13162</td>\n",
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       "      <td>8.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0.55</td>\n",
       "      <td>6.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "      <td>13</td>\n",
       "      <td>328</td>\n",
       "      <td>728</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10735</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.69</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21</td>\n",
       "      <td>19</td>\n",
       "      <td>217</td>\n",
       "      <td>776</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10460</td>\n",
       "      <td>6.74</td>\n",
       "      <td>6.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.44</td>\n",
       "      <td>0.40</td>\n",
       "      <td>3.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "      <td>11</td>\n",
       "      <td>181</td>\n",
       "      <td>1218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-15</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9762</td>\n",
       "      <td>6.28</td>\n",
       "      <td>6.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>2.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29</td>\n",
       "      <td>34</td>\n",
       "      <td>209</td>\n",
       "      <td>726</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12669</td>\n",
       "      <td>8.16</td>\n",
       "      <td>8.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.41</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10</td>\n",
       "      <td>221</td>\n",
       "      <td>773</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Id ActivityDate  DayOfTheWeek  TotalSteps  TotalDistance  \\\n",
       "0  1503960366   2016-04-12           NaN       13162           8.50   \n",
       "1  1503960366   2016-04-13           NaN       10735           6.97   \n",
       "2  1503960366   2016-04-14           NaN       10460           6.74   \n",
       "3  1503960366   2016-04-15           NaN        9762           6.28   \n",
       "4  1503960366   2016-04-16           NaN       12669           8.16   \n",
       "\n",
       "   TrackerDistance  LoggedActivitiesDistance  VeryActiveDistance  \\\n",
       "0             8.50                       0.0                1.88   \n",
       "1             6.97                       0.0                1.57   \n",
       "2             6.74                       0.0                2.44   \n",
       "3             6.28                       0.0                2.14   \n",
       "4             8.16                       0.0                2.71   \n",
       "\n",
       "   ModeratelyActiveDistance  LightActiveDistance  SedentaryActiveDistance  \\\n",
       "0                      0.55                 6.06                      0.0   \n",
       "1                      0.69                 4.71                      0.0   \n",
       "2                      0.40                 3.91                      0.0   \n",
       "3                      1.26                 2.83                      0.0   \n",
       "4                      0.41                 5.04                      0.0   \n",
       "\n",
       "   VeryActiveMinutes  FairlyActiveMinutes  LightlyActiveMinutes  \\\n",
       "0                 25                   13                   328   \n",
       "1                 21                   19                   217   \n",
       "2                 30                   11                   181   \n",
       "3                 29                   34                   209   \n",
       "4                 36                   10                   221   \n",
       "\n",
       "   SedentaryMinutes  TotalExerciseMinutes  TotalExerciseHours  Calories  \n",
       "0               728                   NaN                 NaN      1985  \n",
       "1               776                   NaN                 NaN      1797  \n",
       "2              1218                   NaN                 NaN      1776  \n",
       "3               726                   NaN                 NaN      1745  \n",
       "4               773                   NaN                 NaN      1863  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#r create new list of rearranged columns\n",
    "new_cols = ['Id', 'ActivityDate', 'DayOfTheWeek', 'TotalSteps', 'TotalDistance', 'TrackerDistance', 'LoggedActivitiesDistance', 'VeryActiveDistance', 'ModeratelyActiveDistance', 'LightActiveDistance', 'SedentaryActiveDistance', 'VeryActiveMinutes', 'FairlyActiveMinutes', 'LightlyActiveMinutes', 'SedentaryMinutes', 'TotalExerciseMinutes', 'TotalExerciseHours', 'Calories']\n",
    "\n",
    "# reindex function to rearrange columns based on \"new_cols\"\n",
    "df_activity = daily_activity.reindex(columns=new_cols)\n",
    "\n",
    "# print 1st 5 rows to confirm\n",
    "df_activity.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aggressive-hamilton",
   "metadata": {
    "papermill": {
     "duration": 0.030415,
     "end_time": "2022-10-14T21:40:32.805251",
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     "start_time": "2022-10-14T21:40:32.774836",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Creating new column by separating the date into day of the week for further analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "inside-germany",
   "metadata": {
    "_cell_guid": "b4ce574a-e7fa-4743-abe4-838540fa29ce",
    "_uuid": "8b542b7a-5f83-4404-bcdb-f38ee25a3227",
    "collapsed": false,
    "execution": {
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     "iopub.status.busy": "2022-10-14T21:40:32.868137Z",
     "iopub.status.idle": "2022-10-14T21:40:32.877291Z",
     "shell.execute_reply": "2022-10-14T21:40:32.876801Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.849975Z"
    },
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    },
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      Tuesday\n",
       "1    Wednesday\n",
       "2     Thursday\n",
       "3       Friday\n",
       "4     Saturday\n",
       "Name: DayOfTheWeek, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new column \"day_of_the_week\" to represent day of the week \n",
    "df_activity[\"DayOfTheWeek\"] = df_activity[\"ActivityDate\"].dt.day_name()\n",
    "\n",
    "# print 1st 5 rows to confirm\n",
    "df_activity[\"DayOfTheWeek\"].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "restricted-argentina",
   "metadata": {
    "papermill": {
     "duration": 0.029993,
     "end_time": "2022-10-14T21:40:32.938243",
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    "tags": []
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   "source": [
    "\n",
    "\n",
    "Rearranging and renaming columns from ```XxxYyy``` to ```xxx_yyy```."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "capable-connecticut",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:33.023941Z",
     "iopub.status.busy": "2022-10-14T21:40:33.022138Z",
     "iopub.status.idle": "2022-10-14T21:40:33.029486Z",
     "shell.execute_reply": "2022-10-14T21:40:33.030043Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.859953Z"
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     "exception": false,
     "start_time": "2022-10-14T21:40:32.969079",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['id' 'date' 'day_of_the_week' 'total_steps' 'total_dist' 'track_dist'\n",
      " 'logged_dist' 'very_active_dist' 'moderate_active_dist'\n",
      " 'light_active_dist' 'sedentary_active_dist' 'very_active_mins'\n",
      " 'fairly_active_mins' 'lightly_active_mins' 'sedentary_mins' 'total_mins'\n",
      " 'total_hours' 'calories']\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>day_of_the_week</th>\n",
       "      <th>total_steps</th>\n",
       "      <th>total_dist</th>\n",
       "      <th>track_dist</th>\n",
       "      <th>logged_dist</th>\n",
       "      <th>very_active_dist</th>\n",
       "      <th>moderate_active_dist</th>\n",
       "      <th>light_active_dist</th>\n",
       "      <th>sedentary_active_dist</th>\n",
       "      <th>very_active_mins</th>\n",
       "      <th>fairly_active_mins</th>\n",
       "      <th>lightly_active_mins</th>\n",
       "      <th>sedentary_mins</th>\n",
       "      <th>total_mins</th>\n",
       "      <th>total_hours</th>\n",
       "      <th>calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-12</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>13162</td>\n",
       "      <td>8.50</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.88</td>\n",
       "      <td>0.55</td>\n",
       "      <td>6.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "      <td>13</td>\n",
       "      <td>328</td>\n",
       "      <td>728</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-13</td>\n",
       "      <td>Wednesday</td>\n",
       "      <td>10735</td>\n",
       "      <td>6.97</td>\n",
       "      <td>6.97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.69</td>\n",
       "      <td>4.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21</td>\n",
       "      <td>19</td>\n",
       "      <td>217</td>\n",
       "      <td>776</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-14</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>10460</td>\n",
       "      <td>6.74</td>\n",
       "      <td>6.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.44</td>\n",
       "      <td>0.40</td>\n",
       "      <td>3.91</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "      <td>11</td>\n",
       "      <td>181</td>\n",
       "      <td>1218</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-15</td>\n",
       "      <td>Friday</td>\n",
       "      <td>9762</td>\n",
       "      <td>6.28</td>\n",
       "      <td>6.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.14</td>\n",
       "      <td>1.26</td>\n",
       "      <td>2.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29</td>\n",
       "      <td>34</td>\n",
       "      <td>209</td>\n",
       "      <td>726</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1503960366</td>\n",
       "      <td>2016-04-16</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>12669</td>\n",
       "      <td>8.16</td>\n",
       "      <td>8.16</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.71</td>\n",
       "      <td>0.41</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10</td>\n",
       "      <td>221</td>\n",
       "      <td>773</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1863</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id       date day_of_the_week  total_steps  total_dist  track_dist  \\\n",
       "0  1503960366 2016-04-12         Tuesday        13162        8.50        8.50   \n",
       "1  1503960366 2016-04-13       Wednesday        10735        6.97        6.97   \n",
       "2  1503960366 2016-04-14        Thursday        10460        6.74        6.74   \n",
       "3  1503960366 2016-04-15          Friday         9762        6.28        6.28   \n",
       "4  1503960366 2016-04-16        Saturday        12669        8.16        8.16   \n",
       "\n",
       "   logged_dist  very_active_dist  moderate_active_dist  light_active_dist  \\\n",
       "0          0.0              1.88                  0.55               6.06   \n",
       "1          0.0              1.57                  0.69               4.71   \n",
       "2          0.0              2.44                  0.40               3.91   \n",
       "3          0.0              2.14                  1.26               2.83   \n",
       "4          0.0              2.71                  0.41               5.04   \n",
       "\n",
       "   sedentary_active_dist  very_active_mins  fairly_active_mins  \\\n",
       "0                    0.0                25                  13   \n",
       "1                    0.0                21                  19   \n",
       "2                    0.0                30                  11   \n",
       "3                    0.0                29                  34   \n",
       "4                    0.0                36                  10   \n",
       "\n",
       "   lightly_active_mins  sedentary_mins  total_mins  total_hours  calories  \n",
       "0                  328             728         NaN          NaN      1985  \n",
       "1                  217             776         NaN          NaN      1797  \n",
       "2                  181            1218         NaN          NaN      1776  \n",
       "3                  209             726         NaN          NaN      1745  \n",
       "4                  221             773         NaN          NaN      1863  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# rename columns\n",
    "df_activity.rename(columns = {\"Id\":\"id\", \"ActivityDate\":\"date\", \"DayOfTheWeek\":\"day_of_the_week\", \"TotalSteps\":\"total_steps\", \"TotalDistance\":\"total_dist\", \"TrackerDistance\":\"track_dist\", \"LoggedActivitiesDistance\":\"logged_dist\", \"VeryActiveDistance\":\"very_active_dist\", \"ModeratelyActiveDistance\":\"moderate_active_dist\", \"LightActiveDistance\":\"light_active_dist\", \"SedentaryActiveDistance\":\"sedentary_active_dist\", \"VeryActiveMinutes\":\"very_active_mins\", \"FairlyActiveMinutes\":\"fairly_active_mins\", \"LightlyActiveMinutes\":\"lightly_active_mins\", \"SedentaryMinutes\":\"sedentary_mins\", \"TotalExerciseMinutes\":\"total_mins\",\"TotalExerciseHours\":\"total_hours\",\"Calories\":\"calories\"}, inplace = True)\n",
    "\n",
    "# print column names to confirm\n",
    "print(df_activity.columns.values)\n",
    "df_activity.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "characteristic-cycling",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Creating new column *total_mins* being the sum of total time logged."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "separated-zoning",
   "metadata": {
    "_cell_guid": "35932cb2-08ea-4b28-853e-1dedf3ea4930",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1094\n",
       "1    1033\n",
       "2    1440\n",
       "3     998\n",
       "4    1040\n",
       "Name: total_mins, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new column \"total_mins\" containing sum of total minutes.\n",
    "df_activity[\"total_mins\"] = df_activity[\"very_active_mins\"] + df_activity[\"fairly_active_mins\"] + df_activity[\"lightly_active_mins\"] + df_activity[\"sedentary_mins\"]\n",
    "df_activity[\"total_mins\"].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "remarkable-montreal",
   "metadata": {
    "papermill": {
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     "start_time": "2022-10-14T21:40:33.214331",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Creating new column by converting *total_mins*  to number of hours."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cellular-tolerance",
   "metadata": {
    "_cell_guid": "4869ce13-fd9b-40f3-b2cc-b5297f0ed9d4",
    "_uuid": "65a3b131-424f-4155-b7d5-a331834383f6",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:33.312926Z",
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     "iopub.status.idle": "2022-10-14T21:40:33.320139Z",
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     "shell.execute_reply.started": "2021-07-09T05:00:04.922029Z"
    },
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     "outputs_hidden": false
    },
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     "duration": 0.043214,
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     "exception": false,
     "start_time": "2022-10-14T21:40:33.277650",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    18.0\n",
       "1    17.0\n",
       "2    24.0\n",
       "3    17.0\n",
       "4    17.0\n",
       "Name: total_hours, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create new column *total_hours* by converting to hour and round float to two decimal places\n",
    "df_activity[\"total_hours\"] = round(df_activity[\"total_mins\"] / 60)\n",
    "\n",
    "# print 1st 5 rows to confirm\n",
    "df_activity[\"total_hours\"].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "modern-income",
   "metadata": {
    "_cell_guid": "83bcc39d-2107-452e-87a6-dc5484bd8fed",
    "_uuid": "426c4f87-b4b0-4ce4-bc3a-45b96daf482b",
    "papermill": {
     "duration": 0.032426,
     "end_time": "2022-10-14T21:40:33.385463",
     "exception": false,
     "start_time": "2022-10-14T21:40:33.353037",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Data cleaning and manipulation is completed. Hence, data is now ready to be analysed. \n",
    "\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unique-saskatchewan",
   "metadata": {
    "papermill": {
     "duration": 0.032065,
     "end_time": "2022-10-14T21:40:33.450708",
     "exception": false,
     "start_time": "2022-10-14T21:40:33.418643",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# STEP 4: ANALYZE\n",
    "\n",
    "#### 4.1 Perform calculations\n",
    "\n",
    "Pulling the statistics of df_activity for analysis:\n",
    "* count - no. of rows\n",
    "* mean (average)\n",
    "* std (standard deviation)\n",
    "* min and max\n",
    "* percentiles 25%, 50%, 75%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "toxic-manual",
   "metadata": {
    "_cell_guid": "540e3ee4-f56d-4979-a483-6e2deebc3fd0",
    "_uuid": "5a0f8f34-8675-483a-9255-16fbdd8d5f0d",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:33.519539Z",
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     "iopub.status.idle": "2022-10-14T21:40:33.580752Z",
     "shell.execute_reply": "2022-10-14T21:40:33.581300Z",
     "shell.execute_reply.started": "2021-07-09T05:00:04.932553Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
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     "exception": false,
     "start_time": "2022-10-14T21:40:33.483084",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>total_steps</th>\n",
       "      <th>total_dist</th>\n",
       "      <th>track_dist</th>\n",
       "      <th>logged_dist</th>\n",
       "      <th>very_active_dist</th>\n",
       "      <th>moderate_active_dist</th>\n",
       "      <th>light_active_dist</th>\n",
       "      <th>sedentary_active_dist</th>\n",
       "      <th>very_active_mins</th>\n",
       "      <th>fairly_active_mins</th>\n",
       "      <th>lightly_active_mins</th>\n",
       "      <th>sedentary_mins</th>\n",
       "      <th>total_mins</th>\n",
       "      <th>total_hours</th>\n",
       "      <th>calories</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9.400000e+02</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "      <td>940.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.855407e+09</td>\n",
       "      <td>7637.910638</td>\n",
       "      <td>5.489702</td>\n",
       "      <td>5.475351</td>\n",
       "      <td>0.108171</td>\n",
       "      <td>1.502681</td>\n",
       "      <td>0.567543</td>\n",
       "      <td>3.340819</td>\n",
       "      <td>0.001606</td>\n",
       "      <td>21.164894</td>\n",
       "      <td>13.564894</td>\n",
       "      <td>192.812766</td>\n",
       "      <td>991.210638</td>\n",
       "      <td>1218.753191</td>\n",
       "      <td>20.313830</td>\n",
       "      <td>2303.609574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.424805e+09</td>\n",
       "      <td>5087.150742</td>\n",
       "      <td>3.924606</td>\n",
       "      <td>3.907276</td>\n",
       "      <td>0.619897</td>\n",
       "      <td>2.658941</td>\n",
       "      <td>0.883580</td>\n",
       "      <td>2.040655</td>\n",
       "      <td>0.007346</td>\n",
       "      <td>32.844803</td>\n",
       "      <td>19.987404</td>\n",
       "      <td>109.174700</td>\n",
       "      <td>301.267437</td>\n",
       "      <td>265.931767</td>\n",
       "      <td>4.437283</td>\n",
       "      <td>718.166862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.503960e+09</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.320127e+09</td>\n",
       "      <td>3789.750000</td>\n",
       "      <td>2.620000</td>\n",
       "      <td>2.620000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.945000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>729.750000</td>\n",
       "      <td>989.750000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>1828.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.445115e+09</td>\n",
       "      <td>7405.500000</td>\n",
       "      <td>5.245000</td>\n",
       "      <td>5.245000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.210000</td>\n",
       "      <td>0.240000</td>\n",
       "      <td>3.365000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>1057.500000</td>\n",
       "      <td>1440.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>2134.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.962181e+09</td>\n",
       "      <td>10727.000000</td>\n",
       "      <td>7.712500</td>\n",
       "      <td>7.710000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.052500</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>4.782500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>264.000000</td>\n",
       "      <td>1229.500000</td>\n",
       "      <td>1440.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>2793.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>8.877689e+09</td>\n",
       "      <td>36019.000000</td>\n",
       "      <td>28.030001</td>\n",
       "      <td>28.030001</td>\n",
       "      <td>4.942142</td>\n",
       "      <td>21.920000</td>\n",
       "      <td>6.480000</td>\n",
       "      <td>10.710000</td>\n",
       "      <td>0.110000</td>\n",
       "      <td>210.000000</td>\n",
       "      <td>143.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>1440.000000</td>\n",
       "      <td>1440.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>4900.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id   total_steps  total_dist  track_dist  logged_dist  \\\n",
       "count  9.400000e+02    940.000000  940.000000  940.000000   940.000000   \n",
       "mean   4.855407e+09   7637.910638    5.489702    5.475351     0.108171   \n",
       "std    2.424805e+09   5087.150742    3.924606    3.907276     0.619897   \n",
       "min    1.503960e+09      0.000000    0.000000    0.000000     0.000000   \n",
       "25%    2.320127e+09   3789.750000    2.620000    2.620000     0.000000   \n",
       "50%    4.445115e+09   7405.500000    5.245000    5.245000     0.000000   \n",
       "75%    6.962181e+09  10727.000000    7.712500    7.710000     0.000000   \n",
       "max    8.877689e+09  36019.000000   28.030001   28.030001     4.942142   \n",
       "\n",
       "       very_active_dist  moderate_active_dist  light_active_dist  \\\n",
       "count        940.000000            940.000000         940.000000   \n",
       "mean           1.502681              0.567543           3.340819   \n",
       "std            2.658941              0.883580           2.040655   \n",
       "min            0.000000              0.000000           0.000000   \n",
       "25%            0.000000              0.000000           1.945000   \n",
       "50%            0.210000              0.240000           3.365000   \n",
       "75%            2.052500              0.800000           4.782500   \n",
       "max           21.920000              6.480000          10.710000   \n",
       "\n",
       "       sedentary_active_dist  very_active_mins  fairly_active_mins  \\\n",
       "count             940.000000        940.000000          940.000000   \n",
       "mean                0.001606         21.164894           13.564894   \n",
       "std                 0.007346         32.844803           19.987404   \n",
       "min                 0.000000          0.000000            0.000000   \n",
       "25%                 0.000000          0.000000            0.000000   \n",
       "50%                 0.000000          4.000000            6.000000   \n",
       "75%                 0.000000         32.000000           19.000000   \n",
       "max                 0.110000        210.000000          143.000000   \n",
       "\n",
       "       lightly_active_mins  sedentary_mins   total_mins  total_hours  \\\n",
       "count           940.000000      940.000000   940.000000   940.000000   \n",
       "mean            192.812766      991.210638  1218.753191    20.313830   \n",
       "std             109.174700      301.267437   265.931767     4.437283   \n",
       "min               0.000000        0.000000     2.000000     0.000000   \n",
       "25%             127.000000      729.750000   989.750000    16.000000   \n",
       "50%             199.000000     1057.500000  1440.000000    24.000000   \n",
       "75%             264.000000     1229.500000  1440.000000    24.000000   \n",
       "max             518.000000     1440.000000  1440.000000    24.000000   \n",
       "\n",
       "          calories  \n",
       "count   940.000000  \n",
       "mean   2303.609574  \n",
       "std     718.166862  \n",
       "min       0.000000  \n",
       "25%    1828.500000  \n",
       "50%    2134.000000  \n",
       "75%    2793.250000  \n",
       "max    4900.000000  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pull general statistics\n",
    "df_activity.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "appointed-numbers",
   "metadata": {
    "papermill": {
     "duration": 0.03276,
     "end_time": "2022-10-14T21:40:33.647149",
     "exception": false,
     "start_time": "2022-10-14T21:40:33.614389",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "Interpreting statistical findings:\n",
    "\n",
    "1. On average, users logged 7,637 steps or 5.4km which is not adequate. As recommended by CDC, an adult female has to aim at least 10,000 steps or 8km per day to benefit from general health, weight loss and fitness improvement. [Source: Medical News Today article](https://www.medicalnewstoday.com/articles/how-many-steps-should-you-take-a-day)\n",
    "\n",
    "2.  Sedentary users are the majority logging on average 991 minutes or 20 hours making up 81% of total average minutes.\n",
    "\n",
    "3. Noting that average calories burned is 2,303 calories equivalent to 0.6 pound. Could not interpret into detail as calories burned depend on several factors such as the age, weight, daily tasks, exercise, hormones and daily calorie intake. [Source: Health Line article](https://www.healthline.com/health/fitness-exercise/how-many-calories-do-i-burn-a-day#Burning-calories)\n",
    "\n",
    "***\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "friendly-blackberry",
   "metadata": {
    "papermill": {
     "duration": 0.032388,
     "end_time": "2022-10-14T21:40:33.712071",
     "exception": false,
     "start_time": "2022-10-14T21:40:33.679683",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# STEP 5: SHARE\n",
    "\n",
    "In this step, we are creating visualizations and communicating our findings based on our analysis.\n",
    "\n",
    "#### 5.1 Data Visualisation and Findings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "hundred-section",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:33.781867Z",
     "iopub.status.busy": "2022-10-14T21:40:33.780929Z",
     "iopub.status.idle": "2022-10-14T21:40:33.999105Z",
     "shell.execute_reply": "2022-10-14T21:40:33.999570Z",
     "shell.execute_reply.started": "2021-07-09T05:00:05.005581Z"
    },
    "papermill": {
     "duration": 0.254878,
     "end_time": "2022-10-14T21:40:33.999765",
     "exception": false,
     "start_time": "2022-10-14T21:40:33.744887",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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lxIQJE5CRkZHr3JHbt29DqVSiatWqWuVOTk6wsbHB7du387W9rPrVq1fP9pi3tzcePnxYbBPXKlWqpLWclTy4urpmK9doNNI8j7i4OAgh4OnpCXt7e62/2NhYaeKtu7s7Ro8ejR9//BHly5dHcHAwli5dmud8kfz44osvYGFhgYYNG8LT0xNDhw7VOjT94MEDPH36FCtWrMjW1/79+wP4v4nCWdzd3bNtZ9q0aXj69CmqVauG2rVrY+zYsTh//ny++/u2/e/l5SU9nvXvm8+7nMpu374NZ2dnmJmZvbXetWvXIITAxIkTs43F5MmTAfzfWNy+fRuenp7Ztp1Tv/PjzeccANja2uZ4Dv9Nq1evRp06daQ5O/b29vjjjz9yfD7l1Pdq1aplu9pMqVSiSpUq2eoByPMy+YsXL6Jr166wtraGlZUV7O3tpQ/lrD5dv34dAHS6XYChoSEqVqyoVXb79m24uLjA0tJSqzzrFGzW8+SDDz6An58fBg4cCEdHR/Tq1QsbN27USkzyeq0UVMWKFbMlVm/u07i4OFy8eDHb8y5rrN98Db6pefPmOHXqFFJTU3Ho0CE4OzujXr168PHxkU7VHD58WDqNlLXNZ8+ewcHBIdt2k5OTpW1mfcEIDAzMVm/37t3Z+vby5Ut06NABdevWxcaNG0v9xQGcM1JCVKlSBX379sWKFSvw5Zdf5lqvLN7AycDAIF/l4v9PmNNoNFAoFNixY0eOdV//Jj9//nyEhobit99+w+7duzF8+HDMnj0bf/31V7Y33tflNt6ZmZla2/T29saVK1ewfft27Ny5E5s3b8b333+PSZMmYerUqdKbcd++fXOcQwG8+nb+upzO+/r7++P69etSHD/++CMWLlyI5cuXY+DAgbnGUZJkjcWYMWMQHBycY52ckh99yuu5lZt169YhNDQUXbp0wdixY+Hg4AADAwPMnj1b+sAvTk+fPkWLFi1gZWWFadOmwcPDAyYmJjh9+jS++OKLAl2BpVKpoFQW7HuqqakpoqOjERUVhT/++AM7d+7Ehg0bEBgYiN27d8PAwCDP10pB6bJPNRoNateujQULFuRY980vQG9q1qwZ1Go1jh07hkOHDklJR/PmzXHo0CFcvnwZDx480EpGNBoNHBwcsH79+hzbtLe3l+oBr+aNODk5ZatnaKj9ca1SqdC+fXv89ttv2LlzpzSPpbRiMlKCTJgwAevWrcOcOXOyPebm5gaNRoO4uDitCaGJiYl4+vRprjchy01W/StXrmR77PLlyyhfvjzMzc3zGUHxJkseHh4QQsDd3V36ZvM2tWvXRu3atTFhwgQcPXoUfn5+WL58OWbMmJHrOra2tlqz57Pcvn072zdZc3NzfPDBB/jggw+Qnp6Obt26YebMmRg/fjzs7e1haWmJzMxMBAUF5TvW15UrVw79+/dH//79pYlyU6ZMyVcy8vr+zzpEneXKlSvS41n/Xrt2LVsbb5a5ubkhKioKKSkpWkdH3qyXNW5GRkZ5joWbm1uOp6Ryet4Wh19//RVVqlTBli1btJ7rWUd03pRT369evZptIqJGo8GNGze0nsdXr14FgFwnLQKvrjJ59OgRtmzZojVh8ubNm1r1sk5J/f333wV6/rm5uWHv3r14/vy51tGRrNNAr7//KJVKtGrVCq1atcKCBQswa9YsfP3114iKipK2/bbXSm6XYuvjvcXDwwPnzp1Dq1atCtRew4YNYWxsjEOHDuHQoUMYO3YsgFdfElauXIl9+/ZJy69vc+/evfDz83vrxNKsfeTg4KDTPlIoFFi/fj06d+6M999/Hzt27CjVd7jmaZoSxMPDA3379sUPP/yAe/fuaT3Wvn17AEB4eLhWeVaG36FDB6ns+vXreX5Lc3Z2hq+vL1avXq31Yfv3339j9+7d0vbyKyuByekDXN+6desGAwMDTJ06Nds3WiEEHj16BODVFRBZ80yy1K5dG0qlMs/L+Tw8PPDXX38hPT1dKtu+fXu2S4eztpXF2NgYNWrUgBACarUaBgYG6N69OzZv3pzt0k7g1WkcXby5HQsLC1StWjXfl3c3aNAADg4OWL58uda6O3bsQGxsrPR8cnFxQa1atbBmzRqtywUPHjyICxcuaLUZHBwMtVqNlStXSmUajQZLly7Vqufg4ICWLVvihx9+yHGO1Otj0b59e/z11184fvy41uO5fcssalnfvl9/vsXExEjzBd60bds2rUuljx8/jpiYGOnqjtctWbJE+r8QAkuWLIGRkRFatWqVr/6kp6fj+++/16pXr149uLu7Izw8PNtrM6+jQcCr/ZCZmanVRwBYuHAhFAqFFM/jx4+zrZt1hVHW8yyv10pu9PHe0rNnT9y9e1frOZolNTU1z1PTJiYmeO+99/Df//4Xd+7c0ToykpqaikWLFsHDwwPOzs5a28zMzMT06dOztZeRkSHFExwcDCsrK8yaNSvHccjpPcLY2BhbtmzBe++9J13JVlrxyEgJ8/XXX2Pt2rW4cuUKatasKZX7+PggJCQEK1askA7NHj9+HKtXr0aXLl0QEBAg1c1688rrXPO8efPQrl07NGnSBGFhYdKlvdbW1pgyZUqB+u/r6wsDAwPMmTMHz549g0qlQmBgIBwcHArU3tt4eHhgxowZGD9+PG7duoUuXbrA0tISN2/exNatWzF48GCMGTMG+/fvx7Bhw/D++++jWrVqyMjIwNq1a6UE4W0GDhyIX3/9FW3btkXPnj1x/fp1rFu3TmvyIwC0adMGTk5O8PPzg6OjI2JjY7FkyRJ06NBB+ib5zTffICoqCo0aNcKgQYNQo0YNPH78GKdPn8bevXtzfCN/U40aNdCyZUvUr18f5cqVw8mTJ/Hrr79qTX7UhZGREebMmYP+/fujRYsW+PDDD6VLeytXroxRo0ZJdWfNmoXOnTvDz88P/fv3x5MnT7BkyRLUqlVLK0Hp0qULGjZsiM8//xzXrl2Dl5cXfv/9dymu17+JLl26FM2aNUPt2rUxaNAgVKlSBYmJiTh27Bj+/fdfnDt3DgAwbtw4rF27Fm3btsWIESOkS3vd3NwKNFemsDp27IgtW7aga9eu6NChA27evInly5ejRo0aOd7boWrVqmjWrBmGDBmCtLQ0hIeHw87ODuPGjdOqZ2Jigp07dyIkJASNGjXCjh078Mcff+Crr76SDuPnpGnTprC1tUVISAiGDx8OhUKBtWvXZkswlEolli1bhk6dOsHX1xf9+/eHs7MzLl++jIsXL2LXrl1vjbtTp04ICAjA119/jVu3bsHHxwe7d+/Gb7/9hpEjR0qvh2nTpiE6OhodOnSAm5sb7t+/j++//x4VK1ZEs2bNAOj2WsmJh4cHbGxssHz5clhaWsLc3ByNGjXKcW5Vbj766CNs3LgRn3zyCaKiouDn54fMzExcvnwZGzduxK5du9CgQYO3ttG8eXN88803sLa2liZxOzg4oHr16rhy5Uq2+xK1aNECH3/8MWbPno2zZ8+iTZs2MDIyQlxcHDZt2oTvvvsOPXr0gJWVFZYtW4aPPvoI9erVQ69evWBvb487d+7gjz/+gJ+fX7ZkEHh1amz79u0IDAxEu3btcPDgwRLzUyL5UrwX71CW1y/tfVPW5XVvXv6mVqvF1KlThbu7uzAyMhKurq5i/Pjx2S7ncnNz07rk8m327t0r/Pz8hKmpqbCyshKdOnUSly5d0qqTn0t7hRBi5cqVokqVKsLAwEDrctLcLu19s93cxibrMs03LxvcvHmzaNasmTA3Nxfm5ubCy8tLDB06VFy5ckUIIcSNGzfEgAEDhIeHhzAxMRHlypUTAQEBYu/evTrFM3/+fFGhQgWhUqmEn5+fOHnyZLZYfvjhB+Hv7y/s7OyESqUSHh4eYuzYseLZs2dabSUmJoqhQ4cKV1dXYWRkJJycnESrVq3EihUr8hwXIYSYMWOGaNiwobCxsRGmpqbCy8tLzJw5U+vS6Jy8eWlvlg0bNoi6desKlUolypUrJ/r06aN1KWqWX375RXh5eQmVSiVq1aolfv/9d9G9e3fh5eWlVe/Bgweid+/ewtLSUlhbW4vQ0FBx5MgRAUD88ssvWnWvX78u+vXrJ5ycnISRkZGoUKGC6Nixo/j111+16p0/f160aNFCmJiYiAoVKojp06eLn376qVCX9g4dOjRb3dwu436dRqMRs2bNEm5ubkKlUom6deuK7du3i5CQEK3XXNalvfPmzRPz588Xrq6uQqVSiebNm4tz585ptZl1meb169dFmzZthJmZmXB0dBSTJ08WmZmZb+2PEEIcOXJENG7cWJiamgoXFxcxbtw4sWvXrhz39+HDh0Xr1q2FpaWlMDc3F3Xq1NG6nPn1S0bf9Pz5czFq1Cjh4uIijIyMhKenp5g3b57WpcH79u0TnTt3Fi4uLsLY2Fi4uLiIDz/8UFy9elWqo+trJSe//fabqFGjhjA0NNS6zPfNWyG8Hs+b74Xp6elizpw5ombNmkKlUglbW1tRv359MXXqVJ368McffwgA2W49MHDgQAFA/PTTTzmut2LFClG/fn1hamoqLC0tRe3atcW4ceNEfHy8Vr2oqCgRHBwsrK2thYmJifDw8BChoaHi5MmTWnG9uZ8ePnwoatSoIZycnERcXFyecZQ0CiF0OEZHRPQGX19f2Nvb53n3123btqFr1644fPgw/Pz8iql38rp16xbc3d0xb948jBkz5q11Q0ND8euvv5bKu2YS6QvnjBDRW6nV6mxzbg4cOIBz585lmzD35o/SZWZmYvHixbCyskK9evWKuqtEVEpxzggRvdXdu3cRFBSEvn37wsXFBZcvX8by5cvh5OSETz75RKvuZ599htTUVDRp0gRpaWnYsmULjh49ilmzZpXOW1QTUbFgMkJEb2Vra4v69evjxx9/xIMHD2Bubo4OHTrgm2++yfY7LoGBgZg/fz62b9+Oly9fomrVqli8eHG+J9gS0buFc0aIiIhIVpwzQkRERLJiMkJERESy4pwRvLpLZHx8PCwtLcvkb78QEREVFSEEnj9/DhcXlwL/rhGTEbz6mfS8fiCJiIiIcvfPP/+89YdH34bJCCDdgviff/6BlZWVXtpUq9XYvXu3dOtfeoXjkjuOTc44Lrnj2OSM45K7ohibpKQkuLq6vvV2/nlhMoL/+80MKysrvSYjZmZmsLKy4ovhNRyX3HFscsZxyR3HJmccl9wV5dgUZpoDJ7ASERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrHg7+CJ27ty5Av+KYXEpX748KlWqJHc3iIjoHcVkpIj8+++/AAB/f3+kpqbK3Ju3MzUzw+XYWCYkREQkCyYjReTRo0cAgK4Tl6Gcm7fMvcnd/Zux2DghFA8fPmQyQkREsmAyUsTs3arDybuu3N0gIiIqsZiMkN7cuXMHDx8+fGsdjUYDQN65NJwjQ0RUsjAZIb24c+cOvLy9kZqS8tZ6pqam+O9//yvrXBrOkSEiKlmYjJBePHz4EKkpKeg5YxUc3HOfI2MADYBEDP5xPzJluLKcc2SIiEoeJiOkVw7u3qjwljkySo0a+HcPXKrXgUZpVIw9IyKikqpk3wCDiIiIyjwmI0RERCQrnqYhKgRdriDSVVFeacQriIioJGMyQlRAul5BpKuivNKIVxARUUnGZISogHS9gkhXRXWlEa8gIqKSjskIUSHldQWRrnilERG9qziBlYiIiGTFZISIiIhkxWSEiIiIZMVkhIiIiGTFZISIiIhkxWSEiIiIZMVkhIiIiGQlazISHR2NTp06wcXFBQqFAtu2bcu17ieffAKFQoHw8HCt8sePH6NPnz6wsrKCjY0NwsLCkJycXLQdJyIiIr2RNRl58eIFfHx8sHTp0rfW27p1K/766y+4uLhke6xPnz64ePEi9uzZg+3btyM6OhqDBw8uqi4TERGRnsl6B9Z27dqhXbt2b61z9+5dfPbZZ9i1axc6dOig9VhsbCx27tyJEydOoEGDBgCAxYsXo3379vj2229zTF6IiIioZCnRt4PXaDT46KOPMHbsWNSsWTPb48eOHYONjY2UiABAUFAQlEolYmJi0LVr1xzbTUtLQ1pamrSclJQEAFCr1VCr1XrrO/Dq90aUGv20WRQMoIGpqSk0Gk2hYtdoXrWTV7xKTYbWv8VNX/ECusesq6IaG33GLIesPpfGvhc1jk3OOC65K4qx0UdbCiGE0ENfCk2hUGDr1q3o0qWLVDZ79mxERUVh165dUCgUqFy5MkaOHImRI0cCAGbNmoXVq1fjypUrWm05ODhg6tSpGDJkSI7bmjJlCqZOnZqtPDIyEmZmZnqLiYiIqKxLSUlB79698ezZM1hZWRWojRJ7ZOTUqVP47rvvcPr0aSgUCr22PX78eIwePVpaTkpKgqurK9q0aVPggXzTmTNnkJCQgOgX9nCs7quXNotC/JXzWDEwENHR0fDx8SlwO+fOnYO/vz8G/7gfLtXr5FpPqcmAZ3wU4lwCoFEW/9NPX/ECusesq6IaG33GLAe1Wo09e/agdevWMDLiDwi+jmOTM45L7opibLLOLhRGiU1GDh06hPv372v95HlmZiY+//xzhIeH49atW3BycsL9+/e11svIyMDjx4/h5OSUa9sqlQoqlSpbuZGRkd52jlL5am5wJpQl+hdYM6FEamoqlEploWJXKl+1o2u8GqWhLOOir3iB/MesK32PjT5jlpM+X59lDccmZxyX3OlzbPTRTolNRj766CMEBQVplQUHB+Ojjz5C//79AQBNmjTB06dPcerUKdSvXx8AsH//fmg0GjRq1KjY+0xERET5J2sykpycjGvXrknLN2/exNmzZ1GuXDlUqlQJdnZ2WvWNjIzg5OSE6tWrAwC8vb3Rtm1bDBo0CMuXL4darcawYcPQq1cvXklDRERUSsh6n5GTJ0+ibt26qFu3LgBg9OjRqFu3LiZNmqRzG+vXr4eXlxdatWqF9u3bo1mzZlixYkVRdZmIiIj0TNYjIy1btkR+Lua5detWtrJy5cohMjJSj70iIiKi4sTfpiEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZGcrdASIqPe7cuYOHDx8W6zY1Gg0A4Ny5c1Aqdfv+VL58eVSqVKkou0VEesRkhIh0cufOHXh5eyM1JaVYt2tqaor//ve/8Pf3R2pqqm7rmJnhcmwsExKiUoLJCBHp5OHDh0hNSUHPGavg4O5dbNs1gAZAIgb/uB+ZOpxZvn8zFhsnhOLhw4dMRohKCSYjRJQvDu7eqOBdt9i2p9SogX/3wKV6HWiURsW2XUCe01L58fopLAcHByZfVGoxGSEiyoFcp6Xy4/VTWFAoeGqKSi0mI0REOZDrtFR+ZJ3C6jpxGSK/4qkpKr2YjBARvUVxn5bKj6xTWPZu1eXuClGh8D4jREREJCtZk5Ho6Gh06tQJLi4uUCgU2LZtm/SYWq3GF198gdq1a8Pc3BwuLi7o168f4uPjtdp4/Pgx+vTpAysrK9jY2CAsLAzJycnFHAkREREVlKynaV68eAEfHx8MGDAA3bp103osJSUFp0+fxsSJE+Hj44MnT55gxIgR+M9//oOTJ09K9fr06YOEhATs2bMHarUa/fv3x+DBgxEZGVnc4RARlXol/QqiLLyxXdkiazLSrl07tGvXLsfHrK2tsWfPHq2yJUuWoGHDhrhz5w4qVaqE2NhY7Ny5EydOnECDBg0AAIsXL0b79u3x7bffwsXFpchjICIqK0rDFURZeGO7sqVUTWB99uwZFAoFbGxsAADHjh2DjY2NlIgAQFBQEJRKJWJiYtC1a9cc20lLS0NaWpq0nJSUBODVqSG1Wq2XvmZd/28AzatJZiWUATQwNTWFRqMpVOwazat28opXqcnQ+re46SteQPeYdVVUY1Pc+1jf8jsupT3e/MgaE33FfP/+fUAI9J61qkRPin1w+wq2Th+C+/fvw9nZOdvjWWOgy1j8+++/ePTokd77qG92dnaoWLFiodvJz9jkt83CUAghhB76UmgKhQJbt25Fly5dcnz85cuX8PPzg5eXF9avXw8AmDVrFlavXo0rV65o1XVwcMDUqVMxZMiQHNuaMmUKpk6dmq08MjISZmZmhQuEiIjoHZKSkoLevXvj2bNnsLKyKlAbpeLIiFqtRs+ePSGEwLJlywrd3vjx4zF69GhpOSkpCa6urmjTpk2BB/JNZ86cQUJCAqJf2MOxuq9e2iwK8VfOY8XAQERHR8PHx6fA7Zw7dw7+/v4Y/ON+uFSvk2s9pSYDnvFRiHMJgEZZ/E8/fcUL6B6zropqbIp7H+tbfseltMebH1ljE/3CHssGBr0TMQN572O1Wo09e/agdevWMDLK/a69WfF2nbisVBwJ0sf7lq5jkx9ZZxcKo8QnI1mJyO3bt7F//36tZMHJyenVYcXXZGRk4PHjx3Bycsq1TZVKBZVKla3cyMhIbzsn69dFM6Es9ltY50cmlEhNTYVSqSxU7Erlq3Z0jVejNJRlXPQVL5D/mHWl77GRax/rm67jUlbizY93LWZd483rPT0r3nJu3nAqofeSAfT7vpVFn593+minRN9nJCsRiYuLw969e2FnZ6f1eJMmTfD06VOcOnVKKtu/fz80Gg0aNWpU3N0lIiKiApD1yEhycjKuXbsmLd+8eRNnz55FuXLl4OzsjB49euD06dPYvn07MjMzce/ePQBAuXLlYGxsDG9vb7Rt2xaDBg3C8uXLoVarMWzYMPTq1YtX0hAREZUSsiYjJ0+eREBAgLScNY8jJCQEU6ZMwe+//w4A8PX11VovKioKLVu2BACsX78ew4YNQ6tWraBUKtG9e3csWrSoWPpPREREhSdrMtKyZUu87WIeXS70KVeuHG9wRkREVIqV6DkjREREVPYxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlkxGSEiIiJZMRkhIiIiWTEZISIiIlnJmoxER0ejU6dOcHFxgUKhwLZt27QeF0Jg0qRJcHZ2hqmpKYKCghAXF6dV5/Hjx+jTpw+srKxgY2ODsLAwJCcnF2MUREREVBiyJiMvXryAj48Pli5dmuPjc+fOxaJFi7B8+XLExMTA3NwcwcHBePnypVSnT58+uHjxIvbs2YPt27cjOjoagwcPLq4QiIiIqJAM5dx4u3bt0K5duxwfE0IgPDwcEyZMQOfOnQEAa9asgaOjI7Zt24ZevXohNjYWO3fuxIkTJ9CgQQMAwOLFi9G+fXt8++23cHFxKbZYiIiIqGBkTUbe5ubNm7h37x6CgoKkMmtrazRq1AjHjh1Dr169cOzYMdjY2EiJCAAEBQVBqVQiJiYGXbt2zbHttLQ0pKWlSctJSUkAALVaDbVarZf+azQaAIABNFBq9NNmUTCABqamptBoNIWKXaN51U5e8So1GVr/Fjd9xQvoHrOuimpsinsf61t+x6W0x5sfWWPyLsUM5B1vVlleY1FW4s0PXcemIG0WhkIIIfTQl0JTKBTYunUrunTpAgA4evQo/Pz8EB8fD2dnZ6lez549oVAosGHDBsyaNQurV6/GlStXtNpycHDA1KlTMWTIkBy3NWXKFEydOjVbeWRkJMzMzPQXFBERURmXkpKC3r1749mzZ7CysipQGyX2yEhRGj9+PEaPHi0tJyUlwdXVFW3atCnwQL7pzJkzSEhIQPQLezhW99VLm0Uh/sp5rBgYiOjoaPj4+BS4nXPnzsHf3x+Df9wPl+p1cq2n1GTAMz4KcS4B0CiL/+mnr3gB3WPWVVGNTXHvY33L77iU9njzI2tsol/YY9nAoHciZiDvfaxWq7Fnzx60bt0aRkZGubZTVuLND13HJj+yzi4URolNRpycnAAAiYmJWkdGEhMT4evrK9W5f/++1noZGRl4/PixtH5OVCoVVCpVtnIjIyO97Ryl8tXc4EwooVHqp82ikAklUlNToVQqCxW7UvmqHV3j1SgNZRkXfcUL5D9mXel7bOTax/qm67iUlXjz412LWdd483pPL2vx5oc+P+/00U6Jvc+Iu7s7nJycsG/fPqksKSkJMTExaNKkCQCgSZMmePr0KU6dOiXV2b9/PzQaDRo1alTsfSYiIqL8k/XISHJyMq5duyYt37x5E2fPnkW5cuVQqVIljBw5EjNmzICnpyfc3d0xceJEuLi4SPNKvL290bZtWwwaNAjLly+HWq3GsGHD0KtXL15JQ0REVErImoycPHkSAQEB0nLWPI6QkBCsWrUK48aNw4sXLzB48GA8ffoUzZo1w86dO2FiYiKts379egwbNgytWrWCUqlE9+7dsWjRomKPhYiIiAqmQMnIjRs3UKVKlUJvvGXLlnjbxTwKhQLTpk3DtGnTcq1Trlw5REZGFrovREREJI8CzRmpWrUqAgICsG7dOq27oRIRERHlV4GSkdOnT6NOnToYPXo0nJyc8PHHH+P48eP67hsRERG9AwqUjPj6+uK7775DfHw8fv75ZyQkJKBZs2aoVasWFixYgAcPHui7n0RERFRGFerSXkNDQ3Tr1g2bNm3CnDlzcO3aNYwZMwaurq7o168fEhIS9NVPIiIiKqMKlYycPHkSn376KZydnbFgwQKMGTMG169fx549exAfHy/9wB0RERFRbgp0Nc2CBQsQERGBK1euoH379lizZg3at28v3XXU3d0dq1atQuXKlfXZVyIiIiqDCpSMLFu2DAMGDEBoaKjWrdpf5+DggJ9++qlQnSMiIqKyr0DJSFxcXJ51jI2NERISUpDmiYiI6B1SoDkjERER2LRpU7byTZs2YfXq1YXuFBEREb07CpSMzJ49G+XLl89W7uDggFmzZhW6U0RERPTuKFAycufOHbi7u2crd3Nzw507dwrdKSIiInp3FCgZcXBwwPnz57OVnzt3DnZ2doXuFBEREb07CpSMfPjhhxg+fDiioqKQmZmJzMxM7N+/HyNGjECvXr303UciIiIqwwp0Nc306dNx69YttGrVCoaGr5rQaDTo168f54wQERFRvhQoGTE2NsaGDRswffp0nDt3Dqampqhduzbc3Nz03T8iIiIq4wqUjGSpVq0aqlWrpq++EBER0TuoQMlIZmYmVq1ahX379uH+/fvQaDRaj+/fv18vnSMiIqKyr0DJyIgRI7Bq1Sp06NABtWrVgkKh0He/iIiI6B1RoGTkl19+wcaNG9G+fXt994eIiIjeMQW6tNfY2BhVq1bVd1+IiIjoHVSgZOTzzz/Hd999ByGEvvtDRERE75gCnaY5fPgwoqKisGPHDtSsWRNGRkZaj2/ZskUvnSMiIqKyr0DJiI2NDbp27arvvhAREdE7qEDJSEREhL77QURERO+oAs0ZAYCMjAzs3bsXP/zwA54/fw4AiI+PR3Jyst46R0RERGVfgY6M3L59G23btsWdO3eQlpaG1q1bw9LSEnPmzEFaWhqWL1+u734SERFRGVWgIyMjRoxAgwYN8OTJE5iamkrlXbt2xb59+/TWOSIiIir7CpSMHDp0CBMmTICxsbFWeeXKlXH37l29dAx4ddv5iRMnwt3dHaampvDw8MD06dO1LikWQmDSpElwdnaGqakpgoKCEBcXp7c+EBERUdEqUDKi0WiQmZmZrfzff/+FpaVloTuVZc6cOVi2bBmWLFmC2NhYzJkzB3PnzsXixYulOnPnzsWiRYuwfPlyxMTEwNzcHMHBwXj58qXe+kFERERFp0DJSJs2bRAeHi4tKxQKJCcnY/LkyXq9RfzRo0fRuXNndOjQAZUrV0aPHj3Qpk0bHD9+HMCroyLh4eGYMGECOnfujDp16mDNmjWIj4/Htm3b9NYPIiIiKjoFmsA6f/58BAcHo0aNGnj58iV69+6NuLg4lC9fHv/973/11rmmTZtixYoVuHr1KqpVq4Zz587h8OHDWLBgAQDg5s2buHfvHoKCgqR1rK2t0ahRIxw7dgy9evXKsd20tDSkpaVJy0lJSQAAtVoNtVqtl75n/ZKxATRQavTTZlEwgAampqbQaDSFil2jedVOXvEqNRla/xY3fcUL6B6zropqbIp7H+tbfseltMebH1lj8i7FDOQdb1ZZXmNRVuLND13HpiBtFoZCFPCe7hkZGfjll19w/vx5JCcno169eujTp4/WhNbC0mg0+OqrrzB37lwYGBggMzMTM2fOxPjx4wG8OnLi5+eH+Ph4ODs7S+v17NkTCoUCGzZsyLHdKVOmYOrUqdnKIyMjYWZmprf+ExERlXUpKSno3bs3nj17BisrqwK1UaAjIwBgaGiIvn37FnR1nWzcuBHr169HZGQkatasibNnz2LkyJFwcXFBSEhIgdsdP348Ro8eLS0nJSXB1dUVbdq0KfBAvunMmTNISEhA9At7OFb31UubRSH+ynmsGBiI6Oho+Pj4FLidc+fOwd/fH4N/3A+X6nVyrafUZMAzPgpxLgHQKAv89CswfcUL6B6zropqbIp7H+tbfseltMebH1ljE/3CHssGBr0TMQN572O1Wo09e/agdevW2X6u5HVlJd780HVs8iPr7EJhFOgdb82aNW99vF+/fgXqzJvGjh2LL7/8UjrdUrt2bdy+fRuzZ89GSEgInJycAACJiYlaR0YSExPh6+uba7sqlQoqlSpbuZGRkd52jlL5ajpOJpTQKPXTZlHIhBKpqalQKpWFil2pfNWOrvFqlIayjIu+4gXyH7Ou9D02cu1jfdN1XMpKvPnxrsWsa7x5vaeXtXjzQ5+fd/pop0DJyIgRI7SW1Wo1UlJSYGxsDDMzM70lIykpKdKHehYDAwNpPoa7uzucnJywb98+KflISkpCTEwMhgwZopc+EBERUdEqUDLy5MmTbGVxcXEYMmQIxo4dW+hOZenUqRNmzpyJSpUqoWbNmjhz5gwWLFiAAQMGAHh1Fc/IkSMxY8YMeHp6wt3dHRMnToSLiwu6dOmit34QERFR0dHbiWlPT09888036Nu3Ly5fvqyXNhcvXoyJEyfi008/xf379+Hi4oKPP/4YkyZNkuqMGzcOL168wODBg/H06VM0a9YMO3fuhImJiV76QEREREVLrzMIDQ0NER8fr7f2LC0tER4ernVPkzcpFApMmzYN06ZN09t2iYiIqPgUKBn5/ffftZaFEEhISMCSJUvg5+enl44RERHRu6FAycib8zEUCgXs7e0RGBiI+fPn66NfRERE9I4oUDKSdTULERERUWEV6LdpiIiIiPSlQEdGXr97aV6yfkeGiIiIKCcFSkbOnDmDM2fOQK1Wo3r16gCAq1evwsDAAPXq1ZPqKRQK/fSSiIiIyqwCJSOdOnWCpaUlVq9eDVtbWwCvboTWv39/NG/eHJ9//rleO0lERERlV4HmjMyfPx+zZ8+WEhEAsLW1xYwZM3g1DREREeVLgZKRpKQkPHjwIFv5gwcP8Pz580J3ioiIiN4dBUpGunbtiv79+2PLli34999/8e+//2Lz5s0ICwtDt27d9N1HIiIiKsMKNGdk+fLlGDNmDHr37g21Wv2qIUNDhIWFYd68eXrtIBEREZVtBUpGzMzM8P3332PevHm4fv06AMDDwwPm5uZ67RwRERGVfYW66VlCQgISEhLg6ekJc3NzCCH01S8iIiJ6RxQoGXn06BFatWqFatWqoX379khISAAAhIWF8bJeIiIiypcCJSOjRo2CkZER7ty5AzMzM6n8gw8+wM6dO/XWOSIiIir7CjRnZPfu3di1axcqVqyoVe7p6Ynbt2/rpWNERET0bijQkZEXL15oHRHJ8vjxY6hUqkJ3ioiIiN4dBUpGmjdvjjVr1kjLCoUCGo0Gc+fORUBAgN46R0RERGVfgU7TzJ07F61atcLJkyeRnp6OcePG4eLFi3j8+DGOHDmi7z4SERFRGVagIyO1atXC1atX0axZM3Tu3BkvXrxAt27dcObMGXh4eOi7j0RERFSG5fvIiFqtRtu2bbF8+XJ8/fXXRdEnIiIieofk+8iIkZERzp8/XxR9ISIiondQgU7T9O3bFz/99JO++0JERETvoAJNYM3IyMDPP/+MvXv3on79+tl+k2bBggV66RwRERGVfflKRm7cuIHKlSvj77//Rr169QAAV69e1aqjUCj01zsiIiIq8/KVjHh6eiIhIQFRUVEAXt3+fdGiRXB0dCySzhEREVHZl685I2/+Ku+OHTvw4sULvXaIiIiI3i0FmsCa5c3khIiIiCi/8pWMKBSKbHNCinqOyN27d9G3b1/Y2dnB1NQUtWvXxsmTJ6XHhRCYNGkSnJ2dYWpqiqCgIMTFxRVpn4iIiEh/8jVnRAiB0NBQ6cfwXr58iU8++STb1TRbtmzRS+eePHkCPz8/BAQEYMeOHbC3t0dcXBxsbW2lOnPnzsWiRYuwevVquLu7Y+LEiQgODsalS5dgYmKil34QERFR0clXMhISEqK13LdvX7125k1z5syBq6srIiIipDJ3d3fp/0IIhIeHY8KECejcuTMAYM2aNXB0dMS2bdvQq1evIu0fERERFV6+kpHXk4Li8PvvvyM4OBjvv/8+Dh48iAoVKuDTTz/FoEGDAAA3b97EvXv3EBQUJK1jbW2NRo0a4dixY7kmI2lpaUhLS5OWk5KSALy61b1ardZL3zUaDQDAABooNfppsygYQANTU1NoNJpCxa7RvGonr3iVmgytf4ubvuIFdI9ZV0U1NsW9j/Utv+NS2uPNj6wxeZdiBvKON6ssr7EoK/Hmh65jU5A2C0MhSvAs1KzTLKNHj8b777+PEydOYMSIEVi+fDlCQkJw9OhR+Pn5IT4+Hs7OztJ6PXv2hEKhwIYNG3Jsd8qUKZg6dWq28sjISJiZmRVNMERERGVQSkoKevfujWfPnsHKyqpAbZToZMTY2BgNGjTA0aNHpbLhw4fjxIkTOHbsWIGTkZyOjLi6uuLhw4cFHsg3nTlzBgkJCYh+YQ/H6r56abMoxF85jxUDAxEdHQ0fH58Ct3Pu3Dn4+/tj8I/74VK9Tq71lJoMeMZHIc4lABplgW4AXCj6ihfQPWZdFdXYFPc+1rf8jktpjzc/ssYm+oU9lg0MeidiBvLex2q1Gnv27EHr1q1hZGSUaztlJd780HVs8iMpKQnly5cvVDJS/J8G+eDs7IwaNWpolXl7e2Pz5s0AACcnJwBAYmKiVjKSmJgIX1/fXNtVqVTSJNzXGRkZ6W3nKJWvLlTKhBIapX7aLAqZUCI1NRVKpbJQsSuVr9rRNV6N0lCWcdFXvED+Y9aVvsdGrn2sb7qOS1mJNz/etZh1jTev9/SyFm9+6PPzTh/tFOo+I0XNz88PV65c0Sq7evUq3NzcALyazOrk5IR9+/ZJjyclJSEmJgZNmjQp1r4SERFRwZToIyOjRo1C06ZNMWvWLPTs2RPHjx/HihUrsGLFCgCv7nEycuRIzJgxA56entKlvS4uLujSpYu8nSciIiKdlOhk5L333sPWrVsxfvx4TJs2De7u7ggPD0efPn2kOuPGjcOLFy8wePBgPH36FM2aNcPOnTt5jxEiIqJSokQnIwDQsWNHdOzYMdfHFQoFpk2bhmnTphVjr4iIiEhfSvScESIiIir7mIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsmIwQERGRrJiMEBERkayYjBAREZGsSlUy8s0330ChUGDkyJFS2cuXLzF06FDY2dnBwsIC3bt3R2JionydJCIionwpNcnIiRMn8MMPP6BOnTpa5aNGjcL//vc/bNq0CQcPHkR8fDy6desmUy+JiIgov0pFMpKcnIw+ffpg5cqVsLW1lcqfPXuGn376CQsWLEBgYCDq16+PiIgIHD16FH/99ZeMPSYiIiJdGcrdAV0MHToUHTp0QFBQEGbMmCGVnzp1Cmq1GkFBQVKZl5cXKlWqhGPHjqFx48Y5tpeWloa0tDRpOSkpCQCgVquhVqv10meNRgMAMIAGSo1+2iwKBtDA1NQUGo2mULFrNK/ayStepSZD69/ipq94Ad1j1lVRjU1x72N9y++4lPZ48yNrTN6lmIG8480qy2ssykq8+aHr2BSkzcJQCCGEHvpSZH755RfMnDkTJ06cgImJCVq2bAlfX1+Eh4cjMjIS/fv310osAKBhw4YICAjAnDlzcmxzypQpmDp1arbyyMhImJmZFUkcREREZVFKSgp69+6NZ8+ewcrKqkBtlOgjI//88w9GjBiBPXv2wMTERG/tjh8/HqNHj5aWk5KS4OrqijZt2hR4IN905swZJCQkIPqFPRyr++qlzaIQf+U8VgwMRHR0NHx8fArczrlz5+Dv74/BP+6HS/U6udZTajLgGR+FOJcAaJTF//TTV7yA7jHrqqjGprj3sb7ld1xKe7z5kTU20S/ssWxg0DsRM5D3Plar1dizZw9at24NIyOjXNspK/Hmh65jkx9ZZxcKo0QnI6dOncL9+/dRr149qSwzMxPR0dFYsmQJdu3ahfT0dDx9+hQ2NjZSncTERDg5OeXarkqlgkqlylZuZGSkt52jVL6ajpMJJTRK/bRZFDKhRGpqKpRKZaFiVypftaNrvBqloSzjoq94gfzHrCt9j41c+1jfdB2XshJvfrxrMesab17v6WUt3vzQ5+edPtop0clIq1atcOHCBa2y/v37w8vLC1988QVcXV1hZGSEffv2oXv37gCAK1eu4M6dO2jSpIkcXSYiIqJ8KtHJiKWlJWrVqqVVZm5uDjs7O6k8LCwMo0ePRrly5WBlZYXPPvsMTZo0yXXyKhEREZUsJToZ0cXChQuhVCrRvXt3pKWlITg4GN9//73c3SIiIiIdlbpk5MCBA1rLJiYmWLp0KZYuXSpPh4iIiKhQSsVNz4iIiKjsYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLJiMkJERESyYjJCREREsmIyQkRERLIq0cnI7Nmz8d5778HS0hIODg7o0qULrly5olXn5cuXGDp0KOzs7GBhYYHu3bsjMTFRph4TERFRfpXoZOTgwYMYOnQo/vrrL+zZswdqtRpt2rTBixcvpDqjRo3C//73P2zatAkHDx5EfHw8unXrJmOviYiIKD8M5e7A2+zcuVNredWqVXBwcMCpU6fg7++PZ8+e4aeffkJkZCQCAwMBABEREfD29sZff/2Fxo0by9FtIiIiyocSnYy86dmzZwCAcuXKAQBOnToFtVqNoKAgqY6XlxcqVaqEY8eO5ZqMpKWlIS0tTVpOSkoCAKjVaqjVar30VaPRAAAMoIFSo582i4IBNDA1NYVGoylU7BrNq3byilepydD6t7jpK15A95h1VVRjU9z7WN/yOy6lPd78yBqTdylmIO94s8ryGouyEm9+6Do2BWmzMBRCCKGHvhQ5jUaD//znP3j69CkOHz4MAIiMjET//v21EgsAaNiwIQICAjBnzpwc25oyZQqmTp2arTwyMhJmZmb67zwREVEZlZKSgt69e+PZs2ewsrIqUBul5sjI0KFD8ffff0uJSGGMHz8eo0ePlpaTkpLg6uqKNm3aFHgg33TmzBkkJCQg+oU9HKv76qXNohB/5TxWDAxEdHQ0fHx8CtzOuXPn4O/vj8E/7odL9Tq51lNqMuAZH4U4lwBolMX/9NNXvIDuMeuqqMamuPexvuV3XEp7vPmRNTbRL+yxbGDQOxEzkPc+VqvV2LNnD1q3bg0jI6Nc2ykr8eaHrmOTH1lnFwqjVCQjw4YNw/bt2xEdHY2KFStK5U5OTkhPT8fTp09hY2MjlScmJsLJySnX9lQqFVQqVbZyIyMjve0cpfLV3OBMKKFR6qfNopAJJVJTU6FUKgsVu1L5qh1d49UoDWUZF33FC+Q/Zl3pe2zk2sf6puu4lJV48+Ndi1nXePN6Ty9r8eaHPj/v9NFOib6aRgiBYcOGYevWrdi/fz/c3d21Hq9fvz6MjIywb98+qezKlSu4c+cOmjRpUtzdJSIiogIo0UdGhg4disjISPz222+wtLTEvXv3AADW1tYwNTWFtbU1wsLCMHr0aJQrVw5WVlb47LPP0KRJE15JQ0REVEqU6GRk2bJlAICWLVtqlUdERCA0NBQAsHDhQiiVSnTv3h1paWkIDg7G999/X8w9JSIiooIq0cmILhf6mJiYYOnSpVi6dGkx9IiIiIj0rUTPGSEiIqKyj8kIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJiskIERERyYrJCBEREcmKyQgRERHJqswkI0uXLkXlypVhYmKCRo0a4fjx43J3iYiIiHRQJpKRDRs2YPTo0Zg8eTJOnz4NHx8fBAcH4/79+3J3jYiIiPJQJpKRBQsWYNCgQejfvz9q1KiB5cuXw8zMDD///LPcXSMiIqI8GMrdgcJKT0/HqVOnMH78eKlMqVQiKCgIx44dy3GdtLQ0pKWlScvPnj0DADx+/BhqtVov/UpKSkJKSgoS484iLeWFXtosCo/+iYOJiQmSkpLw6NGjAreTlJQEExMTJF45jYyU57nWM4AGruYpuHPmCDJlyIX1FS+ge8y6KqqxKe59rG/5HZfSHm9+ZI1NYtzZdyZmIO99rFarkZKSgkePHsHIyCjXdspKvPmh69jkx/Pnr8ZOCFHwRkQpd/fuXQFAHD16VKt87NixomHDhjmuM3nyZAGAf/zjH//4xz/+6envn3/+KfBneak/MlIQ48ePx+jRo6VljUaDx48fw87ODgqFQi/bSEpKgqurK/755x9YWVnppc2ygOOSO45NzjguuePY5IzjkruiGBshBJ4/fw4XF5cCt1Hqk5Hy5cvDwMAAiYmJWuWJiYlwcnLKcR2VSgWVSqVVZmNjUyT9s7Ky4oshBxyX3HFscsZxyR3HJmccl9zpe2ysra0LtX6pn8BqbGyM+vXrY9++fVKZRqPBvn370KRJExl7RkRERLoo9UdGAGD06NEICQlBgwYN0LBhQ4SHh+PFixfo37+/3F0jIiKiPJSJZOSDDz7AgwcPMGnSJNy7dw++vr7YuXMnHB0dZeuTSqXC5MmTs50OetdxXHLHsckZxyV3HJuccVxyV1LHRiFEYa7FISIiIiqcUj9nhIiIiEo3JiNEREQkKyYjREREJCsmIzJTKBTYtm2b3N0okAMHDkChUODp06ey9qM4x7CkxJylcuXKCA8Pl7sbhZbXPrx16xYUCgXOnj1bbH0qi0JDQ9GlSxe5uyGrKVOmwNfXV+5ulEhyjs07lYwoFIq3/k2ZMkXuLurF8uXLYWlpiYyMDKksOTkZRkZGaNmypVbdrA/X69evF3MvS5535flRHEJDQ3Mcw2vXruVYPyEhAe3atSvmXurXgwcPMGTIEFSqVAkqlQpOTk4IDg7GkSNHdFp/1apVRXbzxZKosONV1mS9Zj755JNsjw0dOhQKhQKhoaHF37FiUiYu7dVVQkKC9P8NGzZg0qRJuHLlilRmYWEhR7f0LiAgAMnJyTh58iQaN24MADh06BCcnJwQExODly9fwsTEBAAQFRWFSpUqwcPDQ84ulwi6PD9OnjxZJNtOT0+HsbFxkbQtl7Zt2yIiIkKrzN7eXms5K+7c7pZcmnTv3h3p6elYvXo1qlSpgsTEROzbt6/QP2xWEGq1Wm8/glZUStJ4lRSurq745ZdfsHDhQpiamgIAXr58icjISFSqVEnm3hWtd+rIiJOTk/RnbW0NhUIhLS9fvhzNmjXTqh8eHo7KlStrlf3444/w9vaGiYkJvLy88P3330uPpaenY9iwYXB2doaJiQnc3Nwwe/Zs6fG4uDj4+/vDxMQENWrUwJ49e7L18YsvvkC1atVgZmaGKlWqYOLEidIvCd+6dQtKpTLbB2J4eDjc3Nyg0WgAANWrV4ezszMOHDgg1Tlw4AA6d+4Md3d3/PXXX1rlAQEB0Gg0mD17Ntzd3WFqagofHx/8+uuvWtv5888/Ua1aNZiamiIgIAC3bt3Sejzrm92uXbvg7e0NCwsLtG3bVutDviSPYaNGjeDg4JDj88PJyUkrWT116hQaNGgAMzMzNG3aVCtpyelQ+MiRI7WOSrVs2RLDhg3DyJEjUb58eQQHB0MIgSlTpkjfFF1cXDB8+HBpnfv376NTp04wNTWFu7s71q9fny32BQsWoHbt2jA3N4erqys+/fRTJCcnAwBevHgBKyurbPt127ZtMDc3l355U1+yvu2+/teqVatscQPZT9McP34cdevWhYmJCRo0aIAzZ85otZ2ZmYmwsDDp+Vq9enV899130uPR0dEwMjLCvXv3tNYbOXIkmjdvrtc4AeDp06c4dOgQ5syZg4CAALi5uaFhw4YYP348/vOf/wB4+745cOAA+vfvj2fPnmU7EpfTKSwbGxusWrUKwP+dwtqwYQNatGgBExMTrF+/HpmZmRg9ejRsbGxgZ2eHcePGZftV1Z07d6JZs2ZSnY4dO2odJQ0MDMSwYcO01nnw4AGMjY217nqt7/HK6bTc06dPoVAopPe1rKO6+/bty/W1CADffPMNHB0dYWlpibCwMLx8+VLr8RMnTqB169YoX748rK2t0aJFC5w+fVp6fMCAAejYsaPWOmq1Gg4ODvjpp58KPAY5qVevHlxdXbFlyxapbMuWLahUqRLq1q0rlaWlpWH48OFwcHCAiYkJmjVrhhMnTkiPl8qxKfBP7JVyERERwtraWlqePHmy8PHx0aqzcOFC4ebmJi2vW7dOODs7i82bN4sbN26IzZs3i3LlyolVq1YJIYSYN2+ecHV1FdHR0eLWrVvi0KFDIjIyUgghRGZmpqhVq5Zo1aqVOHv2rDh48KCoW7euACC2bt0qbWP69OniyJEj4ubNm+L3338Xjo6OYs6cOdLjrVu3Fp9++qlWP+vUqSMmTZqkVda7d2/Rpk0bafm9994TmzZtEp988olUNyUlRahUKrFq1SoxY8YM4eXlJXbu3CmuX78uIiIihEqlEgcOHBBCCHHnzh2hUqnE6NGjxeXLl8W6deuEo6OjACCePHkijamRkZEICgoSJ06cEKdOnRLe3t6id+/epW4M33x+ZImKihIARKNGjcSBAwfExYsXRfPmzUXTpk2lOiEhIaJz585a640YMUK0aNFCWm7RooWwsLAQY8eOFZcvXxaXL18WmzZtElZWVuLPP/8Ut2/fFjExMWLFihXSOu3atRM+Pj7i2LFj4uTJk6Jp06bC1NRULFy4UKqzcOFCsX//fnHz5k2xb98+Ub16dTFkyBDp8UGDBon27dtr9e0///mP6NevX7ZYCyOnMcgtbiGE1j58/vy5sLe3F7179xZ///23+N///ieqVKkiAIgzZ84IIYRIT08XkyZNEidOnBA3btwQ69atE2ZmZmLDhg3StqpVqybmzp0rLaenp4vy5cuLn3/+Wa+xCiGEWq0WFhYWYuTIkeLly5c51nnbvklLSxPh4eHCyspKJCQkiISEBPH8+fNsY5PF2tpaRERECCGEuHnzpgAgKleuLL2u4uPjxZw5c4Stra3YvHmzuHTpkggLCxOWlpZa++XXX38VmzdvFnFxceLMmTOiU6dOonbt2iIzM1MIIcT69euFra2tVkwLFiwQlStXFhqNpsjGKyumrP0thBBPnjwRAERUVJQQQrfX4oYNG4RKpRI//vijuHz5svj666+FpaWl1nv9vn37xNq1a0VsbKw0To6OjiIpKUkIIcSRI0eEgYGBiI+Pl9bZsmWLMDc3l/aRPmS9ZhYsWCBatWollbdq1UosXLhQdO7cWYSEhAghhBg+fLhwcXERf/75p7h48aIICQkRtra24tGjR6V2bJiM/H+6JCMeHh7SB2OW6dOniyZNmgghhPjss89EYGBgji/SXbt2CUNDQ3H37l2pbMeOHTm+0bxu3rx5on79+tLyhg0btN4cTp06JRQKhbh586bWeitXrhTm5uZCrVaLpKQkYWhoKO7fvy8iIyOFv7+/EOLVEw2AuHXrljAzMxNHjx7VaiMsLEx8+OGHQgghxo8fL2rUqKH1+BdffJEtGQEgrl27JtVZunSpcHR0LHVjmFcysnfvXqnsjz/+EABEamqqEEL3ZKRu3bpadebPny+qVasm0tPTs233ypUrAoA4fvy4VBYbGysAaCUjb9q0aZOws7OTlmNiYrTePBITE4WhoaGUdOpLSEiIMDAwEObm5tJfjx49coxbCO0P3B9++EHY2dlJ4ymEEMuWLcv24fSmoUOHiu7du0vLc+bMEd7e3tLy5s2bhYWFhUhOTi58gDn49ddfha2trTAxMRFNmzYV48ePF+fOncu1/pv7JrfnnK7JSHh4uFYdZ2dnrWRMrVaLihUr5pgkZnnw4IEAIC5cuCCEECI1NVXY2tpqJXl16tQRU6ZMybUNXb1tvPKTjLzttdikSZNsXzwaNWqU7b3+dZmZmcLS0lL873//k8pq1Kih9YWmU6dOIjQ0tKCh5yjrfeP+/ftCpVKJW7duiVu3bgkTExPx4MEDKRlJTk4WRkZGYv369dK66enpwsXFRdrfpXFs3qnTNIXx4sULXL9+HWFhYbCwsJD+ZsyYIR3WDA0NxdmzZ1G9enUMHz4cu3fvltaPjY2Fq6ur1k8s5/RDfhs2bICfn590WmDChAm4c+eO9HiXLl1gYGCArVu3Anh1aiQgICDb6aSWLVvixYsXOHHiBA4dOoRq1arB3t4eLVq0kOaNHDhwAFWqVEFycjJSUlLQunVrrdjWrFkjxRYbG4tGjRppbSOn/puZmWnNP3F2dsb9+/dL5Ri+TZ06dbRiBCDFqav69etrLb///vtITU1FlSpVMGjQIGzdulWahBwbGwtDQ0Otdby8vLJNeNy7dy9atWqFChUqwNLSEh999BEePXqElJQUAEDDhg1Rs2ZNrF69GgCwbt06uLm5wd/fP19910VAQADOnj0r/S1atCjHuN8UGxuLOnXqSPOagJz389KlS1G/fn3Y29vDwsICK1as0NrPoaGhuHbtmnRactWqVejZsyfMzc31EV423bt3R3x8PH7//Xe0bdsWBw4cQL169aTTKXntm8Jq0KCB9P9nz54hISFB6zVraGioVQd4ddrzww8/RJUqVWBlZSW9BrLG0cTEBB999BF+/vlnAMDp06fx999/62UiZV7jpau3vRZ1ed9KTEzEoEGD4OnpCWtra1hZWSE5OVnruTRw4EBp/lNiYiJ27NiBAQMG5KufurK3t0eHDh2watUqREREoEOHDihfvrz0+PXr16FWq+Hn5yeVGRkZoWHDhoiNjdVqqzSNDZOR/0+pVGY7n5o1zwCAdG535cqVWm+wf//9t/RmV69ePdy8eRPTp09HamoqevbsiR49eujch2PHjqFPnz5o3749tm/fjjNnzuDrr79Genq6VMfY2Bj9+vVDREQE0tPTERkZmeOOr1q1KipWrIioqChERUWhRYsWAAAXFxe4urri6NGjiIqKQmBgoBTbH3/8oRXbpUuXss0vyMubk+YUCoU0rqVtDHWNU6FQAIA0Zyev51KWNz8UXV1dceXKFXz//fcwNTXFp59+Cn9//xzXzcmtW7fQsWNH1KlTB5s3b8apU6ewdOlSANCKf+DAgdIbfkREBPr37y/FoE/m5uaoWrWq9Jf1ZqiPZOCXX37BmDFjEBYWht27d+Ps2bPo37+/VpwODg7o1KkTIiIiivwDJIuJiQlat26NiRMn4ujRowgNDcXkyZN13jc5ef01lEWX55MuOnXqhMePH2PlypWIiYlBTExMtj4NHDgQe/bswb///ouIiAgEBgbCzc0t39vKSW7jpVS++mh6Pe7cXgdvey3qIiQkBGfPnsV3332Ho0eP4uzZs7Czs9Mag379+uHGjRs4duwY1q1bB3d39yKZe5RlwIABWLVqFVavXl2o52xpGpt36mqat7G3t8e9e/cghJB22uuTpxwdHeHi4oIbN26gT58+ubZjZWWFDz74AB988AF69OiBtm3b4vHjx/D29sY///yDhIQE6U359YmkAHD06FG4ubnh66+/lspu376dbRsDBw5ErVq18P333yMjIwPdunXLsS8BAQE4cOAAnjx5grFjx0rl/v7+2LFjB44fP44hQ4agRo0aUKlUuHPnjpS0vMnb2xu///67Vtmb/c9LaRzDgrC3t8fff/+tVXb27Fmdrm4wNTVFp06d0KlTJwwdOhReXl64cOECvLy8kJGRgVOnTuG9994DAFy5ckXrfienTp2CRqPB/PnzpTfzjRs3ZttG3759MW7cOCxatAiXLl1CSEhIIaLVP29vb6xdu1brqq839/ORI0fQtGlTfPrpp1JZTpenDxw4EB9++CEqVqwIDw8PrW+TxaFGjRrYtm2bTvvG2NgYmZmZ2dqwt7fXmgQeFxeX59EUa2trODs7IyYmRjrqlfX8qVevHgDg0aNHuHLlClauXCl9eBw+fDhbW7Vr10aDBg2wcuVKREZGYsmSJfkYgfzJGq+sq64SEhKkiZsFuceMt7c3YmJi0K9fP6ksp+fS999/j/bt2wMA/vnnHzx8+FCrjp2dHbp06YKIiAgcO3asyH8Rvm3btkhPT4dCoZAmeWfx8PCAsbExjhw5IiWFarUaJ06cwMiRI3XeRkkbGyYj/1/Lli3x4MEDzJ07Fz169MDOnTuxY8cOWFlZSXWmTp2K4cOHw9raGm3btkVaWhpOnjyJJ0+eYPTo0ViwYAGcnZ1Rt25dKJVKbNq0CU5OTrCxsUFQUBCqVauGkJAQzJs3D0lJSVofmADg6emJO3fu4JdffsF7772HP/74QzqV8Dpvb280btwYX3zxBQYMGCBdAvamgIAADB06FGq1WivJaNGiBYYNG4b09HQEBATA0tISY8aMwahRo6DRaNCsWTM8e/YMR44cgZWVFUJCQvDJJ59g/vz5GDt2LAYOHIhTp07l+3BqaRzDgggMDMS8efOwZs0aNGnSBOvWrcPff/+tNRs+J6tWrUJmZiYaNWoEMzMzrFu3DqampnBzc4OdnR3atm2Ljz/+GMuWLYOhoSFGjhyp1e+qVatCrVZj8eLF6NSpE44cOYLly5dn246trS26deuGsWPHok2bNqhYsaLeYteH3r174+uvv8agQYMwfvx43Lp1C99++61WHU9PT6xZswa7du2Cu7s71q5dixMnTsDd3V2rXnBwMKysrDBjxgxMmzatyPr86NEjvP/++xgwYADq1KkDS0tLnDx5EnPnzkXnzp112jeVK1dGcnIy9u3bBx8fH5iZmcHMzAyBgYFYsmQJmjRpgszMTHzxxRc6JbYjRozAN998A09PT3h5eWHBggVayautrS3s7OywYsUKODs7486dO/jyyy9zbGvgwIEYNmwYzM3N0bVr10KNFZD3eJmamqJx48b45ptv4O7ujvv372PChAn53s6IESMQGhqKBg0awM/PD+vXr8fFixdRpUoVqY6npyfWrl2LBg0aICkpCWPHjs3x/WDgwIHo2LEjMjMzizyBNzAwkE65GBgYaD1mbm6OIUOGYOzYsShXrhwqVaqEuXPnIiUlBWFhYTpvo8SNTb5nmZQROU0WW7ZsmXB1dRXm5uaiX79+YubMmVoTWIV4Nbvc19dXGBsbC1tbW+Hv7y+2bNkihBBixYoVwtfXV5ibmwsrKyvRqlUrcfr0aWndK1euiGbNmgljY2NRrVo1sXPnzmyT08aOHSvs7OyEhYWF+OCDD8TChQtznNT2008/ZZvQ+KasSWBeXl5a5bdu3RIARPXq1aUyjUYjwsPDRfXq1YWRkZGwt7cXwcHB4uDBg1Kd//3vf6Jq1apCpVKJ5s2bi59//jnbBNY3+7p161bx5tOsNIxhXhNYs2IWQogzZ84IAFoTYCdNmiQcHR2FtbW1GDVqlBg2bFi2CawjRozINlaNGjUSVlZWwtzcXDRu3FhrAlpCQoLo0KGDUKlUolKlSmLNmjXCzc1NawLrggULhLOzszA1NRXBwcFizZo12forxP9NXt64cWO2GPXhbVfTvBm3ENknaR47dkz4+PgIY2Nj4evrKzZv3qw1ofHly5ciNDRUWFtbCxsbGzFkyBDx5Zdf5jj5buLEidlm/Ovby5cvxZdffinq1asnrK2thZmZmahevbqYMGGCSElJEULotm8++eQTYWdnJwCIyZMnCyGEuHv3rmjTpo0wNzcXnp6e4s8//8xxAuubk3vVarUYMWKEsLKyEjY2NmL06NGiX79+Wvtlz549wtvbW6hUKlGnTh1x4MCBHCfMPn/+XJiZmWWb8FiU43Xp0iXRpEkTYWpqKnx9fcXu3btznMCa12tx5syZonz58sLCwkKEhISIcePGaT1PTp8+LRo0aCBMTEyEp6en2LRpU7bXlRCv3iPd3NyyXY2mL7m9ZrK8fjVNamqq+Oyzz0T58uWFSqUSfn5+Wu9jpXFsFEK8cTKSSoXp06dj06ZNOH/+vNxdKbXe5TFcu3YtRo0ahfj4+DJ3s7U3hYWF4cGDB9lOM5Lubt26BQ8PD5w4cUI6zfOuSU5ORoUKFRAREaHX07plgT7GhqdpSpnk5GTcunULS5YswYwZM+TuTqn0Lo9hSkoKEhIS8M033+Djjz8u04nIs2fPcOHCBURGRjIRKSC1Wo1Hjx5hwoQJaNy48TuZiGg0Gjx8+BDz58+HjY2NdBM70vPYFPiYCskiJCREGBsbi549e4qMjAy5u1MqvctjOHnyZGFoaCgCAwP1esOmkqhFixbC1NRUjBw5Uu6ulFpZh/urVasmzp8/L3d3ZJF1GqxixYpap01Jv2PD0zREREQkK95nhIiIiGTFZISIiIhkxWSEiIiIZMVkhIiIiGTFZISIiIhkxWSEiIrFkSNHULt2bRgZGaFLly46r7dq1apsv05cGpWVOIiKApMRojIgNDQUCoUCCoUCRkZGcHR0ROvWrfHzzz/n61c6i9Lo0aPh6+uLmzdv5vq7RpUrV0Z4eHix9ouI5MdkhKiMaNu2LRISEnDr1i3s2LEDAQEBGDFiBDp27IiMjAy5u4fr168jMDAQFStW5BECItLCZISojFCpVHByckKFChVQr149fPXVV/jtt9+wY8cOrSMRCxYsQO3atWFubg5XV1d8+umnSE5OBgC8ePECVlZW+PXXX7Xa3rZtG8zNzfH8+fMct52Wlobhw4fDwcEBJiYmaNasGU6cOAHg1e+aKBQKPHr0CAMGDIBCocjxyEjLli1x+/ZtjBo1SjrK87pdu3bB29sbFhYWUuL1uh9//BHe3t4wMTGBl5cXvv/++1zHavv27bCxsUFmZiaAVz9Pr1AotH61duDAgejbt6+0fPjwYTRv3hympqZwdXXF8OHD8eLFC60xGDNmDCpUqABzc3M0atQIBw4cyLUPDx48QIMGDdC1a1ekpaXlWo/oXcBkhKgMCwwMhI+PD7Zs2SKVKZVKLFq0CBcvXsTq1auxf/9+jBs3DsCrnyfv1asXIiIitNqJiIhAjx49YGlpmeN2xo0bh82bN2P16tU4ffo0qlatiuDgYDx+/Biurq5ISEiAlZUVwsPDkZCQgA8++CBbG1u2bEHFihUxbdo0JCQkaCUbKSkp+Pbbb7F27VpER0fjzp07GDNmjPT4+vXrMWnSJMycOROxsbGYNWsWJk6ciNWrV+fY3+bNm+P58+c4c+YMAODgwYMoX768VvJw8OBBtGzZEsCrozpt27ZF9+7dcf78eWzYsAGHDx/GsGHDpPrDhg3DsWPH8Msvv+D8+fN4//330bZtW8TFxWXb/j///IPmzZujVq1a+PXXX6FSqXLsJ9E7Qy83qCciWb3t58c/+OAD4e3tneu6mzZtEnZ2dtJyTEyMMDAwEPHx8UIIIRITE4WhoaE4cOBAjusnJycLIyMjsX79eqksPT1duLi4iLlz50plr//sfW5y+nnyiIgIAUBcu3ZNKlu6dKlwdHSUlj08PERkZKTWetOnTxdNmjTJdVv16tUT8+bNE0II0aVLFzFz5kxhbGwsnj9/Lv79918BQFy9elUIIURYWJgYPHiw1vqHDh0SSqVSpKamitu3bwsDAwNx9+5drTqtWrUS48ePl+KwtrYWly9fFq6urmL48OFCo9G8dTyI3hU8MkJUxgkhtE557N27F61atUKFChVgaWmJjz76CI8ePUJKSgoAoGHDhqhZs6Z0VGHdunVwc3ODv79/ju1fv34darUafn5+UpmRkREaNmyI2NhYvcRgZmYGDw8PadnZ2Rn3798H8OrU0vXr1xEWFgYLCwvpb8aMGbh+/XqubbZo0QIHDhyAEAKHDh1Ct27d4O3tjcOHD+PgwYNwcXGBp6cnAODcuXNYtWqVVvvBwcHQaDS4efMmLly4gMzMTFSrVk2rzsGDB7X6kJqaiubNm6Nbt2747rvvsp2KInpXGcrdASIqWrGxsXB3dwfwav5Gx44dMWTIEMycORPlypXD4cOHERYWhvT0dJiZmQF4NV9i6dKl+PLLLxEREYH+/fvL+sFpZGSktaxQKCD+/298Zs13WblyJRo1aqRVz8DAINc2W7ZsiZ9//hnnzp2DkZERvLy80LJlSxw4cABPnjxBixYtpLrJycn4+OOPMXz48GztVKpUCefPn4eBgQFOnTqVbZsWFhbS/1UqFYKCgrB9+3aMHTsWFSpU0HEEiMo2HhkhKsP279+PCxcuoHv37gCAU6dOQaPRYP78+WjcuDGqVauG+Pj4bOv17dsXt2/fxqJFi3Dp0iWEhITkug0PDw8YGxvjyJEjUplarcaJEydQo0aNfPXX2NhYmlSqK0dHR7i4uODGjRuoWrWq1l9WEpaTrHkjCxculBKPrGTkwIED0nwRAKhXrx4uXbqUrf2qVavC2NgYdevWRWZmJu7fv5/tcScnJ6kdpVKJtWvXon79+ggICMhx7IneRUxGiMqItLQ03Lt3D3fv3sXp06cxa9YsdO7cGR07dkS/fv0AAFWrVoVarcbixYtx48YNrF27FsuXL8/Wlq2tLbp164axY8eiTZs2qFixYq7bNTc3x5AhQzB27Fjs3LkTly5dwqBBg5CSkoKwsLB8xVC5cmVER0fj7t27ePjwoc7rTZ06FbNnz8aiRYtw9epVXLhwAREREViwYEGu69ja2qJOnTpYv369lHj4+/vj9OnTuHr1qtaRkS+++AJHjx7FsGHDcPbsWcTFxeG3336TJrBWq1YNffr0Qb9+/bBlyxbcvHkTx48fx+zZs/HHH39obdfAwADr16+Hj48PAgMDce/evXyMEFEZJfOcFSLSg5CQEAFAABCGhobC3t5eBAUFiZ9//llkZmZq1V2wYIFwdnYWpqamIjg4WKxZs0YAEE+ePNGqt2/fPgFAbNy4Mc/tp6amis8++0yUL19eqFQq4efnJ44fP65VR5cJrMeOHRN16tQRKpVKZL09ZU38fN3WrVvFm29f69evF76+vsLY2FjY2toKf39/sWXLlrdub8SIEQKAiI2Nlcp8fHyEk5NTtrrHjx8XrVu3FhYWFsLc3FzUqVNHzJw5U3o8PT1dTJo0SVSuXFkYGRkJZ2dn0bVrV3H+/Pkc41Cr1aJbt27C29tbJCYmvrWfRGWdQoj/f+KViOg1a9euxahRoxAfHw9jY2O5u0NEZRgnsBKRlpSUFCQkJOCbb77Bxx9/zESEiIoc54wQkZa5c+fCy8sLTk5OGD9+vNzdIaJ3AE/TEBERkax4ZISIiIhkxWSEiIiIZMVkhIiIiGTFZISIiIhkxWSEiIiIZMVkhIiIiGTFZISIiIhkxWSEiIiIZPX/AFW975j61U7cAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 600x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import matplotlib package\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plotting histogram\n",
    "plt.style.use(\"default\")\n",
    "plt.figure(figsize=(6,4)) # specify size of the chart\n",
    "plt.hist(df_activity.day_of_the_week, bins = 7, \n",
    "         width = 0.6, color = \"lightskyblue\", edgecolor = \"black\")\n",
    "\n",
    "# adding annotations and visuals\n",
    "plt.xlabel(\"Day of the week\")\n",
    "plt.ylabel(\"Frequency\")\n",
    "plt.title(\"No. of times users logged in app across the week\")\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "about-secretariat",
   "metadata": {
    "papermill": {
     "duration": 0.034195,
     "end_time": "2022-10-14T21:40:34.068244",
     "exception": false,
     "start_time": "2022-10-14T21:40:34.034049",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "##### **Frequency of usage across the week**\n",
    "\n",
    "In this histogram, we are looking at the frequency of FitBit app usage in terms of days of the week. \n",
    "\n",
    "1. We discovered that users prefer or remember (giving them the doubt of benefit that they forgotten) to track their activity on the app during midweek from Tuesday to Friday. \n",
    "\n",
    "2. Noting that the frequency dropped on Friday and continue on weekends and Monday. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "superb-valentine",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:34.146528Z",
     "iopub.status.busy": "2022-10-14T21:40:34.145563Z",
     "iopub.status.idle": "2022-10-14T21:40:34.497265Z",
     "shell.execute_reply": "2022-10-14T21:40:34.497800Z",
     "shell.execute_reply.started": "2021-07-09T05:00:05.215972Z"
    },
    "papermill": {
     "duration": 0.395596,
     "end_time": "2022-10-14T21:40:34.497972",
     "exception": false,
     "start_time": "2022-10-14T21:40:34.102376",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import matplotlib package\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plotting scatter plot\n",
    "plt.style.use(\"default\")\n",
    "plt.figure(figsize=(8,6)) # specify size of the chart\n",
    "plt.scatter(df_activity.total_steps, df_activity.calories, \n",
    "            alpha = 0.8, c = df_activity.calories, \n",
    "            cmap = \"Spectral\")\n",
    "\n",
    "# add annotations and visuals\n",
    "median_calories = 2303\n",
    "median_steps = 7637\n",
    "\n",
    "plt.colorbar(orientation = \"vertical\")\n",
    "plt.axvline(median_steps, color = \"Blue\", label = \"Median steps\")\n",
    "plt.axhline(median_calories, color = \"Red\", label = \"Median calories burned\")\n",
    "plt.xlabel(\"Steps taken\")\n",
    "plt.ylabel(\"Calories burned\")\n",
    "plt.title(\"Calories burned for every step taken\")\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "configured-transportation",
   "metadata": {
    "papermill": {
     "duration": 0.038706,
     "end_time": "2022-10-14T21:40:34.575338",
     "exception": false,
     "start_time": "2022-10-14T21:40:34.536632",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "##### **Calories burned for every step taken**\n",
    "\n",
    "From the scatter plot, we discovered that:\n",
    "\n",
    "1. It is a positive correlation. \n",
    "\n",
    "2. We observed that intensity of calories burned increase when users are at the range of > 0 to 15,000 steps with calories burn rate cooling down from 15,000 steps onwards. \n",
    "\n",
    "3. Noted a few outliers:\n",
    "    - Zero steps with zero to minimal calories burned. \n",
    "    - 1 observation of > 35,000 steps with < 3,000 calories burned.\n",
    "    - Deduced that outliers could be due to natural variation of data, change in user's usage or errors in data collection (ie. miscalculations, data contamination or human error)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "determined-stack",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:34.660378Z",
     "iopub.status.busy": "2022-10-14T21:40:34.659595Z",
     "iopub.status.idle": "2022-10-14T21:40:34.981245Z",
     "shell.execute_reply": "2022-10-14T21:40:34.981743Z",
     "shell.execute_reply.started": "2021-07-09T05:00:05.590969Z"
    },
    "papermill": {
     "duration": 0.368244,
     "end_time": "2022-10-14T21:40:34.981925",
     "exception": false,
     "start_time": "2022-10-14T21:40:34.613681",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import matplotlib package\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plotting scatter plot\n",
    "plt.style.use(\"default\")\n",
    "plt.figure(figsize=(8,6)) # Specify size of the chart\n",
    "plt.scatter(df_activity.total_hours, df_activity.calories, \n",
    "            alpha = 0.8, c = df_activity.calories, \n",
    "            cmap = \"Spectral\")\n",
    "\n",
    "# adding annotations and visuals\n",
    "median_calories = 2303\n",
    "median_hours = 20\n",
    "median_sedentary = 991 / 60\n",
    "\n",
    "plt.colorbar(orientation = \"vertical\")\n",
    "plt.axvline(median_hours, color = \"Blue\", label = \"Median steps\")\n",
    "plt.axvline(median_sedentary, color = \"Purple\", label = \"Median sedentary\")\n",
    "plt.axhline(median_calories, color = \"Red\", label = \"Median hours\")\n",
    "plt.xlabel(\"Hours logged\")\n",
    "plt.ylabel(\"Calories burned\")\n",
    "plt.title(\"Calories burned for every hour logged\")\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "valid-richards",
   "metadata": {
    "papermill": {
     "duration": 0.041557,
     "end_time": "2022-10-14T21:40:35.064889",
     "exception": false,
     "start_time": "2022-10-14T21:40:35.023332",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "##### **Calories burned for every hour logged**\n",
    "\n",
    "The scatter plot is showing:\n",
    "\n",
    "1. A weak positive correlation whereby the increase of hours logged does not translate to more calories being burned. That is largely due to the average sedentary hours (purple line) plotted at the 16 to 17 hours range. \n",
    "\n",
    "2. Again, we can see a few outliers:\n",
    "   - The same zero value outliers\n",
    "   - An unusual red dot at the 24 hours with zero calorie burned which may be due to the same reasons as above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "focused-punch",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-14T21:40:35.183940Z",
     "iopub.status.busy": "2022-10-14T21:40:35.172564Z",
     "iopub.status.idle": "2022-10-14T21:40:35.396471Z",
     "shell.execute_reply": "2022-10-14T21:40:35.395978Z",
     "shell.execute_reply.started": "2021-07-09T05:00:05.939369Z"
    },
    "papermill": {
     "duration": 0.290737,
     "end_time": "2022-10-14T21:40:35.396631",
     "exception": false,
     "start_time": "2022-10-14T21:40:35.105894",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yZAnx8fG6+wMCApINGXbq1Il79+6xZMmSZHXExMTw7NmzVOusWrUqjo6OLFy4MMnyPLt27SIwMPCNZuC+fs4tW7bQokULOnTokOzD19eXp0+fsn37diDxa3Tu3Dm2bt2a7Fiv3qfU3s/UGBkZ0aFDB37++WdWrVpFfHx8uoam0zpPz549uXTpEh9//DFqtTrVmdhZzd3dndmzZzN9+nSqV6+eKedwdXVFrVZz6NChJPf/93sXUn8f0/uzFhkZmexn/tWi7uldRkoIkUh6GkWe4O7uztSpUxk/frxuuRlra2tu3rzJ1q1bGTRokG7NvdT06tWLlStX8uGHH3LixAm8vb159uwZe/fuZdiwYbRu3RofHx8GDx7M9OnTOXv2LB988AHGxsZcvXqVjRs38r///Y8OHTq8Ue0VK1ZErVbz7bffEhUVhampKfXr16dWrVrY2trSu3dvRo4ciUqlYtWqVcl+QZqYmDBp0iRGjBhB/fr16dSpE8HBwfj7++Pu7p6kJ6dnz55s2LCBIUOG8Pvvv1O7dm0SEhK4fPkyGzZs4Ndff031EgBjY2O+/fZb+vbti4+PD127dtUtuePm5saYMWPe6HUDbN++nadPn9KqVasUH69Zs6Zuoe/OnTvz8ccfs2nTJjp27Ei/fv2oUqUKjx49Yvv27SxcuBAvLy/c3d2xsbFh4cKFWFtbY2lpSY0aNShWrFiqdXTu3Jm5c+fy5Zdf4unpqVvySJ8qVaoAMHLkSBo3bpwsGDZv3pwCBQqwceNGmjZtmuq1eYYwatSoTD1+/vz56dixI3PnzkWlUuHu7s6OHTtSvGY2tfcxvT9rK1asYP78+bRt2xZ3d3eePn3KkiVLyJcvH82aNcvU1ylErmOgWdtCZJg3Wb5l8+bNyvvvv69YWloqlpaWSunSpZXhw4crQUFBujY+Pj5KuXLlUnz+8+fPlQkTJijFihVTjI2NFWdnZ6VDhw7K9evXk7RbvHixUqVKFcXc3FyxtrZWPD09lU8++UQJCQnRtXF1dVWaN2+e7Bw+Pj5JlsFRFEVZsmSJUrx4cUWtVidZquTo0aNKzZo1FXNzc6VQoULKJ598olsm5r/LmcyZM0dxdXVVTE1NlerVqytHjx5VqlSpojRp0iRJu9jYWOXbb79VypUrp5iamiq2trZKlSpVlMmTJytRUVFpvcXK+vXrlUqVKimmpqaKnZ2d0r17d+Xu3btJ2qT3a9ayZUvFzMxMefbsWapt+vTpoxgbGyvh4eGKoihKRESE4uvrqxQuXFgxMTFRXFxclN69e+seVxRF+emnn5SyZcsqGo0myRIv/11y5xWtVqsUKVJEAZSpU6cmezylpWLi4+OVESNGKA4ODopKpUpx2Zhhw4YpgLJmzRq978PrUlty57/vZWrL2vzX60vu6EM6l9yxtLRM9Ryve/jwodK+fXvFwsJCsbW1VQYPHqxcvHjxjd/HtH7WTp8+rXTt2lUpWrSoYmpqqjg6OiotWrRQTp06pff1CiGSUynKG14lLYTIFbRaLQ4ODrRr1y7F4WiR+caMGcOPP/7I/fv3c/T+6EKIvEGuaRQiD3jx4kWyYeuVK1fy6NGjZNsIiqzx4sULVq9eTfv27SUwCiFyBLmmUYg84Pjx44wZM4aOHTtSoEABTp8+zY8//kj58uV1e1uLrBEWFsbevXvZtGkTERERmX79oBBCZBQJjULkAW5ubhQpUoQ5c+bo9jzu1asX33zzTbJFzEXmunTpEt27d8fR0ZE5c+boZvIKIUR2J9c0CiGEEEKINMk1jUIIIYQQIk0SGoUQQgghRJokNAohhBBCiDRJaBRCCCGEEGmS0CiEEEIIIdIkoVEIIYQQQqRJQqMQQgghhEiThEYhhBBCCJEmCY1CCCGEECJNEhqFEEIIIUSaJDQKIYQQQog0SWgUQgghhBBpktAohBBCCCHSJKFRCCGEEEKkSUKjEEIIIYRIk4RGIYQQQgiRJgmNQgghhBAiTRIahRBCCCFEmiQ0CiGEEEKINEloFEIIIYQQaZLQKIQQQggh0iShUQghhBBCpElCoxBCCCGESJOERiGEEEIIkSYJjUIIIYQQIk0SGoUQQgghRJokNAohhBBCiDRJaBRCCCGEEGmS0CiEEEIIIdIkoVEIIYQQQqRJQqMQQgghhEiThEYhhBBCCJEmCY1CCCGEECJNEhqFEEIIIUSaJDQKIYQQQog0SWgUQgghhBBpktAohBBCCCHSJKFRCCGEEEKkSUKjEEIIIYRIk4RGIYQQQgiRJgmNQgghhBAiTRIahRBCCCFEmiQ0CiGEEEKINEloFEIIIYQQaZLQKIQQQggh0iShUQghhBBCpElCoxBCCCGESJOERiGEEEIIkSYJjUIIIYQQIk0SGoUQQgghRJokNAohhBBCiDRJaBRCCCGEEGmS0CiEEEIIIdIkoVEIIYQQQqRJY+gChBACIC4uDq1Wi6Iouvte/Tu1zwDGxsaYmppmYaVCCJE3SWgUQmQ4RVGIjo7m4cOHST7Cw8P/vR0WxsOw0MR/h0cQ/Szmrc9nZmqCrU0+bG1tsbW1w8auALa2dtjb2+Ps7IyTk1OSzw4ODmg08t+fEEK8CZXy+p/sQgjxBp4+fUpgYCCXLl1K/Pz33wReusDde6G8jI1L1j6/hRoHKyMcLBUcLOJxsAQHK3CwBDsL0Lx2wYxK9c9nkt/3+v0v4yHqBUTGJH48/udz5As14c+NuP9EIfJZfJI6VCoVRV0KUqZsecqULUeZMmV0HwUKFMiYN0cIIXIZCY1CiDRFRETowuGlS5cIvPQ3l/6+wN2QB7o2bvbGlLGPp4yjgpsdukBob5n4b3tLMDFQ597LeAiLhvtP4EE0hD6Ba+EQGAaB4cbcCI9Dq01s61DAltJlyiQGytfCZJEiRVC9nlqFECKPkdAohEgiIiKCY8eOcfToUf48foxLf/9NWPgjAIyMoISDMWUd4ijjCGWdEj9KOYBlDr6s8EXcayHyQeLnyxHGXL6fwIu4xDRpaWFGubJl8fapR506dXj//fexs7MzcOXpoygK4eHhODg4GLoUIUQOJqFRiDxMURRu3LjB4cOHOXr0KEcPHyAw6BoABW00vFckngoF0QVEDwcwzUOXAmq1cCvy3zB5JgQOBWu48yhxuNuzXBnq1K1PnTp18Pb2pmDBggauOGXde/Rg7Zo1NGvWnFGjRtKwYUPpNRVCvDEJjULkMSEhIezfv5/9+/ezb89ubt8NRaWCcgU1vO8aT203qO0GbnZJryEU/7r1CA7dhIPX4VCwMVfDEq/f9HB3o07dBtSpU4c6derg6upq8HB2584dihUrhucHnXh442/uBZ2ndJmyjB41kh49emBpaWnQ+oQQOYeERiFyudjYWPbt28fOnTvZt2c3l69cB6BCYQ31i8dTvwR4FwcbcwMXmoOFPoHDN+DQDTh0S8OFe4k9kUUKO+NTryGtWrWiWbNmBglon3/+OTNnz+HT3cGYWFhx8/Rh/ljrx6UD27Gxs+OTsWMZPnw4VlZWWV6bECJnkdAoRC4UGxvL3r172bhxI9u2buZx1FOKO2ho6J4YEuu5g6O1oavMvSKewdHgxJ7IfTc0nLsbj7mZKc2aNadDx440b94ca+vM/wK8fPkSl6JF8ajfkVaf/JDksciQYA76f89fPy3HOl8+Pv7oI3x9fbOkLiFEziShUYhcIjY2lj179rBx40Z+2raFx1FPKeWkoaNnPB0rgGdBGW42lOvhsOk8bLqo4dTteMxMTWjSpAkdOnaiRYsW5M+fP1POGxAQQI8ePRiz+TyOxUqn2Obx/TscXD6DU9uWYW1txUcffsiIESPIly9fptQkhMi5JDQKkYO9CoobNmzgp21biHoSTSknDZ084+noBeWdJShmN8GPYPN52HRRzfHgBExMNHzQ6AM6dupMq1atsLGxybBz1XyvFo8UC/ot2JVm26gHdzno/z2ntv6IhYU5H44Zw8iRIzO0HiFEziahUYgcJjY2lt9++03Xoxj1JJrSzho6lpegmNPcjoQtFxID5NEbCRgba2jYoAEdO3WmQ4cO7zRU/Ndff1G1alV6zNxIuXqt0/28qLB7HFoxk5NblmJuZsqY0aP56KOPZNhaCCGhUYicIiQkhMWLF7NowTzuh4VTxvnfoedyEhRzvHtR/wTIC2oO30jA0sKcHj17M3jwYCpWrPjGx+vbty/bf93Phz9dRv0WWyY+eRjKoRUzObF5MbY2Nnwz/Wt69+6NkZFR2k8WQuRKEhqFyMYUReHYsWP4zZ3Lps2bMFUr9KqsZch7co1ibnbnMSz9E5ae1BDyOJ4a1aoweOhwOnfujIWFRZrPj4iIoLCLC3UHTKBuv3HvVMvj0NvsnvMZ537dQKXKVZg753/Url37nY4phMiZJDQKkQ3FxMSwdu1a/ObM5sy5C3g4ahj+Xjx9qkJ+WRonz4hPgB2BsPC4Eb8FaclnbcX+3w9SuXJlvc+bMWMGn034nHG7b2JlmzG7wASfOcrOmR9x99JpOnfpwnfffkvRokUz5NhCiJxBQqMQ2UhwcDALFixg6ZJFRD6OolkZI3xrafmgZOIWfiLv+jUImixJnBHdrVu3VNslJCTgXsIDu3K16PTV8gytQavVcvrnVezx+5zY508Y98knfPLJJ+nq/RRC5HwSGoUwMEVR2LdvH35z5/Dzjh1YmxnRv2oCQ2tBCXtDVyeyi1HbYM0lG+7cC8XMzCzVdjt27KBly5YMW3mUIuWrZUotL6KfcGDZNxwNmIOjoyPfz/iOLl26GHz3GyFE5pK+CyEMRKvVsn79esqXLU2jRo24fmoXC9op3JuQwMxWEhjFv6Jfgv9fagYOHqo3MAL4+c2jaLmqmRYYAcys8tFk5NeM3nQO25KV6datGw0bNSI4ODjTzimEMDwJjUJkMUVR2LFjB5UrVqBLly64qq5xYCicHxPPoJpgaWroCkV2s/oviH6pZciQIXrbXb16lV9/3U31TvrbZZQCRdzpMXMTff12cPbSVcqVL8+8efPQarVZcn4hRNaS0ChEFvr999+pXasmLVu2JP/zQA4Ph1/6a/Fxl5nQImWKAvOOa2jVsmWaE08WLFiAlU0BKnzQKYuqS1Sy1geMWH8az6bd8fX1pV69+ly/fj1LaxBCZD4JjUJkgRMnTtCoYX3q169PXMhf/DoQDgzR8n4xQ1cmsrtDN+BiSDzDfUfobffs2TN+XLaMKm36Ymyqfwg7M5hZ5aPNZ34MWPgrf9+4jWeFCvzvf/+TXkchchEJjUJkogsXLtCmdStq1KhB6KXDbOkNJ0Yk8EEp6VkU6TPvmIpSHu40aNBAb7uAgACinz6lRodBWVRZytyr12PEur+o2LIPo0ePxruOD1evXjVoTUKIjCGhUYhMcPXqVbp17YqXlxcXju1iVVc4Nyaetp4SFkX6vdolZviIUXpnJiuKwly/eZT2boZtIbesKzAVphZWtBo3m0FL9nHldiieFSowc+ZMEhISDF2aEOIdSGgUIgM9ePCAQQMHUqZMaQ79uomF7RUufxxPjyqglp828YYW/QHm5mb07t1bb7sjR45w8cJ5anYelkWVpU+xKt6MWPcXVdsP5uOPP6Zx4yY8ePDA0GUJId6S/BoTIgMkJCQwf/58SpUsweZ1y5nRXMu1TxJnQxurDV2dyIli42HxCQ09e/UhX758etv6zZuHo5sH7tXrZ1F16WdibkGLj2bQf8FuTp69gFfFShw8eNDQZQkh3oKERiHe0cmTJ6lRrQrDhw+nU5lornycwJg6YGZs6MpETrb5Ajx4Es/w4cP1tgsNDWXL5s1U7zgUo2y8bZB79Xr4rj2JlUtJ6tevz9dffy2TZITIYbLv/zBCZHORkZEMGzqUGjVqkPDwb/4YAYs7QgFLQ1cmcoN5f6ipV7cO5cqV09tu8eLFqE1MqdKiZxZV9vas7Z3pt2A3dft/yueff06zZs0JDw83dFlCiHSSbQSFeEOKorBhwwZGjhhGTHQUUz9IYFgt0MgwtMggZ+9BpR9g06ZNtG/fPtV2cXFxFCnqitv7LWnzmV8WVvjurvyxh01f9MHKzISNG9ZTu3ZtQ5ckhEiD9DQK8Qbu3r1L61Yt6dKlC3UKRXJ5bAIjvSUwiow17xi4FHKmdevWettt3bqVB/dDqZlFO8BkpJLvNWL4mhOYOxfDx8eH7777ToarhcjmJDQKkQ5arZZFixZRrmxpTh7ezZbesLGnQqH8hq5M5DaRzyHgjBGDhw5Ho9HobTtnrh/uVergXKJ8FlWXsfI7Fqbfwt94v9eHjBs3jrZt2xEdHW3osoQQqZDQKEQarl27Rv16PgwZMoROZZ8RODaBtp6GrkrkVstPQrxixMCBA/W2O3/+PEePHKZG56FZVFnmUGs0NBkxjV6zt/Lb3n28712He/fuGbosIUQKJDQKocfq1aup6OXJnUvH2TcYlnQEG3NDVyVyK60W5h/X0LFjR5ycnPS2nTdvHjaOhSjr0yqLqstcZeo0Z9CyA9y+/5Bq1Wtw9uxZQ5ckhPgPCY1CpODZs2f069uXnj170r7sS86Niae+h6GrErndr0Fw/WE8vmnsM/348WNWrV5N1fYDURvnnrWdCpaswJAVR1Dnd6T2+++zc+dOQ5ckhHiNhEYh/uPvv/+metXKrF+7Ev/OsKKLgpWpoasSeYHfMSMqeXlSs2ZNve38/f2Ji4ujetv+WVRZ1snnUIiBS/dTrFp9WrVqxdy5cw1dkhDiHxIahfiHoigsX76calWroIq6zskRWnpXM3RVIq+4Hg67LmvxHTla7z7TWq2WuX7zKNegHdb2zllYYdYxMbek24wN1Oo2kpEjRzJq1CjZt1qIbED/1Dwh8ojo6GiGDhnC6oAABtSA/7UGCxNDVyXykgV/gK1NPrp27aq33Z49e7hx/RqDJyzNosoMw0itpvmH31GgiDt+343m+vUbrFu3FisrK0OXJkSeJaFR5Hnnz5+nY/u2hNy9RUA36FbZ0BWJvOZ5LPx4Us2AYYMwN9c/02ruXD8Kl/bC1eu9LKrOsGp2HIxtITfWfdqNOj512fPbrxQoUMDQZQmRJ8nwtMizFEVh0aJFVK9WFfOYW/w1KkECozCItWcgKkbL0KH6l8+5efMmv/yykxodh+odws5tStVuzKAf93Mt+DY+desRFhZm6JKEyJMkNIo86cmTJ3Tt0oUhQ4bQt0ocx30TKOlg6KpEXqQo4PeHhmZNm1C8eHG9bRcsWIC5dX68mnTJouqyj4Ilvei/eA937j/Eu44PISEhhi4pRSqVim3btqW7/YEDB1CpVDx+/DjTz5VV6taty+jRow1dRjLv8l6LRBIaRZ4THBxMjWpV+OXnzazvAQvag1nuWbVE5DB/3IKzd+PxHTFSb7uYmBiW/vgjVVr3xcTcIouqy16cipdl4NJ9PIyKxruOD3fu3MnyGvr06UObNm1SfTw0NJSmTZtm6DknTZpExYoVM/SYGSG1ELZlyxa++uorwxSlR61atQgNDSV//ozdysvNzY3Zs2dn6DGzKwmNIk/566+/qFmjKrGPgjk1MoFOFQ1dkcjr/I6qKFHcjQ8++EBvu3Xr1vE4MpIaHQZlUWXZk31RDwYs2UfUi3je967DzZs3DV1SEs7Ozpia5u01uuzs7LC2tjZ0GcmYmJjg7Oycpy7tyGgSGkWesXPnTup4v4+r+WP+GB4vw9HC4O4/gU0XYJjvSIyMUv/vWFEU5sz1o1TtJhQo4p6FFWZPdoWLMWDxXmIUDe971+Hq1auGLknnv0PGx44do2LFipiZmVG1alW2bduGSqVKtuPNX3/9RdWqVbGwsKBWrVoEBQUBiWtyTp48mXPnzqFSqVCpVPj7+yc7b/369fH19U1y38OHDzExMWHfvn0p1nr9+nVat26Nk5MTVlZWVKtWjb179yZp8/LlS8aNG0eRIkUwNTWlRIkS/PjjjwQHB1OvXj0AbG1tUalU9OnTB0g6PP3ZZ59Ro0aNZOf28vJiypQputtLly6lTJkymJmZUbp0aebPn59iza/UrVuXESNGMHr0aGxtbXFycmLJkiU8e/aMvn37Ym1tTYkSJdi1a5fuOf/tGfX398fGxoZff/2VMmXKYGVlRZMmTQgNDU1ynv8Otbdp0ybJa7116xZjxozRfX1eOXLkCN7e3pibm1OkSBFGjhzJs2fPdI/Pnz8fDw8PzMzMcHJyokOHDnpfc3YgoVHkCYsXL6ZVq5Y0cn/J74MTcMx+fwSLPGjJn6DRmOh+AaXmzz//5OyZ09ToNCRrCssBbAoWZcCSvSSYWOJdx4fAwEBDl5TMkydPaNmyJZ6enpw+fZqvvvqKcePGpdh2woQJzJw5k1OnTqHRaOjXrx8AnTt35qOPPqJcuXKEhoYSGhpK586dkz1/wIABrFmzhpcvX+ruW716NYULF6Z+/fopnjM6OppmzZqxb98+zpw5Q5MmTWjZsiW3b9/WtenVqxdr165lzpw5BAYGsmjRIqysrChSpAibN28GICgoiNDQUP73v/8lO0f37t05ceIE169f1933999/c/78ebp16wZAQEAAEydOZNq0aQQGBvL111/zxRdfsGLFCr3v74oVK7C3t+fEiROMGDGCoUOH0rFjR2rVqsXp06f54IMP6NmzJ8+fP0/1GM+fP+f7779n1apVHDp0iNu3bzN27Fi9533dli1bcHFxYcqUKbqvDyQG8iZNmtC+fXvOnz/P+vXrOXLkiC7Ynzp1ipEjRzJlyhSCgoLYvXs3derUSfd5DUVCo8jVFEXhs88+Y/DgwQytqbC5lyLrL4psIS4BFp3Q0KNHT2xtbfW29fPzw96lOCVrNc6i6nKGfA6FGLBkH0bWBfD28eHixYuGLimJNWvWoFKpWLJkCWXLlqVp06Z8/PHHKbadNm0aPj4+lC1blk8//ZRjx47x4sULzM3NsbKyQqPR4OzsjLOzc4rLMrVr1w6An376SXefv78/ffr0SXU41svLi8GDB1O+fHk8PDz46quvcHd3Z/v27QBcuXKFDRs2sGzZMtq2bUvx4sVp0KABnTt3Rq1WY2dnB4CjoyPOzs4pXitYrlw5vLy8WLNmje6+gIAAatSoQYkSJQD48ssvmTlzJu3ataNYsWK0a9eOMWPGsGjRIr3vr5eXF59//jkeHh6MHz8eMzMz7O3tGThwIB4eHkycOJGIiAjOnz+f6jHi4uJYuHAhVatWpXLlyvj6+qbaM5sSOzs71Go11tbWuq8PwPTp0+nevTujR4/Gw8ODWrVqMWfOHFauXMmLFy+4ffs2lpaWtGjRAldXVypVqsTIkfqva84OJDSKXCs2NpaePXowffp0ZrSAuW1BLd/xIpv46SLci4xn+H+GFP/rwYMHbNi4keodB+sdws6rrOwc6b9oD6Z2BWn0QWNu3bpl6JJ0goKCqFChAmZmZrr7qlevnmLbChUq6P5dsGBBgDdaWsjMzIyePXuybNkyAE6fPs3Fixf19mJHR0czduxYypQpg42NDVZWVgQGBup6Gs+ePYtarcbHxyfddaSke/fuutCoKApr166le/fuADx79ozr16/Tv39/rKysdB9Tp05N0juZktffM7VaTYECBfD09NTd5+TkBOh/Hy0sLHB3//eSj4IFC2bIkk7nzp3D398/yWtq3LgxWq2Wmzdv0qhRI1xdXSlevDg9e/YkICBAb49odiGLe4tc6fHjx7Rr25qjR46wrgd0rmjoioRIyu8PI96vVQMvLy+97ZYuXYrKSE2VVr2zqLKcx9KmAH3m7mBxv7o0bPQBx44ewcEhZ120bGz87xIOr3oGtVrtGx1jwIABVKxYkbt377J8+XLq16+Pq6trqu3Hjh3Lnj17+P777ylRogTm5uZ06NCB2NhYgDQXmk+vrl27Mm7cOE6fPk1MTAx37tzRDbFHR0cDsGTJkmTXPqrVar3Hff09g8T37U3fx5SOoSiK7raRkVGS25DYO5mW6OhoBg8enGLvYdGiRTExMeH06dMcOHCA3377jYkTJzJp0iROnjyJjY1Nmsc3FPmzVeQ6t2/f5v1aNTl78ih7B2klMIps52IoHLymxXfkKL3t4uPjmb9gIRWadMEiv10WVZczWds702feTsIeRdG0WXNdGDGkUqVKceHChSTXGZ48efKNj2NiYpKuvbc9PT2pWrUqS5YsYc2aNbrrIlNz9OhR+vTpQ9u2bfH09MTZ2Zng4OAkx9NqtRw8eDDVuoA0a3NxccHHx4eAgAACAgJo1KgRjo6OQGJvYKFChbhx4wYlSpRI8lGsWLE0X3Nmc3BwSDIxJiEhIdllECl9fSpXrsylS5eSvaYSJUro3jeNRkPDhg357rvvOH/+PMHBwezfvz/zX9Q7kNAocpWzZ89Ss3pVnoVd5+iwBLz1r5UshEHMOwbOjva0bdtWb7vt27cTcu8u78kEmHQpUMSd3nO383fgZdq2bafrMctoUVFRnD17NslHSmtGduvWDa1Wy6BBgwgMDOTXX3/l+++/B3ijZV/c3Ny4efMmZ8+eJTw8PEkI/a8BAwbwzTffoChKmt9fHh4ebNmyhbNnz3Lu3Dldva+ft3fv3vTr149t27Zx8+ZNDhw4wIYNGwBwdXVFpVKxY8cOHj58qDeod+/enXXr1rFx40bd0PQrkydPZvr06cyZM4crV65w4cIFli9fzqxZs9Lz9mSq+vXrs3PnTnbu3Mnly5cZOnRosnUp3dzcOHToEPfu3SM8PByAcePGcezYMXx9fTl79ixXr17lp59+0k2E2bFjB3PmzOHs2bPcunWLlStXotVqKVWqVFa/xDcioVHkGn/++Sd1vGtTyOQRfwyPp4yToSsSIrmoGFh12ojBQ4frehxSM9dvHm4V36NQ6UpZVF3OV6h0JXrM2syBgwfp3afPGw/xpseBAweoVKlSko/Jkycna5cvXz5+/vlnzp49S8WKFZkwYQITJ04ESHKdY1rat29PkyZNqFevHg4ODqxduzbVtl27dkWj0dC1a9c0zzFr1ixsbW2pVasWLVu2pHHjxlSunHQv1QULFtChQweGDRtG6dKlGThwoG7ZmMKFCzN58mQ+/fRTnJycki3587oOHToQERHB8+fPky2OPmDAAJYuXcry5cvx9PTEx8cHf3//bNHT2K9fP3r37k2vXr3w8fGhePHiuqWGXpkyZQrBwcG4u7vrLouoUKECBw8e5MqVK3h7e1OpUiUmTpxIoUKFALCxsWHLli3Ur1+fMmXKsHDhQtauXUu5cuWy/DW+CZXy38F6IXKg06dPU7+eD+UKxLC7fwLW6f//WIgsNecwfLRTza1bt3W/QFJy6dIlypUrR+evV1IxD24b+K4u7tvCmk+6MmLECGbPnp1tFnQOCAigb9++REVFZdg1g697FV5OnjyZLAAK8a5kIozI8S5cuECjhvUpaRPDL/0kMIrsS6uFecc1tGvbVm9ghMSFf/MVcKJ8g3ZZVF3uUr5BO1qP92PO18NxcnLis88+M0gdK1eupHjx4hQuXJhz584xbtw4OnXqlOGBMS4ujoiICD7//HNq1qwpgVFkCgmNIkcLDAykQX0filpG8+uABPJn/B/uQmSYfdfgyoN4lqSxzM6TJ0/wX7GCGl1HojGWhUXfVo0OA4l+9IAJEybg7Oyc5sSQzHD//n0mTpzI/fv3KViwIB07dmTatGkZfp6jR49Sr149SpYsyaZNmzL8+EKADE+LHOzq1av4eNemgPoRvw9OwN7S0BUJoV8bfxU3lNKcu/C33uFSPz8/Ro0ezSc7r5HfsXAWVpj7KIrCtq99ObPdn/379/P+++8buiQhciyZCCNypJs3b1K/bh3yqyLZO1ACo8j+bj2Cny/B8BGj9AZGRVGY6zePcvVaS2DMACqVilafzKaoVy3atGuXZIs8IcSbkdAocpw7d+5Qv24dzOLD2TcwHifZR1rkAAuPg7WVZbLlRv5r//79XAm6TM3Ow7KostxPbWxM12/XgoklLVu11s3+FUK8GQmNIkcJCQmhft068Ow++wfFUyj5VqdCZDsv4mDJCTV9+w3AyspKb1u/efMo6F6WYpW9s6i6vMHS1p4eszYTdPUqffr2TbbLhxAibRIaRY4RFhZGg3o+vIi8y/5B8RSxMXRFQqTP+rMQEZ3AsGH6ew9v377N9p9+okbnYdlmiZjcxNnDk45TlrNp40ZmzJhh6HKEyHEkNIocISIigob16xL1IJj9g+IpVsDQFQmRfvOOq2n8QUM8PDz0tlu0aBGmFlZUbNYtiyrLe8rVb0Pdvp8wfvx49u3bZ+hyhMhRJDSKbO/Fixe0atGc+7evsG9QPB4Ohq5IiPQ7cRtO3kpguO9Ive1evnzJosVLqNSyF6YW+oewxbtpNGwy7tXr06lLF5kYI8QbkNAosjVFUejXty+nT5/k5z4JsjWgyHHmHQO3oi40a9ZMb7uNGzcSEf6Qmh0HZ1FleZeRWk3naSvB2IJ27Tvo3ctZCPEvCY0iW5syZQpr161jZWctNVwNXY0Qb+ZhNKw7a8TQ4SNQq9V6286Z60fJmg1xcCuVRdXlbZa29nSbsYFz584ZbLcYIXIaCY0i21qzZg2TJk1iWlPo6GXoaoR4cz+eACO1hv79++ttd+rUKU6e+JManYdmUWUCoHDZyjQeMY1Zs2axd+9eQ5cjRLYnoVFkS0ePHqVvn970rgrj6xu6GiHeXIIWFhzX0KVrNwoU0D9za968edgVcqX0+/qHsEXGq9VtBB416tOzV28ePXpk6HKEyNYkNIps5/bt27Rt05KaRbUs6gCy8ojIiXZcgtuP4vFNY5/p8PBw1qxdS/UOgzBKYwhbZDwjIyPaT1rK0+cxDBo8WNZvFEIPCY0iW3n+/DltWrXAUnnK5l5aTDWGrkiIt+N3zIia1atRpUoVve2WLVuGokDV1n2zqDLxX/mdXGg9YT6bN21i5cqVhi5HiGxLQqPINhRFYdDAgVwO/JttveNlP2mRY10Og71XtAwfoX+ZnYSEBPzmzcezcScsbe2zqDqREs+G7ancsifDfX25ceOGocsRIluS0CiyjR9++IGANWtY3kmLVyFDVyPE25t/DBwK2NKxY0e97X755Rfu3L5FzU4yASY7aPnxD5jZONC9R0/i4+MNXY4Q2Y6ERpEt7N27l48/Hsu4etC5oqGrEeLtPX0B/n+pGTh4KKampnrbzp3rR9Hy1ShSrmoWVSf0MbPKR4cpyznx53G++eYbQ5cjRLYjoVEY3O3bt+ncqQONSqqY1tTQ1QjxblafhmcvtQwZMkRvuytXrrBnz2/U6KS/nchabhVr4dNvHJMmTeLUqVOGLkeIbEVCozCohIQEevXsjpXqGWu7aVHLd6TIwRQF/P7Q0LpVK4oUKaK37fz587Gytcezkf4hbJH1Ggz8nIIengwYOEiGqYV4jfyKFgY1c+ZMDh0+wsrO8dhaGLoaId7NwetwKTQe3zQmwERHR7Pc35+qbfphbGqWRdWJ9FIbG9Pqs3mcP3eWefPmGbocIbINCY3CYM6ePcvnn0/gYx/wcTd0NUK8O79jKsqU8qBevXp62wUEBBD99Ck1OgzKosrEmypSvhrVOwzi8y++4N69e4YuR4hsQUKjMIgXL17Qo1sXyjoqTGli6GqEeHd3H8O2izB8xChUelakVxSFOXP9KOPTApuCRbOuQPHGGvt+hcrEnNFjxhi6FCGyBQmNwiDGjx/PtWtXCeiaIAt4i1xh0XGwsDCnV69eetsdPnyYS39flGV2cgBzaxuafTiDTRs3snv3bkOXI4TBSWgUWW7Pnj3Mnj2bb5tpKeds6GqEeHcv42HxCQ29evfF2tpab9u5fn44uZXEvbpsqp4TeDXpgkeN+gwdNpyYmBhDlyOEQUloFFnq0aNH9OnVg4YljRhR29DVCJExNp+HsCfxDB8+XG+7e/fusW3rVqp3Gqp3CFtkHyqVipbj/sfde3eZPn26ocsRwqAkNIosoygKQwYPJuZpBP6dtRjJd5/IJfz+UFO/ng9lypTR227x4sVoTM2o3KJnFlUmMoKDWynq9B7LN998Q1BQkKHLEcJg5Ne2yDKrV69m46ZNLGqXQOH8hq5GiIxx+i78cTMB3xGj9LaLjY1l4aLFeDXrjplVviyqTmSUun3Hkd+5KEOGDkNRFEOXI4RBSGgUWeLWrVv4Dh9KzyoqOnoZuhohMs68Y1CkcEFatmypt92WLVsIe3Cf92QHmBzJ2Myc5h/P4sDv+9m1a5ehyxHCICQ0ikyn1Wrp1bM7tiYvmdtG/kIXucej57DmjBFDhvmi0ehfBmCu3zzcq/rg5F4ui6oTGa1U7Sa4V6nDuE/Ho9VqDV2OEFlOQqPIdCtWrODQ4aP4d4wnv7mhqxEi4yw7AVqMGDBggN52586d49jRI9TsLMvs5GQqlYpGvlO5eOE8a9euNXQ5QmQ5lSIXZ4hMFBUVRUmP4jR0iSSgu3yridwjQQslv9NQq0lnVq1arbftwIED2bxjNx9tv4I6jR5Jkf2t/rA90cEXuRJ0GRMTE0OXI0SWkZ5GkakmT57MsyeP+a6FBEaRu+y+DDfC4/H1HaG3XWRkJKsDAqjaboAExlyi0fAp3Ll9i8WLFxu6FCGylIRGkWkuXbrE3Llz+LyBVmZLi1xn3h9GVKnkRfXq1fW2W758OfHx8VRr2z+LKhOZzcm9HJWa92DyV18RHR1t6HKEyDISGkWmUBSFUSN9cbNTMaaOoasRImNdC4ddgVp8R47Wu0i3VqvFb958yjdsj3UBpyysUGS2BoO/4HHkY3744QdDlyJElpHQKDLFtm3b2Lvvd2a3iJe9pUWus+AY2Nnmp3Pnznrb/frrr9y8cZ2anYZlUWUiq9gWcqVGp6F8N2MG4eHhhi5HiCwhoVFkuJiYGD4cPZJmZY1oXtbQ1QiRsZ69hGWn1AwYOBhzc/3LAfj5zcOldEWKVqiRRdWJrFS33yfEa5HtBUWeIaFRZLgZM2ZwL+Qes1vKOmYi91lzBqJitAwZon+R7hs3brBr1y/U6DRM9pnOpaxsHXi/5xj85s3jwYMHhi5HiEwnoVFkqFu3bjH962l86K3g4WDoaoTIWIoC8/5Q06J5M4oVK6a37YIFC7DIZ0OFxp2yqDphCLW6DEel1uDn52foUoTIdBIaRYYa+9GH2JppmdDA0JUIkfGOBsO5ewkMT2OZnefPn7P0xx+p3KovJuYWWVOcMAjzfLZUad2PefPn8+zZM0OXI0SmktAoMsy+ffvYtHkLM5rHY21m6GqEyHjzjqrwcC9Go0aN9LZbt24dUY8fU7PjoCyqTBjS+91HEhUVxbJlywxdihCZSnaEERkiISEBL89y2Ly8xuGhCcglXCK3CX0CRaep+H7mD4waNSrVdoqiUKlyFV5aF6T3/7ZlXYHCoNZ91pPHl09w7eqVNPchFyKnkp5GkSE2b97M34FBzGwugVHkTkuOg4mJKb1799bb7vjx45w7e4aanWSf6bzEu+eH3Aq+yZYtWwxdihCZRkKjeGdarZapUybxQSkjargauhohMl5cAiz8U0PPXr2xsbHR23aunx8ORUvg8Z7+IezMcPOvw6wY1YavP3BlfGUT/v79pySPb/yyP+MrmyT5WDa8hd5jahMS+G3+l3zXoiRfvJePGa1Ks2/JNF4fpDq0chZTGxRmaoPCHF6VdLHr2xdOMLdbDRLi4zPuhWZDhctUokT1enw343tkAE/kVtKHLt7Zjh07uPB3IPNk/WKRS227CKFR8QwfPlxvuwcPHrBp40Y+GPE1RkZZ/zd57ItnFCxZgaqt+7B6bMqztkvWakyHSUt0tzUmpnqPedB/Bn9uWkzHyT/i5F6Wu5f+YtOkgZhZ5ad2V19Cr5xn78LJ9J69DUVRWDG6DR41G+Ls4UlCfDzbvh5O288X5Il9t9/v+SH+I1py6NAhfHx8DF2OEBku9/8Ui0ylKApTp0ymjrsa7+IJhi5HiEzhd0xNHe+aeHp66m23ZMkSVGoNVVr1yqLKkipVuwmlajfR20ZjYoK1vXO6j3nr3HHK+rSktHczAGwLuXFu93ruXjwJwMPgIJxLeOJevR4Azh6eifd5eHJ45UyKVfamSLmqb/mKcpaStT6gYIlyfPfdDAmNIleS4WnxTn777TdO/nWazxtIYBS504VQOHQ9geG+I/W2i4+PZ/6ChXg17YZ5Ptssqu7N3Th1iKkNCjOzbTm2fe3Ls8cRetu7etXk2onfeXjrCgChV85x6+wxStZuDIBzifKE377K49DbRIbcIvzWVZzcyxFx5zqntq/gg2GTM/01ZRcqlYraPcfwyy87uXTpkqHLESLDyexp8dYURcG7di3iQk5y3FcmwIjcacgm2H7TgVt37mFsbJxqu82bN9OhQwdGrjtJwZJeWVhhysZXNqHHzI2Uq9dad9+5X9djbGaBXSE3Iu7e4De/LzCxsGKo/2GM1OoUj6PVavnN73MOrZiJSq1GSUjgg+FTqNtvnK7Nn5sWcyTgfwC8330UNToMYumQJrzXeSjahHj2LfoKI40xLcfOolgV78x94QYWHxfLd82K069HV2bPnm3ocoTIUDI8Ld7aoUOHOPrHcbb3RQKjyJUex8CqM0Z8Mn643sAIMHeuH8Uq1c4WgTE1Xo076/7t7OFJQQ9PZrQqzY1TBylRo36Kz7mwZyNnd62j89crcSpelpCgc+yYORZrh4JUaZk4DF+jwyBqdPh3Tcq/fl6JqaUVRSvUZFbb8gxffYyoB/dYO74Hn+y4kuZ1lDmZxtiEis16sHL1Cr799ltMTXPvaxV5jwxPi7c29avJeBVW06KsoSsRInOsOAWxCSoGDdK/SPfff//NwYMHqNFJ/37U2Y2dS3EsbeyJuHM91Ta7Zo/Hp8/HeDXujLOHJ5Vb9OD97iM5uPy7FNs/iwxn3+JptPpkNncunsDe1QP7oh64V6uLNj6O8H+GuXOzKq17ERkRwc8//2zoUoTIUBIaxVs5fvw4e/f9zuf1ZVha5E5aLcz7Q0OH9h0oWLCg3rbz5s0jv70z5eq3zaLqMkbUg7s8j4rA2iH1iTGxL56j+s9McCMjNVqtNsX2O2aO5f3uI8nv5IKSkEBCfJzusYSEeLTa3H/9s1PxsrhWqMGPP8oOMSJ3keFp8VamTf2KMs4a2nnm7rXXRN619ypcDYtnma+v3nZRUVGsWLmSmt1GozE2yaLqUvbyeTQRd67pbkfeCyYk6CwW+ewwz2/HvkVTKd+gLdb2TkTcucGu/43Hrog7Jd/7QPecpYMbU7Zea2p1SVxDq0yd5vz+4zfYOBfByb0sIZfPcmT1/6jSOvki51eP7yX89lU6TkkMSy7lqvIwOIigo7uJun8XI7UaB9dSmfwuZA+VW/Xhp6+Hc/fuXVxcXAxdjhAZQkKjeGNnzpxhx85fWNUVDLAUnRBZwu+YCi/PstSuXVtvu5UrV/Ly5UtqdBiYRZWl7t6lv1gy6N9FxXfO+hiAyi170ma8H/evXuD0jlW8ePoYa4dCeNRsSKNhk5JcYxhx9wbPH4frbrf6ZDa/zZ/ET9NHEh0ZRj6HQlRvP4D6gz5Pcu64FzFs/3YUXb8J0K1Rmd/JhVafzGbTpIFojE3pOPlHjM3MM/MtyDYqfNCRnd9/yMqVK/nss88MXY4QGUJmT4s31rFDB04f/Imgj+PRpDzhUogcLfgRFJ8OixYtZuDA1MOgoiiUKl0Gc1dPun67JgsrFDnBhon9eHzpD65fu4pKruMRuYD0E4k3cuvWLTZv2cLHdSQwitxrwTHIn8+abt266W23b98+rl4Jkn2mRYqqtu7DzRvXOXz4sKFLESJDSGgUb2Tp0qVYmRnRo4qhKxEic8TEwY+n1PTtNwBLS0u9befO9aOQR3ncKr+fRdWJnKRYZW/si7izbJlMiBG5g4RGkW5xcXEsXbyQnpUSsJKlx0Qutf4sREQnMGyY/s3Ub926xY4dP1O941AZehQpUqlUVG7Ziw0bN/LkyRNDlyPEO5PQKNJt+/bt3A8LZ3BNQ1ciROZQlMR9pps0/oASJUrobbtw4ULMLK2p2KxrFlUncqKKzboR8/w5u3btMnQpQrwzCY0i3RYtnM97xdRUKGToSoTIHCduw193EvAdoX+f6RcvXrB46VIqtuiFqYVVFlUnciLbQq64lK7Itm3bDF2KEO9MQqNIl2vXrrFn736G1Mj9C/OKvMvvGBRzLUKTJk30ttuwYQOPwsOp2WlwFlUmcrLS9VqzY+dOXr58aehShHgnEhpFuixduhQbCzUds++2ukK8k7CnsOGcEcN8R6JW618aYK7fPEq+1wgH15JZVJ3IycrVbUX006f8/vvvhi5FiHcioVGkKSEhgVUrltO9YgLmxoauRojMsfQEGKk19OvXT2+7kydPcurkCVlmR6SbU4ny2LsUlyFqkeNJaBRp2rNnDyH3w+hd1dCVCJE54hNg4Z8aunXrjp2dnd628+bNw66QK6Xeb5pF1YmcTqVSUbpuK7Zu+ynVPbuFyAkkNIo0+S9fTtmCGqoWMXQlQmSOny/BnUfxDE9jn+mHDx+ydt06qncYjFEaQ9hCvK5s3VaEPbjPiRMnDF2KEG9NQqPQ6/Hjx2zbtpU+leORpehEbjXvDyPeq1GNypUr6233448/oqCiapu+WVSZyC1cvd7DytZehqhFjiahUei1fv164uLjZQcYkWsFPoB9V7T4jhytt11CQgLz5i+gwgedsLQpkDXFiVzDSK2mdJ0WbN6yFUVRDF2OEG9FQqPQa8XyH2lSSkXBfIauRIjMMf8YONrb0b59e73tduzYwd07t3mvs/6dYoRITdl6rbl29QqBgYGGLkWItyKhUaQqJCSEP/48SdeKcuG2yJ2evoAVp9UMGjIMU1P9e2P6+c3D1bM6hcvqH8IWIjUlqtfH2MSU3377zdClCPFWJDSKVO3cuRMjI2ha2tCVCJE5Vv0Fz2MVBg/Wv0h3UFAQe/fuoYYssyPegbGZOUU8q3Pg4EFDlyLEW5HQKFL18/afqF1MTQFLQ1ciRMZTFPD7Q0Ob1q1xcXHR23b+/PlY2zng2ahDFlUnciu3yt4cOnRIlt4ROZKERpGimJgY9u7dS8vSsm2gyJ1+vwaB9+PT3Gc6Ojqa5f7+VGnTD42J/iFsIdJSrHIdIh894u+//zZ0KUK8MQmNIkX79u0j5sVLWpQ1dCVCZI55x1SUK1MKHx8fve1Wr17Ns+hoarQfmEWVidysaIWaqI2NOShD1CIHktAoUrRjxw7cHTSUdjR0JUJkvDuPYdvfMHzEKFR6FiBVFIU5c/0oU7clNgWLZl2BItcyMbegSLmqEhpFjiShUSSjKAo7tm+jZWlZ0FvkTov+AEsLc3r06KG33aFDhwi89Dc1O8oEGJFx3Cp5c+DgIVmvUeQ4EhpFMmfOnOFe6ANaytC0yIVexsPiE2r69O2PtbW13rZz/fxwKlYK9+r1sqg6kRcUq1KH8IdhXL582dClCPFGJDSKZH7++WfyW6jxLm7oSoTIeJvOw8OnCQwbpn+R7rt377Jt61ZqdBqmdwhbiDfl6vUeRmq1DFGLHEdCo0jm55+20qRkAsZqQ1ciRMbzO6amYYN6lC6tfwHSxYsXY2xmTqXm3bOoMpFXmFpa41KmsoRGkeNIaBRJhISE8NeZc7QoY+hKhMh4f92F48EJDPfVv8xObGwsCxctpmLznphZyR6aIuO5VvLm0OEjhi5DiDcioVEksWPHDtkFRuRa845CUZdCtGjRQm+7zZs38zDsATU76d8pRoi35VK2MiH37hIeHm7oUoRINwmNIokdP2+XXWBErhTxDNaeM2Lo8BFoNBq9befM9aNE9Xo4FZfZYCJzFCxdEUiceJgd+Pv7Y2Njk2a7unXrMnr06Eyv501NmjSJihUrGrqMFKlUKrZt22boMjKEhEaho9VqOXToII1KyC4wIvdZdgK0ihH9+/fX2+7MmTMc/+MYNToOyaLKRF5UoEgJzCytMjQ09unTB5VKlezj2rVraT63c+fOXLlyJcNqyUwphbCxY8eyb98+wxSUhtDQUJo2bZqhx+zTpw9t2rTJ0GOmh/4/t0WecuXKFaKeRFPT1dCVCJGxErQw/7iGLl274uDgoLetn58fts4ulPFpmUXVibzIyMiIgh4VOH36dIYet0mTJixfvjzJfWl9zwOYm5tjbm6e6uOxsbGYmJi8c32ZxcrKCisrK0OXkSJnZ2dDl5BhpKdR6Pz5558AVCti4EKEyGC7LkNwRDzDh/vqbffo0SPWrF1LtXYDUacxhC3Em0iIjyfsRiDnf93Ar35f4D+iFfeunGf/gQMZeh5TU1OcnZ2TfKjVambNmoWnpyeWlpYUKVKEYcOGER0drXvef4enXw33Ll26lGLFimFmZpbsXFOmTKF8+fLJ7q9YsSJffPFFivUlJCTQv39/ihUrhrm5OaVKleJ///tfsnbLli2jXLlymJqaUrBgQXx9E3923dzcAGjbti0qlUp3+/Xh6d9++w0zMzMeP36c5JijRo2ifv36uttHjhzB29sbc3NzihQpwsiRI3n27FmKdb9+jmXLllG0aFGsrKwYNmwYCQkJfPfddzg7O+Po6Mi0adOSPO/1ntHg4GBUKhVbtmyhXr16WFhY4OXlxR9//JHsPK+bPXt2kte6YsUKfvrpJ11v8oF/vo/u3LlDp06dsLGxwc7OjtatWxMcHKw7zoEDB6hevTqWlpbY2NhQu3Ztbt26lepr/i/5X1Ho/Pnnn5R2NsbGPM7QpQiRofyOGVGtihfVq1fX22758uXExydQrZ3+IWwh9Hn2OIL7Vy9w/+oFQq+cJ+TyGcJuXiYhLhYAjYkx5laQz1ZFeMgzYmJi9PbyZQQjIyPmzJlDsWLFuHHjBsOGDeOTTz5h/vz5qT7n2rVrbN68mS1btqBWJ1+DrV+/fkyePJmTJ09SrVo1IPHyjvPnz7Nly5YUj6nVanFxcWHjxo0UKFCAY8eOMWjQIAoWLEinTp0AWLBgAR9++CHffPMNTZs2JSoqiqNHjwJw8uRJHB0dWb58OU2aNEmxrgYNGmBjY8PmzZt1l6MkJCSwfv16XaC7fv06TZo0YerUqSxbtoyHDx/i6+uLr69vsp7a112/fp1du3axe/durl+/TocOHbhx4wYlS5bk4MGDHDt2jH79+tGwYUNq1KiR6nEmTJjA999/j4eHBxMmTKBr165cu3YtzeutIXEoPjAwkCdPnuhqtbOzIy4ujsaNG/Pee+9x+PBhNBoNU6dOpUmTJpw/fx4jIyPatGnDwIEDWbt2LbGxsZw4ceKN1qGV0Ch0/vzjKDVcJDCK3OXqQ/j1shZ//1F622m1Wvzmzad8w/ZY2cmm6yJtCXFxhN++QujVC9y/cv6fgHiW6EdhAKiMjDA1NyZfAajgbY5HRQc838+Pk2tir92NC8/4pk8QgYGBVK5cOUNq2rFjR5Jh2qZNm7Jx48Ykk1fc3NyYOnUqQ4YM0RsaY2NjWblyZarD2y4uLjRu3Jjly5frQuPy5cvx8fGhePGUd4cwNjZm8uTJutvFihXjjz/+YMOGDbrQOHXqVD766CNGjfr3Z/bV8V/VYmNjk+qwr1qtpkuXLqxZs0YXGvft28fjx49p3749ANOnT6d79+6698XDw4M5c+bg4+PDggULUuxZhcT/J5YtW4a1tTVly5alXr16BAUF8csvv2BkZESpUqX49ttv+f333/WGxrFjx9K8eXMAJk+eTLly5bh27Vqa68dC4lC8ubk5L1++TPIerF69Gq1Wy9KlS3VBcPny5djY2HDgwAGqVq1KVFQULVq0wN3dHYAyZd5sfT0JjQKAmJgYzl/8mwGtDF2JEBlr/jEoYJefzp076223e/dugm/eYOiXK7KoMpGTREc+TAyG//Qg3gs8zcPgILTx8QBoTEywsFJwKmJCjcYOlKmZjzLVrDE2Tf0qsELuicHkwoULGRYa69Wrx4IFC3S3LS0Tl8LYu3cv06dP5/Llyzx58oT4+HhevHjB8+fPsbCwSPFYrq6uaV4POXDgQPr168esWbMwMjJizZo1/PDDD3qfM2/ePJYtW8bt27eJiYkhNjZWNxwbFhZGSEgIDRo0eINXnVz37t2pWbMmISEhFCpUiICAAJo3b64bgj937hznz58nICBA9xxFUdBqtdy8eTPVMOXm5pZk+1EnJyfUajVGRkZJ7gsLC9NbX4UKFXT/LliwIJD42tMTGlNz7tw5rl27lmx71BcvXnD9+nU++OAD+vTpQ+PGjWnUqBENGzakU6dOuvOnh4RGAcDp06eJj0+QSTAiV3n2Epb/pWbIiCGp9hy8MneuH0XKVqaIp/4hbJG7xcfF8vDmZd3wckjQOUKCzvL8cQTwqvdQQ357FRXrWuFRyQqvOvmxL2T6xucys1Bj72xBUFBQhtVvaWlJiRIlktwXHBxMixYtGDp0KNOmTcPOzo4jR47Qv39/YmNjUw2NrwKnPi1btsTU1JStW7diYmJCXFwcHTp0SLX9unXrGDt2LDNnzuS9997D2tqaGTNm6K6pz6hh+mrVquHu7s66desYOnQoW7duxd/fX/d4dHQ0gwcPZuTI5Av9Fy1aNNXjGhsbJ7mtUqlSvE+r1eqt7/XnvOoVfPUcIyMjFEVJ0j4uLu1RwOjoaKpUqZIkCL/yKvwvX76ckSNHsnv3btavX8/nn3/Onj17qFmzZprHBwmN4h9//vkn5iZGeDrr/0YXIicJOANPX2gZMkT/8jnXrl3j1193027iYtlnOg95Gn5f13P46trD8FtX0SYk9h4am5pgbqVQqJgJxco6Uu49a0pWsUZjknFzSB1djTM0NKbkr7/+QqvVMnPmTF2P2IYNGzLk2BqNht69e7N8+XJMTEzo0qWL3uB39OhRatWqlWTv9+vXr+v+bW1tjZubG/v27aNevXopHsPY2JiEhLSXhuvevTsBAQG4uLhgZGSkGw4GqFy5MpcuXUoWsLMDBwcH7t+/j6Iouv+Pzp49m6SNiYlJsvegcuXKrF+/HkdHR/LlS30nq0qVKlGpUiXGjx/Pe++9x5o1ayQ0ijfz559/UsVFhUb2mxa5hKLAvD80tGzRVDfrMDULFizAIp8tXo07ZU1xIkvFx74k7GbgP+HwAqFB5wgJOkfMk0cAqIzUmFmosXEwonJ9KzwqW1PBOz8FCmb+EjOORY0J/PvvTD1HiRIliIuLY+7cubRs2ZKjR4+ycOHCDDv+gAEDdMO5ryaspMbDw4OVK1fy66+/UqxYMVatWsXJkycpVqyYrs2kSZMYMmQIjo6ONG3alKdPn3L06FFGjBgBoAuVtWvXxtTUFFtb2xTP1b17dyZNmsS0adPo0KEDpqb/9gaPGzeOmjVr4uvry4ABA7C0tOTSpUvs2bMHPz+/d31L3kndunV5+PAh3333HR06dGD37t3s2rUrSRB0c3Pj119/JSgoiAIFCpA/f366d+/OjBkzaN26NVOmTMHFxYVbt26xZcsWPvnkE+Li4li8eDGtWrWiUKFCBAUFcfXqVXr16pXu2iQ0CgD+/OMIHYrLot4i9zhyE87fi+f75SP0tnv+/Dk/LltGldb9MDbL3BmsInMpisLT8FBCr1zg/tXE6w9DAs8Qfvsaijbx/zdjUxMs8im4lDChWHlHyr2XH4/Klmg0hlmBzrGoGcd3BCfpVcpoXl5ezJo1i2+//Zbx48dTp04dpk+f/kZhQR8PDw9q1arFo0eP9E7+ABg8eDBnzpyhc+fOqFQqunbtyrBhw9i1a5euTe/evXnx4gU//PADY8eOxd7ePsmQ98yZM/nwww9ZsmQJhQsXTrKkzOtKlChB9erVOXHiBLNnz07yWIUKFTh48CATJkzA29sbRVFwd3dP89rnrFCmTBnmz5/P119/zVdffUX79u0ZO3Ysixcv1rUZOHCgbnJLdHQ0v//+O3Xr1uXQoUOMGzeOdu3a8fTpUwoXLkyDBg3Ily8fMTExXL58mRUrVhAREUHBggUZPnw4gwenf7tUlfLfgXOR5zx48ABnZ2c29ISOXoauRoiM0XmVinPPi3Pp8pUkF6n/19KlSxk0aBBjt1/GrnCxVNuJ7CXu5QvCbgQSeuV8Yg/iP9cevoiOAsBIrcbUQo2tgxGFPcwpVdWKCt75sXHIXgtUnzv0mHljbnDv3j0KFSpk6HLeiqIoeHh4MGzYMD788ENDlyMykfQ0Ct0FyDVSv/ZXiBwlJAq2XISZs0bqDYyKojDXbx6lvZtKYMymFEXhSdi9f8Ph1fPcCzzDo7s3UP6ZOGBsZoJlPgXX0qYU93Si3Hv5cK9oiVqd/fevcHBJHDK9fv16jgyNDx8+ZN26ddy/f5++ffsauhyRySQ0Cv7880+c82soYhNv6FKEyBCLjyfujNG7d2+97Y4dO8b5c2fp6zc1iyrLHW7+dZhDK2dyL/AMT8ND6TFzI+XqtU61/ZOHofzywyfcvfQXj+5c570uvrT8eGaSNleP7+Wn6SN48jAUZw9PCpepnDjEfOU8L589BRJnLptbarBxMqJGExtKVrHC8/185LfPXr2Hb+LVdZO3b982cCVvx9HREXt7exYvXpzqtYUi95DQKDhz+jRVCycgk0ZFbhAbD4tOaOjZqw/58+fX29Zv3jwcipagRM2GWVRd7hD74hkFS1agaus+rB6b9uShhLiXWNo6UH/AeI4EzAEUIkNu6XoOQ4LOc+n3bbqewzsX/iQk8BT57IwoVs6U50/McfeypPNYF709xzmRWqPCwtr4jbZyy07kCre8RUKj4Mb1IJoVlB98kTtsvQj3o+IZPny43nahoaFs2riRxqO+yXVBJLOVqt2EUrWbpKttbMwznkaE4VS8LHcunuLR3Zs8uH6JY2sTZ6gaqTWYmqtQtFpqNLWlTA1rbgXGoGgVun1alOvnolk34y6dPyqCkVHO+ss27qWWyLA4IsNiefwg8XNkWByRD2KJCE38HB0VD0riPshCZHcSGvM4rVbLzVt3KV7O0JUIkTHm/aHGp857lC9fXm+7JUuWoDY2oUqrjJlBmtdptVoeh97699rDKxcIuXyGyNBbiesfASZmJmgT4rCx11CrpTOe3vlxLWOOSqXikyYXqdLIljLV83Foy1Xea2FHfJxCwPQ79P7SFSN19gqML2MSeBwWR+R/wmDkgzgiQmOJfBDL86dJV6RQq1WYGKuxUJtga2ZORRtHirjm58SdO+nac1gIQ5Pv0jwuJCSE2Ng4ihcwdCVCvLvzIXD4egIbv9G/z3RcXBwLFi7Cq2k3zK1tsqa4XOTls6fcv3aR+1cvALDrf5+xfkJv4l48B0Ct0WBmaYSds5oyVe0oXc2a8rXzYZVfw/eDrlCkpDmthiSd9DHom2JsmHWX9d/fxbN2Pmq3sme3/31KVbXC2ETFt/2CiH4cT73ODtTvnLl7g8dEJyQGwQdJewkfPYjjUWgskWGxvHiWdCMEtUaFqUaDpdoEO3NLStg7U7SEDSUKFKCsoyMVChbE6T/bu70y4qefuBwSkqmvKbepW7cuFStWTLaUjqEdOHCAevXqERkZqduyMDeR0JjH3bhxA0BCo8gV5h2DwgWdaN069UkZANu2beN+aAidOunfKSav02q1PLp7Q7elXuiVc4RcPsvj+3cSG/xzIXTs05uUrGyOu1dBPN/PR5GS5m885O9RyYoJq/7dd/fBrRcc3/mIz9eUZsaAKzTo6kj52vmY3CmQkpWtcPFIees7fRRF4fnThGRhMDIsMQxGhMby+GEcsS+SBkKNsQpTjTFWahMKWOSjrLM1rra2lChQgHJOTng6O2OXylZ86eFsbc3v16699fNf17JlS+Li4ti9e3eyxw4fPkydOnU4d+5ckr2Ps7PUQtiWLVuSbd+XHdSqVYvQ0NA0r6d+U25ubowePZrRo0dn6HHflITGPO5VaHSTSW8ih3scA6vPGPHphOFp/jKZ6zeP4pXfp2DJnPGLMyu8eBrF/WsXE7fVu3KekKCz3L92kfiXL4DE3kNzq8Tew/I1C1CmujXlaudjtM95ekwoSqV6Nhlaz6ppt+kwpjCKFu4ExVCloS2m5kZ4VLbiyl/RyUKjoihEP47/d7j4tWD46H4cEfdjefwwlvjYpNdvGxsbYarRYK0xxcnSlkpFEgOhh729LhBam775vtJvwtnamvthYWi12ne+vrZ///60b9+eu3fv4uLikuSx5cuXU7Vq1bcKjLGxsZiYZJ9Z6nZ2doYuIUUmJiY4OzsbuoxMI6Exj7tx4waFbY0xM057M3QhsjP/kxCnNWLgwIF62124cIHDhw7S9ZuALKose9EmJBBx97puv+X7/1x7GBV2L7GBSoWpuQlWNgplqpnh7mWH5/v5cPEwz7J9uY9sC8cyv4aKPjY8e5K4FFjikHACj+7HEvTXU901hI/ux/HofixR4XEkxL8WCFVgYmyEmcYYa40pLpZ2VC+Wj2J2dpT8JxCWc3LCPBv0VjlYWhIfH09kZCQFCrzbsE+LFi1wcHDA39+fzz//XHd/dHQ0GzduZMaMGUDixJvx48dz6tQp7O3tadu2LdOnT8fS0hJI7Nnq378/V69eZdu2bbRr147bt29TtmzZJNvsPXz4kMKFC7Nr1y4aNGiQrJ7r16/z4Ycfcvz4cZ49e0aZMmWYPn06DRv+u2LBy5cvmThxImvWrCEsLIwiRYowfvx4GjRooNt/+tVyPr1798bf3z/J8PRnn33Gvn37dGsOv+Ll5UX79u2ZOHEikLiQ/8yZM7l58yZubm6MHDkyyR7Y/1W3bl08PT1Rq9WsWLECExMTpk6dSrdu3fD19WXTpk04OTkxd+5cmjZtCiTvGfX392f06NGsX7+e0aNHc+fOHd5//32WL19OwYIFdef571B7mzZtdM+vW7cut27dYsyYMYwZMwb4d9Z6Wl/H+fPn88MPP3Dnzh3y58+Pt7c3mzZtSvU1p0VCYx53/fp1ittp024oRDam1cK84xo6tO+Q5l/58+fPJ79DQcrVa5M1xRlQzJNI7l+9SOjVxMkpIZfP8OD6JeJjXwKgNjbG3BLsCxnj5f1P72GtfJhZ6P/V8OJ5Ag/vvNTdDg95yZ2g51jk01CgoAlb5t7j8cM4+k1x07W5E5R4vePL51qeRsZzJ+g5amMVTkXNeBIRpwuBocEv+G3lA0pWseabPkE8uh8LwMR2l3THCv4bTE2iMdMYk9/YlGJWDhT2SAyEpRwcKO/kRGkHB0xyyOQSG/PE7SsfP378zqFRo9HQq1cv/P39mTBhgi7ob9y4kYSEBLp27cr169dp0qQJU6dOZdmyZTx8+BBfX198fX1Zvny57ljff/89EydO5MsvvwQS1/T19fVl5syZun2cV69eTeHChalfv36K9URHR9OsWTOmTZuGqakpK1eupGXLlgQFBVG0aOKOEr169eKPP/5gzpw5eHl5cfPmTcLDwylSpAibN2+mffv2BAUFkS9fPszNk2/12b17d6ZPn87169dxd3cH4O+//+b8+fNs3rwZgICAACZOnIifnx+VKlXizJkzDBw4EEtLS73rua5YsYJPPvmEEydOsH79eoYOHcrWrVtp27Ytn332GT/88AM9e/bk9u3bWKRyicLz58/5/vvvWbVqFUZGRvTo0YOxY8cSEJC+P1y3bNmCl5cXgwYNSvJHcVpfx1OnTjFy5EhWrVql2+bx8OHD6TpnanLGT5TINDeuXaGUrew5LXK2367AtbB4VozQv890VFQUK1et4r0eH6LOBj1MGSUhPp6IO9e4fyVxv+XQK+cJuXyGp+H3AVCpVJiYm5DPTqFcTTPcKxbA8/38FHZ/u722b116zszBV3W3N85K7KV8r4UdfSe7ERWe2PsXH6clKjxxhvF3/a/8+/zA55zYHYnKCFB0k6t1NBoVt0+9xMbUnJKWtlgUM+b8/fu8TEigm5cX3zZtmquWScpvZgZAZGRkhhyvX79+zJgxg4MHD1K3bl0gcWi6ffv25M+fn48++oju3bvrro/z8PBgzpw5+Pj4sGDBAsz+qad+/fp89NFHuuMWLlwYX19ffvrpJzp1Slyf09/fnz59+qTaC+3l5YWX17/703711Vds3bqV7du34+vry5UrV9iwYQN79uzR9T4WL15c1/7VMLSjo2OqE0vKlSuHl5cXa9as4YsvvgASQ2KNGjUoUaIEAF9++SUzZ86kXbt2ABQrVoxLly6xaNEivaHRy8tL12M7fvx4vvnmG+zt7XXhbeLEiSxYsIDz589Ts2bNFI8RFxfHwoULdYHW19eXKVOmpHrO/7Kzs0OtVmNtbZ3kj+Lp06fr/Trevn0bS0tLWrRogbW1Na6urlSqVCnd502JhMY87saNGzStbOgqhHg3844ZUbFCWd577z297VasWMHLly+p3m5AFlWW8Z49jnhtYkpiOAy7eZmEuMQeOY2xMeZWYF/YmCr17ClTIx9la+bD1DzjQlapqtaMnleCXcvvc/dqDM+iEqjZzBYzSzXzP7quW4Nw2HtnQc8SsIoW8pmaMqxmTco4OnI3Kop5x4/zLDaWbhUq8nWTf9eCvBUZSbtVq/iiQYNcFRgBbP4JaY8fP86Q45UuXZpatWqxbNky6taty7Vr1zh8+LAuqJw7d47z588n6elSFCVxCbabNylTpgwAVatWTXJcMzMzevbsybJly+jUqROnT5/m4sWLbN++PdVaoqOjmTRpEjt37iQ0NJT4+HhiYmJ0O+CcPXsWtVqNj4/PO73m7t27s2zZMr744gsURWHt2rW6fbCfPXvG9evX6d+/f5Keuvj4+DQnrLx+/adaraZAgQJ4enrq7nNycgIgLCws1WNYWFjoAiNAwYIF9bZPr7S+jo0aNcLV1ZXixYvTpEkTmjRpQtu2bVPtEU0PCY15WHR0NGHhj2TmtMjRbkbAzkAtS5aM1nvNnVarZa7fPMrVb0s+h4JZWOHbSYiLI/z2Fd3ElMSAeJboR4m/bFQqI0wtNOSzU+FZ25wSFR3w9M5PQTezdz7362sQPnoQ+++EkgexPApNnGDy3zUIT+yOxMzEGHO1MXZm5lSycaSImw0l7Owo4+hIMTs7bF8bWozXanl/4UIGVa/Op/XqEfHsGeV++IH5bdrgZmtLp4AA6hQrRpNSpQAYu3MnXzZsSD6zd3992U1G9zRC4oSYESNGMG/ePJYvX467u7sumEVHRzN48GBGjhyZ7HmvhowB3XVxrxswYAAVK1bk7t27LF++nPr16+Pq6ppqHWPHjmXPnj18//33lChRAnNzczp06EBsbOIfOSkNN7+Nrl27Mm7cOE6fPk1MTAx37tyhc+fOQOLrhcS1WWvUqJHkeWq1Wu9x/zupTqVSJbnv1f85Wm3ql3mldIzXd9IxMjJKtrNOXFza8wzS+jqamJhw+vRpDhw4wG+//cbEiROZNGkSJ0+efOvlgCQ05mE3b94EZLkdkbMt+ANs8ueja9euetvt27ePa1evMGjcwiyqLP2iIx9y/8qFf689DDxDWPBltPGJk0A0Jom9h44uxlT7wIFyNa0pXS0fJmZv3uOW6hqE/0woSWsNwgIWVng4WFPUwwaPAgUo4+hIh4AAVnbsTIt/eqjSY0dgII9jYuj+z3BZcGQk+UxNaffPouzexYpxJTycJqVKsenCBTRqNa3Kln3j15sTvJqd/fTp0ww7ZqdOnRg1ahRr1qxh5cqVDB06VBdwKleuzKVLl3RDt2/C09OTqlWrsmTJEtasWZNkUkxKjh49Sp8+fWjbti2QGHSCg4OTHE+r1XLw4MEkk2NeeTVjOyFB/2VULi4u+Pj4EBAQQExMDI0aNcLRMXE9TycnJwoVKsSNGzfo3r37m7zcLOHg4EBoaKjudkJCAhcvXtRNAoLE9+G/70F6vo4ajYaGDRvSsGFDvvzyS2xsbNi/f79umP5NSWjMw3RrNGbPlQuESFNMHPx4Sk2/wQPTHHKZO9ePQiU9catUO4uqSy4+Lpbw4KDXdk05z73LZ3j+OAIAlZERpuYa8hdQ4VXHCo9KllTwzo9jkbR71xRF4fmT1wPhPzuUhMUReV/fGoRGmOkCYT7KFcyHq40NJeztKefoiGfBgkl6CDPKqjNnqFu8OEX/6fFwL1CAmLg4zoWGUjR/fk7fu0ePSpV4HBPDtP37+blPnwyvIbtQGxlhZmzMs2fPMuyYVlZWdO7cmfHjx/PkyRP6vPb+jRs3jpo1a+Lr68uAAQOwtLTk0qVL7NmzJ80QCIm9jb6+vlhaWurCYGo8PDzYsmULLVu2RKVS8cUXXyTplXNzc6N3797069dPNxHm1q1bhIWF0alTJ1xdXVGpVOzYsYNmzZphbm6OlZVViufq3r07X375JbGxsfzwww9JHps8eTIjR44kf/78NGnShJcvX3Lq1CkiIyN1w9iGUr9+fT788EN27tyJu7s7s2bNSnapgpubG4cOHaJLly6Ymppib2+f5tdxx44d3Lhxgzp16mBra8svv/yCVqul1D+9929DQmMeduPGDcxNjHCyltnTImdadwYin2kZOnSo3nbBwcHs2PEzbT6bl2XLxjyNeKALh/evXuBe4GnCb11Fm/Cq99AEC2uFQm4muJV1pGxNa0pXs0Zjkrz38F3WIDTTaLD6Zw3CyimsQWiVyWsQpiT0yRP2Xr3K0vbtdffZmJszv21bhm7dSkxcHF28vGhQogS+P/3EwOrVuRUZSde1a4lPSODTunVpXS537X1qaWqqG0bNKP379+fHH3+kWbNmFCr07w48FSpU4ODBg0yYMAFvb28URcHd3V03nJuWrl27Mnr0aLp27aqbNJOaWbNm0a9fP2rVqqULOk+ePEnSZsGCBXz22WcMGzaMiIgIihYtymeffQYkTr6ZPHkyn376KX379tXNDE9Jhw4d8PX1Ra1W06ZNmySPDRgwAAsLC2bMmMHHH3+MpaUlnp6eBl8sGxInLp07d45evXqh0WgYM2ZMkl5GgClTpjB48GDc3d15+fIliqKk+XW0sbFhy5YtTJo0iRcvXuDh4cHatWsp9w4/OyrlvwPpIs8YP34863+cyY1xskajyHkUBarOUeNcvhE7f9mlt+2nn37K3PkLGbc7GBPz5NdpvYv42JeE3Qz8JxxeJCToLCFB54iJegQk9h6aWWjIb6+isIc5JStZ4emdH/tCiWFNq1V4EhHP49fCYJI1CENjiYpIfQ3CfBpT7C0tKZwvcckZD3t7PJ2dKevoiFkWzRC3mTSJ1Z3TPzw96/Bh/I4d4/JHH+ldFudIcDBf/PYbO/v0ofKcOSzt0AEnKysaLFnCXyNG4JBKj1NOVGHOHHoOHcrUqVMNXUqagoODcXd35+TJk1SuLDMp8xLpaczDIiMjsc34USchssSft+H0nQR+WZT8IvDXvXjxgsVLl1KpVZ93CoyKovA0PJTQK//MXL56npDAM4TfvoaiTbzWyNjUBAsrBRd3E9zKOVKmujVOrmY8fRSvGyoOD4lly9wQ3bZ1Tx/F8fo19CoVmJioMVNryG9iTjHL/LiUzE8xW1tKOzhQ3tmZ0g4OaNK4gD+7UhSF1WfO0NnLS29gfBkfz9idO1nYti03Hj1KnDjj5gYkDmWfunePpu8wzJbdWJiYZOjwdGaIi4sjIiKCzz//nJo1a0pgzIMkNOZhkZGR2JrJGo0iZ/I7Cu7FXGncuLHeduvXrycyIoKaHQel+9hxL18QdiNQd91h6JVzhASd48XTxwAYGakxMVdjbqVQtLQpds4mOLiYkBCnEBkWR0RILH/ufMTe1WFJ1iBUGYGpsRoztTE2puaUtrLDpWx+iv+zKHUFZ2dKFCiQ65aUed2R4GBuPHpEzzTWi5tx6BANSpSgYqFCnAsNJf61ZB2XkECCntmqOZHGyCjNyR6GdvToUerVq0fJkiXfaVcRkXNJaMzDIh9FYGuWu/7jFXnDg6ew8bwR078dmWbAmjPXj1K1GmNf1CPZY4qi8CTs3r/L2vwzczni7nWUf0KJkcYYbfy/l3CYWRphZKTw/GksL55B5IM4bl16jpFahalGjbnaGFszc8pbO1DEJT/udnaUdnTEq2BBiuTPn2sCYfTLl9x49Eh3+9bjx5wPDcXW3JwiNjZM3ruXkCdPWPSfWZqrzpyhauHClP1nfbuUXA4LY+vFixwaMgSAkvb2GKlUrDx9GicrK66Gh1O5cOHMeWEGolKp9C7bkh3UrVs32dIwIm+R0JiHRT4Kx1WGp0UOtPRPUGuM6du3r952J06c4PRfp+g1eytxL2J4cOOSbnJKSNBZQoPO8/JZ4kX5KqPE4d5XQ82vaOPjdEvOWKiNsTO3wMnKiqLuNrgXKEAZBwcqFCxI4TQWCc5tzoSE0HLFCt3tCb/+CkBXLy8WtG3L/adPuRsVleQ5US9e8POlS3zzzz69KVEUhdE//8y0xo2x/Ge5FXNjY+a3acPYX34hNj6eGc2aUShfvkx4VYZjpFJl+55GIWQiTB7mUdyVtq63+a6FoSsRIv3iE6DYNxqatOvNkqVL9bZt2rQpu3fvxraQG49Db+l6SV7vPVQZJV5H+HpWzG9mhqOVFS758uFma6vbG1iIzLLm3Dlad+3KokWLDF2KEKmSnsY87HHUE2zkd6HIYbZfgruR8Qz39U2zbfUaNdizdy9Pw+5iZmKCsYkJpiYmGBsbo1GrUavVqQ4Xa4HbWi23IyIy+BUIkZy1vX2aax4KYWjS05iHmZuZ8l3TWEa8b+hKhEi/+ouMiLWvzpFjfxi6FCGEyFNyxxXZ4o1ptVpevIzFImuWcRMiQ1y6D79f1TJ8hP5ldoQQQmQ8CY15VExMDAAWJgYuRIg3MO8YODkUoP1rO4kIIYTIGhIa8yhdaJSeRpFDPHkBK0+rGTx0OCYm8teOEEJkNQmNedTz588B6WkUOcfKUxATpzBoUPoX6RZCCJFxZPZ0HqULjdLTKHIARYF5xzW0a9uGwrlsUWchhMgpJDTmUS9evADAVL4DRA6w/xpcvh/PwnQssyOEECJzSGTIozSaxC99fPbetUoIAOYdU1HSozheXl5E/WeXESGyE41Gg6WlpaHLECJTSGjMo0xNTQF4GW/gQoRIg6LAXyEabkdcx9bW1tDlCKGXuZkpR44eo3LlyoYuRYgMJ6Exj5LQKHIKlQp+6RtH4ANDVyKEfi/ioefalwQFBUloFLmShMY8SkKjyEnKOSd+CJGdRSWuZKa7/EeI3EaW3MmjJDQKIUTGSvhnU161Wm3YQoTIJBIa8yhdaEwwcCFCCJFLxP/z/6n0NIrcSkJjHvUqNL6IM3AhQgiRS0hPo8jtJDTmUUZGRmg0ahmeFkKIDPJqCTPpaRS5lYTGPMzUxFiGp4UQIoPE/vNHuLGxbLUlcicJjXmYmamp9DQKIUQGeZS4OysFChQwbCFCZBIJjXmYqamJhEYhhMggD58lfra3tzdsIUJkEgmNeZiERiGEyDjhEhpFLiehMQ8zNZHhaSGEyCgPo8HaykK3OoUQuY2ExjzMOl8+ol4YugohhMgdwp+Dg72docsQItNIaMzDChdx494TlaHLEEKIXOFhNNjbOxi6DCEyjYTGPMzFxYW7T2Q9MSGEyAjhz8DBsaChyxAi00hozMMKFy7MvSjF0GUIIUSu8DBGjb2D9DSK3EtCYx7m4uJC5LN4nr00dCVCCJHzhT8zwkFCo8jFJDTmYS4uLgDce2LgQoQQIhd4GK3IcjsiV5PQmIcVLlwYgHtRBi5ECCFyuPgEiHwWLz2NIleT0JiHvQqNdyU0CiHEO4n4ZwtB6WkUuZmExjzMwsIC2/zW0tMohBDvSHaDEXmBhMY8zsWlMHcfG7oKIYTI2W5FJn5+da24ELmRhMY8zqWImwxPCyHEO7r0ACwtzChSpIihSxEi00hozOMKu7hw76ks8C2EEO8iMAxKlyqJSiW7bIncS0JjHufi4iI9jUII8Y4CH6opU66CocsQIlNJaMzjXFxcePAknpfxhq5ECCFyJkWBwAdQpkwZQ5ciRKaS0JjHlS5dWvcfnhBCiDf34Ck8fp5A2bJlDV2KEJlKQmMeV6FCBVQqFWdDDF2JEELkTJf++aNbehpFbiehMY+ztramRHFXztwzdCVCCJEzBYaBsbEGd3d3Q5ciRKaS0CioVKU6Z0PVhi5DCCFypMAH4OFeDI1GVqIQuZuERkHFihU5GwJaraErEUKInCfwoZHMnBZ5goRGQaVKlXgSk0BwpKErEUKInCfwoVquZxR5goRGQcWKFQHkukYhhHhDj2Mg9HGczJwWeYKERoGzszPOjvYyg1oIId5QoMycFnmIhEYBQMVKlTkTIttfCSHEm7hwH4yMjChZsqShSxEi00loFABUqlyFs6Ey808IId7EkZtQycsTCwsLQ5ciRKaT0CiAxOsa70XG8TDa0JUIIUTOcTBYQ5269Q1dhhBZQkKjABJnUANyXaMQQqTTrUdwOyIeHx8fQ5ciRJaQ0CgAcHd3x8rSXGZQCyFEOh28kfj5/fffN2whQmQRCY0CSLyQu0qVKvxxSybDCCFEehy6AZ7lylCgQAFDlyJElpDQKHTq1W/IgRtGJMjOMEIIkaaDwcZyPaPIUyQ0Cp0GDRrw+HmCXNcohBBpCImCa2Fxcj2jyFMkNAqd6tWrY2Fuxr6rhq5ECCGyt0P/XM/o7e1t2EKEyEISGoWOiYkJderUYf91+bYQQgh9Dt2AUh7FcXZ2NnQpQmQZSQciifoNGnL4JsTGG7oSIYTIvg4GG+NTr6GhyxAiS0loFEk0aNCA5y+1HL9l6EqEECJ7ehgNl0LjqFOnjqFLESJLSWgUSVSsWBGHArbsDjJ0JUIIkT0dvpn4WUKjyGskNIokjIyMaNKsBb9ckX2ohRAiJQeuQzFXF4oUKWLoUoTIUhIaRTJNmzbl3N147kUZuhIhhMheFAV+vqyhcdMWhi5FiCwnoVEk88EHH2BkpGL3ZUNXIoQQ2cu5EAgOj6dt27aGLkWILCehUSRToEABalavxi+XZUtBIYR43baLkD+fFXXr1jV0KUJkOQmNIkXNWrRizzWjXL/0ToIWvtgNxaaB+afgPh2+2pM4BPXKlgvwwWIoMBFUY+HsvbSPu+UCVJ0NNp+D5XioOAtW/ZW0zfcHwPHLxI+ZB5I+9uctqPIDxCe84wsUQmSorZc0tGjZGhMTE0OXIkSWk9AoUtS8eXOexiSw/5qhK8lc3/4OC46BX1sI/AS+bQbfHYC5R/5t8ywW3neDb5un/7h25jChAfwxAs5/BH2rQd/18Os/s9LPh8DEX2FdD1jbAz7fDRdCEx+LT4Ahm2Fhe9CoM+qVCiHe1Y0IOH9PhqZF3iVTZEWKvLy8KF2yBKtPX6NJaUNXk3mOBUPr8tC8bOJtNztYexZO3Pm3Tc8qiZ+DH6X/uHVLJL09yhtWnIIjN6FxKbgcBhUKQn2PxMcrFEy8z7MgzDgAdYpDtaJv+aKEEJli6wUwMzWhSZMmhi5FCIOQnkaRIpVKRc/efdn6txHRLw1dTeap5Qb7rsKVh4m3z4UkBrumGRiUFSXxHEFhiWEQEsPhlYdwOxJuPYIr4VDeGa6Hw/KTMFV+JwmR7Wy6qOaDDz7A0tLS0KUIYRDS0yhS1a1bNyZMmMDWi//2tuU2n9aDJy+g9HegVkGCAtOaQPfK737sqBgo/BW8jAe1EcxvB41KJj5Wxgm+bgqNFifent408b6Gi+C7FonD2JN+A2M1/K811HF/93qEEG/vZgQcD05gzdfdDF2KEAYjoVGkys3NjTretVl1+g96VtEaupxMseEcBJyGNd2gnDOcDYHRP0GhfNC72rsd29oUzn4I0S8Texo/3A7F7f4duh5SK/HjlRUnE5/zniuU+hZOjoK7UdAlAG5+Bqby0yqEwaw/BxbmZrRq1crQpQhhMPJrSOjVo2dvhgw5RkgUFMpv6Goy3sc74NP60KVS4m3PgnArEqbvf/fQaGQEJewT/12xMASGJR73v9c7AoQ/g8l74NAw+PM2lHQAj38+4hISh7I9C75bPUKIt7fuvIaWLVvJ0LTI0+SaRqFXx44d0WjUrD1j6Eoyx/M4MPrPcpRqFWiVlNu/C62SOFSdkjE/wZg64GKTuAxQ3GtL7cRrE+8TQhhG4AM4dzeert1kaFrkbdLTKPSysbGhZYtWrD6xnY/q5r5FG1uWhWn7oKhN4vD0mXsw6xD0e62X8dHzxAkrIU8Sbwf9M2nG2Rqc8yX+u9daKJwfpjdLvD19H1QtAu4FEoPiL4GJ6zQuaJ+8hj1XEnsSV3RJvF2tSOJM6l2BcCcqMcSWcsyUly+ESIe1ZxIX9JZZ0yKvk9Ao0tSzVy/abNnCxVAon8uGSOe2gS9+hWFbICw6cQh+cE2Y2OjfNtv/Tlxj8ZUuqxM/f9kIJjVO/PftyKQ9ls9iE4959zGYG0NpR1jdDTpXTHr+mDjw3QrreyQOZ0Nib+PcttB3A5iqE8OkuXHGvm4hRPpotbD2vIZ27Tpgampq6HKEMCiVoiiZMBAncpPY2FgKOjswwOsJ37YwdDVCCJF19lxJ3BHq4MGD1KlTx9DlCGFQck2jSJOJiQmdu3Qn4JwGrVxbJ4TIQ/yOqahQvize3t6GLkUIg5PQKNKlZ8+e3IuM58B1Q1cihBBZI/gR/Py3gu/I0ahUqrSfIEQuJ8PTIl0URcHDvRjeBW6xvIuhqxFCiMw3bgcsPmPN3XuhstSOEEhPo0gnlUpF7779WX/eiIhnhq5GCCEyV0wcLD2lpl//gRIYhfiHhEaRbkOGDEFRaZh/zNCVCCFE5lp3BiKfaRk6dKihSxEi25DQKNLNwcGBPn37MfeYmhdxhq5GCCEyh6LA3D/UNG3SmBIlUtjCSYg8SkKjeCMffvgh4dFaVv1l6EqEECJzHL8FZ+4k4DtipKFLESJbkYkw4o21a9uGS3/s5NJH8boFqYUQIrfoHqDiz8dFuXLtBkbyn5wQOvLTIN7Yx5+MI+hBPDsCDV2JEEJkrPtPYOMFGD5ilARGIf5DehrFW6n9Xk2Mwk5xeFiCoUsRQogM89Ue+OaQGXfvhWBra2vocoTIVuTPKPFWPh73KUduJHD8lqErEUKIjBGXAAv/1NCjZy8JjEKkQHoaxVtJSEigTCkPvKyC2dhTvoWEEDnfipPQZz2cP38eT09PQ5cjRLYjPY3irajVaj76eBxbLsD1cENXI4QQ7yY2Hibt1dCubRsJjEKkQnoaxVuLiYmhaJHCdC4ViV87Q1cjhBBvb8ExGL5VxYULFyhXrpyhyxEiW5KeRvHWzM3N8R0ximWnjAiXrQWFEDlUTBxM3a+he7duEhiF0ENCo3gnw4cPByNjZh8ydCVCCPF25h+FsGiFSZMnG7oUIbI1CY3indjb2zNq9BhmHTbiXpShqxFCiDfz9AV8c1BNv779cHd3N3Q5QmRrck2jeGdRUVGUcC9Gy+KRLOts6GqEECL9vtoDU3/XcO3aDYoUKWLocoTI1qSnUbyz/PnzM2nyV/ifgnMhhq5GCCHS59Fz+P6QmqFDh0tgFCIdpKdRZIi4uDjKly1NUaNgfhuoRaUydEVCCKHf+F9gzh9m3LgZjJOTk6HLESLbk55GkSGMjY357vtZ7L2i5dcgQ1cjhBD63X8Cc44aMWr0GAmMQqST9DSKDKMoCnV9vIm4dpyzoxPQqA1dkRBCpGzUNlhx3oqbwbdly0Ah0kl6GkWGUalUzJw1m79DE/A/ZehqhBAiZbcjYeFxI8Z+PE4CoxBvQHoaRYbr0b07+3Zu4Oon8ViZGroaIYRIqscaFb/esuHGzVtYW1sbuhwhcgzpaRQZbtrXXxMZo+L7A4auRAghktpzBQJOK8z4fpYERiHekIRGkeFcXV0ZPeZDZhwyIkQW/BZCZBMxcTB0qwafOu/Tu3dvQ5cjRI4jw9MiU0RFReFe3I3WJR7zYydDVyOEEPD5LphxSMO58xcoXbq0ocsRIseRnkaRKV4t+L38JJy8behqhBB53d/34buDKsZ/NkECoxBvSXoaRaaJj4+nRrUqxIX9zamRCZhoDF2RECIv0mrBZ6GaMCNXzl34GzMzM0OXJESOJD2NItNoNBp+XL6CSw8Uvjtg6GqEEHnVspNw5EYCi5b8KIFRiHcgoVFkqooVK/Lxx5/w1V4jAh8YuhohRF7z4Cl8vFNNnz69qVu3rqHLESJHk+FpkeliYmLw8iyHo3KbQ0MSMJI/VYQQWaR7gIpfb+XnctBV7O3tDV2OEDma/PoWmc7c3Jyly/w5eiOB+ccMXY0QIq/4LQjWnFGYOWu2BEYhMoD0NIosM3TIEFb5L+HcGC3u8v+3ECITxcRB+ZkaipZ7j/2/H0SlUhm6JCFyPAmNIss8ffoUL89yFFaHcGBIAmrp5xZCZJLPfoGZhzWcv3CRUqVKGbocIXIF+bUtsoy1tTUrVgVw9KaWHw4ZuhohRG51+AZ8e0DFFxO/lMAoRAbKFqFx0qRJVKxY0dBlZAv+/v7Y2NgYuoxM4+3tzYcffsiE3UZcDDV0NUKI3CbyOXRfp6F2rfcYP368ocsRIld5o9D48OFDhg4dStGiRTE1NcXZ2ZnGjRtz9OjRzKrvreXU8NW5c2euXLmS4cdVqVRs27Ytw4/7NqZOnUqJEiXotV5NbLyhqxFC5BaKAoM2q3iaYM7qgLWo1WpDlyRErvJGe3S0b9+e2NhYVqxYQfHixXnw4AH79u0jIiIis+ozOEVRSEhIQKPJmu1MzM3NMTc3z5JzGYqZmRmrAtZSo0Z1Ju+BaU0NXZEQIjf48QRsOqewceMyihYtauhyhMh10t3T+PjxYw4fPsy3335LvXr1cHV1pXr16owfP55WrVolaTdgwAAcHBzIly8f9evX59y5c0mO9c033+Dk5IS1tTX9+/fnxYsXyc63dOlSypQpg5mZGaVLl2b+/Pm6x4KDg1GpVGzZsoV69ephYWGBl5cXf/zxBwAHDhygb9++REVFoVKpUKlUTJo0CYBVq1ZRtWpVrK2tcXZ2plu3boSFhemOfeDAAVQqFbt27aJKlSqYmpqyevVqjIyMOHXqVJIaZ8+ejaurK1qtNsX3zM3NjalTp9KrVy+srKxwdXVl+/btPHz4kNatW2NlZUWFChWSHPe/PaSvhu5XrVqFm5sb+fPnp0uXLjx9+jTJeWbPnp3k3BUrVtS9Zjc3NwDatm2LSqXS3Qb46aefqFy5MmZmZhQvXpzJkycTH5/Y/acoCpMmTdL1LBcqVIiRI0em+FrfVOXKlZky5Su+3gc7LmXIIYUQedjlMBi13YgB/fvToUMHQ5cjRK6U7tBoZWWFlZUV27Zt4+XLl6m269ixI2FhYezatYu//vqLypUr06BBAx49egTAhg0bmDRpEl9//TWnTp2iYMGCSQIhQEBAABMnTmTatGkEBgby9ddf88UXX7BixYok7SZMmMDYsWM5e/YsJUuWpGvXrsTHx1OrVi1mz55Nvnz5CA0NJTQ0lLFjxwIQFxfHV199xblz59i2bRvBwcH06dMn2ev49NNP+eabbwgMDKRVq1Y0bNiQ5cuXJ2mzfPly+vTpg5Ge1ap/+OEHateuzZkzZ2jevDk9e/akV69e9OjRg9OnT+Pu7k6vXr3QN4n9+vXrbNu2jR07drBjxw4OHjzIN998k2r7/zp58qSu3tDQUN3tw4cP06tXL0aNGsWlS5dYtGgR/v7+TJs2DYDNmzfzww8/sGjRIq5evcq2bdvw9PRM93nTMm7cOFq3akmPdWquhWfYYYUQeUxMHHQJUFPUtTiz//c/Q5cjRK6V7tCo0Wjw9/dnxYoV2NjYULt2bT777DPOnz+va3PkyBFOnDjBxo0bqVq1Kh4eHnz//ffY2NiwadMmILF3rn///vTv359SpUoxdepUypYtm+RcX375JTNnzqRdu3YUK1aMdu3aMWbMGBYtWpSk3dixY2nevDklS5Zk8uTJ3Lp1i2vXrmFiYkL+/PlRqVQ4Ozvj7OyMlZUVAP369aNp06YUL16cmjVrMmfOHHbt2kV0dHSSY0+ZMoVGjRrh7u6OnZ0dAwYMYO3atbrAfPr0aS5cuEDfvn31vm/NmjVj8ODBeHh4MHHiRJ48eUK1atXo2LEjJUuWZNy4cQQGBvLgQep77Gm1Wvz9/Slfvjze3t707NmTffv2pfEV+5eDgwMANjY2ODs7625PnjyZTz/9lN69e1O8eHEaNWrEV199pXufb9++jbOzMw0bNqRo0aJUr16dgQMHpvu8aTEyMmLFylU4FXKl7Uo1z1L/W0QIIVI1YisEhatZv3EzlpaWhi5HiFzrjSbCtG/fnpCQELZv306TJk04cOAAlStXxt/fH4Bz584RHR1NgQIFdD2TVlZW3Lx5k+vXrwMQGBhIjRo1khz3vffe0/372bNnXL9+nf79+yc5xtSpU3XHeKVChQq6fxcsWBAgyVBzSv766y9atmxJ0aJFsba2xsfHB0gMSK+rWrVqkttt2rRBrVazdetWIHEYuV69ekmGelPyeo1OTk4ASXrrXt2nr243Nzesra11twsWLJjm60yPc+fOMWXKlP+3d+/xOdeNH8df12GzjR26NYfJMEYop8gcmghLuLEcf0rsUEopitXNlNR9a04V6haxxCqUw5xmJFTmFGOEu5zHlDM7cR1+f6xbuamL2nx3eD8fj+txXY/tuq69rz249r4+38/n873m9xwdHc2JEyfIysqiR48eZGdnExQURHR0NAsXLrx66Dq/+Pr68sWiJRw850b0AhPaNVREbkX8lry5jO//e9o177cikv9ueXWHh4cH7dq1o127dsTGxhIVFcWrr75K//79uXTpEhUrVuSrr7667nE3u5L5vyN+06dPv65c/u9KODc3t6u3/7vb/+/NL4S8QhoWFkZYWBhz587F39+fI0eOEBYWxuXLl6+57/9+WnV3d6dfv37MmjWL8PBwEhISeOcmDoPcKOOt5v7t/f/7mN/e32w2X3d4+8qVKy6zXbp0idGjRxMeHn7d9zw8PKhcuTL79u1j9erVJCcn88wzzzBu3DjWrVt3Xaa/om7dusyc9RG9evWiaSA8/0C+PbWIFGO7TsAzC81EDHjihtOMRCR//eUlwXXq1Lm6lUujRo3IyMjAarX+7ghc7dq12bRpE/369bv6tZSUlKu3y5cvT0BAAAcOHKBv375/Ope7uzt2u/2ar+3du5fTp08zduxYKleuDHDd4pY/EhUVxT333MN7772HzWa7Ydkygr+/PydO/Lrp4YULFzh48OA193Fzc7vu99GoUSP27dtHjRo1fve5PT096dy5M507d2bQoEHcfffd7Nq1i0aNGuXra+jZsyebN2/mpbcn0jDASWj1fH16ESlmLuTAox9bCK5ZiylTpxodR6REuOnSePr0aXr06EFERAT16tXD29ubrVu3EhcXR5cuXQBo27YtzZo1o2vXrsTFxVGzZk2OHz/OsmXL6NatG40bN+b555+nf//+NG7cmBYtWjB37lx2795NUFDQ1Z81evRoBg8ejK+vLw8//DC5ubls3bqVs2fPMnTo0JvKW7VqVS5dusSaNWuoX78+Xl5eBAYG4u7uzuTJkxk4cCBpaWmMGTPmpn9ZtWvXJiQkhJiYGCIiIgrN1jht2rQhPj6ezp074+fnx6hRo64bla1atSpr1qyhRYsWlCpVijvuuINRo0bRqVMnAgMD6d69O2azmdTUVNLS0njjjTeIj4/HbrfTtGlTvLy8mDNnDp6enlSpUqVAXsfYsWPZtnUzPedu5LvnbQT4FsiPEZEizuGAyPkmMrJKse2LRYXmvVikuLul1dNNmzZl0qRJhIaGcs899xAbG0t0dDRTpkwB8g6bLl++nNDQUAYMGEDNmjXp3bs3hw8fvjp3r1evXsTGxjJ8+HDuu+8+Dh8+zNNPP33Nz4qKimLGjBnMmjWLe++9l1atWhEfH0+1atVu+oU1b96cgQMH0qtXL/z9/YmLi8Pf35/4+Hjmz59PnTp1GDt2LOPHj7/p5wSIjIzk8uXLRERE3NLjCtIrr7xCq1at6NSpEx07dqRr165Ur37tUN2ECRNITk6mcuXKNGzYEICwsDCWLl3KqlWraNKkCSEhIUyaNOlqKfTz82P69Om0aNGCevXqsXr1ahITEylbtmyBvA6r1cpn8xZgLV2W7nO08beI3NjIlfD5Tvho9hyCg4ONjiNSYpicf7TXi1xnzJgxzJ8//5pV45K/Nm3aROgDLYluYmNK4ZgBICKFxLSNMPBzGD9+PC+++KLRcURKlEJx7umi4NKlS6SlpTFlyhSee+45o+MUa02bNuXdyVOY+i3MvvkppyJSzC3/Hp5ZaOLZQYNueqqSiOQfjTTepP79+/PJJ5/QtWtXEhISdE7TAuZ0OomKjCRh7kesjnbQ4uZnJohIMbTtGLR638xD7R/hi4WL9B4sYgCVRim0cnJyeDisHalbN7JuoJ16AUYnEhEjHDoDzaZaCQyuz9p16/Hy8jI6kkiJpNIohdqFCxdo3SqU9ANpfPOMnep3Gp1IRG6ns1nQ4j0LOaUCSNm8lXLlyhkdSaTE0pxGKdR8fHxYkbQK33JVaDfDyokLRicSkdsl1wbdZps5mVuGFUnJKowiBlNplEKvXLlyJK9ZyxX3O2k/w8LZLKMTiUhBczoh4jMTKUcsLF6ylFq1ahkdSaTEU2mUIiEwMJBVq7/kRI43HWdayMw1OpGIFKSRKyFhu5OP58ylZcuWRscREVQapQipXbs2K1auYtfP7jz6sVmbf4sUUx+kwD/X5O3F2KNHD6PjiMgvVBqlSGnSpAmLFiey9kcz/T41YXcYnUhE8tOszXmbd2svRpHCR6VRipyHHnqITz79jPk74bmFeXOfRKTom7YRIubBU08+xTvvvovJZDI6koj8hkqjFEnh4eF88MF03t8Io5KMTiMif9Xkr/NGGAcPHsx777+P2aw/TyKFjdXoACJ/VmRkJGfOnGH48OGUssKIh0ADEyJFz/ivYNhSeOmll4iLi9MIo0ghpdIoRdqwYcPIzc0lNjaW05kwoTNogEKk6Hhzdd5K6REjRjBmzBgVRpFCTKVRiryRI0dStmxZBg0axKksmNnTiZtOSytSqDmd8NoqeD0ZXn/9dWJjY42OJCIu6DSCUmx89tlnPP74Y4QFO5j3uANPN6MTiciNOJ3wjxUw9ksYO3YsMTExRkcSkZug0ijFSlJSEuHdunJfwBWW9Lfj52l0IhH5LacTXkyESeth4sSJDBkyxOhIInKTVBql2ElJSeGRDmEEls5kZaSdCj5GJxIRAIcDBi+Cqd/ClClTGDRokNGRROQWqDRKsbR7927at22Dp/0MyVE2qpU1OpFIyZZrg6cWwOxtJqZNm0Z0dLTRkUTkFqk0SrF16NAh2j3UmszTx0iKsnFvRaMTiZRMP1+C8NkWNh81MXNWPH379jU6koj8CSqNUqydPHmSh9u349APe1gWYad5VaMTiZQsu05A53gr2WYfFi1eSrNmzYyOJCJ/kna0k2KtfPnyfLV+A/XuC6HtB2YWpxmdSKTkWLIbmk+14BdQiy1bt6swihRxKo1S7Pn6+rIyKZlHOnWhazyMXpU3IV9ECobTCW99CV3jod3Dnfj62xQCAwONjiUif5FKo5QInp6ezJu/gDFjxjA62cSjH5u4mGN0KpHiJ+cKPPGpiZeXw4gRI1nw+ReUKVPG6Fgikg80p1FKnMTERB7r24e7yuSyqJ+NYH+jE4kUDxkXoNtsCztOWJg5K54+ffoYHUlE8pFKo5RIe/fupevfO5GRfoiEPnYeqW10IpGibXs6dPnIis3tDhYnLqNJkyZGRxKRfKbD01Ii3X333Wzaso0HWofRaSbErgS75jmK/Cmf74SW75kpV6UuW7ZtV2EUKaZUGqXE8vX1ZfGSRN5885/880sT7aebOXnR6FQiRUeuDV5cAt1nQ+cu3Vn/9bdUqlTJ6FgiUkB0eFoEWLt2LX169cB8+Tyf/p+N0OpGJxIp3Pb9BH0SLKSdNDF27FsMGTIEk8lkdCwRKUAaaRQBWrduzfbUXdSsH0KbaSbi1mpbHpEbcTph5mZo9I6ZTI8qpKRsYujQoSqMIiWASqPILypWrMjqNWsZHvMyMcug9TQzP5wyOpVI4XEuG3rPNRE5D3r/3xNs255Ko0aNjI4lIreJDk+L3MDatWuJHPAEGSfS+VcHB8+1ALM+YkkJtuY/MGC+hQs2Tz6Y/iE9e/Y0OpKI3Gb6MyhyA61bt2Zn2h6inhrEC4sh9N8W9v9sdCqR2y/rMjy3ENpOgxr1WpC6M02FUaSE0kijiAvr168non8/0o8d5Y0wBy+EgkUft6QESDkMT8yzcuScmbfixvHss89i1pC7SIml//0iLoSGhrIzbQ8DBw1m2DITLd+zsPcno1OJFJxcG4xYAS2mmvCrXJ8dqTsZPHiwCqNICaeRRpFb8M033zDgicc5cuQwr7d3MDQUrBajU4nkn+XfwwuJVg6ecfLaa6OJiYnBarUaHUtECgGVRpFblJWVxahRo5g4cSKNK5uZ1dNO3QpGpxL5a344BUOWmFm6x0Gb1q14d/JU6tata3QsESlEVBpF/qSNGzcy4InHOXjwIDEPOhjeGsqUMjqVyK3JzIU318CE9WYqVKjAxLffJTw8XPsuish1VBpF/oLs7GzGjBnDxAnj8fNw8Hp7OxFNdMhaCj+nEz7bAS8tt3Iq00TMy68QExODl5eX0dFEpJBSaRTJB4cPH2bEP/7B3IQE6lS0MO4ROx3uBg3WSGG08zgMXmJm3Q8Ounb5OxMnvU21atWMjiUihZyWwonkgypVqjBn7ly2bNmCf3AzOn4IbT8wsz3d6GQivzqblbfnYsO3TWSYqpGUlMTCRYtVGEXkpmikUSSfOZ1Oli5dyvCXhrLvPz/wWCN4swNU9jM6mZRUNjvM3AIjkizkONx59bXXGTx4MO7u7kZHE5EiRKVRpIDYbDZmzJjBq7EjuHDhHENaOni5Dfh4GJ1MSorLNvhoK/zrKysHT9l4/LHHeCsujooVKxodTUSKIJVGkQJ28eJF4uLimDB+HKXdbLzW1s6TIeCmxTJSQHKuwIeb4a11Vo6dtfNoeDgjRo6kQYMGRkcTkSJMpVHkNjl27BijYmOJ/+gjKvlZeKGFjegQjTxK/snMhWkpMG69lZ8u2unTuw//GDGCOnXqGB1NRIoBlUaR2ywtLY3x48eRkJCAp9XJk/fbGfyA5jzKn3chB6Z+AxO/tnAuG/o93o+XX3mF4OBgo6OJSDGi0ihikPT0dCZPnsy/359KZmYmvRs4eTEUGlQyOpkUFWez4J0N8M43FrKumIiIjCImJoaqVasaHU1EiiGVRhGDXbx4kQ8//JBJE8Zx5Nhx2tY081IrB+1rap9HubHj52HKNzBlo4UrDgtPDXyaYcOGUamSPnGISMFRaRQpJGw2GwsWLGDcW//iux07uTfAwosP2OnTENytRqcTo9nssGIvTN9sYvn34OHhwaBnn2Po0KGUL1/e6HgiUgKoNIoUMk6nk3Xr1jF+XBzLlq8gwM/KoGY2+jeGAF+j08nt9uOpvD0WZ22zcuKcjfsa1ifqyYH06dMHX1/9gxCR20elUaQQ27NnDxMnTGDu3DlcvnKFsFom+t/n4O91wcPN6HRSUHKuwKI0mLHFzJr9Dnx9ytD3sX5ERUXRsGFDo+OJSAml0ihSBJw/f5558+YRP3MG36Zsxs/LQp/6dvo3gSaVNfexuEg7kbe/4uztFs5csvNAy+ZERT9F9+7d8fLyMjqeiJRwKo0iRcy+ffuYPXs2s+Nncux4BsHlrPSuZ6N3A6hTweh0cqtOZ8LCNPhwi4WUQ3b8y95B/4goIiMjqVWrltHxRESuUmkUKaLsdjtffvkln37yCZ9/Pp/zFy5xb6VfC2RQWaMTyu85ei7v8PPC3WbW/+jE4YSw9u2Iin6Szp0765zQIlIoqTSKFAO5ubkkJSXxSUICS5YsJis7h0aVrbQPttG+JjSvCqW0AtswTifsOQmLd8PC3Ra2HrHj5malTevWdAt/lC5dulChgoaJRaRwU2kUKWYyMzNJTEwkMTGR5KQV/Hz6LF6lzLQKgvbBefs/1i6veZAF7VIurPlP3jY5y/dbOXrGRmkvDzp06Ei38HA6duyo1c8iUqSoNIoUYw6Hg507d7Jq1SqSV61kw4avyb18hQA/K+1r2GhfC9oGg38Zo5MWfbk22JEOXx+EFfvNbDgAl20OgqtX5ZFOXejQoQOtWrXCw0MnGxeRokmlUaQEycrKYsOGDSQnJ7Nq5XJ27f4egIaVrbSrbuOhYGh0F9xZ2uCghZzTCQfPwKYjkHIYNh2zsP2Yg8s2Jx6l3HnwwQd5pGMnOnToQI0aNYyOKyKSL1QaRUqwEydOsHr16ryRyKQVnPz5NAB3/c2NBhVsNAhw0iAAGgRAtb+B2WxwYIOcz4YtR38piUdMbDpq4eeLNgCqVwskpPkDNG3alJCQEOrXr6+FLCJSLKk0igiQdyaa/fv3k5qayvbt29mx/Tt2bP+OjJ9OAeDtaaF+RWgYYL9aJOtWKF4LbLIuw4HTcOBM3vWuDEg56sb3GVdwOsHXpwxNm4bQNKQZISEh3H///dx5551GxxYRuS1UGkXkD2VkZJCamsqOHTvYsWMH27dtZv8PB3E6nVgtJmpXsBLkd4VKvuRdfPKu7/LLu+1diKbwOZ1w8iL8+Esx/PHULwXxrIUfT5vIOG+7el9Pj1LUqlnjmlHEmjVrYi6pw60iUuKpNIrILcvMzGTXrl3s2LGD1NRUDh86RPqxw6SnH+f02fPX3Nfb00IlXzOVfOzc5eO4Wiwr+EBpd/ByAy/3a2+XsoDFDFZz3rXZ9Otqb4cDMi/DhVy4mAsXcn655MLFX66v+VounMuGQ+fdOHDKTvZlx9VsFcqVJSioOtWDaxEUFERQUBDVq1cnKCiIChUqYNIScxGRq1QaRSRfZWdnc/z4cdLT00lPT+fYsWNXb6cfPUx6+jGOZ/yEzWa/pec1m8FqNnHF7uSP3rU8Srnj410aH29vvH188PHxw8fvDqpUqXJNKaxWrRqlS2vFj4jIzVJpFJHbzuFwcPbsWbKysm54ycnJwW63Y7PZrrsuVaoU3t7e+Pj4XHPx9vbG29tbi1BERAqISqOIiIiIuKQZ3SIiIiLikkqjiIiIiLik0igiIiIiLqk0ioiIiIhLKo0iIiIi4pJKo4iIiIi4pNIoIiIiIi6pNIqIiIiISyqNIiIiIuKSSqOIiIiIuKTSKCIiIiIuqTSKiIiIiEsqjSIiIiLikkqjiIiIiLik0igiIiIiLqk0ioiIiIhLKo0iIiIi4pJKo4iIiIi4pNIoIiIiIi6pNIqIiIiISyqNIiIiIuKSSqOIiIiIuKTSKCIiIiIuqTSKiIiIiEsqjSIiIiLikkqjiIiIiLik0igiIiIiLqk0ioiIiIhLKo0iIiIi4pJKo4iIiIi4pNIoIiIiIi6pNIqIiIiISyqNIiIiIuKSSqOIiIiIuKTSKCIiIiIuqTSKiIiIiEsqjSIiIiLikkqjiIiIiLik0igiIiIiLqk0ioiIiIhLKo0iIiIi4tL/A79P+vXjZJgMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# import packages\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# calculating total of individual minutes column\n",
    "very_active_mins = df_activity[\"very_active_mins\"].sum()\n",
    "fairly_active_mins = df_activity[\"fairly_active_mins\"].sum()\n",
    "lightly_active_mins = df_activity[\"lightly_active_mins\"].sum()\n",
    "sedentary_mins = df_activity[\"sedentary_mins\"].sum()\n",
    "\n",
    "# plotting pie chart\n",
    "slices = [very_active_mins, fairly_active_mins, lightly_active_mins, sedentary_mins]\n",
    "labels = [\"Very active minutes\", \"Fairly active minutes\", \"Lightly active minutes\", \"Sedentary minutes\"]\n",
    "colours = [\"lightcoral\", \"yellowgreen\", \"lightskyblue\", \"darkorange\"]\n",
    "explode = [0, 0, 0, 0.1]\n",
    "plt.style.use(\"default\")\n",
    "plt.pie(slices, labels = labels, \n",
    "        colors = colours, wedgeprops = {\"edgecolor\": \"black\"}, \n",
    "        explode = explode, autopct = \"%1.1f%%\")\n",
    "plt.title(\"Percentage of Activity in Minutes\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "wireless-surrey",
   "metadata": {
    "papermill": {
     "duration": 0.045513,
     "end_time": "2022-10-14T21:40:35.487789",
     "exception": false,
     "start_time": "2022-10-14T21:40:35.442276",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "**Percentage of Activity in Minutes**\n",
    "\n",
    "As seen from the pie chart, \n",
    "\n",
    "1. Sedentary minutes takes the biggest slice at 81.3%. \n",
    "\n",
    "2. This indicates that users are using the FitBit app to log daily activities such as daily commute, inactive movements (moving from one spot to another) or running errands. \n",
    "\n",
    "3. App is rarely being used to track fitness (ie. running) as per the minor percentage of fairly active activity (1.1%) and very active activity (1.7%). This is highly discouraging as FitBit app was developed to encourage fitness."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "innovative-expression",
   "metadata": {
    "papermill": {
     "duration": 0.043502,
     "end_time": "2022-10-14T21:40:35.575568",
     "exception": false,
     "start_time": "2022-10-14T21:40:35.532066",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# STEP 6: ACT\n",
    "\n",
    "In the final step, we will be delivering our insights and providing recommendations based on our analysis. \n",
    "\n",
    "Here, we revisit our business questions and share with you our high-level business recommendations.\n",
    " \n",
    "**1. What are the trends identified?**\n",
    "\n",
    "* Majority of users (81.3%) are using the FitBit app to track sedentary activities and not using it for tracking their health habits.\n",
    "\n",
    "* Users prefer to track their activities during weekdays as compared to weekends - perhaps because they spend more time outside on weekdays and stay in on weekends. \n",
    "\n",
    "**2. How could these trends apply to Bellabeat customers?**\n",
    "\n",
    "* Both companies develop products focused on providing women with their health, habit and fitness data and encouraging them to understand their current habits and make healthy decisions. These common trends surrounding health and fitness can very well abe pplied to Bellabeat customers.\n",
    "\n",
    "**3. How could these trends help influence Bellabeat marketing strategy?**\n",
    "\n",
    "* Bellabeat marketing team can encourage users by educating and equipping them with knowledge about fitness benefits, suggest different types of exercise (ie. simple 10 minutes exercise on weekday and a more intense exercise on weekends) and calories intake and burnt rate information on the Bellabeat app.\n",
    "\n",
    "* On weekends, Bellabeat app can also prompt notification to encourage users to exercise.\n",
    "\n",
    "\n",
    "***\n",
    "\n"
   ]
  }
 ],
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