life_expectancy_gdp.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction\n",
    "\n",
    "For this project, we will act as a data researcher for the World Health Organization. We will investigate if there is a strong correlation between the economic output of a country and the life expectancy of its citizens.  \n",
    "\n",
    "During this project, we will analyze, prepare, and plot data, and seek to answer questions in a meaningful way.\n",
    "\n",
    "After we perform analysis, we'll be creating an article with our visualizations to be featured in the fictional \"Time Magazine\".\n",
    "\n",
    "**Focusing Questions**: \n",
    "+ Has life expectancy increased over time in the six nations?\n",
    "+ Has GDP increased over time in the six nations?\n",
    "+ Is there a correlation between GDP and life expectancy of a country?\n",
    "+ What is the average life expactancy in these nations?\n",
    "+ What is the distribution of that life expectancy?\n",
    "\n",
    "GDP Source:[World Bank](https://data.worldbank.org/indicator/NY.GDP.MKTP.CD)national accounts data, and OECD National Accounts data files.\n",
    "\n",
    "Life expectancy Data Source: [World Health Organization](http://apps.who.int/gho/data/node.main.688)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1. Import Python Modules"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the modules that you'll be using in this project:\n",
    "- `from matplotlib import pyplot as plt`\n",
    "- `import pandas as pd`\n",
    "- `import seaborn as sns`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2 Prep The Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To look for connections between GDP and life expectancy we will need to load the datasets into DataFrames so that they can be visualized.\n",
    "\n",
    "We load **all_data.csv** into a DataFrame called `df` and then, quickly inspect the DataFrame using `.head()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Country  Year  Life expectancy at birth (years)           GDP\n",
      "0   Chile  2000                              77.3  7.786093e+10\n",
      "1   Chile  2001                              77.3  7.097992e+10\n",
      "2   Chile  2002                              77.8  6.973681e+10\n",
      "3   Chile  2003                              77.9  7.564346e+10\n",
      "4   Chile  2004                              78.0  9.921039e+10\n"
     ]
    }
   ],
   "source": [
    "df=pd.read_csv('all_data.csv')\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3 Examine The Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The datasets are large and it may be easier to view the entire dataset locally on your computer. You can open the CSV files directly from the folder you downloaded for this project.\n",
    "\n",
    "Let's learn more about our data:\n",
    "- GDP stands for **G**ross **D**omestic **P**roduct. GDP is a monetary measure of the market value of all final goods and services produced in a time period. \n",
    "- The GDP values are in current US dollars."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What six countries are represented in the data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Chile' 'China' 'Germany' 'Mexico' 'United States of America' 'Zimbabwe']\n",
      "['China', 'Mexico', 'Zimbabwe', 'United States of America', 'Germany', 'Chile']\n",
      "['Chile', 'China', 'Germany', 'Mexico', 'United States of America', 'Zimbabwe']\n"
     ]
    }
   ],
   "source": [
    "# method 1\n",
    "print(df.Country.unique())\n",
    "\n",
    "# method 2\n",
    "print(list(df['Country'].value_counts().index))\n",
    "\n",
    "# method 3 (same as 1)\n",
    "print(df.Country.unique().tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What years are represented in the data?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004, 2003, 2002, 2001, 2000]\n",
      "[2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013\n",
      " 2014 2015]\n",
      "[2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015]\n"
     ]
    }
   ],
   "source": [
    "# method 1\n",
    "print(list(df['Year'].value_counts().index))\n",
    "\n",
    "# method 2\n",
    "print(df.Year.unique())\n",
    "\n",
    "# method 3\n",
    "print(df.Year.unique().tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4 Tweak The DataFrame\n",
    "\n",
    "We look at the column names of the DataFrame `df` using `.head()` once again. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Country  Year  Life expectancy at birth (years)           GDP\n",
      "0   Chile  2000                              77.3  7.786093e+10\n",
      "1   Chile  2001                              77.3  7.097992e+10\n",
      "2   Chile  2002                              77.8  6.973681e+10\n",
      "3   Chile  2003                              77.9  7.564346e+10\n",
      "4   Chile  2004                              78.0  9.921039e+10\n"
     ]
    }
   ],
   "source": [
    "print(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We notice the first two column names are one word each, and the third is five words long! `Life expectancy at birth (years)` is descriptive, which will be good for labeling the axis, but a little difficult to wrangle for coding the plot itself. \n",
    "\n",
    "**Revise The DataFrame Part A:** \n",
    "\n",
    "We change the name of the last column to `LEABY`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Life expectancy at birth (years)': 'LEABY'}, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Running `df.head()` again to check your new column name worked."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Country  Year  LEABY           GDP\n",
      "0   Chile  2000   77.3  7.786093e+10\n",
      "1   Chile  2001   77.3  7.097992e+10\n",
      "2   Chile  2002   77.8  6.973681e+10\n",
      "3   Chile  2003   77.9  7.564346e+10\n",
      "4   Chile  2004   78.0  9.921039e+10\n"
     ]
    }
   ],
   "source": [
    "print(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 5 Bar Charts To Compare Average"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To take a first high level look at both datasets, create a bar chart for each DataFrame:\n",
    "\n",
    "A) We create a bar chart from the data in `df` using `Country` on the x-axis and `GDP` on the y-axis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df.Country, df.GDP)\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('barPlot_GDP.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "B) Create a bar chart using the data in `df` with `Country` on the x-axis and `LEABY` on the y-axis.\n",
    "Remember to `plt.show()` your chart!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(df.Country, df.LEABY)\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('barPlot_LEABY.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you notice about the two bar charts? Do they look similar?\n",
    "> There is no similarity between the two bar charts at all. Infact there is a huge variance between the GDP of countries, where as the Life Expectancy at Birth (LEABY in years) show very close if not similar between the countries except for Zimbabwe."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 6. Violin Plots To Compare Life Expectancy Distributions "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way to compare two datasets is to visualize the distributions of each and to look for patterns in the shapes.\n",
    "\n",
    "1. Assign figure size 15x10 by creating an object and assigning to `fig` \n",
    "2. Created an `sns.violinplot()` for the dataframe `df` and map `Country` and `LEABY` as its respective `x` and `y` axes. \n",
    "3. Plotting the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.subplots(figsize=(15, 10)) \n",
    "sns.violinplot(data=df, x='Country', y='LEABY')\n",
    "plt.savefig('violinPlot_LEABY.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you notice about this distribution? Which country's life expactancy has changed the most?\n",
    "> We get a much better picture in this violin plot than the bar chart as we can see the interquartile ranges and distributions amongst the various countries. Zimbabwe comes up to be the country with the lowest Life Expectancy which would probably be followed by China and Mexico. Germany and Chile top the charts with higher Life Expectancy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 7. Bar Plots Of GDP and Life Expectancy over time\n",
    "\n",
    "We want to compare the GDPs of the countries over time, in order to get a sense of the relationship between GDP and life expectancy. \n",
    "\n",
    "First, we plot the progession of GDP's over the years by country in a barplot using Seaborn.\n",
    "1. We save `sns.barplot()` to a variable named `ax`\n",
    "2. We then chart `Country` on the x axis, and `GDP` on the `Y` axis on the barplot.\n",
    "3. Used the `Year` as a `hue` to differentiate the 15 years in our data.\n",
    "4. Since the names of the countries are long, we rotate their label by 90 degrees so that they are legible. \n",
    "5. Also, since our GDP is in trillions of US dollars, we make sure our Y label reflects that by changing it to `\"GDP in Trillions of U.S. Dollars\"`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rSpKkWdP5mZundbz17zt4zj4FBQXs3LmT6upqTpw4QU1NDalUivb2durq6mhubqalpYWWlhZaW1s5ePAgvb299Pb20t3dzZYtW+ju7iaRSPDNb36TefPmMTo6yjXXXEN9ff3Eq51eqlx4IECSJOmCSSQSVFdXA1BYWEgymSSTydDZ2UlTUxMATU1N7N+/H4DOzk42bdpECIFVq1Zx7Ngxstksr3jFK5g3bx4Av/jFL3juueempT7DmSRJylt9fX309PSwcuVKBgcHSSQSwHiAGxoaAiCTybB06dKJc0pKSshkMsD4EumyZctYunQpH/7wh6c8awaGM0mSlKdGR0dpbGykra2NhQsXnrHfZK+6PPXgIkuXLuXRRx/lBz/4Ael0msHBwSnXZTiTJEl5Z2xsjMbGRjZu3EhDQwMAxcXFZLNZALLZLEVFRcD4TFl/f//EuQMDA6fNkC1ZsoSKigoeeOCBKddmOJMkSXklxsjmzZtJJpNs27Ztor2+vp50Og1AOp1m/fr1E+179+4lxsjhw4dZtGgRiUSCgYEBfv7znwMwMjJCV1cXr3/966dcn09rSpKkvNLV1UVHRweVlZVUVVUBsH37dpqbm9mwYQO7d++mtLSUffv2AbBu3ToOHDhAWVkZCxYsYM+ePQA8/vjjfPCDHySEQIyRP/3TP6WysnLK9RnOJEnSrDmfrS+m25o1aya9jwzg0KFDp7WFELjrrrtOa0+lUjz66KPTXp/LmpIkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkKa/09/dTW1tLMpmkoqKCXbt2ATA8PEwqlaK8vJxUKsXIyAgwvmnt1q1bKSsrY9myZRw5cuQF4x0/fpxf//Vf5/3vf/+01Oc+Z5IkadZ8qmPttI73B7/zj+fsU1BQwM6dO6murubEiRPU1NSQSqVob2+nrq6O5uZmWlpaaGlpobW1lYMHD9Lb20tvby/d3d1s2bKF7u7uifHuuOMOrr/++mm7BmfOJElSXkkkElRXVwNQWFhIMpkkk8nQ2dlJU1MTAE1NTezfvx+Azs5ONm3aRAiBVatWcezYsYl3cD788MMMDg5y4403Tlt9hjNJkpS3+vr66OnpYeXKlQwODpJIJIDxADc0NARAJpNh6dKlE+eUlJSQyWR47rnn+OAHP8hf/uVfTmtNhjNJkpSXRkdHaWxspK2tjYULF56x32Svegoh8IlPfIJ169a9ILhNB+85kyRJeWdsbIzGxkY2btxIQ0MDAMXFxWSzWRKJBNlslqKiImB8pqy/v3/i3IGBAZYsWcI///M/88ADD/CJT3yC0dFRnnnmGS677DJaWlqmVJszZ5IkKa/EGNm8eTPJZJJt27ZNtNfX15NOpwFIp9OsX79+on3v3r3EGDl8+DCLFi0ikUjwN3/zN/zoRz+ir6+PHTt2sGnTpikHM3DmTJIk5Zmuri46OjqorKykqqoKgO3bt9Pc3MyGDRvYvXs3paWl7Nu3D4B169Zx4MABysrKWLBgAXv27JnR+sJk66gvV8uXL48PPfTQbJchSdIFcXTnE6e1zXlF9gW/iz5Qe6HKOS+PP/44yWRytsu44Ca77hDCwzHG5S/u67KmJElSDjGcSZIk5RDDmSRJUg4xnEmSJOUQw5kkSVIOMZxJkiTlEPc5kyTpZeB7nxw8re1Vs1DHxaC/v59NmzZx9OhR5syZw2233cbtt9/O8PAw7373u+nr6+Oqq67i7rvv5vLLLyfGyO23386BAwdYsGAB7e3tEy9Ov+SSS6isrASgtLSUL3/5y1Ouz3AmSZJmzYe/eNO0jtf6znvO2aegoICdO3dSXV3NiRMnqKmpIZVK0d7eTl1dHc3NzbS0tNDS0kJraysHDx6kt7eX3t5euru72bJlC93d3QD82q/9Go888si0XoPLmpIkKa8kEomJma/CwkKSySSZTIbOzk6ampoAaGpqYv/+/QB0dnayadMmQgisWrWKY8eOkc1mzzj+VBnOJElS3urr66Onp4eVK1cyODhIIpEAxgPc0NAQAJlMhqVLl06cU1JSQiaTAeDpp59m+fLlrFq1aiLMTZXLmpIkKS+Njo7S2NhIW1sbCxcuPGO/yV51GUIA4Ec/+hFLlizhhz/8IW9961uprKzkda973ZTqcuZMkiTlnbGxMRobG9m4cSMNDQ0AFBcXTyxXZrNZioqKgPGZsv7+/olzBwYGWLJkCcDE39e+9rXccMMN9PT0TLk2w5kkScorMUY2b95MMplk27ZtE+319fWk02kA0uk069evn2jfu3cvMUYOHz7MokWLSCQSjIyM8Itf/AKAn/zkJ3R1dXH11VdPuT6XNSVJUl7p6uqio6ODyspKqqqqANi+fTvNzc1s2LCB3bt3U1payr59+wBYt24dBw4coKysjAULFrBnzx4AHn/8cf7gD/6AOXPm8Nxzz9Hc3Gw4kyRJL2/ns/XFdFuzZs2k95EBHDp06LS2EAJ33XXXae1vetOb+M53vjPt9bmsKUmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmS8kp/fz+1tbUkk0kqKirYtWsXAMPDw6RSKcrLy0mlUoyMjADjm9Zu3bqVsrIyli1bxpEjRybG+tGPfsSNN95IMpnk6quvpq+vb8r1uc+ZJEmaNev2f3BaxzvwWzvP2aegoICdO3dSXV3NiRMnqKmpIZVK0d7eTl1dHc3NzbS0tNDS0kJraysHDx6kt7eX3t5euru72bJlC93d3QBs2rSJj3zkI6RSKUZHR5kzZ+rzXs6cSZKkvJJIJKiurgagsLCQZDJJJpOhs7OTpqYmAJqamti/fz8AnZ2dbNq0iRACq1at4tixY2SzWR577DGeffZZUqkUAJdddhkLFiyYcn2GM0mSlLf6+vro6elh5cqVDA4OkkgkgPEANzQ0BEAmk2Hp0qUT55SUlJDJZPj+97/PK1/5ShoaGnjjG9/Ihz70IU6ePDnlmgxnkiQpL42OjtLY2EhbWxsLFy48Y7/JXvUUQuDZZ5/lgQceYMeOHXzrW9/ihz/8Ie3t7VOuy3AmSZLyztjYGI2NjWzcuJGGhgYAiouLyWazAGSzWYqKioDxmbL+/v6JcwcGBliyZAklJSW88Y1v5LWvfS0FBQX81m/91gseFnipDGeSJOWgg1/4yQs+mj4xRjZv3kwymWTbtm0T7fX19aTTaQDS6TTr16+faN+7dy8xRg4fPsyiRYtIJBKsWLGCkZERnnzySQDuu+8+rr766inX59OakiQpr3R1ddHR0UFlZSVVVVUAbN++nebmZjZs2MDu3bspLS1l3759AKxbt44DBw5QVlbGggUL2LNnDwCXXHIJO3bsoK6ujhgjNTU1/P7v//6U6zOcSZKkWXM+W19MtzVr1kx6HxnAoUOHTmsLIXDXXXdN2j+VSvHoo49Oa30ua0qSJOUQw5kkSVIOMZxJkiTlEMOZJElSDjGcSZIk5RDDmSRJUg4xnEmSpLzS399PbW0tyWSSiooKdu3aBcDw8DCpVIry8nJSqRQjIyPA+Ka1W7dupaysjGXLlk28BeD++++nqqpq4jN//vyJl6VPhfucSZKkWfO2v/v4tI73lYYPnLNPQUEBO3fupLq6mhMnTlBTU0MqlaK9vZ26ujqam5tpaWmhpaWF1tZWDh48SG9vL729vXR3d7Nlyxa6u7upra3lkUceAcaDXVlZGTfeeOOUr8GZM0mSlFcSiQTV1dUAFBYWkkwmyWQydHZ20tTUBEBTU9PELFhnZyebNm0ihMCqVas4duzYxDs4f+mLX/wiN998MwsWLJhyfYYzSZKUt/r6+ujp6WHlypUMDg6SSCSA8QA3NDQEQCaTYenSpRPnlJSUkMlkXjDO5z//eW699dZpqclwJkmS8tLo6CiNjY20tbWxcOHCM/ab7FVPIYSJ79lslu985zusXbt2WuoynEmSpLwzNjZGY2MjGzdupKGhAYDi4uKJ5cpsNktRUREwPlPW398/ce7AwABLliyZ+H333Xdzyy23MHfu3GmpzXAmSZLySoyRzZs3k0wm2bZt20R7fX096XQagHQ6zfr16yfa9+7dS4yRw4cPs2jRoonlT4DPfe5z07akCT6tKUmS8kxXVxcdHR1UVlZSVVUFwPbt22lubmbDhg3s3r2b0tJS9u3bB8C6des4cOAAZWVlLFiwgD179kyM1dfXR39/P9dff/201Wc4kyRJs+Z8tr6YbmvWrJn0PjKAQ4cOndYWQuCuu+6atP9VV1112sMBU+WypiRJUg4xnEmSJOUQw5kkSVIOMZxJkiTlEMOZJElSDjGcSZIk5RDDmSRJyiv9/f3U1taSTCapqKhg165dAAwPD5NKpSgvLyeVSjEyMgKMb1q7detWysrKWLZsGUeOHJkY6z//5/9MRUUFyWSSrVu3nnGLjl+F+5xJkqRZ8/Yv/s20jvcP79x4zj4FBQXs3LmT6upqTpw4QU1NDalUivb2durq6mhubqalpYWWlhZaW1s5ePAgvb299Pb20t3dzZYtW+ju7uab3/wmXV1dPProo8D4/mlf//rXueGGG6Z0Dc6cSZKkvJJIJKiurgagsLCQZDJJJpOhs7OTpqYmAJqamti/fz8AnZ2dbNq0iRACq1at4tixY2SzWUIIPP300zzzzDP84he/YGxsjOLi4inXZziTJEl5q6+vj56eHlauXMng4ODEOzMTiQRDQ0MAZDIZli5dOnFOSUkJmUyG1atXU1tbSyKRIJFIsHbtWpLJ5JRrMpxJkqS8NDo6SmNjI21tbSxcuPCM/Sa7jyyEwA9+8AMef/xxBgYGyGQy3HfffXzjG9+Ycl2GM0mSlHfGxsZobGxk48aNNDQ0AFBcXEw2mwUgm81SVFQEjM+U9ff3T5w7MDDAkiVL+NKXvsSqVau47LLLuOyyy7j55ps5fPjwlGsznEmSNMtav5Q97aOZE2Nk8+bNJJNJtm3bNtFeX19POp0GIJ1Os379+on2vXv3EmPk8OHDLFq0iEQiQWlpKV//+td59tlnGRsb4+tf//q0LGv6tKYkScorXV1ddHR0UFlZSVVVFQDbt2+nubmZDRs2sHv3bkpLS9m3bx8A69at48CBA5SVlbFgwQL27NkDwDvf+U7uu+8+KisrCSFw00038Y53vGPK9RnOJEnSrDmfrS+m25o1a864H9mhQ4dOawshcNddd53Wfskll/CpT31q2utzWVOSJCmHGM4kSZJyiOFMkiQphxjOJEmScojhTJIkKYcYziRJknKI4UySJOWV/v5+amtrSSaTVFRUsGvXLgCGh4dJpVKUl5eTSqUYGRkBxjet3bp1K2VlZSxbtowjR45MjPXhD3+Ya665hmuuuYYvfOEL01Kf+5xJkqRZs/6LB6d1vM533nzOPgUFBezcuZPq6mpOnDhBTU0NqVSK9vZ26urqaG5upqWlhZaWFlpbWzl48CC9vb309vbS3d3Nli1b6O7u5itf+QpHjhzhkUce4Re/+AXXX389N99881nf03k+nDmTJEl5JZFIUF1dDUBhYSHJZJJMJkNnZydNTU0ANDU1sX//fgA6OzvZtGkTIQRWrVrFsWPHyGazPPbYY1x//fUUFBRw6aWXcu2113LPPfdMuT7DmSRJylt9fX309PSwcuVKBgcHSSQSwHiAGxoaAiCTybB06dKJc0pKSshkMlx77bUcPHiQn/3sZ/zkJz/h/vvvf8EL0l8qlzUlSVJeGh0dpbGxkba2trMuRU72qqcQAjfeeCPf+ta3eNOb3sQVV1zB6tWrKSiYerRy5kySJOWdsbExGhsb2bhxIw0NDQAUFxeTzWYByGazFBUVAeMzZc+fERsYGGDJkiUAfOQjH+GRRx7h3nvvJcZIeXn5lGsznEmSpLwSY2Tz5s0kk0m2bds20V5fX086nQYgnU6zfv36ifa9e/cSY+Tw4cMsWrSIRCLByZMneeqppwB49NFHefTRR7nxxhunXJ/LmpIkKa90dXXR0dFBZWUlVVVVAGzfvp3m5mY2bNjA7t27KS0tZd++fQCsW7eOAwcOUFZWxoIFC9izZw8wPvv25je/GYCFCxfy2c9+dlqWNQ1nkiRp1rJJYusAACAASURBVJzP1hfTbc2aNZPeRwZw6NCh09pCCNx1112ntc+fP5/HHnts2uubsWXNEMJnQghDIYTvnuH4DSGEfw8hPHLq82fPO3ZTCOFfQgg/CCE0z1SNkiRJuWYm7zlrB246R58HYoxVpz7/FSCEcAlwF3AzcDVwawjh6hmsU5IkKWfMWDiLMX4DGH4Jp14H/CDG+MMY4zPA54H101qcJElSjprte85WhxC+DfwY+NMY4/eAXweev4PbALDyTAOEEG4DbgMoLS2dwVIlSZq6d/7tkdPaVsxJzEIlylWzuZXGEeA3YozXAh8H9p9qD5P0nfyuPSDG+OkY4/IY4/IrrrhiBsqUJEm6cGYtnMUYj8cYR099PwDMDSG8mvGZsqXP61rC+MyaJEnSRW/WwlkI4coQQjj1/bpTtTwFfAsoDyG8JoTwCuA9wJdnq05JknRx6e/vp7a2lmQySUVFBbt27QJgeHiYVCpFeXk5qVSKkZERAJ544glWr17NvHnz2LFjxwvGuueee3j9619PWVkZLS0t01LfjN1zFkL4HHAD8OoQwgDwUWAuQIzxk8A7gS0hhGeBnwPvieObjjwbQng/8I/AJcBnTt2LJkmSLjKT3YM3FV9srD5nn4KCAnbu3El1dTUnTpygpqaGVCpFe3s7dXV1NDc309LSQktLC62trSxevJg777yT/fv3v2CckydP8sd//Mfce++9lJSUsGLFCurr67n66qltMjFj4SzGeOs5jv818NdnOHYAODATdUmSpPyWSCRIJMYfwigsLCSZTJLJZOjs7ORrX/saAE1NTdxwww20trZSVFREUVERX/nKV14wzoMPPkhZWRmvfe1rAXjPe95DZ2fnlMOZ79aUJEl5q6+vj56eHlauXMng4OBEaEskEgwNDZ313Ewmw9Kl/+82+ZKSEjKZzJRrMpxJkqS8NDo6SmNjI21tbSxcuPBXPn+yV0Cdup1+SgxnkiQp74yNjdHY2MjGjRtpaGgAoLi4mGw2C0A2m6WoqOisY5SUlNDf//+2Zh0YGGDJkiVTrs1wJkmS8kqMkc2bN5NMJtm2bdtEe319Pel0GoB0Os369Wd/QdGKFSvo7e3lX//1X3nmmWf4/Oc/T319/ZTrm+03BEiSJF1QXV1ddHR0UFlZSVVVFQDbt2+nubmZDRs2sHv3bkpLS9m3bx8AR48eZfny5Rw/fpw5c+bQ1tbGY489xsKFC/nrv/5r1q5dy8mTJ3nf+95HRUXFlOsznEmSpFlzPltfTLc1a9ZMer8YwKFDh05ru/LKKxkYGJi0/7p161i3bt201ueypiRJUg5x5kySpGny9i/+zWlt//DOjbNQiV7OnDmTJEnKIYYzSZKkHGI4kyRJyiGGM0mSpBxiOJMkSXmlv7+f2tpakskkFRUV7Nq1C4Dh4WFSqRTl5eWkUilGRkYAeOKJJ1i9ejXz5s1jx44dLxjrfe97H0VFRVxzzTXTVp9Pa0qSpFnT+qXstI734VsS5+xTUFDAzp07qa6u5sSJE9TU1JBKpWhvb6euro7m5mZaWlpoaWmhtbWVxYsXc+edd7J///7TxvpP/+k/8f73v59NmzZN2zU4cyZJkvJKIpGgunp889vCwkKSySSZTIbOzk6ampoAaGpqmghjRUVFrFixgrlz55421lve8hYWL148rfUZziRJUt7q6+ujp6eHlStXMjg4SCIxPvOWSCQYGhqalZpc1pQk6SV42999/LS2wPTOoGhmjY6O0tjYSFtbGwsXLpztciY4cyZJkvLO2NgYjY2NbNy4kYaGBgCKi4vJZsfvgctmsxQVFc1KbYYzSZKUV2KMbN68mWQyybZt2yba6+vrSafTAKTTadavXz8r9RnOJElSXunq6qKjo4P77ruPqqoqqqqqOHDgAM3Nzdx7772Ul5dz77330tzcDMDRo0cpKSnhr/7qr/iLv/gLSkpKOH78OAC33norq1ev5l/+5V8oKSlh9+7dU67Pe84kSZpB67948AW/54biWaokN53P1hfTbc2aNcQYJz126NCh09quvPJKBgYGJu3/uc99blprA2fOJEmScorhTJIkKYcYziRJknKI4UySJCmHGM4kSZJyiOFMkiQphxjOJElSXunv76e2tpZkMklFRQW7du0CYHh4mFQqRXl5OalUipGREQCeeOIJVq9ezbx589ixY8c5x5kq9zmTJEmz5uAXfjKt49387lefs09BQQE7d+6kurqaEydOUFNTQyqVor29nbq6Opqbm2lpaaGlpYXW1lYWL17MnXfeyf79+89rnKuvvnpK1+DMmSRJyiuJRILq6moACgsLSSaTZDIZOjs7aWpqAqCpqWkijBUVFbFixQrmzp17XuNMleFMkiTlrb6+Pnp6eli5ciWDg4MkEuNvLEgkEgwNDb2kcabKcCZJkvLS6OgojY2NtLW1sXDhwlkf55cMZ5IkKe+MjY3R2NjIxo0baWhoAKC4uJhsNgtANpulqKjoJY0zVYYzSZKUV2KMbN68mWQyybZt2yba6+vrSafTAKTTadavX/+Sxpkqn9aUJEl5pauri46ODiorK6mqqgJg+/btNDc3s2HDBnbv3k1paSn79u0D4OjRoyxfvpzjx48zZ84c2traeOyxx3j00UcnHWfdunVTqs9wJkmSZs35bH0x3dasWUOMcdJjhw4dOq3tyiuvZGBg4FcaZypc1pQkScohhjNJkqQcYjiTJEnKIYYzSZKkHGI4kyRJyiGGM0mSpBxiOJMk6Tys2//BF3z08tXf309tbS3JZJKKigp27doFwPDwMKlUivLyclKpFCMjIwA88cQTrF69mnnz5rFjx46JcZ5++mmuu+46rr32WioqKvjoRz86LfW5z5kkSZo13/vk4LSOV/GHxefsU1BQwM6dO6murubEiRPU1NSQSqVob2+nrq6O5uZmWlpaaGlpobW1lcWLF3PnnXeyf//+F4wzb9487rvvPi677DLGxsZYs2YNN998M6tWrZrSNThzJkmS8koikaC6uhqAwsJCkskkmUyGzs5OmpqaAGhqapoIY0VFRaxYsYK5c+e+YJwQApdddhkw/o7NsbExQghTrs9wJkmS8lZfXx89PT2sXLmSwcFBEokEMB7ghoaGznn+yZMnqaqqoqioiFQqxcqVK6dck+FMkiTlpdHRURobG2lra2PhwoUvaYxLLrmERx55hIGBAR588EG++93vTrkuw5kkSco7Y2NjNDY2snHjRhoaGgAoLi4mm80CkM1mKSoqOu/xXvnKV3LDDTdwzz33TLk2w5kkScorMUY2b95MMplk27ZtE+319fWk02kA0uk069evP+s4Tz75JMeOHQPg5z//Of/0T//EG97whinX59OakiQpr3R1ddHR0UFlZSVVVVUAbN++nebmZjZs2MDu3bspLS1l3759ABw9epTly5dz/Phx5syZQ1tbG4899hjZbJampiZOnjzJc889x4YNG3j7298+5foMZ5Ikadacz9YX023NmjXEGCc9dujQodParrzySgYGBk5rX7ZsGT09PdNen8uakiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiQpr/T391NbW0symaSiooJdu3YBMDw8TCqVory8nFQqxcjICABPPPEEq1evZt68eezYseO08U6ePMkb3/jGadnjDNznTJIkzaKjO5+Y1vGu/OC5d+gvKChg586dVFdXc+LECWpqakilUrS3t1NXV0dzczMtLS20tLTQ2trK4sWLufPOO9m/f/+k4+3atYtkMsnx48en5RqcOZMkSXklkUhQXV0NQGFhIclkkkwmQ2dnJ01NTQA0NTVNhLGioiJWrFjB3LlzTxtrYGCAr3zlK/ze7/3etNVnOJMkSXmrr6+Pnp4eVq5cyeDgIIlEAhgPcENDQ+c8/0/+5E/4n//zfzJnzvRFKsOZJEnKS6OjozQ2NtLW1sbChQt/5fP/4R/+gaKiImpqaqa1LsOZJEnKO2NjYzQ2NrJx40YaGhoAKC4uJpvNApDNZikqKjrrGF1dXXz5y1/mqquu4j3veQ/33Xcf733ve6dcm+FMkiTllRgjmzdvJplMsm3bton2+vp60uk0AOl0mvXr1591nP/xP/4HAwMD9PX18fnPf563vvWtfPazn51yfT6tKUmS8kpXVxcdHR1UVlZSVVUFwPbt22lubmbDhg3s3r2b0tJS9u3bB8DRo0dZvnw5x48fZ86cObS1tfHYY4+9pKXQ82E4kyRJs+Z8tr6YbmvWrCHGOOmxQ4cOndZ25ZVXMjAwcNYxb7jhBm644YbpKM9lTUmSpFxiOJMkScohhjNJkqQcYjiTJEnKIYYzSZKkHGI4kyRJyiGGM0mSlFf6+/upra0lmUxSUVHBrl27ABgeHiaVSlFeXk4qlWJkZASAJ554gtWrVzNv3jx27NjxgrGuuuqqif3Sli9fPi31uc+ZJEmaNUMfv39axyv6QO05+xQUFLBz506qq6s5ceIENTU1pFIp2tvbqauro7m5mZaWFlpaWmhtbWXx4sXceeed7N+/f9Lx7r//fl796ldP2zU4cyZJkvJKIpGguroagMLCQpLJJJlMhs7OTpqamgBoamqaCGNFRUWsWLGCuXPnXpD6DGeSJClv9fX10dPTw8qVKxkcHCSRSADjAW5oaOic54cQuPHGG6mpqeHTn/70tNTksqYkSS/y4S/edHpjQcWFL0QzanR0lMbGRtra2l7yezK7urpYsmQJQ0NDpFIp3vCGN/CWt7xlSnU5cyZJkvLO2NgYjY2NbNy4kYaGBgCKi4vJZrMAZLNZioqKzjnOkiVLgPGlz1tuuYUHH3xwyrUZziRJUl6JMbJ582aSySTbtm2baK+vryedTgOQTqdZv379Wcf56U9/yokTJya+f/WrX+Waa66Zcn0ua0qSpLzS1dVFR0fHxBYYANu3b6e5uZkNGzawe/duSktL2bdvHwBHjx5l+fLlHD9+nDlz5tDW1sZjjz3GT37yE2655RYAnn32WX77t3+bm26aZEn8V2Q4kyRJs+Z8tr6YbmvWrCHGOOmxQ4cOndZ25ZVXMjAwcFr7woUL+fa3vz3t9bmsKUmSlEMMZ5IkSTnEcCZJkpRDDGeSJOmCOtP9XherX/V6DWeSJOmCmT9/Pk899VTeBLQYI0899RTz588/73N8WlOSJF0wJSUlDAwM8OSTT852KRfM/PnzKSkpOe/+hjNJknTBzJ07l9e85jWzXUZOc1lTkiQphxjOJEmScojhTJIkKYcYziRJknKI4UySJCmHGM4kSZJyiOFMkiQphxjOJEmScojhTJIkKYcYziRJknLIjIWzEMJnQghDIYTvnuH4xhDCo6c+3wwhXPu8Y30hhO+EEB4JITw0UzVKkiTlmpmcOWsHbjrL8X8Fro8xLgP+G/DpFx2vjTFWxRiXz1B9kiRJOWfGXnweY/xGCOGqsxz/5vN+HgbO/3XtkiRJF6lcuedsM3Dweb8j8NUQwsMhhNtmqSZJkqQLbsZmzs5XCKGW8XC25nnN/yHG+OMQQhFwbwjhiRjjN85w/m3AbQClpaUzXq8kSdJMmtWZsxDCMuD/AOtjjE/9sj3G+ONTf4eALwHXnWmMGOOnY4zLY4zLr7jiipkuWZIkaUbNWjgLIZQCfwf8Tozx+89rvzSEUPjL78CNwKRPfEqSJF1sZmxZM4TwOeAG4NUhhAHgo8BcgBjjJ4E/A14FfCKEAPDsqSczi4EvnWorAP5vjPGemapTkiQpl8zk05q3nuP47wG/N0n7D4FrTz9DkiTp4pcrT2tKkiQJw5kkSVJOMZxJkiTlkFnf50ySpNn0qY61pzf+WrjwhUinOHMmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTnEcCZJkpRDDGeSJEk5xHAmSZKUQwxnkiRJOcRwJkmSlEMMZ5IkSTmkYLYLkCTpQur8zM0vbJg7O3VIZ+LMmSRJUg4xnEmSJOUQw5kkSVIOMZxJkiTlEMOZJElSDjGcSZIk5RDDmSRJUg4xnEmSJOUQw5kkSVIOMZxJkiTlEMOZJElSDjlnOAshXBpCmHPq+2+GEOpDCL6JTJIkaQacz8zZN4D5IYRfBw4Bvwu0z2RRkiRJ+ep8wlmIMf4MaAA+HmO8Bbh6ZsuSJEnKT+cVzkIIq4GNwFdOtRXMXEmSJEn563zC2e3AfwG+FGP8XgjhtcD9M1uWJElSfjrrDFgI4RLgHTHG+l+2xRh/CGyd6cIkSZLy0VnDWYzxZAih5kIVI+WToY+/cAK66AO1s1SJJCmXnM+9Yz0hhC8D+4Cf/rIxxvh3M1aVJElSnjqfcLYYeAp46/PaImA4kyRJmmbnDGcxxt+9EIVIkjTdvvWpd5ze6DbqynHnDGchhPnAZqACmP/L9hjj+2awLkmSpLx0PltpdABXAmuBrwMlwImZLEqSJClfnU84K4sx3gH8NMaYBt4GVM5sWZIkSfnpfMLZ2Km/x0II1wCLgKtmrCJJkqQ8dj5Pa346hHA5cAfwZeAy4M9mtCpJkqQ8dT5Pa/6fU1+/Drx2ZsuRJEnKb2cMZyGEbWc7Mcb4V9NfjiRJUn4728xZ4QWrQpIkScBZwlmM8WMXshBJkiSdfVnzzrOdGGPcOv3lSJIk5bezLWs+fMGqkCRJEnD2Zc3083+HEArHm+PojFclSZKUp865CW0I4ZoQQg/wXeCxEMLDIYSKmS9NkiQp/5zPGwI+DWyLMf5GjLEU+CDwv2e2LEmSpPx0PuHs0hjj/b/8EWP8GnDpjFUkSZKUx87n9U0/DCHcAXSc+v1e4F9nriRJkqT8dT7h7H3Ax4C/AwLjr3H63ZksSpKklyL7iQ+/sOGS2alDmorzebfmCOCeZpIkSRfAWe85CyE0hRCOhBB+eurzUAhh04UqTpIkKd+c7Q0Bm4A/AbYBRxhf0qwG/jKEQIxx74UpUZIkKX+cbebsj4BbYoz3xxj/PcZ4LMZ4H9B46pgkSZKm2dnuOVsYY+x7cWOMsS+EsHDmSpIuPkd3PnFa25xXzEIhkqScd7aZs5+/xGOSJEl6ic42c5YMITw6SXsAXjtD9UiSJOW1s4azC1aFJEmSgLOEsxjjv13IQiRJknR+79aUJEnSBWI4kyRJyiGGM0mSpBxyPi8+P00I4c9jjH8+zbVIknTenvxfn53tEqQZ8VJnzh6e1iokSZIEvMRwFmP8++kuRJIkSWcJZyGE3w8hlJ/6HkIIe0IIx0MIj4YQ3njhSpQkScofZ5s5ux3oO/X9VmAZ8BpgG3DnzJYlSZKUn84Wzp6NMY6d+v52YG+M8akY4z8Bl858aZIkSfnnbOHsuRBCIoQwH6gD/ul5x35tZsuSJEnKT2fbSuPPgIeAS4Avxxi/BxBCuB744QWoTZIkKe+c7d2a/xBC+A2gMMY48rxDDwHvnvHKJEmS8tBZt9KIMT77omBGjPGnwGUzWpUkSVKeeqmb0O4+n04hhM+EEIZCCN89w/EQQrgzhPCDU1t0VD/vWFMIoffUp+kl1ilJkvSy8lI3oX3beXZtB246y/GbgfJTn9uA/wUQQlgMfBRYCVwHfDSEcPlLqVWSJOnl5Gyb0C5+0efyEEL4VQaPMX4DGD5Ll/WMb9ERY4yHgVeGEBLAWuDeGOPwqWXVezl7yJMkSboonO1pzYeBCDw/kF0WQvg28Hsxxr5p+Pd/Heh/3u+BU21naj9NCOE2xmfdKC0tnYaSJEmSZs/ZntZ8zWTtIYQG4JNMz0zWZDNxLw6Ez28/vTHGTwOfBli+fPmkfSRJkl4ufuV7zmKMfwcUTdO/PwAsfd7vEuDHZ2mXJEm6qP3K4SyEcNlLOe8MvgxsOvXU5irg32OMWeAfgRtP3ed2OXDjqTZJkqSL2hmXNUMI2yZpvhyoB/76fAYPIXwOuAF4dQhhgPEnMOcCxBg/CRwA1gE/AH4G/O6pY8MhhP8GfOvUUP81xni2BwskSZIuCmd7IKDwRb8jcBR4b4zxO+czeIzx1nMcj8Afn+HYZ4DPnM+/I0mSdLE42wMBH7uQhUiSJGn67h2TJEnSNDCcSZIk5ZCzvSGg9dTfd124ciRJkvLb2WbO1oUQ5gL/5UIVo/+/vTsPt/2c78b//mQ0BpEjSRHTz1NDKZHwFNWaU1PQKEpLKR0MbSk6Pa3h6VW0pZoaSzyKmiIITUSVmGrIQEKCGoqkgkQUpUKSz++PtU7tc/Y5O+fs7LW+373W63Vd59r7e6+1Tt52r57zPvf9/d43ALDs1npa851JLkhy5ar6Tia79m/dvb+7e7855AMAWCo7nTnr7qd099WS/FN379fdV135dY4ZAQCWxlozZ0mS7j6yqg5Mcvh06KPdff5sYwEALKfLfFpz+kDAx5I8KMkvJflYVR0162AAAMvoMmfOkvxJksO7+xtJUlVbkrw7ybGzDAYAsIx2ZZ+zPbYWs6lv7uLnAADYTbsyc/bOqjopyeum1w/O5MByYAfOesnXV41dc4AcAGxOu/JAwFOq6oFJ7pjJNhov6+63zDwZAMAS2pWZs3T3cUmOm3EWAICl594xAIARUc4AAEZkt8pZVV2jqm45qzAAAMtuVzahPbmq9quq/ZOckeSVVfW82UcDAFg+uzJzdrXu/k6SByZ5ZXffJsndZhsLAGA57Uo526uqDs7k6KZ3zDgPAMBS25Vy9swkJyX5fHefUlU3TPK52cYCAFhOu7IJ7ZuSvGnF9ReT/OIsQwEALKvLLGfTg84fk+T6K9/f3Y+aXSwAgOW0KycEvC3JB5K8O8kls40DALDcdqWcXam7nzbzJAAA7NIDAe+oqnvNPAkAALtUzn4nk4L2g6r67vTXd2YdDABgGe3K05pXnUcQAAB27Z6zVNX9ktxpenlyd9uMFgBgBnblbM1nZ7K0efb01+9MxwAA2GC7MnN2ryS36u5Lk6SqXpXk40n+YJbBAACW0a48EJAkV1/x/dVmEQQAgF2bOfuLJB+vqvcmqUzuPfvDmaYCAFhSu/K05uuq6uQkh2dSzp7W3V+bdTAAgGW002XNqrrJ9OuhSQ5Ocm6Sc5L8xHQMAIANttbM2ZMzOfD8r3fwWie5y0wSAQAssZ2Ws+5+zPTrnecXBwBgue20nFXVA9f6YHcft/FxAACW21rLmvdd47VOopwBAGywtZY1f22eQQAAWHtZ80lrfbC7n7fxcQAAlttay5pXnVsKAACSrL2s+Yx5BgEAYO1lzad293Or6uhMHgDYRnc/cabJAACW0FrLmp+efj11HkEAAFh7WfPtVbVnkp/q7qfMMRMAwNLa6dmaSdLdlyS5zZyyAAAsvbXuOduruy9O8vGqOj7Jm5J8b+vrTggAANh4a91z9rEkhybZP8k3s+1B504IAACYgbXKWSVOCgAAmKe1ytmWtU4JcEIAAMDGW6uc7ZnkKpnOoAEAMHtrlbPzuvuZc0sCAMCaW2mYMQMAmLO1ytld55YCAIAka5Sz7r5wnkEAAFj7njNgF5z4hgu2uT5koBwALIY1j28CAGC+LrOcVdUDq+pzVfXtqvpOVX23qr4zj3AAAMtmV5Y1n5vkvt396VmHAQBYdruyrPl1xQwAYD52Zebs1Kp6Q5K3Jrlo62B3O/gcAGCD7Uo52y/J95PcY8VYJ1HOAAA22GWWs+7+tXkEAQBgjXJWVU/t7udW1dGZzJRto7ufONNkAABLaK2Zs60PAZw6jyAAAKxRzrr77dOvr5pfHACA5eaEAACAEVHOAABGZFeObzpgHkEAAFijnFXVfavq/CSfrKpzq+r2c8wFALCU1po5+/MkP9vdByf5xSR/MZ9IAADLa61ydnF3fyZJuvujSa46n0gAAMtrrX3OrlVVT9rZdXc/b3axAACW01rl7O+z7WzZ9tcAAGywtTahfcY8gwAAcBlbaVTVnavqzVV11vTXsVX183PKBgCwdNbaSuPeSY5J8o4kv5zkYUlOSHJMVd1rPvEAAJbLWvecPSXJ/bv7jBVjn6iqU5McnUlRAwBgA621rHnQdsUsSdLdZyY5cHaRAACW11rl7HvrfA0AgHVaa1nzRlV1/A7GK8kNZ5QHAGCprVXOjlzjtb/a6CAAAKy9z9n75hkEAIC1t9I4sqoet+L6o1X1xemvo+YTDwBguaz1QMBTk6y852zfJIcn+fkkvzXDTAAAS2ute8726e5zVlx/sLu/meSbVXXlGecCAFhKa82cXWPlRXc/fsXlltnEAQBYbmuVs49W1WO2H6yq30jysdlFAgBYXmsta/5ekrdW1S8nOX06dptM7j27/6yDAQAso7W20vhGkttX1V2S3Hw6/E/d/Z65JAMAWEJrzZwlSaZlTCEDAJiDte45AwBgzpQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARucytNC6PqjoiyQuS7Jnk5d397O1ef36SO08vr5TkWt199elrlyT55PS1r3T3/WaZFXbFc95y3qqxW2bvAZIAsKhmVs6qas8kL0xy9yTnJjmlqo7v7rO3vqe7f2/F+5+Q5NYrfov/7u5bzSofAMAYzXJZ87ZJPt/dX+zuHyZ5fZIj13j/Q5O8boZ5AABGb5bl7NpJzllxfe50bJWqul6SG2TbkwiuUFWnVtVHqmqnZ3lW1WOn7zv1/PPP34jcAACDmWU5qx2M9U7e+5Akx3b3JSvGDunuw5L8cpK/qaob7eiD3f2y7j6suw/bsmXL5UsMADCwWZazc5Ncd8X1dZJ8dSfvfUi2W9LsXw229AAAIABJREFU7q9Ov34xycnZ9n40AICFNMtydkqSG1fVDapqn0wK2PHbv6mqfjLJNZJ8eMXYNapq3+n3ByS5Q5Kzt/8sAMCimdnTmt19cVU9PslJmWylcUx3n1VVz0xyandvLWoPTfL67l655HnTJC+tqkszKZDPXvmUJwDAoprpPmfdfUKSE7Yb+9Ptrp++g8/9a5JbzDIbAMAYOSEAAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBHZa+gAMFZHvfn0VWOH73HwAEkAWCZmzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYkb2GDgBjceSxJ25zvXcdOFASAJbZTGfOquqIqvpsVX2+qv5gB68/sqrOr6pPTH/9+orXHlFVn5v+esQscwIAjMXMZs6qas8kL0xy9yTnJjmlqo7v7rO3e+sbuvvx2312/yR/luSwJJ3ktOlnvzWrvAAAYzDLmbPbJvl8d3+xu3+Y5PVJjtzFz94zyT9394XTQvbPSY6YUU4AgNGYZTm7dpJzVlyfOx3b3i9W1ZlVdWxVXXc3PwsAsFBmWc5qB2O93fXbk1y/u2+Z5N1JXrUbn528seqxVXVqVZ16/vnnrzssAMAYzLKcnZvkuiuur5Pkqyvf0N3f7O6Lppd/n+Q2u/rZFb/Hy7r7sO4+bMuWLRsSHABgKLMsZ6ckuXFV3aCq9knykCTHr3xDVR284vJ+ST49/f6kJPeoqmtU1TWS3GM6BgCw0Gb2tGZ3X1xVj8+kVO2Z5JjuPquqnpnk1O4+PskTq+p+SS5OcmGSR04/e2FVPSuTgpckz+zuC2eVFQBgLGa6CW13n5DkhO3G/nTF93+Y5A938tljkhwzy3wAAGPj+CYAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBEZnrwOYzVfY597aqxPbP/AEkAYFtmzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARmSvoQMAzMLX/vozq8YOevJNBkgCsHvMnAEAjIhyBgAwIsoZAMCIKGcAACOinAEAjIinNYG5uM+xr1019o6jHnaZn3vOW85bNfa0Bxy8zfVZL/n6qvdcczeyAYyJmTMAgBFRzgAARkQ5AwAYEeUMAGBElDMAgBFRzgAARkQ5AwAYEeUMAGBEbELLwrv3cUevGqvsP0ASNsqJb7hgm+tDBsoBMAtmzgAARkQ5AwAYEeUMAGBE3HMGbDj3+QGsn3IGDObIY0/c5nrvOnDVew7f4+B5xQEYBcuaAAAjYuYMWBrfOPq921xf6wl3HigJwM6ZOQMAGBHlDABgRJQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIAR2WvoAMDmd6+3Pnmb68r1hwkCsADMnAEAjIhyBgAwIsoZAMCIKGcAACOinAEAjIinNYHd8rRjj1g9uNfN5x8EYEGZOQMAGBEzZ8BOvfTV91w9eMWafxCAJWLmDABgRJQzAIARsazJwnGUEACbmZkzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARUc4AAEZkpuWsqo6oqs9W1eer6g928PqTqursqjqzqv6lqq634rVLquoT01/HzzInAMBYzGyfs6raM8kLk9w9yblJTqmq47v77BVv+3iSw7r7+1X1W0mem+TB09f+u7tvNat8AABjNMuZs9sm+Xx3f7G7f5jk9UmOXPmG7n5vd39/evmRJNeZYR4AgNGbZTm7dpJzVlyfOx3bmUcnOXHF9RWq6tSq+khV3X8WAQEAxmaWxzfVDsZ6h2+seniSw5L83IrhQ7r7q1V1wyTvqapPdvcXdvDZxyZ5bJIccsghlz81LLG3HfML2w7sPUwOgGU2y5mzc5Ncd8X1dZJ8dfs3VdXdkvxxkvt190Vbx7v7q9OvX0xycpJb7+g/0t0v6+7DuvuwLVu2bFx6AIABzLKcnZLkxlV1g6raJ8lDkmzz1GVV3TrJSzMpZt9YMX6Nqtp3+v0BSe6QZOWDBAAAC2lmy5rdfXFVPT7JSUn2THJMd59VVc9Mcmp3H5/kL5NcJcmbqipJvtLd90ty0yQvrapLMymQz97uKU8AgIU0y3vO0t0nJDlhu7E/XfH93XbyuX9NcotZZgMAGCMnBAAAjIhyBgAwIsoZAMCIKGcAACMy0wcCYNaeduwRqwf3uvn8gwDABjFzBgAwIsoZAMCIKGcAACOinAEAjIhyBgAwIsoZAMCIKGcAACOinAEAjIhNaGFJnfLS+64e3Hv+OQDYlpkzAIARUc4AAEZEOQMAGBHlDABgRDwQwKbx0lffc/XgFWv+QTaB81/8mlVjF/cntx3Yc05hANgtZs4AAEZEOQMAGBHlDABgRJQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARUc4AAEZEOQMAGBHlDABgRJQzAIARcfA5o/W2Y35h24G9h8kBAPNk5gwAYESUMwCAEVHOAABGRDkDABgR5QwAYESUMwCAEVHOAABGxD5njMIpL73v6kH7mgGwhMycAQCMiHIGADAiyhkAwIgoZwAAI6KcAQCMiKc1GcR5L3ratgN7DpMDAMZGOQNgQ3ztrz+zauygJ99kgCSwuVnWBAAYETNnAOy2s17y9VVj1xwgBywiM2cAACNi5oyZO//Frxk6AgBsGsoZAJfpxDdcsM31IQPlgGWgnAGwjee85bxVY7fM3gMkgeWknAEwM984+r3bXF/rCXceKAlsHh4IAAAYETNnAAvqPse+dtXYO4562ABJgN1h5gwAYETMnAEsgHsfd/Sqscr+l/m5o958+qqxw/c4eEMyAetj5gwAYESUMwCAEVHOAABGxD1nAJvQvd765G2uK9cfJgiw4cycAQCMiHIGADAiljUBlsiRx564zfXedeBASYCdUc4ARu5pxx6xenCvm88/CDAXljUBAEZEOQMAGBHlDABgRNxzBjAiL331PVcPXrHmHwQYjHIGMCenvPS+q8YO/423D5AEGDPlDGBGznvR07Yd2HP1e952zC9sO7D37PIAm4N7zgAARsTMGcAGOP/Frxk6ArAgzJwBAIyIcgYAMCLKGQDAiChnAAAjopwBAIyIcgYAMCLKGQDAiChnAAAjopwBAIyIcgYAMCLKGQDAiChnAAAjopwBAIyIcgYAMCLKGQDAiChnAAAjstfQAZits17y9VVjN//NAwdIAgDsCuVsE3vOW85bNXbLH+69zfUhO/jc1/76M6vGDnryTTYqFgBwOShnJEm+cfR7t7m+1hPuPFASAFhuytkmcdSbT181dvgeBw+QBACYJeVsBO5z7GtXjb3jqIcNkAQAGJpyNmP3euuTt7muS6+/6j2V/VeNHXnsidtc711u4geAZWArDQCAETFztoGeduwRqwf3uvn8gwAAm5Zytk4vffU9Vw9eseYfBABYKDMtZ1V1RJIXJNkzycu7+9nbvb5vkn9Icpsk30zy4O7+0vS1P0zy6CSXJHlid5+0EZnOf/FrVo1d3J/c5vrcPc9e9Z6v7n3xtgN7r3oLAMDlNrN7zqpqzyQvTPILSW6W5KFVdbPt3vboJN/q7v8vyfOTPGf62ZsleUiSmyc5IsmLpr8fAMBCm+XM2W2TfL67v5gkVfX6JEcmWTktdWSSp0+/PzbJ31VVTcdf390XJfn3qvr89Pf78AzzAgBL7MQ3XLDN9SHfumTVe675vW+tGttjn21P7Lm8G7lXd1+u32Cnv3HVUUmO6O5fn17/SpLbdffjV7znU9P3nDu9/kKS22VS2D7S3a+Zjr8iyYndfewO/juPTfLY6eVPJvnsTP4HzdYBSS64zHexkfzM58/PfP78zOfPz3z+NvPP/HrdvWX7wVnOnO3o7vjtm+DO3rMrn50Mdr8syct2L9q4VNWp3X3Y0DmWiZ/5/PmZz5+f+fz5mc/fIv7MZ7nP2blJrrvi+jpJvrqz91TVXkmuluTCXfwsAMDCmWU5OyXJjavqBlW1TyY3+B+/3XuOT/KI6fdHJXlPT9ZZj0/ykKrat6pukOTGST42w6wAAKMws2XN7r64qh6f5KRMttI4prvPqqpnJjm1u49P8ookr57e8H9hJgUu0/e9MZOHBy5O8rjuXn1X3uLY1Muym5Sf+fz5mc+fn/n8+ZnP38L9zGf2QAAAALvP2ZoAACOinAEAjIhyBgAwIsoZMDNV9fiqusbQOZZNVR1YVfeZ/rrW0HkWWVXduKqOraqzq+qLW38NnYvNTTkbSE08vKr+dHp9SFXdduhci6yqtlTVX1XVCVX1nq2/hs614A5KckpVvbGqjpgez8YMVdUvZbL10IOS/FKSj05PbGE2XpnkxZnsLHDnJP+Q5NWDJloCVXWlqvo/VfX30+sbV9V9hs61UTytOZCqenGSS5PcpbtvOp1deFd3Hz5wtIVVVe9K8oYkv5/kNzPZY+/87n7aoMEW3LSQ3SPJryU5LMkbk7yiu78waLAFVVVnJLl7d39jer0lybu7+6eHTbaYquq07r5NVX2yu28xHftAd//s0NkWWVW9IclpSX61u3+qqq6Y5MPdfauBo20IM2fDuV13Py7JD5Kku7+VZJ9hIy28a3b3K5L8qLvf192PSvK/hw616KYbS39t+uviJNdIcmxVPXfQYItrj63FbOqb8Wf9LP2gqvZI8rnpMv4DklhKnr0bdfdzk/woSbr7v7Pjox83pVmercnaflRVe2Z6Zuj0X7eXDhtp4f1o+vW8qrp3JkeCXWfAPAuvqp6YyQzlBUlenuQp3f2jrX+ZJXnqkPkW1Dur6qQkr5tePzjJiQPmWXS/m+RKSZ6Y5FmZLG0+Ys1PsBF+OJ0t2/p36I2SXDRspI1jWXMgVfWwTP7QPDTJqzI5vupPuvtNgwZbYNP7ET6QybmtRyfZL8kzpqdVMAPTE0Fe0d1f3sFrN+3uTw8Qa+FV1QOT3DGTmYT3d/dbBo4EG6qq7pHkj5PcLMm7ktwhySO7++Qhc20U5WxAVXWTJHfN5A/Qf/EXFYtoOkN8YFbM1Hf3V4ZLtNim5xGf190/mF5fMcmB3f2lQYMtqKr65yQP6u7/nF5fI8nru/uewyZbfFV1zUxuTakkH+nuCwaOtGGUszmrqv3Xer27L5xXlmUzXTp+TJLrZ9ui8KihMi266fm6T0/y9fx42b67+5aDhVpwVXVqktt39w+n1/sk+ZCHjWajqj7e3be+rDE2VlW9Osn7k3yguz8zdJ6N5p6z+TstkzXylTcubr3uJDccItSSeFsmy5rvTnLJwFmWxe8m+cnu/ubQQZbIXluLWZJ09w+nBY3ZuLSqDtk6G1xV18v0Pihm6pWZLN0fXVU3TPKJTJbwXzBsrI2hnM1Zd99g6AxL7Eq2zZi7c5J8e+gQS+b8qrrf1nspq+rITB7IYDb+OMkHq+p90+s7JXnsgHmWQne/Z/ozPzyThzB+M8nNkyxEObOsOWdVdZPu/kxVHbqj17v79HlnWhZV9X+T/Gt3nzB0lmVRVa9I8pNJ/ikrnqTq7ucNFmrBTZ9ae22Sn8hkRv6cTPaC+vygwRZYVR2QH9/79OFFuvdprKrqX5JcOcmHM1kR+eB2W8hsasrZnFXVy7r7sVX13h283N19l7mHWhJV9d1M/p/5oky21ahMfub7DRpsgVXVn+1ovLufMe8sy6aqrpLJn/HfHTrLIvIP7WFV1fOT3CaTP88/lMn9Zx+e7ne26SlnAAugqh7e3a+pqift6HWzlRvLP7THYfqPkF/L5OSXg7p734EjbQj3nA2oqm6f1U8O/sNggRaUf+EOZ/qE7FMzuRfkClvH/cU1E1eefr3qoCmWxLSY7ZHJ/pQfGjrPspk+Cf6zmcyefTnJMZksby4EM2cDmT4GfKNMnjDZ+uRgd/cTh0u1mPwLdzjOMx2Hqtpn5ROcbJyq+nB3/8zQOZZNVT0lk6XM07r74qHzbDTlbCBV9ekkN2v/B2CBrTgU+syte5tV1fu6++eGzraoqurkTHZK/9L0+vAkL3fw+WxU1TOSnJnkOH+ez9d0NeSOmWxd8qFFWgWxrDmcTyU5KMl5QwdZJpaS5855pvP3F5mcr/m3Sa6d5BcyuSeH2XhSJkvKl1TV1sO3PWg0Y1X1f5L8UpLjpkOvrKo3dff/HTDWhjFzNmdV9fZMWv5Vk9wqycey7RYD9xso2sKzlDx/zjMdRlX9fJJ/zmR/s1t399eGTQQba7r6dOvtjik7vbtvOmyyjWHmbP6Oz+Scwe1vXPy5JP8x/zhL5bBYSp6r7n7H9NtvZ7JRJDO2YkbhTklumeTkqnpyd//TsMkWU1VVkocluUF3P6uqrpvk4O7+2MDRFt2XMnnI6AfT632TfGGwNBtMOZu/I5P8UXefuXKwqr6X5M+SvGKQVMvBUvKcTQ/hfkJWLyWbIZ6dA5Lcdrrf04er6p1JXp7JRsBsvBdlcm7sXZI8K8l/JXlhJjvXs8Gq6uhMVp8uSnLW9OD5TnL3JB8cMttGsqw5Z1X1qe7+qZ289snuvsW8My06S8nDqaozMvkHxyfz44PP093v2+mHuNymSzyHdPdnh86y6Krq9O4+dOVh51V1hgcwZqOqHrHW6939qnllmSUzZ/N3hTVeu+LcUiwXS8nD+UF3/+3QIZZJVd03yV8l2SfJDarqVkme6R8hM/Ojqtoz08POp3v7Xbr2R1ivRSlfl0U5m79Tquox3f33Kwer6tFJThso06KzlDycF0yPcHpXtp2tXJhH3kfo6Ulum+TkJOnuT0yXl5mNv03yliTXqqo/T3JUkj8ZNtLiq6obZ/Jk8s2y7QbXNxws1AZSzubvd5O8paoelh+XscMy+VfuAwZLtdiuv30xS5LuPrWqrj//OEvlFkl+JZP7cbbOJvT0mtm4uLu/PblP/X+4f2VGuvu1VXVakrtmso3G/bv70wPHWgavzOQf18/P5GGjX8vk578QlLM56+6vJ7l9Vd05ydZ7z/6pu98zYKxFZyl5OA9IckO708/Vp6rql5PsOZ1deGKSfx0406L7eia3TeyV5IpVdajZ4Zm7Ynf/S1VVd385ydOr6gOZFLZNTzkbSHe/N8mOjhNi41lKHs4ZSa6e5BtDB1kiT0jyx5ksI78uyUmZPEXIDFTVs5I8MpNtHLbOUJodnr0fTM82/dz0nM3/SHKtgTNtGE9rsvCq6sBM7gn5YXawlGyDztmZHiV0yySnxBOyLKCq+mySW5gdnq/psWSfzuQff89KcrUkz+3ujwwabIMoZyyN7ZaSz7KUPHtVtcMzNG2lsfGqas1TFxTi2aiqNyf5re42OzyAqtovk5Nevjt0lo2knAEzMV1yOHNn+/qxsarq/CTnZLKU+dFsd3O0QjwbVXVYkrdlssm12eE5mf7cX5nJ/pXJ5BSSR3X3Qtyq4p4zYCa6+9KqOqOqDunurwydZwkclMku6Q9N8suZnAjwuu4+a9BUi+9VSZ6T7TZaZuaOSfLb3f2BJKmqO2ZS1m45aKoNopwBs3RwJkesfCzJ97YOmlXYeN19SZJ3JnlnVe2bSUk7uaqe2d1HD5tuoV1go+VBfHdrMUuS7v5gVS3M0qZlTWBm3HM2X9NSdu9Mitn1Mzkd45judhLGjFTV8zJZzjw+Nlqeuao6dPrtryS5UibL+J3kwUm+1d1/PFS2jaScATNVVddLcuPufndVXSnJnot28+4YVNWrMnng5cQkr+/uTw0caSlU1Y62ROrutpXGDOzk573VwvzclTNgZqrqMUkem2T/7r7RdFPUl3T3XQeOtnCq6tL8eOl45R/slclfWvvNP9VyqqoDpxuOw7q45wyYpcdlcs7jR5Okuz9XVQuzUeSYdPceQ2dYZlV1tSS/mMnDGDdNcu1hEy22qrp6kl/NZPn+f7pMdz9xqEwbSTkDZumi7v7h1nMeq2qvOOeRBVFVV0xyv0wK2aGZbOtw/yTvHzLXkjghyUeyoE/JKmfALL2vqv4ok/MG757kt5O8feBMcLlV1WuT3CnJu5L8XZL3JPl8d588ZK4lcoXuftLQIWbFPWfAzEw3on10kntMh07q7pcPGAk2RFWdkcn9fP+Q5A3dfU5VfbG7bzhwtKVQVb+X5L+SvCPbPiV74WChNpByBmy4qjoyyXW6+4XT648l2ZLJkuZTu/vYIfPBRqiqm2SypPngJN9IcpNMztl0Xu+MVdXjkvx5kv/MigPnF6UcK2fAhquqDyV5SHefM73+RJK7JLlKkld6WpNFMz1O6KFJHpTk3O6+/cCRFlpVfSHJ7br7gqGzzIJ7zoBZ2GdrMZv64HS54cKquvJQoWBWuvvUJKdW1e9nci8as3VWku8PHWJWlDNgFq6x8qK7H7/icsucs8Dc9GQ5ygkYs3dJkk9MN6Vdec+ZrTQAduKjVfWY7v77lYNV9RtJPjZQJmBxvHX6ayG55wzYcNONZt+ayb9ot54xeJsk+ya5v93T2eyq6ne6+wVVdYfu/tDQeVgsyhkwM1V1lyQ3n16e1d3vGTIPbJSq+kR336qqTu/uQy/7E2yEqnpjd/9SVX0yO9jQurtvOUCsDWdZE5iZaRlTyFhEn66qLyXZUlVnrhjfepbpQpSEEXrL9Ot9dvDag+cZZJbMnAHAOlTVQUlOyuQIp21095fnn2jxVdUlmRyP9fDu/o/tXluYWUwH5QLAOnT317r7p5Ocl8m5mldN8lXFbKbOTPKPST5SVQ/a7rUaIM9MKGcAsE5V9XNJPpfkhUlelOTfqso+Z7PT06fA75rkqVX1yqq60tbXBsy1oZQzAFi/5yW5R3f/XHffKck9kzx/4EwLr7v/LcnPJPl6ko9X1e0GjrShPBAAAOu3d3d/dutFd/9bVe09ZKAF9z9Ll919cZI/qKp3JnldFmiDa+UMANbv1Kp6RZJXT68fluS0AfMsumdsP9DdJ1fVbZL8xgB5ZsLTmgCwTlW1b5LHJbljJrM670/you6+aM0PwhqUMwCAEfFAAADAiChnAAAjopwBwAaoqj2qar+hc7D5KWcAsE5V9Y9VtV9VXTnJ2Uk+W1VPGToXm5tyBgDrd7Pu/k6S+yc5IckhSX5l2EhsdsoZAKzf3tNNZ++f5G3d/aMs0DFCDEM5A4D1e2mSLyW5cpL3V9X1knxn0ERsevY5A4ANVFV7TY8WgnUxcwYA61RVB1bVK6rqxOn1zZI8YuBYbHLKGQCs3/9LclKSn5he/1uS3x0sDQtBOQOA9Tugu9+Y5NIkmS5nXjJsJDY75QwA1u97VXXNTJ/QrKr/neTbw0Zis9tr6AAAsIk9KcnxSW5UVR9KsiXJg4aNxGbnaU0AWKeq2jeTZcyfTFJJPptkj+6+aNBgbGrKGQCsU1Wd3t2HXtYY7A7LmgCwm6rqoCTXTnLFqrp1JrNmSbJfkisNFoyFoJwBwO67Z5JHJrlOkuetGP9ukj8aIhCLw7ImAKxTVf1id7956BwsFuUMAC6Hqrp3kpsnucLWse5+5nCJ2OzscwYA61RVL0ny4CRPyOS+swclud6godj0zJwBwDpV1ZndfcsVX6+S5LjuvsfQ2di8zJwBwPr99/Tr96vqJ5L8KMkNBszDAvC0JgCs3zuq6upJ/jLJ6Zkc4/TyYSOx2VnWBIB1qqp9t54GMD0t4ApJfuCEAC4Py5oAsH4f3vpNd1/U3d9eOQbrYVkTAHaTEwKYJeUMAHbfyhMC/jo/LmdOCOByc88ZAKyTEwKYBfecAcBuqqr7VtX1thazqvrTqjqjqo6vKltpcLkoZwCw+/48yflJUlX3SfLwJI9KcnySlwyYiwWgnAHA7uvu/v70+wcmeUV3n9bdL0+yZcBcLADlDAB2X1XVVapqjyR3TfIvK167wk4+A7vE05oAsPv+Jsknknwnyae7+9QkmW6rcd6Qwdj8PK0JAOtQVddOcq0kZ3T3pdOxg5Ps3d1fGTQcm5pyBgAwIu45AwAYEeUMAGBEPBAAALupqvZf6/XuvnBeWVg87jkDgN1UVf+epDM5U/OQJN+afn/1JF/pbqcEsG6WNQFgN3X3Dbr7hklOSnLf7j6gu6+Z5D5Jjhs2HZudmTMAWKeqOq27b7Pd2KndfdhQmdj83HMGAOt3QVX9SZLXZLLM+fAk3xw2EpudZU0AWL+HZnKW5lumv7ZMx2DdLGv3DHgeAAAESklEQVQCwOVUVVfp7v8aOgeLwcwZAKxTVd2+qs5Ocvb0+qer6kUDx2KTU84AYP2en+Semd5n1t1nJLnToInY9JQzALgcuvuc7YYuGSQIC8PTmgCwfudU1e2TdFXtk+SJST49cCY2OQ8EAMA6VdUBSV6Q5G6ZnBDwriRPdHwTl4dyBgDrVFV36O4PXdYY7A7lDADWqapO7+5DL2sMdod7zgBgN1XVzyS5fZItVfWkFS/tl2TPYVKxKJQzANh9+yS5SiZ/j151xfh3khw1SCIWhmVNAFinqrped3956BwsFuUMAHZTVf1Nd/9uVb09kwPPt9Hd9xsgFgvCsiYA7L5XT7/+1aApWEhmzgAARsTMGQCsU1XdIcnTk1wvk79TK0l39w2HzMXmZuYMANapqj6T5PeSnJYVZ2p29zcHC8WmZ+YMANbv29194tAhWCxmzgBgnarq2ZlsOntckou2jnf36YOFYtNTzgBgnarqvTsY7u6+y9zDsDCUMwCAEXHPGQDspu3O00wmG9FekOSD3f3vA0RigewxdAAA2ISuut2v/ZIcluTEqnrIkMHY/CxrAsAGqar9k7y7uw8dOgubl5kzANgg3X1hJhvRwropZwCwQarqLkm+NXQONjcPBADAbqqqT2byEMBK+yf5apJfnX8iFol7zgBgN1XV9bYb6iTf7O7vDZGHxaKcAQCMiHvOAABGRDkDABgR5QxYSFV1UFW9vqq+UFVnV9UJVfW/NvD3//mquv1G/X4AWylnwMKpqkryliQnd/eNuvtmSf4oyYEb+J/5+SQ7LGdV5Ul4YN2UM2AR3TnJj7r7JVsHuvsTST5YVX9ZVZ+qqk9W1YOT/5kFe8fW91bV31XVI6fff6mqnlFVp08/c5Oqun6S30zye1X1iar62ar6f1X1vKp6b5K/rKrPVdWW6e+xR1V9vqoOmNcPANi8/OsOWEQ/leS0HYw/MMmtkvx0kgOSnFJV79+F3++C7j60qn47ye93969X1UuS/Fd3/1WSVNWjk/yvJHfr7kuq6j+TPCzJ3yS5W5IzuvuCy/2/DFh4Zs6AZXLHJK/r7ku6++tJ3pfk8F343HHTr6cluf4a73tTd18y/f6Y/Hgz0kcleeXuxwWWkXIGLKKzktxmB+M7O/Pw4mz75+EVtnv9ounXS7L2isP/bEDa3eck+fr0OJ/bJTlxrcAAWylnwCJ6T5J9q+oxWweq6vBMzjx8cFXtOb0f7E5JPpbky0luVlX7VtXVktx1F/4b301y1ct4z8uTvCbJG1fMqAGsSTkDFk5Pjj55QJK7T7fSOCvJ05P8Y5Izk5yRSYF7and/bTrL9cbpa69N8vFd+M+8PckDtj4QsJP3HJ/kKrGkCewGxzcBzEhVHZbk+d29s/IGsIqnNQFmoKr+IMlvZfLEJsAuM3MGADAi7jkDABgR5QwAYESUMwCAEVHOAABGRDkDABgR5QwAYET+fyQ2Ut07aO4FAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(10, 15)) \n",
    "sns.barplot(data=df, x='Country', y='GDP', hue='Year')\n",
    "plt.ylabel('GDP in Trillions of U.S. Dollars')\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('barPlot_GDP_with_Years.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have plotted a barplot that clusters GDP over time by Country, let's do the same for Life Expectancy.\n",
    "\n",
    "The code will essentially be the same as above!\n",
    "1. Changed our `y` value to `LEABY` in order to plot life expectancy instead of GDP. \n",
    "2. Tweaked the name of our `ylabel` to reflect this change, by making the label `\"Life expectancy at birth in years\"` "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(10, 15)) \n",
    "sns.barplot(data=df, x='Country', y='LEABY', hue='Year')\n",
    "plt.ylabel('Life Expectancy at Birth in Years')\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('barPlot_LEABY_with_YEARS.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What are your first impressions looking at the visualized data?\n",
    "\n",
    "- Which countries' bars changes the most?\n",
    "- What years are there the biggest changes in the data?\n",
    "- Which country has had the least change in GDP over time? \n",
    "- How do countries compare to one another?\n",
    "- Now that you can see the both bar charts, what do you think about the relationship between GDP and life expectancy?\n",
    "- Can you think of any reasons that the data looks like this for particular countries?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "## China has a very steep growth over the years, especially after 2003, 2004 its GDP shoots up and keeps on increasing.\n",
    "## We can notice the slight dip in GDP around 2008-2009 when the financial crisis happened. It's affect can be see in countries like \n",
    "## USA, Mexico, Germany, but no affect on China\n",
    "## Zimbabwe GDP is too minimal that it barely shows up when compared on the scale to other countries\n",
    "## Chile and Germany both have Life Expectancy above 80, and this tells even though Chile's GDP is very low,\n",
    "## the life expectancy is still high.\n",
    "## Zimbabwe's Life Expectancy does catch attention as the LEABY decreases after 2000 over the 5 year period, \n",
    "## only to improve and get better after 2005. This is possible because of the turbulent government, and crisis.\n",
    "## This again can be noticed in Mexico & USA, two neighbouring countries with a huge difference between the GDP\n",
    "## yet the life expectancy isn't too far from each other. USA does have higher life expectancy, but still falls short\n",
    "## when compared to Chile and Germany with much much lower GDP.\n",
    "## This gives an idea that GDP and Life Expectancy don't have a correlation and would need further studied to be proven so."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: We've mapped two bar plots showcasing a variable over time by country, however, bar charts are not traditionally used for this purpose. In fact, a great way to visualize a variable over time is by using a line plot. While the bar charts tell us some information, the data would be better illustrated on a line plot.  We will complete this in steps 9 and 10."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 8. Scatter Plots of GDP and Life Expectancy Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To create a visualization that will make it easier to see the possible correlation between GDP and life expectancy, you can plot each set of data on its own subplot, on a shared figure.\n",
    "\n",
    "To create multiple plots for comparison, Seaborn has a special (function)[https://seaborn.pydata.org/generated/seaborn.FacetGrid.html] called `FacetGrid`. A FacetGrid takes in a function and creates an individual graph for which you specify the arguments!\n",
    "    \n",
    "Since this may be the first time you've learned about FacetGrid, we have prepped a fill in the blank code snippet below. \n",
    "Here are the instructors to fill in the blanks from the commented word bank:\n",
    "\n",
    "1. In this graph, we want GDP on the X axis and Life Expectancy on the Y axis.\n",
    "2. We want the columns to be split up for every Year in the data\n",
    "3. We want the data points to be differentiated (hue) by Country.\n",
    "4. We want to use a Matplotlib scatter plot to visualize the different graphs\n",
    "\n",
    "\n",
    "Be sure to show your plot!\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 736.75x576 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# WORDBANK:\n",
    "# \"Year\"\n",
    "# \"Country\" \n",
    "# \"GDP\" \n",
    "# \"LEABY\" \n",
    "# plt.scatter\n",
    "\n",
    "g = sns.FacetGrid(df, col='Year', hue='Country', col_wrap=4, height=2)\n",
    "g = (g.map(plt.scatter, 'GDP', 'LEABY', edgecolor=\"w\").add_legend())\n",
    "plt.savefig('scatterPlot_LEABY_with_Years.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Which country moves the most along the X axis over the years?\n",
    "+ Which country moves the most along the Y axis over the years?\n",
    "+ Is this surprising?\n",
    "+ Do you think these scatter plots are easy to read? Maybe there's a way to plot that! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# China moves across the X axis the most\n",
    "# Zimbabwe moves across the Y axis after the years 2005 there's an increase and growth in Life expectancy.\n",
    "# Based on seeing the other charts and this, it's not surprisng at all.\n",
    "# Their policies and communist rule with heavy focus on mass manufacturing reved up their economy increasing their\n",
    "# GDP at a steep growth.\n",
    "# Since there are too many scatter plots, and they are mini-graphs it's hard to get an accurate reading but rather\n",
    "# only to see some trends which does help."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 9. Line Plots for Life Expectancy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the scatter plot grid above, it was hard to isolate the change for GDP and Life expectancy over time. \n",
    "It would be better illustrated with a line graph for each GDP and Life Expectancy by country. \n",
    "\n",
    "FacetGrid also allows you to do that! Instead of passing in `plt.scatter` as your Matplotlib function, you would have to pass in `plt.plot` to see a line graph. A few other things have to change as well. So we have created a different codesnippets with fill in the blanks.  that makes use of a line chart, and we will make two seperate FacetGrids for both GDP and Life Expectancy separately.\n",
    "\n",
    "Here are the instructors to fill in the blanks from the commented word bank:\n",
    "\n",
    "1. In this graph, we want Years on the X axis and Life Expectancy on the Y axis.\n",
    "2. We want the columns to be split up by Country\n",
    "3. We want to use a Matplotlib line plot to visualize the different graphs\n",
    "\n",
    "\n",
    "Be sure to show your plot!\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 872x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# WORDBANK:\n",
    "# plt.plot\n",
    "# \"LEABY\"\n",
    "# \"Year\"\n",
    "# \"Country\"\n",
    "\n",
    "\n",
    "# Uncomment the code below and fill in the blanks\n",
    "g3 = sns.FacetGrid(df, col=\"Country\", col_wrap=3, height=4)\n",
    "g3 = (g3.map(plt.plot, \"Year\", \"LEABY\", marker='.', linestyle='-', color='b').add_legend().set_axis_labels('Year', 'Life Expectancy (years)'))\n",
    "g3.set(xticks=df.Year)\n",
    "g3.set(xticklabels=range(2000,2016))\n",
    "g3.set_xticklabels(rotation=90)\n",
    "plt.savefig('linePlot_LEABY_by_Year_and_Country.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What are your first impressions looking at the visualized data?\n",
    "\n",
    "- Which countries' line changes the most?\n",
    "> Zimbabwe has a very visual change among all the countries\n",
    "- What years are there the biggest changes in the data?\n",
    "> Again it seems to be Zimbabwe with the biggest changes in data, whilst other ofcourse have a change but not as significant.\n",
    "- Which country has had the least change in life expectancy over time? \n",
    "> Mexico, where the Life Expectancy start at 75 in 2000 and increase only by an year or two by 2015\n",
    "- Can you think of any reasons that the data looks like this for particular countries?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 10. Line Plots for GDP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's recreate the same FacetGrid for GDP now. Instead of Life Expectancy on the Y axis, we now we want GDP.\n",
    "\n",
    "Once you complete and successfully run the code above, copy and paste it into the cell below. Change the variable for the X axis. Change the color on your own! Be sure to show your plot.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 872x576 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g3 = sns.FacetGrid(df, col=\"Country\", col_wrap=3, height=4)\n",
    "g3 = (g3.map(plt.plot, \"Year\", \"GDP\", marker=\".\", color='g').add_legend().set_axis_labels('Year', 'GDP in Trillion (USD)'))\n",
    "g3.set(xticks=df.Year)\n",
    "g3.set(xticklabels=range(2000,2016))\n",
    "g3.set_xticklabels(rotation=90)\n",
    "plt.savefig('linePlot_GDP_by_Year_and_Country.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Which countries have the highest and lowest GDP?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Highest**: USA and China\n",
    "\n",
    "> **Lowest**: Zimbabwe, Mexico and Chile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Which countries have the highest and lowest life expectancy?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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    "> **Highest:** Germany and Chile\n",
    "\n",
    "> **Lowest:** Zimbabwe"
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