google play analysis .ipynb

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      "Total number of apps in the dataset =  9659\n",
      "      Unnamed: 0                                           App  \\\n",
      "8203        9324                                            EG   \n",
      "2437        3137  HSL - Tickets, route planner and information   \n",
      "6607        7666                   2-Player Co-op Zombie Shoot   \n",
      "325          361                                  Xperia Link™   \n",
      "4547        5513                                   中国語 AQリスニング   \n",
      "\n",
      "              Category  Rating  Reviews  Size     Installs  Type Price  \\\n",
      "8203      PRODUCTIVITY     NaN        3   4.4         100+  Free     0   \n",
      "2437  TRAVEL_AND_LOCAL     3.3      256  17.0     100,000+  Free     0   \n",
      "6607              GAME     4.2       33  13.0       1,000+  Free     0   \n",
      "325      COMMUNICATION     4.1    45487   NaN  10,000,000+  Free     0   \n",
      "4547            FAMILY     NaN       21  17.0       5,000+  Free     0   \n",
      "\n",
      "     Content Rating          Genres      Last Updated         Current Ver  \\\n",
      "8203       Everyone    Productivity      July 1, 2016                 4.2   \n",
      "2437       Everyone  Travel & Local    August 1, 2018               1.1.2   \n",
      "6607           Teen          Action      July 1, 2018              1.0.13   \n",
      "325        Everyone   Communication  October 27, 2016  Varies with device   \n",
      "4547       Everyone       Education     June 22, 2016               2.4.0   \n",
      "\n",
      "             Android Ver  \n",
      "8203        4.0.3 and up  \n",
      "2437          5.0 and up  \n",
      "6607          2.3 and up  \n",
      "325   Varies with device  \n",
      "4547          4.0 and up  \n"
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    "# Read in dataset\n",
    "import pandas as pd\n",
    "apps_with_duplicates = pd.read_csv(\"datasets/apps.csv\")\n",
    "\n",
    "# Drop duplicates from apps_with_duplicates\n",
    "apps = apps_with_duplicates.drop_duplicates()\n",
    "\n",
    "\n",
    "# Print the total number of apps\n",
    "print('Total number of apps in the dataset = ', len(apps))\n",
    "\n",
    "# Have a look at a random sample of 5 rows\n",
    "n = 5\n",
    "print(apps.sample(n))"
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    "## 2. Data cleaning\n",
    "<p>By looking at a random sample of the dataset rows , some entries in the columns like <code>Installs</code> and <code>Price</code> have a few special characters (<code>+</code> <code>,</code> <code>$</code>) due to the way the numbers have been represented. This prevents the columns from being purely numeric, making it difficult to use them in subsequent future mathematical calculations. Ideally, as their names suggest, these columns should contain only digits from [0-9].</p>\n"
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      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9659 entries, 0 to 9658\n",
      "Data columns (total 14 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Unnamed: 0      9659 non-null   int64  \n",
      " 1   App             9659 non-null   object \n",
      " 2   Category        9659 non-null   object \n",
      " 3   Rating          8196 non-null   float64\n",
      " 4   Reviews         9659 non-null   int64  \n",
      " 5   Size            8432 non-null   float64\n",
      " 6   Installs        9659 non-null   object \n",
      " 7   Type            9659 non-null   object \n",
      " 8   Price           9659 non-null   object \n",
      " 9   Content Rating  9659 non-null   object \n",
      " 10  Genres          9659 non-null   object \n",
      " 11  Last Updated    9659 non-null   object \n",
      " 12  Current Ver     9651 non-null   object \n",
      " 13  Android Ver     9657 non-null   object \n",
      "dtypes: float64(2), int64(2), object(10)\n",
      "memory usage: 1.1+ MB\n",
      "None\n"
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    "# List of characters to remove\n",
    "chars_to_remove = ['+', ',', '$']\n",
    "# List of column names to clean\n",
    "cols_to_clean = ['Installs', 'Price']\n",
    "\n",
    "# Loop for each column in cols_to_clean\n",
    "for col in cols_to_clean:\n",
    "    # Loop for each char in chars_to_remove\n",
    "    for char in chars_to_remove:\n",
    "        # Replace the character with an empty string\n",
    "        apps[col] = apps[col].apply(lambda x: x.replace(char, ''))  \n",
    "\n",
    "# Print a summary of the apps dataframe\n",
    "print(apps.info())"
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      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 9659 entries, 0 to 9658\n",
      "Data columns (total 14 columns):\n",
      " #   Column          Non-Null Count  Dtype  \n",
      "---  ------          --------------  -----  \n",
      " 0   Unnamed: 0      9659 non-null   int64  \n",
      " 1   App             9659 non-null   object \n",
      " 2   Category        9659 non-null   object \n",
      " 3   Rating          8196 non-null   float64\n",
      " 4   Reviews         9659 non-null   int64  \n",
      " 5   Size            8432 non-null   float64\n",
      " 6   Installs        9659 non-null   float64\n",
      " 7   Type            9659 non-null   object \n",
      " 8   Price           9659 non-null   float64\n",
      " 9   Content Rating  9659 non-null   object \n",
      " 10  Genres          9659 non-null   object \n",
      " 11  Last Updated    9659 non-null   object \n",
      " 12  Current Ver     9651 non-null   object \n",
      " 13  Android Ver     9657 non-null   object \n",
      "dtypes: float64(4), int64(2), object(8)\n",
      "memory usage: 1.1+ MB\n",
      "None\n"
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   "source": [
    "import numpy as np\n",
    "#converting data types\n",
    "# Convert Installs to float data type\n",
    "apps[\"Installs\"] = apps[\"Installs\"].astype(float)\n",
    "\n",
    "# Convert Price to float data type\n",
    "apps[\"Price\"] = apps[\"Price\"].astype(float)\n",
    "\n",
    "# Checking dtypes of the apps dataframe\n",
    "print(apps.info())"
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   "source": [
    "#Distribution of app ratings\n",
    "import plotly\n",
    "plotly.offline.init_notebook_mode(connected=True)\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "# Print the total number of unique categories\n",
    "num_categories = len(apps[\"Category\"].unique())\n",
    "print('Number of categories = ', num_categories)\n",
    "\n",
    "# Count the number of apps in each 'Category'. \n",
    "num_apps_in_category = apps[\"Category\"].value_counts()\n",
    "\n",
    "# Sort num_apps_in_category in descending order based on the count of apps in each category\n",
    "sorted_num_apps_in_category = num_apps_in_category.sort_values(ascending= False)\n",
    "\n",
    "data = [go.Bar(\n",
    "        x = num_apps_in_category.index, # index = category name\n",
    "        y = num_apps_in_category.values, # value = count\n",
    ")]\n",
    "\n",
    "plotly.offline.iplot(data)"
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  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f3ce2cc5",
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      "Average app rating =  4.173243045387998\n"
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          4,
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          4,
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          2,
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          4,
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          5,
          5,
          5,
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          4,
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          5,
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          1,
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          4,
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          4,
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          4,
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          5,
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          4,
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          4,
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          4,
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          4,
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          null,
          null,
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          null,
          null,
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          null,
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          4.4,
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          4,
          5,
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          5,
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          5,
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          4,
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          4,
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          5,
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          5,
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          null,
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          4,
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          3,
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          4,
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          5,
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          4,
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          4,
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          4,
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          4,
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          5,
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          5,
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          3,
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          5,
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          null,
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          null,
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          null,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          1,
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          null,
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          null,
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          4,
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          4,
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          4,
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          3,
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          5,
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          4,
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          null,
          5,
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          5,
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          3.1,
          4.5,
          4.4,
          4.5,
          4.5,
          null,
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   ],
   "source": [
    "# Average rating of apps\n",
    "avg_app_rating = apps[\"Rating\"].mean()\n",
    "print('Average app rating = ', avg_app_rating)\n",
    "\n",
    "# Distribution of apps according to their ratings\n",
    "data = [go.Histogram(\n",
    "        x = apps['Rating']\n",
    ")]\n",
    "\n",
    "# Vertical dashed line to indicate the average app rating\n",
    "layout = {'shapes': [{\n",
    "              'type' :'line',\n",
    "              'x0': avg_app_rating,\n",
    "              'y0': 0,\n",
    "              'x1': avg_app_rating,\n",
    "              'y1': 1000,\n",
    "              'line': { 'dash': 'dashdot'}\n",
    "          }]\n",
    "          }\n",
    "\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c92ce18",
   "metadata": {},
   "source": [
    "## 6. Size and price of an app\n",
    "<p>examining app size and app price. For size, if the mobile app is too large, it may be difficult and/or expensive for users to download. Lengthy download times could turn users off before they even experience your mobile app. Plus, each user's device has a finite amount of disk space. For price, some users expect their apps to be free or inexpensive. These problems compound if the developing world is part of your target market; especially due to internet speeds, earning power and exchange rates.</p>\n",
    "<p>How can we effectively come up with strategies to size and price our app?</p>\n",
    "<ul>\n",
    "<li>Does the size of an app affect its rating? </li>\n",
    "<li>Do users really care about system-heavy apps or do they prefer light-weighted apps? </li>\n",
    "<li>Does the price of an app affect its rating? </li>\n",
    "<li>Do users always prefer free apps over paid apps?</li>\n",
    "</ul>\n",
    "<p>We find that the majority of top rated apps (rating over 4) range from 2 MB to 20 MB. We also find that the vast majority of apps price themselves under \\$10.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "944754d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_style(\"darkgrid\")\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# Select rows where both 'Rating' and 'Size' values are present (ie. the two values are not null)\n",
    "apps_with_size_and_rating_present = apps[(~apps['Rating'].isnull()) & (~apps['Size'].isnull())]\n",
    "# Subset for categories with at least 250 apps\n",
    "large_categories = apps_with_size_and_rating_present.groupby([\"Category\"]).filter(lambda x: len(x) >= 250)\n",
    "\n",
    "# Plot size vs. rating\n",
    "plt1 = sns.jointplot(x = large_categories[\"Size\"], y = large_categories[\"Rating\"])\n",
    "\n",
    "# Select apps whose 'Type' is 'Paid'\n",
    "paid_apps = apps_with_size_and_rating_present[apps_with_size_and_rating_present[\"Type\"] == \"Paid\"]\n",
    "\n",
    "# Plot price vs. rating\n",
    "plt2 = sns.jointplot(x = paid_apps[\"Price\"], y = paid_apps[\"Rating\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2288f423",
   "metadata": {},
   "source": [
    "## 7. Relation between app category and app price\n",
    "<p>How are companies and developers supposed to make ends meet? What monetization strategies can companies use to maximize profit? The costs of apps are largely based on features, complexity, and platform.</p>\n",
    "<p>There are many factors to consider when selecting the right pricing strategy for your mobile app. It is important to consider the willingness of your customer to pay for your app. A wrong price could break the deal before the download even happens. Potential customers could be turned off by what they perceive to be a shocking cost, or they might delete an app they’ve downloaded after receiving too many ads or simply not getting their money's worth.</p>\n",
    "<p>Different categories demand different price ranges. Some apps that are simple and used daily, like the calculator app, should probably be kept free. However, it would make sense to charge for a highly-specialized medical app that diagnoses diabetic patients. Below, we see that <em>Medical and Family</em> apps are the most expensive. Some medical apps extend even up to \\$80! All game apps are reasonably priced below \\$20.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4101e937",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>App</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3327</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>most expensive app (H)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3465</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>💎 I'm rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3469</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich - Trump Edition</td>\n",
       "      <td>400.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4396</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4398</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I am Rich Plus</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4399</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich VIP</td>\n",
       "      <td>299.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4400</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I Am Rich Premium</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4401</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am extremely Rich</td>\n",
       "      <td>379.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4402</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich!</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4403</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich(premium)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4406</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich Pro</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4408</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich (Most expensive app)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4410</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich</td>\n",
       "      <td>389.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4413</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4417</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I AM RICH PRO PLUS</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8763</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>Eu Sou Rico</td>\n",
       "      <td>394.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8780</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich/Eu sou Rico/أنا غني/我很有錢</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Category                                App   Price\n",
       "3327     FAMILY             most expensive app (H)  399.99\n",
       "3465  LIFESTYLE                         💎 I'm rich  399.99\n",
       "3469  LIFESTYLE           I'm Rich - Trump Edition  400.00\n",
       "4396  LIFESTYLE                          I am rich  399.99\n",
       "4398     FAMILY                     I am Rich Plus  399.99\n",
       "4399  LIFESTYLE                      I am rich VIP  299.99\n",
       "4400    FINANCE                  I Am Rich Premium  399.99\n",
       "4401  LIFESTYLE                I am extremely Rich  379.99\n",
       "4402    FINANCE                         I am Rich!  399.99\n",
       "4403    FINANCE                 I am rich(premium)  399.99\n",
       "4406     FAMILY                      I Am Rich Pro  399.99\n",
       "4408    FINANCE     I am rich (Most expensive app)  399.99\n",
       "4410     FAMILY                          I Am Rich  389.99\n",
       "4413    FINANCE                          I am Rich  399.99\n",
       "4417    FINANCE                 I AM RICH PRO PLUS  399.99\n",
       "8763    FINANCE                        Eu Sou Rico  394.99\n",
       "8780  LIFESTYLE  I'm Rich/Eu sou Rico/أنا غني/我很有錢  399.99"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Select a few popular app categories\n",
    "popular_app_cats = apps[apps.Category.isin(['GAME', 'FAMILY', 'PHOTOGRAPHY',\n",
    "                                            'MEDICAL', 'TOOLS', 'FINANCE',\n",
    "                                            'LIFESTYLE','BUSINESS'])]\n",
    "\n",
    "# Examine the price trend by plotting Price vs Category\n",
    "ax = sns.stripplot(x = popular_app_cats[\"Price\"], y = popular_app_cats[\"Category\"], jitter=True, linewidth=1)\n",
    "ax.set_title('App pricing trend across categories')\n",
    "\n",
    "# Apps whose Price is greater than 200\n",
    "apps_above_200 = popular_app_cats[popular_app_cats['Price'] > 200]\n",
    "apps_above_200[['Category', 'App', 'Price']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc4476ef",
   "metadata": {},
   "source": [
    "## 8. Filter out \"junk\" apps\n",
    "<p>It looks like a bunch of the really expensive apps are \"junk\" apps. That is, apps that don't really have a purpose. Some app developer may create an app called <em>I Am Rich Premium</em> or <em>most expensive app (H)</em> just for a joke or to test their app development skills. Some developers even do this with malicious intent and try to make money by hoping people accidentally click purchase on their app in the store.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "72d35fc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'App pricing trend across categories after filtering for junk apps')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5xPZr164lLi6Oe++9lw4dOgTC7KG/hyP9/fg+//xz3G43fr+fZ599lldeeeW4dZ6Mv+9n4sSJgc/A66+/zhNPPPFft925c2e+/fbbQE/vlClTjgqrf9euXTvmzZtHSkoKUDxyYt++fbRs2bLU+42NjWXdunWYpkleXl6pvjQAcDgcnHvuuYwcOZIhQ4aQlpZWYnlOTs4Jr8mMjAzmzp0LwKxZs7Db7TRo0AAoni09NzcXv9/PhAkT6NKlCxkZGXTu3JmYmBhuvvlmHnroIdasWVPq4xSRs4N6aEVEKqAvv/ySW265pUSvRVRUFAMHDuTTTz8lISGB1157jT179hAXF8eYMWMC6zmdTv71r3+Rk5NDt27dAsMj/6606x3SuXNntmzZwnXXXQdAcnIyw4YNK9VjROrUqcPgwYO57bbbcDgcNG7cmNDQ0GOue+mll/L4448zZMiQo5Y9/fTTjBgxgl69euHxeLjwwgv/8ZFG1157Lbt27eKKK64gJiaGWrVqHXO9W2+9leeeey4wLLdVq1Zs2rQJgOeee44hQ4bQq1cvTNPkrrvuKtGzeMjYsWMZOnQo3333HW63m169etGvXz/8fj9z587liiuuICwsjOjoaIYNG0bVqlWP+f7fHW//d955J3379iUsLIzKlStzzjnnsHPnTtq1a1fiPB7vvNntdl555RWefPJJLBYLzZo1w2azERoayoABA9i3bx9XXXUVfr+fWrVqlZhk6Fji4uJ44403GDNmDC6XC9M0GTNmDElJSdx0000MGjQoMPy7YcOG9OzZs8T27du3Z+LEiXTv3h3DMGjTpg1xcXHs3LnzqCDdtWtXXnnlFTweD/feey+jR4+mb9+++Hw+GjduXGaPZurUqVNgkqY77riDAwcOcPXVV2MYBlWrVi0xgdPJuuuuuxg6dCi9evUiMjKS+Pj4Er2jx5KcnMzzzz/P/fffj8/nw+l08u677x5zorPjufLKK/n999+57LLLqFy5Mm3atDlmz/7xXHDBBfTs2ZOnnnqKDz74IPB+VFTUca/JGjVqEBISwqRJkxg7dixOp5O33nor8DMuISGBO+64g8zMTM4//3zuvvtunE4n99xzDzfffDNOpxOr1VqmjwgTkTODYZ7MTzARESl3ixcvZtiwYSXu4zxk0KBB1K9fn9tuu+2EbZR2vbKSkpLCpEmTuPfee7FYLPz666988MEHJ+yplVMvLy+Pt99+mwceeIDQ0FDWrVvHXXfdxe+///6PPYXyv5s6dSoRERF07twZv9/PAw88QPv27QNDmsvShg0buPXWW0/584KP58hZlv/u77Mui4icDPXQiojIKVelShVSU1Pp1asXVquVyMhIRo4cWd5lnfUiIiKw2+0MGDAAm82GzWbjtddeU5g9TerXr89zzz0X6Gm+4IILuOqqq8p8P9OnT+eFF17Q851F5IykHloREREREREJSpoUSkRERERERIKSAq2IiIiIiIgEJQVaERERERERCUqaFKqC8/v9+HwV7zZnq9WokHWJHKJrVIKBrlOp6HSNSkWna/TsYLdbj7tMgbaC8/lMsrIKyruMo8TEhFXIukQO0TUqwUDXqVR0ukalotM1enZITDz+s7Y15FhERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZO2mOP/ZtLLrmYzz77uLxLERERERGRs5gCrZTawYNp9Onfi607tuM3/Xw7aTJ9+vcs77JEREREROQspUArpXbXXTcDYBrFl43fYsPAwsMP31+OVcmZZNeunQwZ/gI3334zw0YOY/fulPIuSUREREQqMFt5FyDBww9gseFzRlEYUY3QjC1gWNi1a3t5l3aUnJxsJn43kbXrN1C3di2u7n81lSpVKu+y5ASys7MZ/Owg9iWcT2Ht3qSkb2HTM4N45813iYiILO/yRERERKQCUg+tnAQDb0gkhjuf0IPr8VkdYJqnZE+maZKbm4vX6z3pbT0eD08MfoLvlm1niaMZUzZm8diTj5CTk30KKpWyMm/eHHIja5Nb7Ty8ofHkVLuAvPBqLFgwr7xLExEREZEKSj20UmomYHPlYGDit4dh8+RjGn8tKEObNm3g5ddfJTM9DZvdznXXXE+vK64s9fbLlv1ButfGgQaXAVAUUweHr4DZv82k95X9yrbYIJKZmUFeXh7VqydhsVS877IKCwtwW0JKvOexOikqKix1G36/nyVLFrN23VqS69WiTZsOhIaGlXWpIiIiImec7OwssrKySEqqgdVqLe9ySi3oA+3ixYt56KGHSE5OxjRNvF4vI0aM4IMPPqBHjx506tQpsG779u2ZP38+RUVFDBkyhNTUVAzDICIigiFDhhAbG8vAgQMZMmQIBw8e5L777uPHH3+katWqAIwdO5a6devSr18/mjVrRuvWrUvUMnbsWBITExk9ejSbNm3CYrFgt9t5+umnqVGjBjt37mTEiBH4fD68Xi/NmjXj0UcfrZDh4thMTHso+5oPxO+IwJGzm0rrvv6fW927dw9fTviK7bt20bh+feYv+J3dSRdTWKchtsIMPvvmG2rWqEHLlq3/uTEgKysTlyOmxHsFtkjSMzL+51r/Gykpu9i3bw/16zckNjbutO/f4/Hw2rjXWbp0MYbdSbjTztNPPkXdusmnvZYTadv2Qr754XtyEpriCa+MI3cf4ekbadPm3lK38fJrL7Nk3UbSoxoQvXQDCV9/w6svvUp4eMQprFxEREQkePl8Pt55721+nzcHIyQCB16efOxJmjZtXt6llUrQB1qAtm3b8uqrrwIwb948xowZQ2xs7HHX//bbb0lISGDUqFEAfPrpp7z11ls888wzJdaz2+0MHjyYTz75BMMwSiyLjo5m/PjxR7U9Z84cUlNT+eSTTwCYMWMGI0eO5J133uGVV17hhhtuoFOnTpimyf3338/MmTO59NJL/6fjP20sdnKrno/fURwO3FFJuKKSCM3eEVilsLCQbyZ+zcIlS4iPi+O6q66hadNmx20yMzODJwY/zv74lhRFXsDWdesJdXspjKsPhoE3LJ7UxNbM/G12qQNty5bnEPLpJ9gqt8EbGovFnU906mrOP3fQ/3T4J8vn8/HKG6+ydPky/JGVsWTt5vrrBnJlr96ntY7JP/7Awo272N3qLkyLnbCD6xn+4gg+ePfDCvXtW1JSTe694y7e/+gDvKaJ3WrhnnsfoEqVqqXafvv2rSxduZIdzW7FtNrJAXzbpvDLrz/Tr++AU1u8iIiISJCaNWs6vy1fx66Wd2HaQnBmbmPk6JF88uH/4XA4yru8f3RGBNoj5eTkUL16dQoKCo67TvXq1Zk4cSLnnHMObdq0YeDAgZjHuBe0bdu2+P1+Pv/8c2644YZS7b9KlSqsXbuWadOm0bZtWy6++OJAL3G1atX4/vvvCQ8Pp0WLFrz22mvYbEH0V2D6sbhzjnhtYnPllFhl+IvDWXPQTXpie+yFmWx5cThDnxtCgwaNjtnkzFkzyIqqS3b1dgC4opKokruX0MytFMY3AMDm9+AMObkeNtM0qbL6//A4Y7EXZUI5BLdFi+azZN0mdjS/HdNqx1qUzedf/Ye2F7SlUqXKp62OuQsWkFrpPExr8Q+kgsQmFBxYSErKLmrXrnPa6iiNzp270r59J7Kzs4iOjjmpz8fu3Sl4o6phWu2B97LDk9i6Y8cpqFRERETkzDBnwULSEltj2opv/SqKrYs3NZpNmzbQrFmLcq7unwXLWNcTWrRoEQMHDuSaa67hqaeeolu3bsdc71Av60UXXcQ999zDxIkTufjii7n55pvZunXrMbcZMmQIn376KTv+9ktxdnY2AwcODPz36KOPAtCwYUOGDRvGjBkzuOKKK+jfvz8rV64E4OGHH6Zly5a88sorXHjhhQwePJjc3NyyOQmng+kjcv8KIvYuxZG7l7itP2N1H65/9+5dbN2xnX11e+KOSiK/UnNSq1zAd5MmHbfJrOwsimwlw6o3JJrI1FVYi7IJTd9IfOoKLu/W/ahtCwsLycs7+vytWrUcT0xNPM4YQvL347OHkR9dmyXLlvwPB3/ylqxYQVpM40DA8jmj8cTW4c8/157WOqKiorAd8fdk+DyY7kIiIyvmzME2m434+IST/rKnXr362DJ3YfH89WWWaRKfs4XmjRufgipFREREzgyx0VHYj/hdEdMPRblERkaVX1EnIYi6B4/vyCHH27Zt49prr+Xiiy/G7XaXWO/QjLkrVqygXbt2XHbZZfh8PiZNmsTgwYP57rvvjmo7NjaWp556ikGDBnHOOecE3j/ekOMNGzZQp04dXnnlFUzTZP78+Tz00EPMnz+fRYsWcfPNN3PzzTeTn5/P6NGjefvttxk06PQOhf1vGRj4LXYi9y/H2LMInz0M/IdnIc7LywNHBBiHvyfxOiLIzt1x3DbbtmnL9DkvkVepOT5HJPb8NCLzdtGkcVO2bP6KxMTK3Pz4k9SpUy+wjcfj4c133mThgt8BqJPcgEGPPhG4PzUkJARrxg6ykrtzIL4RIdm7SNz4A1bL6Q021atUIWLjavIOvWH6sRekkZh4+npnAa7u24/NY0axDwNfSBSJqUtp0aIV8fEJp7WOU61ater07NGDqT//H4Wx9QgrOECNxFi6dg2SIf0iIiIi5aDvlb1Z8tzT+CwOPKHxxKWtoG6tWtSqVbu8SyuVMyLQHikhofiX9CZNmjB9+nQuueQSAJYuXUpycvEkOFOnTiU8PJyHH34Yq9VKw4YNTzg+vGvXrkyfPp3vv/+exx9//IT7X7hwIRs2bGDkyJFYrVbq169PaGgohmHw0ksvYbVaad++PeHh4dSpU4fMzMwyOvJTzzSsGKZJfkJjXJHVCE9di82TD3/1iNWrVx+7N5/Q9E0UxjfA8BZRKW0ZFw04/gzFzZq1oG/PHnz/wycYodEYrlzuvuteOnfuetxtvvz6C+b+uZM9re/GtNjJ2TOfUS+PYfTw4nuiPR4vruiaFCQ0AcAVU5u8Si3w+XxleDb+2WWXdmfKT1Px75xBXlhV4rM2ULtqZZo0aXpa62jevCVPPf4kX3/3LdnZG+jYtd0Ze0/pjdffRKf2nVi/fh3JybWpV69JEE26JiIiInL61a2bzNDnXuDLbyaQdnALbTucR/9+V5V3WaV2RgTaQ0OOLRYL+fn5DBo0iF69ejFy5Eh69+5NeHg4drudoUOHAvDQQw8xbNgwevfuTWhoKGFhYYwYMeKE+3j66adZtGhR4PWhIcdHeuSRRxg4cCCjR4+mT58+REREYLFYGDNmDACvvfYaw4cP5+WXX8bhcJCUlMSQIUPK9mScQobpJy+xCdk1OwJQFFOXqsvf49DdqXa7nWefepYXXxpF4Z45mO5COna6iEsuOfYQ8EOuvfo6ruhxBampqVSvXp2QEOcJ1/9t7hwOJPXAtBWvl169PduXjSM3N5fIyEhsNhshDnuJbawWg1Bn6H934P+l6OhoXhv7Gj9O/ZEdu1I4p0NXLr20+1ETjJ0OLVq0okWLVqd9v+Whdu061K5dh5iYMLKyjn8vvYiIiIgUa9CgEc8//Vx5l/FfMcxjzYYkFYbH46swv5T3GdCH7NoXkVf18NDrxHVfE5q9g2+/nRp4z+fzsW/fXqKiooiKii7zOu5+4B7WxnbAFV0DAMNbRO2V7/F/H39GaGgoeXm53HXPHeyp1pGC+IY4s3dRbecvvDLmFapVq17m9UjFpEArwUDXqVR0ukalotM1enZITDz+3C8aiyelZpgeIvctxfC6ALAXpBGSk3LUelarlaSkGqckzAL0veJKqqXMICQ7BXt+KtW2/0Tbtu0JDS3ugY2IiGTokGGcY26j1tJxNM1dyqDHnlSYFRERERE5w5wRQ47l9LG486i+9C28IVHYi7Lwm/7TXsNllxXPePz9lMm4XEVc1LEz/7r2+hLr1KtXn1fGvHzaaxMRERERkdNHQ44ruIo05HjhwvmMHjsKg8Mh1gR+OGK4sUhFoSFIEgx0nUpFp2tUKjpdo2cHDTmWMtGuXXs+fO8TLBRfOJHhEXz3zY/lXZaIiIiIiJylNORYTkpCQgLffjtV34aJiIiIiEi5Uw+tiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCjZyrsACS7XXz8A3LmYpoGJyfkXXswjjzxR3mWJiIiIiMhZSD20Umq33XYDpisPK2Cz+ME0+GP+LHbt2lnepYmIiIiIyFlIgVZKLSsrHQAfBqFWE59h4AcefvjeMt9XZmYGCxfOZ9u2rWXetoiIiIiInBk05FhKzQAsFuhRNYOmUQX8tD+WtdnhFPrKdj8//zSZL8Z/SNOYInbkh1C3YUsefmIINpsuVxEREREROUwJQUrNYfjpUimbfzfYC0CXyllcs6AxhT5rme0jIyOdz//zAR+fu45qoW48foP7VxQye/Z0Lr308jLbj4iIiIiIBL8zesjx7t27Oeeccxg4cGDgvzfffJP27dsDMG7cOAYMGIDX6w1sc/XVV7N79+7A6/fff58OHTrgcrkC7w0aNIj777+/xL4OtQmwdOlSbrnlFgYOHEj//v35/PPPAVi8eDHt2rUrUc+DDz54So79VDAMg0aRhYHXVgNqhxeV6T6WL19Ko/BsqoW6AbBbTK6smsrvs6aV6X5ERERERCT4nfE9tMnJyYwfP77Ee19++WXgz3v27OG9997jvvvuO+b2P/74Iz169GDq1Kn069cv8P6yZcv44Ycf6NOnT4n1U1JSGD58OB9++CEJCQkUFRVx4403UqNGDUJCQmjbti2vvvpq2R3gaeTxG0zaE8/lVTMIsZrsLXSwOiu8TPeRm5vDznwnXj/Y/vq6ZX1OKAWWw0HaNE2m/zqNX36cgMvtpl2Hrlx93c3Y7fYyrUXkbOD3+1m1agU7d26ndu26tGjRCovljP6uU0RERM4gZ3yg/Se3334733zzDV26dKFJkyYlli1evJiaNWty7bXX8vjjj5cItI8++ijjxo2jbdu2VKlSJfD+pEmT6NOnDwkJCQA4nU4++ugjwsLCWLp06ek5qFPExGRvkZ2+85tgAB7TwOM3ynQfjRs35UesPLKyHt2rZLAxN4zZqTF0uLhlYJ3pv07jl6/f4dF6m4mw+fhgURofZB7k3n8PLtGWz+cjPf0gMTGxOByOMq1T5Ezg8/l4edRzpG5bzfnRBxn/YwJVk1vxyJMvnFSozcnJ5tdfprB35xYaNDuPrl0v1WdOREREToszPtBu2bKFgQMHBl6PHTu2xPKwsDCGDx/OoEGDmDhxYoll33zzDVdddRV169bF4XCwatUqWrYsDlaVKlXi3//+N08//TQfffRRYJvU1FQaNWpUop3IyMjAnxctWlSins6dO3P77bf/7wd6GhT/emtwf/IemkQX8NO+OL7fHY/PX3b7aNiwMUl1GpC7bz2/7o/FhwXDEU7vvtcE1vl1yjc8UnczLWPyAXi6wSYGLArjljsLCQ0NBeCPxQv54N1XsPjcuP0WrrvhNi7rfkXZFSpyBli5chkHt6/io1YrsVnA49/N7Sth1arltG59XqnayMvLZfBj93JO6B7aRaQzY9ICFs+bwbNDX1ZPr4iIiJxyZ3ygPdaQ478777zzuPDCC3n99dcD72VnZzN37lwyMjIYP348eXl5fPbZZ4FAC3DllVcyY8YMvvjii8B71apVY//+/SXa37BhA6ZpAgT1kGOrxaR/Ujo9qmUCcE/yPv7IiGRrXmiZ7cMwDJ5+fjTTpkxi/apFVKtWizv7XENiYqXAOi63mwjb4amVnVYTAzNwL3R6+kHefmM0o5v+SbPoAnbmh/DQFx9QN7khycn1geJhy7/9NpPZP3+H6ffT+bI+XHxJNwyjbHucpez5fD62bNmEzWajbt1k/Z39D7Zu3ULbqAOB4f12i0m76FS2bt1S6kA7a+avNHPuY1CDLQB0q5rJrSsdrFu3hubNW/7D1iIiIiL/mzM+0JbWww8/zIABA0hNTQVg8uTJ9O/fnyeffBKAwsJCLr74YjIyMkpsN2TIEK6++mry84t7C6+44gruu+8+evToQVxcHPn5+Tz33HPcd999OJ3O03tQZcwAYuzeEu9F2v67Z/YcOLCfvLxcateui9VacpbkkBAnfftfQ9/+1xxz23YdL+bd+WlcnrgXv2mwIS+S+vXqBXrCly1bQtuEHJpFFwBQK9xFz0p7WbRgTiDQTp3yHbN/+IS7a27FYsD7X6eQk51BvwH/+q+OR06P3btTeHHoIEL9ubh94IypzODnRhMbG1fepQWlWrXqMGl6ZW4392E1wOuHJbmJ9K9Vp9RtpO5LoVHo4Z+LVgPqhxdw4MB+BVoRERE55RRo/xISEsLIkSO59tprgeLhxmPGjAksDw0N5bLLLmPChAkltouLi2PQoEGBSaWSkpJ4/PHHuf/++7FareTn5zNgwAA6d+7M4sWLjxpyDPDBBx8ERdh1+w2+2FWJDok5VAt180d6BH/mhJ1cG243b7w8lD/XrSY2xCAPJ48NGkr9+g1L3UaXiy/nqZ8nk15QmQirj415ETzwyFWB5aGhoeR4S96/l+NzEh4eEXg95YcJjK6/geTI4lmaq4eu555JE+nb/zr1+FVg777xIlfH/8mApDRME97ZVoP/fPQm/37sufIuLSidd14bpk9rxL2rTS6I3M+i3CpEVm/MOeeUrncWoEmLc5mybDq9q6cTYjVJd9lYnB5BrybNTmHlIiIiIsUM89BYWKmQPB4fWVkF5V0GADdc1Y2m0QWsywnHZpjYDJNou5cdBaF8++3UUrXxzdfj2TX3/xjaaCMOi8lvqdG8uacFb7732VE9tcfz+tih1N4/ldvr7AFgwcFI3th7Dq+/Mx6LxYLLVcS/772ZK+K20iUxg+WZkXyyuy4vvfY+8fHFk3Vdf+2VTLhgFTGO4h7mAq+FnvNa8NXXk3XfXwXlchVx08AB/NJxZWCIbJrLxi0rzuGT8d8dtX5MTFiF+exUZD6fjz/+WMSO7VupU7ce55/fttSfxUPbv/XaSNatWkKjaDerMhxc2fdajXYoJV2nUtHpGpWKTtfo2SExMfK4y9RDK6Xm9htsyQvl1VZbiXN4WZMdzpgNNU6qjRWL53Jv1RQcluLvUS6qlM27uwrYsyeFmjVrl6qN9evXcnejtMDrdvG5jNiUS05ONjExsYSEOHlh5Gt8/dkH/LppPUk1avHcsDsCYRagzbnn8n+70rmv7k4MA/5vVzXOa9lcYbYCs9nshIbY2VfkoEZY8XOKd+U7iY+JKufKgpvVaqVdu/a0a9f+n1c+zvYPPvosO3ZsY8+ePVxfvwGVKlUu4ypFREREjk2BVkrNT3FP5iMr6+HxGzitfjjJDv7omDj2FTpoHVt8z3GB10KOyyQysvShpGrlKvyZE0bSX6EmpSAEw2IrMaS4cuUqPPjos8dt45a7HuKVUen0WxyPAVStXoNH7nv8pI5FTi+r1Uqfftcw+EcvN1bfjttv4ZPdtRl4xy3lXZoAtWvXpXbtuuVdhoiIiJxlFGil1JLrN2Hb5j+xmiY+08A0TUwMPvjgxLNIH+mK/gN5ZdQGvOZ2EkM8fLWvJm3atDupSX2uuuFOXhq5i12F+4iwuvl2fw2uunYgdru91G1ERUUzZOQbpKYewDRNKleu8s8bSbm7ss81JFauzvSZU7HZ7dzzSD9atmxd3mWJiIiISDnRPbQVXEW6hxbgwQfvImPfTuwWk3yvhetuuJW+fa/65w2PsH79OqZ+/yV5uVmc264rl/e4Epvt5L5b2b17F7OmT6OoqIB2HS7WbKpyFN1TI8FA16lUdLpGpaLTNXp2ONE9tAq0FVxFC7SH6IeHVHS6RiUY6DqVik7XqFR0ukbPDicKtJoBR0RERERERIKSAq2IiIiIiIgEJQVaERERERERCUoKtCIiIiIiIhKUFGhFREREREQkKCnQioiIiIiISFBSoBUREREREZGgpEArIiIiIiIiQUmBVkRERERERIKSAq2IiIiIiIgEJQVaERERERERCUoKtCIiIiIiIhKUFGhFREREREQkKCnQioiIiIiISFBSoBUREREREZGgpEArIiIiIiIiQUmBVkRERERERIKSAq2IiIiIiIgEJQVaERERERERCUoKtCIiIiIiIhKUFGhFREREREQkKCnQioiIiIiISFBSoBUREREREZGgpEArIiIiIiIiQUmBVkRERERERIKSAq2IiIiIiIgEJQVaERERERERCUoKtCIiIiIiIhKUFGhFREREREQkKCnQioiIiIiISFBSoBUREREREZGgpEArIiIiIiIiQUmBVkRERERERIKSAq2IiIiIiIgEJQVaERERERERCUoKtCIiIiIiIhKUFGjlpKxZs4b+/Xty8cVduOGGqygsLDxqHY/Hw6ZNG0hNPVAOFYqIiIiIyNnCVt4FSPCYPXsGb7z5MlgBE/JdeVx3Q1++n/gThmEAsHr1Ssa8MgJ/qA9fnp9zWp3Lo/8ejM2mS01ERERERMqWemil1N5482WwgT/Kj7uhGxxgWA0GDrwGALfbzZiXh5Pa4QD7e+0n7apUlqYs4aefp5yw3WnTJnPNTX3od3UPbrhtAEuXLsbn83HgwH6KiopOx6GJiIiIiEgQUreZnBRfjA+sYN9tx5voxbbXRmFhPgBbt27GH+nHW81bvLINchpmM3/JHHpd0QcA0zSZMu0HJn7/NUX5hdSuV4/NmzeQ3zEfb1UvhVsLeXH0UCKiI3B53eA16XPlAK656vpAL3Bpbdu2hU2bNlKjRi2aNGl60tuLiBzLwYNpbN68ierVk6hZs1Z5lyMiInJWU6CV0rOALctGUZMifJV8ODY6iocf+4oXR0fH4M/1F7+2Fr9nzbURH5sYaGLu3Nl8Pun/SO+cjj/cj/sHN+6Gbjx1PQC4GrgIXRbKvjb78Fb1YuQb/DD9W5LrNuC889qUutR3PhjHnAWz8FR340h10LhOU55+4gWsVmsZnQwRORtN/P5rvvn2S4yqQJrBea3a8MiDT2KxaMCTiIhIedC/wFJ6JriSXRSdX4Snlof8S/MxHWZgcbVq1WnauDnxs+OxpdhwrnUSvTaK/ldeE1jnx19/ILN1Jr54H6bTxBfmw7QdbsO+1443zot9l52Yz2KI/i6aQksBM+b8Uuoyt2zZzJwFs0jtfYDMCzM5cOUB/ty9lj/+WFg250FEzkp79+5h4ndfcrB3GqldUkntd4ClmxazeLF+toiIiJSXoO2hXbx4MV999RWvvvpq4L1BgwbRo0cPOnXqRLNmzWjdunVgWb169RgyZMhR7wOMHTuWxMRERo8ezaZNm7BYLNjtdp5++mkKCgoYPnw4ACtXrqRFixZYLBb69evHK6+8wueff07NmjUBmDVrFu+//z6ff/45nTp1Yv78+SX2M27cOKZMmUKlSpUC71144YXcc889ZX5+Tgkr+GP9h18bxffTWvMO93ree8e/GT76eczfduIIcXB1v39Rt269wHLT74cjRv66mrgIWxCGp5YHX4IPa6YVa44VM8Qk+5psTKtJ2OIwtm7bXKIUl6uIpUv/oKioiPPOa0N0dExg2aZNG3AlFYHjrzcskJ2UzZ8b1tKuXYeyPCMichb588+1eGv4MMP/+hLOBtm1s1m+eint2rUv3+JERETOUkEbaP9JdHQ048ePL/X7c+bMITU1lU8++QSAGTNmMHLkSN55553A+l27duXjjz8mJCQEAMMweOqppxg/fjw5OTmMGTOGDz744ITDWm+++Wauu+66sjjE088PjvUOXMkucIAly4LtwOFLyDRNho1+ju3OreT3yceSbeGrSZ9Tp049WrYs/hKhxyVXsvub3aRHH8Qf5seR7SAyNBLLTxZMr4lhN8CEwvMLMZ3FvzQWXFBA1heZFBUV4XQ62b9/H4OeeZiiqCJ8Dj+2T6088cgztG59LgCVK1eBFOACiscgmMX3/CY2rYSIyH+rUqXK2DNsYBL4Yi4sM5ykRknlWpeIiMjZ7IwNtCerSpUqrF27lmnTptG2bVsuvvhiOnXqdMJt+vTpw8yZM/n6669ZvXo1d999NzVq1DhNFZcP02ESPSEaf4wfS6YFX6gPW17xZbRz53YOpO8jt19uce9tpJ+sFplM/vn7QKDt2vVSMrMz+H7SN7gKXDRr1YIHX36UqKhosrOziY2N5ba7ryfHlxPYp+E3MCxG4B61j/7zLmn10ihsWfwMXNseG2+88zIfvfsZFouFwsICLH4LkdMicddyY99rx5pjo/AUzZicmpqK3W4jNjbulLQvIhVDs2YtqJlQG+9ML7m1cglNDSM6I5quXS4r79JERETOWmdsoM3OzmbgwIGB108++STNmjU76v1KlSrx8ssv07BhQ4YNG8aECRMYPnw4VapUYdCgQbRpc+KJiF544QWuueYamjdvTp8+ff6xrk8//ZRp06YFXt999920bx8kQ9UMsGZbKWhXgOkwsWRZCFsRFljsdrvBbpQYUmzaTVy5h4OkYRgM6Hct/fteg2maJSZSiY+PB+CKy/swYcYXZFyQgWk3iV4Ww4XtO+BwFI8h3rRpA65LXIHtvNW8FBTmk52dRWxsHPn5+ZAERVWLsKXZcNdyY433U1RUUKanIz39IMNHP8e+/Xsx/SaNGjXlyUeeISws7J83FpGgY7FYGPrsKGbM+JlVf66gdvO69Ly8N5GRkeVdmoiIyFnrjA20JzvkeMOGDdSpU4dXXnkF0zSZP38+Dz30EPPnzz/h417i4uI499xz6dGjR6nqCuohxz4wDZOwhWEYbgPTbuI3/Vj/mtK4Xr36hBGGc72TooZFWPItxK6Npdv1R58bwzCOe1779r4K0zSZ+stkvB4vnTp04aYbbgssr1Y9iQP7D+COcgNgybRgs9iJjIwC4JxzzsM+3o6/kZ/CeoVYcizE/BJLu2vL9v7Zsa+PZEv0ZvI75YMJ7gUr+fg/73H/3Q+X6X5EpOIICQmhZ8/e9OzZu7xLEREREc7gQHuyFi5cyIYNGxg5ciRWq5X69esTGhqqZ5f+jb+yn7xuecW9sG6I/jo6sMxqtfLCMyN56fWR7Fu6F6vVypW9+tGhQ+eT2ofFYmFAv2sZ0O/aYy6/5fo72Dl8O/lZ+XjtXiI3R3HzDbdhsxVfzomJlXjgnkd4+/038Nv9UGRy7TU30KBBo8PH4fcz+cfvmDb9R0zT5LKul9Ovz9WlfqxPUVERWzZuJv+G/MBc4bktc1j8ywIFWhERERGR0ySoA+38+fPp169f4HWdOnX+cZu/DzkGeOSRRxg4cCCjR4+mT58+REREYLFYGDNmzH9dW1ZWVonabr31VuDoIcd16tRh6NCh//V+Tis7uGu7Dw8pdoC3ihfHLkdglaSkmrz+0rvk5+fhcIRgt9vLvIwGDRrx6ktvM+u36RQWFdLx6s7Ur9+wxDrt23eiTZt2HDiwn4SERJxOZ4nlX0/8gh/mfkPGeRlgwDdzviS/IJ+bB95eqhqsVitWmxXDZWCGFU9eZRQahIZruLGIiIiIyOlimKZp/vNqUl48Hh9ZWWV77+d/q++Ay/FV95F3WckeWovbwrffTi3v8k7KwFuuYt+l+/DHFD+GyJJrIfHHRL4Y/12pe+U/+vRdfln2E1ktM8ELccviuOWqO+l2WemGn8upFRMTVmE+OyLHo+tUKjpdo1LR6Ro9OyQmHn++iqDuoZXTzATrfisRUyLwVfZh32YH/z9vVhF53B5Mx+HvckyHidftxTTNUgfamwfeQWJ8JX6d/RN2u50+Nwygc+eup6pkERERERH5GwVaKTULFvxeP9Z0K9aD1uJeWh9cd92N5V3aSWvbrj1zls0mu20WGBC5LJLzLmhTYtblf3LoHuEre/X755VFRERERKTMlf63dznrffPNjxgYYAJWwAcOWwgDBlxT3qWdtDtvvY9zY84n4asEEr5MoHXYudx310PlXZaIiIiIiJwE3UNbwVWke2gPWbNmDStWLKJnz36BZ8cGq/z8fMAkPDyivEuRMqZ7aiQY6DqVik7XqFR0ukbPDrqHVspU8+bN6djxgjPih0d4eHh5lyAiIiIiIv8lDTkWERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtnLTXX3+Jnj0vZ8GC34+7js/nwzTNU1rHwYNp7Nmz+4T78fv9p7QGEREREREpP7byLkCCh8vl4vpr+xACeAyDt14aycumybc//BxYZ/v2rbz0wjOk5mTjsFjo1PVS7r733yXamTDhC6Z9NwHT46Vqcn2GvPAiTqczsDw9/SD/+fAd1q5ZTeXESlx36500b94ysLywsIBXXxzKpo0bsBsGkXFxPP7sMKpWrRZYZ8OGP3nn1THsPphGfGQUt9/7b9q0aXtSx5uefpDvv/mSnZs2Uq9JU/oMuJaYmNiTPGsiIiIiInKqGOap7kaT/4nH4yMrq6C8ywCgf/+e2Hw+ooEsi4VKPh9pViuRcXF8+OFn+Hw+brqmN+EeD/kWCw7TxAX0uf4mrrrqOgA+++xTpn43gcvyC4jz+/glLAxXeAQfffEtUNyze/dt15OfnU2k3yTHYmC1WLj6ptvZsnY1zrAwXG43ngXzuDE9HSswIzycVY0aM+q1twHIzc3hnluvx+bx0sTtZovDToHVyshX36JmzdqlOtb8/Hweuu824jIysfn9eKwWchMSee3tDwkJcf5zA1LuYmLCKsxnR+R4dJ1KRadrVCo6XaNnh8TEyOMu05BjKTWL30+IYXBTTi6vpR2kS2EhVtMkMzMTgAULfsf0+Wjs9vBUZiYDc/OwGAY/fvt1oI3pP0ykb14evQoKaF/k4snMLPKLClm3bi0AS5YsJicnh2peHxlWC9F+P3avl+//70Pqzp5JzM/TWLpoPt2zsrABBnBxfj679+4mJycbgKlTJ2PzehmakcGtubm8kJ5BrNfLhK8+L/Wxzpo1HXd2DvE+L+2Kioj2+ijMzGDBgnlldj7PVgcPppGaeqC8yxARERGRM4CGHEupWYGLCwpp6PEA0LmwiIVOJ9stxd+LrFixHLsJ/8rLwwJU8rnpn5fPRMDlKmLlyhX4fD5qer2BNsNNk3C/n40b19O0aTMWL16AzTRp4yrikawidtrtvBcdRbzbTYeiIgDmhTjIslqo5vMBkG8YmEBISAgA+/fvI9ntZnxkJNvtNqp6fdR3u9l/MK3E8SxbtoSZUybhN/107dGLNm3aBZatXbOKGh4Pt+bkAnCBy8Wo2BjWrFlFly6XnIKze+bLzc3llZHPs33bVgwMqiXV4LFnXiA2Nq68SxMRERGRIKVAKyfJPO6r8PAwHKZZots/5K8R7ffefiNVPW78wBxnKHU9uViATXY7BRZLINSkpaWR6PPRtbA4vNb3eLg0v4BZoYeH+XYoKOTjyCiuy8sl1G8yOSIcp82Ow1EcaFu3Ppd358zmioJ8+uflsdHh4OuIcC5r0izQxszpPzPho3fpkZ6OBfhkw5+kD7yFy3v2BiAqKopEryewvgHU8niJior+n87e2ezjd98gdt1a7s7MwgB+yMvj3dfHMnjIyPIuTURERESClALtMaSkpPDSSy+xf/9+nE4nTqeTxx9/nPr16wNw9913A/Duu+8GtunatSt169blww8/DLz3ySefMGrUKDZu3Mi4ceOYMmUKlSpVCiy/8MILueeee07TUf3vfMCMsDAaeLzU9nhY6HSyx3b4EjIMC3kWg7lOJx2KisiyWJgWHoYXiMnJxuv3Y7Va2WW3MSQulhi/n902G34T7HYrALVr12bt6hVH7dv46/8mcNBmo5LPy++hobgxOK/IxZQQJzk52URHx2CaJnV9ProVFAKQUFTEdrsNZ4gj0N63X47ntgOp1P2rt7jG/gO8+dXngUDbqXNXxv02k24FhYSaJnmGwcqIcJ7q0KnMz+vZYsmyJQzNysb61+ueOTk8vHY1Pp8Pq7X43U2bNjD+/bfZuSeFOjVqcdPd91O3bnL5FS0iIiIiFZoC7d8UFhZyzz33MGzYMFq3bg3A6tWrGTp0KOPHj2ffvn0UFBTg8XhISUmhRo0agW0PHDhARkYGcXHFvY1z5swhOvpwj97NN9/Mddddd3oPqAzZgdouN29HR1FgGET7/VTxekmx2wHYtWs7NtNkXqiTbyPCsQAN3W7SHQ6uysvDj8GHkZHkWgw6FxZi95tgwk67jdWrV7Ft82bsdjv7bTZmhzrpUFjETruNn8PDKLJYGFu9OgUGZHm9tMrLY4/djsswyLAYYDEICXHicrlwuYpw+n0lag/3+ykqLAy8zszLpbLv8DqVfT6yCvLx+/1YLBaaNWtB20u78+ys6dT2+dlutXBZjytJTm5wOk71GSnCGUqW1UrUX18i5FgthDocWP4asp6Rkc7IIU/RPy2NW1xuVh9MZ9izT/La2x+X+ByJiIiIiByiQPs3s2fPpm3btoEwC9CiRQv+85//ADBx4kQuvvhinE4nX3zxBU8++WRgvW7duvHzzz/zr3/9i61bt1KzZk02b9582o/hVHEB20Mc3JmdQ22vl0XOEL4PDw8sN03wGgb13R5uKcoh02Llo+gofEBTd/Hw3ao+L3tsNuY6nVgpvv8VYNvMX2mRl8/0iAjivF5WhITwdUQEiT4fTVwuNkVGcc2TzxAaGsqCeXNZOOUHbszJJdQ0+TYinNAQJ3dc3x+PaWKzWPA6HGyw22no8bDbZmVuaCiV/1wbqLVlk2bMzM+n11/3yM6MCKd5g0aBcGUYBr0HXEt+fgFbN2/ggibNuKJP/9Nyns9UV/S7mk8//5S+B9OxYjIpPoGeV/TB+OsamDdvLi0LCmhX5AKgQ1ERmwqLWLjwd7p3v6I8SxcRERGRCkqB9m92795NzZo1A6/vuece8vLySE1N5ZNPPmHKlCl8/fXX2Gw2evbsyb///e/AM1SvuOIKnn32Wf71r38xefJkevXqxcyZMwNtffrpp0ybNi3w+u6776Z9+/an7+D+RzbgkoJCmvw1KVTXwiIWOZ3s/CsEJiXVYPPqlWRYLYyJLR5SXN/lZoPDHmijqs9HnN/PHTm5GMBGu51x0dHcnXaQGNMkyzDY5rDzSFY2JsVDjX8NDWWzzUrr1ucC8MHrL3NzTm5gcqq7s3N4wm7nluwc6nm9zA11Mis0lP9ERVJkGFhNk8YuF2t2bA/Ucfv9DzPi2SdZlpWJBTAio3jq348Flufn5/P0Yw/S4mAafQsKWL1nN0+vXsnLb34QmHyqLPh8PmbO/JVFs6YTHhlFj35X0bhx0zJr/2Rs376VlSuXExsbR9u27Us8G7gs9OzVh/DISKZP+g6/38+lPXrRrVuPwHKv14Pd5y+xjd3vx3vEJGIiIiIiIkdSoP2bKlWqsHbt4Z68d955B4Crr76a3377jfz8fB599FEA/H4/P/74I1dddRUAVatWBWDfvn0sX76chx56qETbwT7k2AB8mMwKdZJqtVLf4wnc2wpgmiZxfj93/dXrCbDa4WCTw4Gf4vtfNzgc3JaTE9iuocdDuOlnq93OuW43cX4fi61O5jqdtC8qYpfNxvSwUJzO0ECbha4iwv2Hg4/zr4moGnk8RJgmvfMLWB4SQu+8fJI9HhymyYi4WDjift+EhERefutDtm3bgmma1KtXP9A7CzBv3hxq5uRwdVbxo4CaurMY5wxl8eIFdOrUpczO6Sfvv8Wm2TO4ND2DHKuVl9as5KGnhtCiRasy20dpTPpuApMnfMG5efmsDg3lm88+ZcTYN4iJiS2zfRiGQZculxx3lugLL+zIoAlf0jo/nwYeD+vtdlaGOhnYNni+9BERERGR00uB9m8uvvhiPvjgA1auXEmrVq0A2LlzJ/v37+enn35i+PDhXHTRRQAsW7aM4cOHBwItQI8ePRg1ahStW7cODKU8U/iAmWFhNHG7qefxMi0sjDSr9fByn5+DVispNis1vD78wOzQUNwGPFmtGibg87hJsdlI9hT3uuUbBvkWC5X+6oUrNCyE+k0WO518ERlBnN9PLY+HbPvhXt52HTvzY1YWtxw8iN00+TE8nHifjwjz8JzLVtPk06hIwkwTt2EQ6fNRs0atEsdjsViOe09sZkY6iQUlH9KdUFREZmZGiffS0w8WP2rIZqdduw5ERh7/oc9/l5eXy5zfZjJ8/wHC/6o99KCfH74cf1oDbU5ONhO//pzn9h8g1u+H7Gy+dBUx+dsJ3HjbXaetjipVqnLfo4P45J03yMjNISE6hofu+zcJCYmnrQYRERERCS4KtH8THh7OO++8w8svv8zYsWPxer3YbDYeeeQRXnnlFTp06BBY99xzz8XlcrF8+fLAe927d2fEiBH88MMPR7X99yHHderUYejQoaf0eMqSBWjmdnPnXz2wFxUWMjg+HtdfyytVqoTfNHk5Joa6Hi9pVgsmxT2zo954F4vFwuDHHuA7IM+wEOf3MT0sDJtp8n6VyjQpcrEyxEGhx0Mjj48r8/PZZbPxY3gY3S/sGKjj6n/dxLtpqQxatgQLEB0VTe7BNPZarVTx+VjgDCHNaqV9URHnuVxssDuYERaKLzur1MfavEUrXgp10rWggGi/n3SLhT/sNq5ocfje6hUrlvLa6BG0dBXhtlr58v8+4vkRY6hdu26p9pGXl4fTsBB2RBCv5PORkZFe6jrLwu7dKVS1WIvD7F+a5+cze/2601oHwPnnX8B5532Gy+UiJCTkjPtSSERERETKlgLtMSQlJfHqq68e9X6fPn2Oeu9QQJ01axYAISEhJYYsz58/H4AHHniABx544BRUe/pYgEbuw89mtQO1vB7WWovvKd28eQOV/X4ey8xis91OjN9PrsXCx1GRVK5cBYAQi4VL8vJIs9o4YLPSPb+AL6IiGXDnvRQWFnFObCxvvzKaFSEONjrs+AAHBmGhh4cch4SE8O8nniE/Pw+3201sbBzvvv06L878FZ9pYjUMqrk9XJuXD0Cyx8sBq5VVOTmlPtb09IOEWiwMiYulss/HfquVcIuFgwfTqFOnLqZp8sG4V7k9NZXGf93LOyc0lPHvv82zI8eWah+VKlXGERHB0pAQzne5invAo6M554ILS11nWahevQb7/H6yLRai/wq168LCqdOo8Wmt4xDDMMr8/l0REREROTMp0Eqp+YCFzhA6FBVhAXINgy1HDAU2TYM0q5VCw6CV240JfBoZwZEP0ImMjKKqbxeXFBYVbwN8b4ulYcMmJCXVYP7832lstdIrPYPNDjsJPh9ZFgs7th49W3R4eASHJlm++95/c8dd9+N2u3jssQeptH17iXUr+XzYLaXv7du9O4Xz8/LoUlDIAZuVql4fU6Oj2LMnhfPPv4DCwkIyc3No5Dkc8Fu5XEzZsf0ErZZksVh4eNBzjB72LD+7XeSbJjXrJnPVdTeUuo2yEB0dTd/+VzPquwmcl5NLWlgYe6KiGNn/mtNah4iIiIjIyVKglVLzAZlWK0PjYqnl8bDOEYJxeLQs/fpdxao/FvJiXCwtXS5SrVZSrVYcYYcf7dOpWw+m7ttHUuoBIvwmM8LDiU5IpHr1JADq1KnLB4aFWL+fiwqLMIH3KyXSvHGzf6zParUSGhrGZZf14Kv/+5C9BQVU8/nItFiYExpKi3PPL/WxNmzYiP/ExHB5fgHJHi9FBqwJD+eiBo0AcDqdRIWHs9V++H7gPx12av51HKWVnFyfdz76jG3bthAWFk5SUo1/3ugU6Hf1v2hxznmsWLGMerFxtG/fkdDQsHKpRURERESktBRopdTOa9OOVX8sJM7nw2MYOE0/WRYL33zzIwANGzamUuUq5O3fR57FAiYUWCwMefbwfcLdL+/Fwf37eP7XnzFNP7WSavLEE08H7pWsVq06XS7tzogZP9M6N49dEeF4KlXm0su6l7rOK6/sy8+Tv2MkEOPzkWW14nQ4eOCBR0vdRuvW5zG39bkMheJHD4U4aN2uQ+CROhaLhZvveoB3X3+JNnn5uK1WVoaH8fSd95Z6H4fYbDYa/BWUy1NycoPjTpIlIiIiIlIRGaZ5xIw0UuF4PD6ysgr+ecXT5KuvPuObrz/HBngtFt5660OqVKkaWO73+/nuuwnM/20mcQmVuPWOewK9r0dyu9243S4iIo49K/DGjetZt24NlStXoU2bdtiPGNpcGqZp8ttvM1iw4HeaNWtJr159SzyWp7RtbNq0gZ07d1C3bjLJyfWPWmfPnt0sWPA7drudjh0vIj4+4aT2IadOTExYhfrsiByLrlOp6HSNSkWna/TskJh4/CeJlCrQfvzxx/Tp04e4uLgyLUz+WUULtIfoh4dUdLpGJRjoOpWKTteoVHS6Rs8OJwq0pRpyHBoayr333kulSpXo378/nTp10uM0REREREREpFyVagzmddddx1dffcUDDzzA5MmT6dKlC+PGjSPnJB6DIiIiIiIiIlKWStVDm5OTw9SpU5k0aRKRkZE8/fTTeL1e7r33Xj777LNTXaOIiIiIiIjIUUoVaAcMGMCVV17Jq6++StWqhycA2rBhwykrTEREREREROREShVoO3XqxP3333/U+w8//HCZFyQiIiIiIiJSGqW6h3bHjh26X1ZEREREREQqlFL10G7dupULLriAuLi4wOzG8+bNO6WFiYiIiIiIiJxIqQLt7NmzT3UdIiIiIiIiIielVEOON27cSP/+/enQoQN9+vThzz//PNV1iYiIiIiIiJxQqXpohw8fzogRI2jUqBHr16/nhRde4KuvvjrVtYmIiIiIiIgcV6l6aE3TpFGjRgA0btwYm61UOVhERERERETklClVoLXZbMyePZvc3FxmzZqFw+E41XWJiIiIiIiInFCpAu2IESP4/vvvue6665g0aRLDhg071XWJiIiIiIiInFCpxg4bhsGgQYMwTRPDMLDZbHg8Hux2+6muT0REREREROSYShVo77rrLg4cOEDdunXZvn07oaGheL1eHn/8cXr37n2qaxQRERERERE5SqmGHCclJfHzzz/z1Vdf8euvv9K8eXOmTJnCZ599dqrrExERERERETmmUgXa9PR04uLiAIiOjubgwYPExMRgsZRqcxEREREREZEyV6ohx02bNuWRRx6hVatWrFy5ksaNGzNt2jTi4+NPdX0iIiIiIiIix2SYpmmWZsWZM2eybds2GjRoQOfOndm2bRtVq1YlNDT0VNd4VvN4fGRlFZR3GUeJiQmrkHWJHKJrVIKBrlOp6HSNSkWna/TskJgYedxlpRoznJeXx+rVq9m+fTsul4udO3dSt25dhVkREREREREpN6UKtE899RQ1atRgx44dJCQk8PTTT5/qukREREREREROqFSBNisriwEDBmCz2TjnnHMo5ShlERERERERkVOm1NMUb926FYD9+/drdmMREREREREpd6VKps888wxPPfUUf/75Jw8++CCDBw8+1XWJiIiIiIiInFCpHtuzZ88evv7668DradOm0aRJk1NWlIiIiIiIiMg/OWGgnT17NsuXL2fq1KmsWLECAL/fz8yZM+nRo8dpKVBERERERETkWE4YaBs1akRWVhYhISHUqVMHAMMw6Nmz52kpTkREREREROR4Thhoq1atSt++fendu3eJiaBSU1NPeWEiIiIiIiIiJ1Kqe2jffPNNvvjiCzweD0VFRdSuXZupU6ee6tpEREREREREjqtUsxzPnTuXuXPn0qtXL6ZNm0blypVPdV0iIiIiIiIiJ1SqQBsTE4PD4SA/P59atWpRWFh4qusSEREREREROaFSBdoqVaowceJEQkNDGTt2LHl5eae6LhEREREREZET+sd7aL/++muee+450tLSqF27Nhs2bOC11147DaWJiIiIiIiIHN8Je2jHjRvH/Pnz8fl8VK9enSpVqrBo0SJ+/vnn01WfiIiIiIiIyDGdMNDOnTuX119/ndDQUACSkpJ49dVXmTVr1mkpTkREREREROR4Thhow8LCMAyjxHt2u53w8PBTWpSIiIiIiIjIPznhPbROp5OUlBRq1KgReC8lJeWokCtnj/79ewJgYMHED8C335bumcQ+nw+LxfKP109mZiaDBz1G2sH9OOwOHnn0Cc4/v12Jdfx+P5s2baCoqIgmTZrhcDiOasc0TfLy8ggPD8diKdX8ZyIiIiIiEkROGGgfe+wx7r33Xtq1a0eNGjXYu3cv8+bNY/To0aerPqlA+vfvidVwYDEMohyJZLr2Y5o+fv55Ct27X3Hc7TIzMxj3+qusXrsSZ0golSpVYu+efWCaRMdEM3LUS8THJwDFofeO22/EYlhIDKtNjiuNl0aP4aFHHuHCCzsCkJWVyTNPPUlWZg5WixW/4eH5IcNJTm4Q2OfUqZP5fPx4XJ4C7NYQuvfowc03335qT1AFl5ubS0FBPpUqVdaXUnJSTNPkwIH9WK1WEhMrlXc5IiIiIgGGaZrmiVbIzc1l5syZpKamUq1aNS666CIiIiJOV31nPY/HR1ZWQXmXARQH2qiQRC6tcwc2i4M8dwY/b30bn+kN9NL6/X5efXUMy5b+QVh4OA8++DCvjn2ZvII8DAzCHTEUuLNpktiZcHs06w/Op8jM4fMvJwAwcuQQVi5fweX17iPcEYvP9DJz+8dkFu0N7GP40OdZsWo5NsNevE/TS0REJB9/+hkHD6bxxmuvsnHjn7Sp1oekqCakFexgXspXPPzo47Rte2H5nLwTcLmKWL16FXa7nebNW2K1Wsu0fZ/Px7vvvMX8+XOxW+1ERkXx+JODqVWr9km1Y5om27dvpbCwiAYNGmK328u0zrIWExNWYT47wSw9/SAvjhhGWmoqftNPnTr1eGLQYCIiIsu7tKDmdrtJS0slObkWhYW+8i5H5Lj0s1QqOl2jZ4fExOP/3vGPgVbKV0UKtNcM6EeD+Aso8OSQ584gMawm6UV7SM3fHgib1193FS53EWH2aHx+Dx5fEVWjGtCmWm9M0+TXbe/SKKEDybHnAeD2FTF501gSEyuTl5dLXkEOlcLq0KX2TYH9bstczor9P/P1xO8BuHrAlYCFBnEXYLeGsjF9Pm5fEd269+D33+bi90K4PRa/6SGr6ADhjliiQyoRUQ1GjHzptJ+3E1m1ajmjR47E7XVhtVhxOkMZM/Y1KleuXGK97OwsMjMzSUqqgc32j0/bKmHypO/5ddIs2la5GrslhO3ZK9jpXsJb77xf6qHYubk5DHvheVIPpGG3OPAZbp55bgh16yafVC1lraioiLlzZ5OyK4UmTZvQpk27wBcC+geubDz/7NNwMJom8Z0xMVmR9hPVG0fz4EOPlHdpQWvmzOl8+smH2C0heP0ubrzpVi65tFt5l3XKZGZmsH79OhISEqlfv6FGiAQZ/SyVik7X6NnhRIH25H4zlrOaz3SzKWMxTRI6UDumJTuyVpJZuDew/Pff5+J2u4kKSSDCHovP9JFWsBObYS/uTTXAYQ0lypEQ2MZhdWK3hmIrjKJKSDW2FCwhx5WG3/RhMYqDSUbhHvwc/t7FYtg5p2oPake3AKB6ZEN+3fYuW/7YR5PYi9icsYSMwj3YLHaqRzbiYOEu9uVtoVp+1TI9H6ZpMmfOLGbNmInD4eDynj0599zzT2r7MS++SJWw+kQ5E8GEndmreXHEC7z2xttAcY/3B++9w9y5vxEaEoEfDw8/+jjNm7cs9X7m/f47DaIvxGF1AlAnujWbUxaQkrKr1L20H3/0Ial70inyFuKxeLAZDka9OIL33v+43H45LSwsZNATj2IUhhJrT2Lp/M+YM/s3nhz8tH5hLiMej4f1G9bSt8GTGIYFA2gc25GZSz8o79KC1u7dKXz68Yd0qnYj0c5K5LjS+M+nn9CgYSNq1qxV3uWVuZkzfuXjjz+gcmRtsgtTqVG7Bk8989wx5z0QERH5b5z1M+Xs3r2bc845h4EDBwb+e/PNNwHo3bs3L7zwQon1GzZsyPPPP1/iveHDh9O1a1eg+Nm9X375JQDt27cvsd6DDz7I+++/H3idn59Pt27d2LBhQ5kf16lhUDu6JY0TOlI5vA5tqvUhxBoWWPrjj99hGBZ8fi8xzqrYraFYLTb25Gzg2w0j+XbDi/j9PjZlLMRvFk8otS9vCx5fEfnubBzWUCyE4DU9zNz+Mdsyl7Nk74/syF6N3/QE9uM3/cSHVg+8jnTEYxhWmiZ0oW7sOSSE1sBmtdOz/r+5sMZV9Kz/b8LtUaSmHSjTszHh6y/54tOviM5tiCMtiTdfe4Pf5/5W6u137dqBy+NiX/5m8t2ZpBfuxu0rZN/efYF1fvttJiv/WMPldR7gshr30jq2Fy+NfhGXq6jU+4kIj6DImx947Td9uDxFhIWFnWCrkhYtnE90SCWubPAoV9Z/hLqx55CdlU1WVmap2yhrs2fPwFIUTrsq19A4oQOdqt/E5o1b2LhxPbm5uWzZsgWXy1Vu9Z0JLBYLdrujxPVT6MklIky3nfy3li5dTI2IpkQ7i+9FjgpJJCmiGUuXLi7nyspeTk42H3/8AV2TbqVtpau5tOY9ZOzJ59dffyrv0kRE5AyiHlogOTmZ8ePHl3hv2bJlNGjQgEWLFpGXlxe4bzgmJoYlS5bg9Xqx2Wz4fD7Wrl1bqv0MGTKE/v3707VrV5KTkxk9ejTXXHMNjRo1KvNjOhUshoWokPjAa8MwCLPHkOcpDjUxMTGY5naqRtRnU8ZCfKaXcFsMPsPHZXXvxMTPgt0TSc3byQ8bRmO12PH63YDBBdX7Eu1MpMCdw778LdSJaU1qwQ4i7LHUiGrCzuw1gf1arRa2Z62kRaWLAdiXtwm7xUGItfhxUulFKVSPaBjokbQaNmrHtGTdwTn/0/F7PB6m//oTy5YuJzExgd/nzeGSGncS7ogBINQeyTcTJtCx00Wlai8zMxOLYXBRrRuJdRb3Hq9Jnc2mjEWBdRbNX0idyPNxWIufBV05oi5RuQls2LCeli1bl2o/V/btw6tjx2K12AizRbM5eyFNmzY9qcl9TL9Jk8TO2CzF9802jL+QdWm/kZ6eTmxsXKnbKUu7du4i3l4z0BtrNWzEO5P4/ruJrF2zmojQGArdudx1z/20b9+xXGoMdlarlZ49r+T3Gd/SKKYzftPLusxZXHXdVeVdWtAKCwvHbZYcGuc28wkLO/Meh7d58yYSwqsTGVI8KsdiWKkZ3pzVK1ZxxRW9y7k6ERE5UyjQHsc333xDt27dqFq1Kj/88AM33HADADabjTZt2jB//nw6d+7MvHnzaNeuHZMmTfrHNuPi4nj22Wd55plneOSRR0hJSTmqB7gi85l+NqUvomZ0c0KsYWQW7uNgYUpgeWpqKg6rk8yivVxe7z4c1lDWpc1la9ZS9uZtxMBC44QOzE/5moSwGoTbY9iVsxb8fqL++oVnf/42okISSI47j2SK77PdmrmM3TnrA/uxWC1sSl/E/rwt2C1ODhamEGGPwcSPgZXokMqkFe7Cb/qxGJbiGVrzt+MIOblJjLZt28p/Pv2EXbt2UKdOPbxeNxl7C6gV3orde/fjchURaj88nj/CHkf2wdL3WEZHx2CzhATCLEBSVCO2Zv1xeJ2YaNL35QRe+00/Be4cIiOjSr2fVq3O4fIrevLTlKl4vB5q1qrJvff/u9TbA1isVoq8eYHXHn8RJma5hVmARo0bMXHp9ySb52MxrLh9hezJ2cjB9aFcVvteQm2RZBTu5e233qBJk6blWmswu/a664mLi2PWjJlYbVZuuv0mOna8qLzLClrt23fkqy8+Z93BOVQLb8C+/M1kuFPo0KFTeZdW5ipXrkxW4QF8fg/Wv74My3Lvp171auVcmYiInEnO+iHHAFu2bCkx5HjPnj0sW7aMiy66iP79+weGEB9yxRVXMG3aNACmTJlCr169Sr2vrl27UqdOHQYNGsSoUaOC6l4/C1YiHPFM3fwGv2x9h992/ScQRAFM04/P9NCsUldC7VFYLXaaVeqC3/SxK/tPdueuZ8Hub6gZ3ZzEsFpYLXZaV+6OaRQHTgC/30t6wW62Z61gbepstmYuY0vGUsy/higDeN1ebIYDv+nD43dhmBYKPNn8svMt5u39gp3Zqyny5DFzx0dsTF/I3JTPSS9Iwe32lvpYMzMzGPL80zgyqtOx8o0YqQmsX7+e8yr1pmZ0M1pUuoRwRzSbMhZjmiam6WdT1kLOOee8Uu+jWrXqmIaXXNfBwHv787bS4Ige+569rmRz9iK2ZC4hNX8HSw58T7WkqtSpU7fU+1mxYhk/TZlGy/judEq6AU+GjTffeK3U2wN06NSRP/b+wJ7cDaTm7+D3XV9SuVI14uPj/3njU6R9+04kJsUwa/cHLE+bwoxd71G5chVqR5xDqK34i4a40GpUjazHypXLy63OYGexWOh+eU/GvPwKL45+SWH2fxQeHsHIUS8Rk2yypmAa8Y0MRrw45oycNTopqSYtWrbi932fsTVzGSvTfmZP4Tqu6HVleZcmIiJnEPXQcvSQ4y+++AK/389dd90FQFpaGgsXLqRdu3YAnHvuubzwwgtkZmaSlZVF9erVj9nu8fTp04eioqKjZrKt6Ex8+E0vUSGJf81yXJuDBTsDy+vWTebA3jT8/sPB0TT9mKZJTEhlWlTuyqRNL7Mndz01o5oRZo/mz4O/YzMcLEj5htjQKrjNIqyGlTWps6gd3ZIdWavI82Tg48gwapAcdx7NKnUBYF/eZubtmsB1A6/jl59/xpYdQkJYEh6/i/UH5xFqi6RGVDN2ZK8q9bH+/vscqoY1CMzG3CCuLQfytrE3dxP1Ys8FIDm2DRuz5rErfyVev4cqVSpzy62l7/kMCQkhIiKSGTs+om7MORR580jJ+ZPu5/cIrFO7dh2ef2EY33w9ge1pGzmn8zn063/VSX0RMvmHH2ga15WkqMYAnOfsw7QNr5GWllrqYcf33PMAFouF+XOm4PP7qVe/Lk89PaTUNZwKdrudZ58fytq1q9mzZzcNG97I4sULWTNne2Ad0zQp8OYQFRVdjpWKlFSlSlUefvRx4MyfnfOhRx5j7tzZrFi2nJpVavLo5fcEnjsuIiJSFhRoj2HixIm8++671K9fH4DJkyfz+eefBwKtYRh07tyZIUOGcMkll5RnqaeViUl64R7aVOtNfGh1tmWtYH/elsDyhIQEfH4PS/dPoZ11AE5bBOvSfiPUFsXWrCUYhoHf9NEovj1NEovvaawd3YIpW97AYtrw+AsBE4th4fJ692G3OjFNk/m7v2Jf7pYSldSOOTzLb5XwZAwDmjVrydbNW9m/O5UcVyruv4bF5nuy8JkeTEo+oWrJksX8+tPP+E0/l1x2Ge3aHZ7Ey+UqwkrJWTjtVie57nQAfKaXVNcW/nXDQBo1aoLdbicpqcZJBc0DBw6QnZ3NRbVvYn/uZmKcVagaUZ+5s2dw6613BtZLTm7A4KefKXW7f1eQX0DsEZN3WbBit4ZQWHj4l2iPx8Ovv/7EquUrqVKtKr2u7H1U2K1fvwEb/lxPUVERDRs2OenHB50KFouFFi1a0aJFKwCioqL4edqDWEwrIdZwcjxpWJ1+WrU6p3wLFTlLWa1WunS5hC5dzp5/K0VE5PTSkOO/+fPPPzFNMxBmAbp168ayZcvYt+/w7LO9evVi5syZdO/e/bhtZWVl0a9fv8B/U6ZMOaW1n2oGFhrEtaVmdDPCHbE0r9SVCMfh+xJ37doJGEQ5Evk95Utmbv8Qq8XOZXXvoFJ47cBkR5XCDz+aItQeRYg1DKc9jMrh9QixhhEXWh37XxM6GYZB9chGGH89wufQe2kFuwKvc90HARObzU6v3r0p8uVS5CugcUInute9l9ZVulHgycFyRNicPv0X3hn3Fva06jjTa/LRux8ydcrkwPJ27dqTkreG9MI9AKTl72R/wWZ25C5n3v7x/LxjHNXrVeLSS7tTt249atSoedLDx1NT9wMQ56xKs0pdaBjfjhBbWJnPzNuhc0c2Zc/H7SvENE22ZS3HGeYgKakmUNyL+eKIYfzy3SwcaUlsW5rGE489zMGDaYE2Zs2azpf/+ZJ6tk60jurN0jmreeetcWVaZ1mIj0+gRctWbM1cxq6ctaRkr+OSSy8LPJtWRERERM4s5d/FUs6SkpKYMGFC4HWTJk34/vvvS6wTEhLCwoULAZg/fz5Q/PieI2c3njVrFgAPPPBA4L1169Ydc58XXHABF1xwQdkcwGlkMSyBmYMPOfJ1ZmYm4Y5oKoXXJjIknnOqXB5YFulIYI+5EUyTHVmrSAgrDlOZhftw+wro3eBx7NYQaka3YNaOj3D7CnFYQzFNk5ScP/GbvkBbftPHygO/kO1KxWFxsiVzKX7TxOUqokaNmsTExBLiiaVxQnGPax1HazIK95KSf3im5IkTvuL8Sn2JD00CIDqkMhO/+ZKeVxTf25WUVJO77r6Xjz/6AJfLRWhoGA8/+hhNmjRn06YNJCQkUqNGzf/pfEZGRmExLKw6MJ1miRdR5Mtn1YHpYJj/vPFJ6NGjF7tTdjPt99exWuzExsYy6KlnsViKv8/aunULO7bt4LKa9xbPQkpzzDQ/P02bwsAbbwFgyqTJtIzvTuXw4nt3z3P0Ydqi17i94O6TevzPqfbHHwvZuHYzVyQ/jN0aQp47gwkTPuTC9h1OalZnEREREQkOZ32gldIzTT8bMxZSLbJBcUDN3UBG4d7A8vj4BHZu30WlsNrM2/0VjeLbE2aPosibx46slYRYw/D7/ezO3UD61j2E2aM4kL+dKhH1sVtDAIh1VibcHstPW9+iZlRTMgr3ke1KxcR/RCUGcc4kDAyKvHlUj2zEjqyV+HzFobdVq3PYvGzvkaVjt4SQdEQAzc7JIjLx8IRGEY44cvOz8fv9gaDXoWNn2l3YIfDYpkO9fK1bn1sm57NKlapggVx3Oj9sHIPNGkK8swbV65btvdVWq5V77r2fG2+6mYKCAhISEkv0Jh88mEq0MxHLEb3gkfZKHNh3+Lm9Ra4iHI7QwGubxQ6Ggcdz+PnAFcGKZcupEdYicD1FOOKoFlmfNWtW0bXrpeVcnYiIiIiUNQ05llLz48PrczNz+8d8v3EUK/b/XGL24Suu6A2myarU6VQNT+anrW/y89a3mbL5NTx+Nz48VK9ZPIFWjajGJITVJCokgSJvbqAdr9+Dy5uHy1vAruy1ZBTtxW/6qFbt8GMeQp1h5LhS2ZK5lF0560jJWYvP9FK5chUArr32Bvbnb2F/3lZM0ySzcB9bMpdw41+9jQAtW7RmU+bCv2YoNtmcuYimjVsGwuwhVquV6OjoUzJk1el0ct11N5DrS6NxQmdqRjcj27+XW267rcz3BcWzqyYmVjpqaHTjxk1JzdtFzl+zLfv8HlLyV9H6vMP3nbbv0JH1WXNw+4rwmz7Wp8+ldq26REdXrMmWEhITyPelB16bpkmu+6AmoRERERE5Q6mHVk6Kz/TjN/348f71fz8dO3YGoEmTZkRFR+MudHHQu5twWwy5rnSuH3gTPXsWD+W12+18+eV4fpo6DY/HRe3adfB4fMxO+Zj4kNrsK9yA1WHBLIQiX/GkRXaLndGjXwvUMPDmm/jwvfdIjjkfq2FjW/ZyOna8iNDQ4h7ExMRKPPTwo7z79lu4druwWq1cP3AgzZq1CLRx5933MuyF5/k15S0MLIRGhPDsA6f/mcC9+/QjuX4DFi6cT0R4VR675N7TPjQ2OjqG2267i48+eo+EiOpkFaTSvEULLrro4sA611z7LzLS05m26DUwDGrXqsujjz9xWussjUsu7ca0qVNYnTaduJAkdhesIyohgubNW/7zxiIiIiISdAzTNMv2hj0pUx6Pr0I90qF//54YWDHxBf7/7bdTA8tzcrJ5561xrF27hoiISG648Ubat+90wja9Xi9LliwiJWUXDRo0omXL1qxbt4YpUybRuHFTrryy71G9iqtXr+LrLz/H5XLTvUd3Lr6421Hr+P1+8vJyCQ+POGYPq2mabN++DdP0U6dOvaN6Z882ubk5bNq0gUqVqhz3/uCCggI8Hk+F65k90sGDaUz64Xv2791DoyZN6NHzysCXHSIVzZn+2B4JfrpGpaLTNXp2SEw8/vPaFWgruIoWaA/RDw+p6HSNSjDQdSoVna5Rqeh0jZ4dThRoz+4uKREREREREQlaCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQUqAVERERERGRoKRAKyIiIiIiIkFJgVZERERERESCkgKtiIiIiIiIBCUFWhEREREREQlKCrQiIiIiIiISlBRoRUREREREJCgp0IqIiIiIiEhQspV3ARJcUlJSeOKJB3G73VSqVIU333wfq9V62uvIyspiypQfKCws4PLLe5GUVOOk2ygoKGDp0sX4/Sbnn9+G8PCIU1Dp6WGaJllZmYSGhuF0Osu7HDnD+Hw+tm7djNVqpW7dZAzDKO+SRETkLJeZmcHataupVas6NWro36azmWGaplneRcjxeTw+srIKyrsMAFauXMaIYc8BEGI1cPlM/MC3304NrFNYWMiErz/jj0XziYtP4Np/3UTTps1Pel9bt25m3bq1VK5chXPPPR+b7fB3L3/+uY4Xnh9EnM3AZjE4UOTl+htvpXfv/qVuf/v2rQx5fjAxVgPDgAy3j2efH0H9+g1Putb/VW5uLsuXL8Fut3PuuecTEnJygXTnzh28/NJwMtLT8Zsm3br1YOBNt2OxHB6AkZGRzsyZv5CdlUWbCy6kRYtWJ13nsmV/MPn7iRQVFdK5y6V0696zXL7MKK2YmLAK89kJZnv37uHZpx/DW1SAaUJkTBzDX3yZ2Ni4016Ly+Viy5ZNREdHk5RU87Tv/1TQdSoVna5RqYhmzZrORx+8TaVQB3k+k4TK1Xh+6Ch9qX8GS0yMPO4yBdoKriIF2v79exJqNeicEE6IxUKWx8fvB/NJqFSZd975GIDHH32APbu24zeLw67VYuH5oaNp1KhJqfcz/j8fMf3nqSQ6LOSbBpHxlRg28uXAD6nbb/0X3rxc3KaJzQATcPlNvvhqUong+3fp6QdZtWoFUVHRTJzwOeEH91ArzA5ASqGHjMhEXn7tneNu73K5+HHy9yxfuojESpXpN+A6atWq/Y/Hk55+kN27U6hVqzYxMbEllq1YsZxRI5/HME0MAyx2By+NHUe1atX/+URR3HN2z503UYMiajptuPwmy/L9XH3THVx88WVAcSAZ/ORDVLaBw/Sx12vhsp69ufa6gaXaB8DChfN5761XaBBiYDcMtrnh3A5duP3Oe0vdxuni8/lYuXI5WVlp1KqVTHJyg/IuKajdd/fNxBflkBwRgmmarMt1YatWm5GjXj2tdaxevZKxY0YQbrNQ4PGS3KAhTwx6npCQkNNaR1lTWJCKTtfo2WXDhj/5v4/fY/ee3dSrW49b77iXmjVrl3dZJeTn53Hn7QO5MNpOpM2KaZosz/fRqVd/+ve/trzLk1PkRIFWQ46l1KxAcngIIX/1/MXYrcQ5rKSmHgBg587t7Ny5jRZRTmqE2nH5TRZmFPDOW6/z+rj3jtuuaZqsX7+O3btTiIuL56dpk3GYflLy/FgNA49nD1OnTqZatWo4nU5ysrOpGmKldrgTn2mS4/WzMc/F7t27qF277jH38fvvv/Hu269TOdRBod8kPS+frgnhgeXVnTaWp+zC7/eX6Nk80osjniNj51Zq2CEzNYVnli/lxdGvHrenyDRNPhv/MT//NIVYZwiZRS769b+W/gOuCSx/adQQ4u0GjSNDcflNlmcVMnLk87z55of/8LdRbNu2LZheN7Uii4O502pQx+5jzqzpgUA74avx1LD5aRDuAGzU9PmZPPk7el7Rh8jI4/9wONK3Ez6jidOgirN4PzF2P7Nm/cr1A28hNDS0VG2cDh6PhyHPDeLg3hRirCYH3H46dL6Y2++oeME7GBQVFXEgLY3zqxRfJ4ZhkBzuYMaWzae1Do/Hw8tjR9IyFBJDLPhNO8u3bWby5O+46qrrTmstIiJnqtTUA4wY9iyNnAYdo2zs3bOV5555grfe+YTw8PB/buA02bp1CzHOECJtxUOMDcOgms1k9YplCrRnKQVaKTUTyPP6Dr82TQp9/sDrRYsWEvJXj+nSrEJCLBZqhtrZfGDvcdv0+XyMfvEFtm78k1i7lf0FLrweL81jQqnmtJHn8zPvYD4TvhpP5cgwPP7i9rN9Jiuzi7BbDAp9fnwmuFzuY+7D5Sri/XfH0TbKTrTdgmmarPTZWZvjok1cGFA85DgxPv64YXbHjm3s2LaFi6LtWAyDyoAfDz9O+pa7730I4Kh7N9avX8esX3+iS6wDh8Wg0Olg0ndfc+55bahduw47duzA4/VxfkIk1r+2bRXtZPn+/Sf+iziC0xlKQZELMyI0sH+PaZYYCpyycwdJ9sPH5bRaCHfYSUtLLXWgzc3NpTKwPrcInwlVQ2wYBhQVFVaoQDtnziyy9u7iwggrhmHQwGky57cZXHpZj1L1psvRDCDf5yfSVnxN5Xn9nO7blHbu3E6IAYkhxf9kWQyDmg5Y9seCoAy0LlcRs2ZNZ8umDTRv0Zy27S7SMDkRKXdz5syimsOgRmjxl9d1wxxkFfhZvHgBXbteWs7VHVa5chWyXS68oSHYLMX/IGX5oE6NWuVcmZQXBVopNT/FQ3NDrRZi7VZSCj24/YdHrNvtNtwm7CrwUDvcQb7Xx8Y8Fyca075o0Xx2bV5PxygbFsOgsdPJ9AMe8n1+VucUEWYtDmLnRYdQ2Vn852l5kOCw0jzKiWEYpBR6WJVdSGJipUC7hYUF/DTtR9atWUVsQgJOq4Voe/Ev5IZhUMNpZ0lWIb+n5wMGBRg8+NDDJWrbtWsH4//vQ3bu2E58YiXCbFYsR/wmH2KYrFi+lGuv6Y3VauXSS7oz8KbbAsOeV65cThWrH4el+B+GUKuFKiFWVq9eQe3adcjNzcZilJxq3G45uaQQHh6Oz+9jZXYR9cId5Pv8/JnroqndHlinSbMWbJw/i3hH8etsj48ir4/q1Us3rBmgfsMmLFk8n5qhdhwWgyVZhYRHxZzUfZRer5fPx3/MzJm/4jdNOnfqwk233InD4Sh1G/9k04Z1JFr8GEbx34HdYpAYYmfLlk0KtP8Fp9NJTHQMizOyaRgRgh9Yn+siqfrpvX81JiaWArcHr98S+OUlz+snPqHSP2xZ8Xg8Hp4Z/CiujFTiDT/fr1zCj5MnM2rM69iP+NyKiJxuHo8by9/uRLRg4vV6y6miY6tcuQrt2nVk0ZKFVLf6KTAsHPBZeajPgPIuTcrJGRtoFy9ezI033sirr75Kjx49Au/36tWLpk2b8scff1C1atUSPXJPPvkk+fn5PPTQQyQnJ2OaxR/iG2+8MdBG+/btmT9/PgAzZszg//7v/4DioXm33XYb3bt3D7T3/PPPs2rVKn744YfAewMHDmTIkCHUq1fvVB7+KWEFaofayfX62V/kJc5hJdJmIcNT3Etbv34jTBNiHBa25LlwWg2qhNhI9R0/pP25bg2VDB+WIwKIw2qwp9BDzTA7mW4fPhOij+hhNAyDuuGOQI9kktPGqizIy8shLi4On8/HE489QGZaKoU+P3YDfEBReATOvwJyutuHiUG8w4YBpLhNjrydPCsrk2effpzaNj8tQ6zs3b+TtDwXGY4w4hw2vH6TjfkeEkJM2iSE4jNh6dwZhDid/Ov6mwBISEik0HL4I2aaJgUYxMcnAFCzZi1MYHOei+SIELwmrM9xYfnbL7WrVq3g6y/+j/T0g7RsdS433HgrUVHRABw4sJ/osDCsfg9/ZBYSYjGoE+qgIC83sP2Aq6/n6eVLWZyfj9OA/YUe7r7nwZOafCo7K4NmUU5qhRWHz2qhdhbmFLB48UJ8Pi+tWp1LWFjYCdv4/LNPWPLbdNpFWDEMWLPgNz7yernnvodKXcc/qV0nmY1LF2KaJoZh4DNNMtw+ataseN/a+nw+fv/9N1YuW0KVatXp1r1nuUy09E8GP/MCzz37JBvyPYBBSHgETwx+7rTWkJCQyHnnX8DSVcuoaTMp8Jtsd8OQAcE3tGzJkkXkZ6RxQbgVw7BR2zT5I/MgixcvoEOHzuVdnoicxTp06MxPUyZR2e0l1m4l1eUltchPmzZty7u0o9xz30MsXHg+y5YspHmNJDpfdFng9ys5+5yxgRagbt26TJkyJRBGN27cSGFhYWD5xx9/fNSEIosXL6Zt27a8+mrxhCf5+fkMHDiQOnXq0Lhx48B6y5cv59NPP+W9994jPDyczMxMrrnmGpKTk0lOTqawsJDly5fToEEDFi9ezAUXXHAajvjU8gO7i7x0iA8n3GYh1eVle/7hYb5WqwWrYeD2mbSKDiXP52dtdhFRMTHHbbNGzdqsXWALBJBMtxePH7pUDi8ehhsOyzIL2JjrpmVM8dBWwzTZkucm3e3FZ5pUdtrxA5UrVwXgjz8WkXrgAE0iHdQMc5Dt8bEwo4A5B/OpG+6gwOcnpdBDs8gQaocX//0nurx8+vF7tG3bHii+5zbRBvXCiwNcwwgr6V6DP3I8RDkt5Ba5cPv8NI9wBHpVGztNZs34JRBoO3TozLfffMGa/EISrJDqBcKiOf/84n8YCgsLsVqtbM53synfjWmCzYDo2OjA+dm8eSMvjxlOY6dBNZuFHUvn88LWzYx95S0Mw6B27Trke7w0j7TTItpZPJw630ublq0DbURHR/PauPdZsWIp2dnZtG597kn/0N+7Zw/nOg8PY7Zi4Ha7+PTtV3FYLbzr9vLUM0NPOPnXrJm/ckG4hXBb8ZcKzcNg5tzZ3HXPg8cd6n2yunS9lF9/nsLS3CyiTC9pppWmLVpVyImhxo4Zzp+rV2D1+1hjWPjppym8+trbxMXFl3dpJdStm8zHn3zJmjWrsNlsNG3a/ISTr50qD/z7caZP/5lF8+cQH5fALX36U6dO8H0xuHfvHqLwYRiHR4xEmj727Tv+rRkiIqdDzZq1ufu+h/nko3fIzcojPjaWJwY9fNSElhWBxWKhffuOtG/fUROXyZkdaBs1asSOHTvIyckhKiqKyZMn06tXr/9v7z4DoyrzPY5/z5mZTHonCSGBEAKEKh1BmoUV2WV3sYIaRHRVLAgLKteKKxYsa12xry4quiCKIui6ooBSVKp0BGlJgEAKmbQp59wXgcFcwJW9aDLy+7xyzjlz5j/DI8NvnkZhYeFPvkdUVBSXXHIJH330UZ1AO2PGDK644orgJPmEhARmzJhBbGwsAPPmzaNXr17069ePN95441cRaAH8ls3n+z2YhoEBdYYT+3xebGy6xNfO50zAgc+y2OHzHfd+/fufxbw577HCU0Y8fr6r9BHrMoNzSgGS3U6+PVhNdIWJH5MaGwqrfQQA24Y91X4Maofyud1u1qxZSYzTpPmhsJoY5qRlVBg7Kn1UBWzCTZOADRkRR4a6JoY5KNpzILgoVFVVFaYVYGelxUG/RbzLQbTTYNCFl9OmTTtiYmL587i6Cw3ZUDvh8JDIyEimPPIU78+exbbvNtGtTXt+N2RocIhto0Yp2DZ0iA3HZ9m4TYM9NT6iEo+EzbkfvEfzMGhyaD5LO6fJwgNFfPfdZlq2bE1ERCRXX3MDLz7/DKkRJhUBi+jEFH7/h7rDbpxOZzBI/zdcLie7q6rJjan9R/jKsipaRIXR5tDjQhOeeuJh/jb178fdB862beqc+RnmYUZERDDl0af44ouFFBUV0qJFa7p27dHg9qbbvv17Vq34hniXQbNoN2X+ANsqKpjxzze59rqb6ru8o4SFhdG1a/d6rcHhcDBo0G8ZNOi39VrH/1ebNu2YO3smLS0bl2ngt2yKLOOEVoIXEfm5nHFGX3r1OoOammrCwyMa3PenyLH8qgMtwMCBA/nkk084//zzWbNmDX/605+CgXbUqFHBniHTNIPDh/+vpKQk1q1bV+fYvn37yMzMrHMsLu5Iz9qMGTP4y1/+QosWLZg0aRJ79+4lNTX1ZL61X5wNGEZtiIxwGJT7rTqB9rvvthBmGlRbNnurvUQ4TNyGgbe6uu59bJvt27dRXl5O69ZteOiRp1iwYD47tm8l/5uvKSktpipgEeGoXcBpd5UP24ZGnXsTERnF5nlziHM56JoQgdMwWH+wmh1VPgoLC2jZshXNmjVn2TF2o4pymnSMqx1mu63Sy+4qb7CHNr/aT0RYWLA9dOvWg1kz3iTWaZLqdrKtwosnYNOzZ28aN04HoGeP01n77XJyIxwEbNhQbTPwvPPqvGZ8fAIjrrjqmJ9ncfEBDMNgfXkNkQ6TGsvCZRgEykqD11RWVuD6wXeJYRiEHQrchw0YcDYdO3ZizZrVJCQk0KHDaSetx/Mwr8/Hjkofxd4ALtOgxBegc9yRxaDS3E5WHSjB4yknJib2mPfoP+BsVi2aT4fI2na0rjLAGb37nPRa3e5wzj77Nw36F9s1a1ZiYtMzIQrTMEjHhWXDt6tX1ndp8jNr27Y93Xv1YeGXi0h2O9nv9dPz9D60b9+xvksTEQFq/00cEfHj04hEGpJffaAdMmQIkyZNIjMzk27dutU5d6whx8dSUFBAWlpanWPp6ekUFhaSm5sbPLZ8+XKSk5Px+/1s2bKFhx56CKgNIdOnT2fs2LH//zdUz9ymQctoN1UBmxYOg1Vl1cFQ27hxEyoCNvOLPBxeK8o0wOF08eTjD+P3++jTbwAfzJ5F/s4dRLgceHwWt068K9jrsvOOWygvLebzogpS3E7K/AECh/ZovXHMBAD+9dEc2saGB7cPahsbzvZKX7C3vGfPXrzy0rNs9dTQLDKMUl+ALRVewpy1wbQaE69ls9HjZW9N7arNxb4AXssO9tAWFOQTF+6md6wruFXJojIvBQW7g4F29A3jeOWlqSz4ciFOh4PfnDuYCy+69Cd/lmFhbgIBPwMbRXPQb+EyDSr9Ab6rOfIDQL8zB/LqpvU0CliEmwYF1X6qbQdt2rSrc6/ExCQGDDjrxP4wT0BGk0wcBVtxmyZ+26bCb1HiCxB5aPhwud/C5XSxdOlitmxaT9OsbM4++zd1vhBHXHE1fr+fzz7/FNu26XNGX66+5safreaGLCYmlgiHWWeRsRinie8kLpAlDZNhGIy+fiznDf4D27dvo0OHNiQlpdd3WSIiIiHrVx9oMzMzqaysZNq0afz5z39m165dJ/R8j8fDjBkzePLJJ+scP//883nsscfo2bMnkZGRHDhwgNtvv50nn3yS9957j3HjxnHZZZcBtYH4kksu4frrQ3svTJMjKx3Huxxs8vgINw0qD6XX5s1b4ADaxLhpHhlGVcBmcXEFlT4fxWuWYQJPfrOMJJeDAXFuDMNgX43FY488wIsvv47T6aRjx9P4btN6Ip0GpmET5ai9Jvr/7H8W+EEP7OHwXFNTA8DKlctJiYqksLqGdeU1RDoMksPDyO7UnTCXi/iEREoXLSC+ppwirx/s2sWu9jsjg72FO3fuIMm0gkNtDMMgyWmya9dOunbtAdSuAHv9jeO4/sa6qyP/VBUVtQs3rSyrolW0m6qAxZqDNRjOI1sj9e7dhx3bt/LhnNkYBsTFxnP7xIm/+Gqol19xFffdewcZYeC0bbyGg28rfHgscGCz0wexcfG8+/rLpJgWm79ZysfzPuDhR58Jbuvjcrm49rqbuObaG7Ft+6T3zIaSzMxmlPkCHPQFiHU5CNg231d6adXqp688LaEtK6s5WVnNG/RIAhERkVDwqw+0AIMHD2b27Nk0b968TqD94ZBjgBEjRhAbG8vSpUvJy8vDNE0CgQA33XQT2dnZde7ZuXNnLr74YkaNGoXT6aS6upo///nPZGdn8+GHHzJ79uzgtenp6eTm5vLxxx8DcPPNNwfnUfbs2ZPbbrvt53z7J40NRDtNTk+IrN3jM9rmk31HVtNdvXolbodB9qFhvJFOg9yYcNYerA4urrS90kvzCGcwKKa4nawuryQ/fzfNmmWRlNSIgA2VfguP38K2wWXwf7bnMFhVWk2X+AhcJqw9WI0BxMfXDvm2bRuXw6RH8pEQvN7jo3F6Ey69tHbBplWrVrCztJh2seEYwPqD1SSkHulNbNmyNZ9/5CRg2zgMA79tsz9Qe/xkqayswgTiXQ5WH9pTt0VUGN9XH9nb1zAMLr1sJBdcOAyPx0NiYlK9zGdp1SqXhx99mk///RFVlZVc2u9MoqKi+eRfc/HWVNMtM4sPZr5JnxhHcMuc5RXlLFgw/6g5j4ZhnPJzcg4c2E98RDhfHKgg1uXA47eIdphY/uPPNxcRERGRo/1qA23Pnj2DCzHl5eWRl5cHQL9+/ejXr9+PPnfJkiXHPXd4yx6A3//+9/z+978/6ppFixYddezFF18EaodAhyoTaBzuCoYRl2mQEOZg36Fhu05n7VzSwysWQ21P6g+3w4lymJT7LZIPjfT2WTbVfj+WVRvi4uJqV9Kz7No5r5V+C9MwiP3B/OReZ/Tl68WL+Ka0EutQ4G3UqBEJCbWrw/bo0YvX/v4Cu40A6eFO9nsD5Hstbux3ZEju7l076J0QSUJY7aJGsU6ThXsKgkOOu3btzvw27fli/bckuUyKvBaduvagbdv2J+3zzMjIxDZNmkaGkRtzaG6vp4bMY2wx43aHn9A2Oz+Hxo3TuTxvVJ1jV109GoCPPvqQeEfdoBpr+9m9a8cvWmOoaNYsiyrLon9yNBUBiwjT4Lsam5attTCQiIiIyIn41QZaOfkCQEGVj2YRtaHWZ9Xu8XlYenoTLBvWlFWTE+2mImCx7mA1jh90xkU5TdaVV+O3bSIcJtsqaghzOILbgPh8NcSFu6moqSHMNPA7DByGQUT4kTA35uZbeNK2Wbb0SwK2TWbzHO68e3LwfExMDHfePZnnpz7J8p07SUtJYez40WRkHFnEK2DZwe1jDtcVsAkGWtM0uXXi3axfv5YdO7bTokUOrVrlntSexYiICC666DLen/UWTd0mNZZNoR/uGz3mpL3GLyU3tw1vev20jjAJMw0s22af5WCwFro5prS0xpx99iAWfvYJqQ6LCsMJUbGcN/h39V2aiIiISEhRoJUTUuwLsGB/BcluJ7urfFg29OlzJlA7HNcVHk6Jr4bP93twGQZulwvDFcaX5QEchsFBv0F0WBjlfotib4BopwNnZCxNmmQAtVtaVFs23RMiqTy0ENJWL3T9wZYzpmky7s8Tf7TOVq1yeezxqXV6i3+oUVIyWzwHaRtT21W8xVNDYlxcnf01DcOgXbsOtGvX4f/9uR3PhRcNo3VuGxZ/uZDo6BgmDBxEamraf35iA5OVlc3ZA8/j03/No1G4ixJfgNZtO9CjR6/6Lq3BGjnqGk7v3Ye1a9fQqFEqvXqd8ZMWqRMRERGRIwzbPsb+JtJg+HyBBrNgSE1NDZdeen6d7UNt4J13Pgw+XrduLY8+PBmHHaDK56dHj16MvmEsmzdvJBAI0Lp1Ls9PfZplyxbjcjiIjonl1v+5h2bNsoL3+PjjD/nHqy+RHOGmzOujTbuOjL/ljjph8/9rz54CJt5yM97q2u1vnGFu7n/or2RmHj3cV366nTt38N13m8nIyKRly9b1OldWi+1IKFA7lYZObVQaOrXRU0OjRjHHPadA28A1pEB72KxZM/jqq8Vcfvko2rc/uvfS7/ezc+cO4uPjSUxMOuY9ysrKqKysIC2t8TFDT2lpCZs2bSQ1NY2srOYn/T1A7VzfrVu3YNs2OTmtTvmFin5t9AUnoUDtVBo6tVFp6NRGTw0KtCGsIQZa0F8e0vCpjUooUDuVhk5tVBo6tdFTw48F2lN3I0gREREREREJaQq0IiIiIiIiEpIUaEVERERERCQkKdCKiIiIiIhISFKgFRERERERkZCkQCsiIiIiIiIhSYFWREREREREQpICrYiIiIiIiIQkBVoREREREREJSQq0IiIiIiIiEpIUaEVERERERCQkKdCKiIiIiIhISFKgFRERERERkZCkQCsiIiIiIiIhSYFWREREREREQpICrYiIiIiIiIQkBVoREREREREJSQq0IiIiIiIiEpIUaEVERERERCQkKdCKiIiIiIhISFKgFRERERERkZCkQCsiIiIiIiIhSYFWREREREREQpICrYiIiIiIiIQkBVoREREREREJSQq0IiIiIiIiEpIUaEVERERERCQkKdCKiIiIiIhISFKgFRERERERkZCkQCsiIiIiIiIhSYFWREREREREQpICrYiIiIiIiIQkBVoREREREREJSQq0IiIiIiIiEpIUaEVERERERCQkKdDKCaupqSE/Px/Lsuq7FBEREREROYU567sACS2XDhsKfhu/beHEpFmrHB588NH6LuuYLMuivPwg0dExOByO+i5HJGRVVHhYseIbTNNB167dCQ8Pr++SRERERAAFWjkBo0ZdhuW3sGyLMNNFjeVjy+YNrF27mvbtTztpr5Ofv5uXn3uW9ZvWkZKUyrC8PHr37ntC91i58hteePYZKioqcLlcXD5yFGeeec5Jq1HkVLFp0wYenHwvrWOa4rX9/P2l55l03wNkZDSt79JEREREFGjlpysrKyXC4cbASUZkKtsr8rFtk3vuuZ133vnwpLyGz+fjL3ffwXkJPRjT7Q9878nnb1OnkpzciFatcoPXrV27ho/nzKGmupreAwbQv/+ZGIYBQElJMU88+jBjsi+hXVw2OyoLefiVl8nKak7z5i1OSp0ip4oX/vYMV2b8ltOTOwAwr3Axr774AnfeO7meKxMRERFRoJUTYGKQ7I7nLx2uw+0IY2/1AW5b9TTYx3+ObdssWvQ5n//rE0zT5JzB53H66Wcc9/pvv11NkiOW8xqfQXXAS25sFoMa9eKzTz4JBtqvv17G8089yflpA4h0hvP+tLfYk5/PsMvygudPS2hF+/ja8JoVlc6ApC58+cWiYKC1bZsvvljAp/M+wrZtBvxmIAMGnB0MxSJSO19+V+EuevS8KnjsjOTTeGfN/HqsSkREROQIBVr5ycLMMM5J64nbEQZAangSbWObs6p083GfM/vdd/h8zkdckHYmgUCAac+9SHl5OQMHDjrm9bZtURPwcsfqv7G7ch9RznBax2YRa6cHr3n37bcY1XQIXRPbANA6phm3zX2GoRdejNvtxu12U2XV1LlvlVVD4g/m/c2bO4ePZr7LxY3PxjRNZkx7m7KSUv54/oX/9ecj8msTFhZGfEw82zz55MRkArDp4A7SU5vUc2UiIiIitX6WQLts2TLGjh1LTk4OUPsr/5AhQ1i3bh2DBw+mX79+wWvPOOMMvvzySwCWLl3Ks88+i23b+Hw+zj33XEaOHMnmzZuZPLl2eNuqVavo2LEjpmly1VVX0b9/f958803mzJmD01n7dq6++mr69+8PQGVlJY8//jirVq0KLmQyYsQIBg4ceFSdFRUVZGRk8OijjxIWVhva5s6dy+23387HH39MamoqAE8//TRz5swhJSUFqB0mO27cOHr27MlZZ53FvHnzcLvdAGzdupVJkyYxceJEbrzxRt577z3i4uIA+Mc//sGKFSt44oknfo4/hpPOZ/n53lMQfGzZFrsq9x73etu2mf3uTO5pfTWNI5IBaORO4InXp/HPN1+nzHOQDm07cu0NY4KfZatWbSg4uJerW/yR3skd2V25j/vXvcwFzU4P3re4pJjGzZODj+PDYsCG6uoq3G43PXr04vVXX+GD/EWcntSedWVbWVz8LQ/3vyb4nPdnzWRc1iVkRdcG5cYRydz33iv8YegF6qUVOcQwDC4feSV/ffEFzknujs8O8Nn+5Yy95bb6Lk1EREQE+Bl7aE8//XQef/xxALxeL4MGDSI3N/e412/ZsoUpU6bw/PPPk5KSgt/vZ9KkSbz88stcffXVTJs2DYCzzjqLV155JRgY33rrLVasWMGrr76K2+2mpKSEa665hri4ODp16sTtt99Oly5duOOOOwAoLi7mqquuonv37kfVCTB+/Hjmz5/PoEG1PYgzZszg8ssv55///Cc33XRT8LqRI0cyfPhwoDa0TpgwgXffffe4769du3ZceOGFTJ48mUceeYSdO3cyffp03n777RP+bOuLjc3i/atxm05ax2Yxf+/XVPqrjnu9ZVlUVFeS5I4LHmvkTuBgRTlNIlJoHpfKug3ruOt/JjD1xVcxTZNvvllGk4hG9GnUCYCmUWn8IWMAXy9ZypAhQwHo1KUr8zYs5sqsIZiGycJ9K2iUnEJsbO3rREREcO/9U3j+b0/z/vqFpKU05va77w2GZoCDFeUkueODjxPD4vBUVWDbtgLtr4BlWVRXV+vP8yTo1+9M0tMz+GLBZzicTv5y1sNkZmpBKBEREWkYfpF9aD0eD6ZpBntQj2X69Olce+21wdDhdDqZOHHifwx8r7/+OnfccUcw4CYkJHDjjTcyffp0ioqK+P777xkxYkTw+sTERGbNmkV8fPxR9/J6vezbty/Yg7pr1y7Kysq49tprmT17Nj6f75g1lJaWEhkZ+aN1Alx33XVs376dhQsXMmnSJCZNmkRsbOx/fF5D4TRMTovL4ct9q3jxu1nsrTpAouv49TscDjq06cicwi+wbRvLtpid/zkp4Qk8cNoNjG+Tx+1tR3Hw4EE2blwPQGFhPhZ197f1Wj7KSkuDjy8bMZLdkWX8+dsn+J8Nz/Ju8SLGjL+lTnCZ+8FsCnftpkdiO6pKPbz7z7cJBALB8107d2d2wQIsu3bV5vcLFtC5QxdMU1szh7oFn8/nuquu4I+/H8L4MTewadOG+i4p5OXktGTkVdeQd8UohVkRERFpUH62HtqlS5eSl5eHYRi4XC7uuusu5s2bxyOPPMKLL74YvK6srAyoDY8XXlh3/mJ0dDRVVVVYlnXcoFFSUkJiYmKdY5mZmRQUFJCfn09mZmbw+FNPPcXXX39NWVkZ119/PQkJCcE6Dxw4gGmaXHzxxfTq1QuAmTNncsEFFxATE0OnTp345JNPGDx4MACvvvoqc+fOxTRNYmNjue+++4KvM2rUqGC9VVVVREREALUBb8qUKeTl5TF06FB69uz5X3229cVvB1hZsgXTNPBbAfBX4bWOHfIPu+6mMTx0370s/HYlAduiqqaK0TkXBsNnTkwmMa5I9u3bQ9u27enatScfvjebWbvmc2ZqN773FDAnfxGJyclcOmwo4WHhDBr8O+578BF27dpJTU01OTmt6uwz+913m/n6y8VMaXcjkc5w/FaAeze9xLJli4Pb/1x17XU88sBkblr9KIZhkNSoEbfccOfP9+H9CNu2KSoqIiIinJiY0PmBoyHasmUT015+ifE5l5IVlc5XB9bx4OR7+dtzLxMVFVXf5YmIiIjISfaLDDk+bN68edxyyy1HzaEFSE1NJT8/n7Zt2wbPeTwewsLCfrTXLDo6mtLS0jo9rjt27KBx48akpaWRn58fPD5mzBgAHn30USorK0lISAjWWVJSwqhRo8jIyAAgEAjwwQcf0KRJE+bPn09ZWRmvv/56MND+cMjx//XDIdGH59Aelp2dTXZ2NkOHDj3ue2qoLGwinC7uaDuKplFpLN3/Lc9/N4uAbR33OY0apXDrHXfz0Ucf4HA4WL96LYVV+4Pny7weDvoq6Ny5GwCtWrUmO7sF87YtZl7hYoxDr5tjpnFnpxFU+Kt47t+zKNpfhAODuIQEkpKSSU5uFLzn5s2bOC2+FZHO2jnTTtNB95g2bN64MRho4+MTuP/hxygoyMe2bdLTm9TL0NSCgnz+OuUBig8U4wv46NHjdK678WZcLtcvXsuvwaIFn3NOcneyo2v/Pz49uQNflK1hxYqv6dt3QP0WJyIiIiInXYMZXzl8+HCmTp1KUVERULvQ0v3338+wYcN+9HmXX345kydPxuv1AnDgwAGeeeYZhg0bRlpaGhkZGbzxxhvB68vLy9mwYcNR4SUhIYFHHnmEO++8k3379rFgwQLat2/PtGnTePnll5k5cyYHDhxg48aNJ/mdh44w08WQ9L5kRadjGia9G51GVlT6jz5n9eqV3DZ+DBXfFFCybAe78ncwc/enTFj5BBNWPs4tq57kzDPPIS4uPvgcv99Px8SWjG09nN816YdlWwxO6U2sK4rGEclc1uRcvlr0JY23u/As28Wtf76ZgoIjP1xkZGSy2bOTgF07xNi2bTZW7SCj6dFDJdPTm9CkSUa9hFnbtnnsoQfoYbZiROZ5XJd9PiUbC3h31oxfvJZfC6fTic/21znms/w/Ot1BREREREJXg/lXXrt27Rg3bhzjxo0jEAjg9/sZOHAgV1999Y8+Ly8vj0AgwGWXXYbT6cQwDK6//nq6dOkCwJQpU3j66acZPnw4DoeDyspKhg4dyu9+9ztWrFhR5145OTnk5eUFA/JFF11U5/yFF17IG2+8UWdxoVOJQW04+CG/HTj2xYe88vxURmedT6eE1gDEGZF8sncZQ5r0Iyksjvf3LKKq8sjCUhs3rqeyuJx72o7AMAzaxbXgoNfDZ/u+Ia/5bw8VYhDnimZQ494AxDgieW/mP7l+zDgA2rfvSKNm6dy36RW6xeSyvnI7B8O99O3b/yR9EidHUdE+ior2MSewl1axTSnzeajwV1O8YAEXX3JpfZcXks48eyB3//tWmkem0yqmGV/uX01+TRFdunSr79JERERE5Gdg2LZt13cRcnw+X4DS0sr6LgOAiy8YQrjDzXUtLyAnOpOFRSt4b/fnVAVqeOedD4+63u/3M2zYH5l2+l8wjdrBAFPWv0av5A70S6n9waEm4OWmVY/y+DNTSUxMYsmSL/l02rvc0uLy4H0+3fMVH+9Zwt3t/kRFoIonNk2nT3InftukDwBrS7fybs0SJj/8aJ3XXrLkC7Zs3EhGs2b0738mbnc4DUlxcTE3XDuKW9uMoG1cNgB/3/YBq6q+47lXXqvn6kLX6tUrmf7aqxTuK6RVTi4j/3QNTZpk1HdZIscUHx/ZYP6OFzkWtVFp6NRGTw2NGsUc91yD6aGVhs80HPhsP2/v+Bcl3oM0cifULg51HE6nk4yUJqwu3ULnQz20+2tK6myXE2a6iAqLwOMpJzExifbtOzK17Em2lu+mRUwGHn8V/z7wNTEZydywYgrusHACfh/t4loAtcN2FxWvos3p7Y967b59BzToeZM1NdVEuMKDYRZgQEoX1uzaVo9Vhb7TTuvMaX/trC84ERERkVOAAq38ZD7bR5o7CY+/imrLS7XlxcTA6Tz+AkZXXnsdjz/yEN3K2mLZFgf8B5mzZxEtozMJc7hYsn8NuEwyMmrnt8bExHDDmLE8/MxTJLpj2V9ZwplnnsPIq68BwDAMvvhiAfc/+wztElpQVFOCGevmT+dfeNwaGqr4+Hj8BCiuKSPx0F692zz5NG2WVb+FiYiIiIiECA05buAa0pDjd955m1lvvU1KeAK5sVks3f8t1YEaXn97Vp1tc/6voqJ9LFnyJaZp0qPH6bzx6t9ZtWoF0WGRWC645X/uJDs7p85zampq2LVrB8nJjYiPTzjqnqWlJaxZs4r4+ATat+8YsvvHzvzndD6b+zEDk3pQFvDw2f7l3DlpMjk5Leu7tJCnHloJBWqn0tCpjUpDpzZ6avixIccKtA1cQwq0AIsWfc4TTzwC1PaWvvDCP47aB/inOHBgPx6Ph4yMzB8Nw6eCFSu+YdmXXxAVHc05555HenqT+i7pV0FfcBIK1E6loVMblYZObfTUoEAbwhpaoD1Mf3lIQ6c2KqFA7VQaOrVRaejURk8NPxZoQ3OcpoiIiIiIiJzyFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQpEArIiIiIiIiIUmBVkREREREREKSAq2IiIiIiIiEJAVaERERERERCUkKtCIiIiIiIhKSFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQpEArIiIiIiIiIUmBVkREREREREKSAq2IiIiIiIiEJAVaERERERERCUkKtCIiIiIiIhKSFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQpEArIiIiIiIiIUmBVkREREREREKSAq2IiIiIiIiEJAVaERERERERCUkKtCIiIiIiIhKSFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQpEArIiIiIiIiIUmBVkREREREREKSAq2IiIiIiIiEJAVaERERERERCUkKtCIiIiIiIhKSFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQ5KzvAiS0jB9/E9u3bws+HjNmAv37nxl8XFNTw+zZ7/DVV0tJSkrmggsuplWr3B+9p8/nY+nSL9m9exetWuXSuXNXNmxYx5IlX9CsWXMGDDgbl8sVvD4QCLB8+Vfs27eXtm07kJ3d4uS/URERERERafAM27bt+i5Cjs/nC1BaWlnfZQBw1VWXcfDgQUzTJCoqivLycizL4rXX3iY6OhqAe++9g61btxAIBDBNk0AgwF/+MoWcnJbB++zatZMZM6ZTUlJM//5n8fHHcykvLyMqKorS0jJM0+TgwTJSU1MpKyvDNB387W8vERkZSXV1NXfddStlZWVERUVy4MABzj13MJddNrJOrbZt89VXS1m+/Ctyc9vSv/9ZOByOX/LjknoWHx/ZYP7fETketVNp6NRGpaFTGz01NGoUc9xzCrQNXEMKtBdc8FuioqLo1q0bDoeDqqoqli1bhmVZvPPOh+Tn72bcuBtwOEzS09OpqKhg//79hIeH4/V6AUhPb0JBQT6GYeByuaipqSEqKppu3bpiGAaBQIAlS5aQm5tLcnIytm2zZs0a2rc/jTFjxvPBB+/x0Ucf0KZNGwzDwOv1snz5ch599GnS0hoDtWH21lvHsn37NqKioqisrCQ+PoFnnnmRsLCw+vwI5Rf0a/iCs22bXbt2UFVVRU5OK/0o8yv0a2in8uumNioNndroqeHHAq2GHMtP5nA4yMjICP6jOiIigoSEBA4cOADAhg1rsW2LHj1ODwbHJUuW4Ha76dixI7Zts2HDBpxOJ507d8ayLCorK9m4cSOWZVFSUkJNTQ2xsbFUV1djWRaGYZCSksL69WsB2LhxPfHx8ezYsYP8/HwCgQBudzgbN64jNTWNQCDA0qVfsmPH9/Ts2ZOIiAh8Ph9fffUVM2ZM57LLrqifD0/kBFVUeJg8+R4KCnYTFhaGZdnceee9NG+uIfYiIiIihynQyk9mWRYHDx6kSZMmQG3vkcfjCZ4vLS0jIiICy7IoKCjA5XJRXV1Nly5dcLvdALRt25avv/6ab775BpfLxeEBAl9//TVOp5PIyEj2799PSUkJW7duxbIsHA4HYWFu5s79gObNs5k7dy22bdOpUyecTidbtmxh5sy3ee21VygvP0hkZBRJSUlEREQA4HK5SE9P5+uvlynQSsh4443XqKz00L17dwzDoLCwkMcee4inn34BwzDquzwRERGRBuGUD7QPPfQQ69ato6ioiOrqajIzM0lISOCWW27h4YcfprS0FJ/PR25uLhMmTAjOFV26dCnPPvsstm3j8/k499xzGTlyJIZhkJeXx6RJk2jRom5PygsvvMDixYsxTRPDMBg3bhzt27evj7f9X7Ftm71792IYBvHx8eTn5+P3+4PnGzVKpaKigmXLlhEIBDAMA9u2Mc0ji2kf/u8zzjgDh8PBnj172LhxI1FRUbRv3x6Px8O+fftIT08nOjqa/Px8AJo3b857782ga9ceVFRUcNpppxEVFQVAWloaGzZsoFOnTkRFRbFhwwYqKiqwbTv4D/8fBm+RULB8+ddkZzcPtuG0tDS+/347xcUHSEpKrufqRERERBqGUz7QTpw4EYBZs2axbds2JkyYQHV1NRdddBGTJ0/mtNNOA+Ddd99l/PjxPP/882zZsoUpU6bw/PPPk5KSgt/vZ9KkSbz88stcffXVx3yd7777jvnz5zN9+nQMw2DDhg3cdtttvP/++7/Yez0ZIiMjcblc7N+/n6SkJMrLy4PnqqsrcTgcNGnShObNm+P1evnmm2/YvHkzrVu3xrZttmzZgmEYVFRU4PP5SE5Oxul0kpCQgGEYbN68mfT0dDIzMykrKyMnJ4e1a9fidrtp06YNCxbMrxNUAfbt20dWVhYxMbVj6+Pi4iguLmbDhg2kpKRQUlJCSUkJ0dHHH3svP83hHnX1EP78EhISqKysDP6I5vP5sG2LyMioeq5MREREpOE45QPtsXz++ed07949GGYBhg4dyvTp09m1axfTp0/n2muvJSUlBQCn08nEiRMZOnTocQNtYmIiBQUFzJw5k379+tGmTRtmzpz5i7yfk8U0axd7cjgcBAIB4uLiiI+Pp7i4GIBvv10NQIsWLTAMg4iICFq3bs2GDRvYt29f8B6BQIDVq1fjdDrxer3Yth0MxoFAgOrqapYtW1and7eyspKoqChs28ayLDZt2kSHDh1wOp2Ul5cHe2uhdq5vZGQkgUCADRs2EBVVOwQ5MjK6zvtZtmwJH300B9u2+c1vzqN3774n/TNbtmwJ//jHyxQV7SMnpyXXXnsTzZplnfTX+bkFAgGmT5/GRx/Nwev10r376YwefZN+JPgZXXzxZTz++BR8Ph8ul4uCggJ+85vBwaH0IiIiIgLmf77k1LNr1y6aNm161PGMjAwKCgqOeT46OpqqqiosyzrmPRMTE5k6dSorVqzgkksuYdCgQXz22Wc/S/0/F8uy2LZtG5s2baKkpITVq1dTWloaPN+iRTZwpBcPagOsaZq0aNGCli1b4nA4ME0z2NN7+Pq9e/eydu1aAoEAxcXFNGvWjN69e9OuXTsASktL2b17N02aZOByuXC73SxdupRFixZhmibbt2+nuLgYn89HdXU15eXlFBcXExcXR0VFBUVFRfzxjxcG6/rXv+YxdepT+P1eLMvPSy9N5YMP3j2pn9e2bVt55pm/kpaWSp8+fQCbe+75H2pqqk/q6/wS3n9/FgsXfkanTp3o3bs3+fk7efzxh+u7rF+1Ll26MXHiPcTFJQAmw4eP4IorrqrvskREREQaFPXQHkNqaipr1qw56vj27dtJT08nNTWV/Px82rZtGzzn8XgICwurM1/0h3bs2EF0dDQPPvggAN9++y3XXHMNPXv2JD4+/md5Hz8Hl8tFt27dcLlceDwevvnmm+C51NTaxaI2bdpEdnY2Xq+XzZs3EwgE2LZtG1A7VNXtduP3+4MLRRmGQbt27aiqqqKsrIzIyEiysrIASEpKomnTpuzYsYOUlFRuv30SEyaMoaysjLS0NBwOB3v37iUQCFBYuIf169cTHR2DaZr06tULl8tFIBDgq6++4v3336FPn34AzJgxnSZN0ikrKwMgPT2dmTPf5ne/++NJG0772WefkJaWRmJiIgBNmjShtLSUFSuW06vXGSflNX4pn3wyj6ysZsHewezsbBYvXkx5eXlwqLecfO3ataddu9CZZy8iIiLyS1MP7TGcffbZLF68uE6onTFjBomJiWRmZjJ8+HCmTp1KUVERUDu37f7772fYsGHHveemTZuYNGkSNTU1QO0iRzExMSG1r6TD4SAzMzPYsxodHU1cXFzw/HffbcbpdFJdXc2SJUtYtWoVsbGxxMbG0q9fP/r164dlWcTFxdGjRw86deoUHNbt9Xpp2rQpGRkZRwVK0zSJjo5h8uSHiYuLx7YtsrOzyc3NpWXLlpx22mmYpsnDDz/J9OnvYts2jRo1CtbpcDho3Lgxu3btCt6zrKyUbdu2ER4eTkREBFu3bsXjKedkbst8rHvVvrfQ2/q5svLo/d1qF/6qh2JERERERA5RD+0xREVF8dxzz/HAAw9QWlpKIBCgdevW/PWvfwWgXbt2jBs3jnHjxhEIBPD7/QwcOLDO/Nmbb745uBdrz549ue2229i6dSsXXXQRkZGR2LbNrbfeGlK9W5ZlUVFREXxs2zZVVVXBx4GAn0AgEAyYUDt8u6SkJPjY6XSSnp4eDK3x8fG4XC6cztqm2KRJE77//nsKCgpo3LgxHo+H7du3ExbmZvToqwA7OH/3sJiYGAzDoKSkmOjoaGJiYigq2ldn8ajS0lJcriPN3eFw0LZt22DvaVxcHKtXrz5uD/t/Y8CAc1iwYD5xcXHExcWxZ88ePJ4KOnfudtJe45diWRabN2+mbdu2uFwutm7dGpwPLSIiIiJSXxRoDzn//PPrPG7atCnPPffcca/v27cvffseexGhadOmHfP46NGjGT169H9fZAOwd+9ewsLCiI2NZc+ePXUCTVpaY2zbZt26dTRt2pTKykq2bdtGWFgYpaWl2LYdXADq8DBrn8+Hz+ejqKgIn8/H3r17gdoh2hs3bsTpdGIYBikpjcjKysKyLL79di1btmyhc+fOAMHAnJ5eO+R54MDzeO21l1i5ciWpqakcOHCAsrIy+vc/O1irz+cjNjY2+DgmJga/vzaQn6xe85yclowePYbXXnuZlStXkp2dw6RJ9xMeHn5S7v9LSkxMwufzsnLlSgKBAMnJyRiGGfzRRkRERESkPijQyglJS0ujpqaGnTt3EhcXh9vtxufzAbBnzx6cTieRkZFs3ryZsLAwMjIy2L17N4WFezBNk5iYWLZt24bX6yU8PJydO3dimg769h3A/v37adq0OcuXf0Xnzp2xLAufz8fSpUvJysoKLjCVk9OCFStWsHLlSlwuFwcOHODaa28MBtG+fQfwxhuvYlkWu3fvxuFw4HA4+OMfLwi+D4fDQUFBQXBxr8LCQhwOx0nfjqZ377707t33qK2GQs3QoRfx97+/SG5uLk6nk127dtO3b38iIiLruzQREREROYUp0MpPZts2hYWFdOjQgdjYWAoLC+vMrezUqTMff/wh2dnZtGjRAoCCggKioqJ55pkXAViy5AueffYpKisrqaioICIigqysxlx66RVA7Z6yixZ9Tk1NDW63G9M0g1v1HB4O7PP5SEtrzKBBv6OqqpIBA84mKSk5WEdMTAz33vsgzz//DNu3f09aWmPGjBlPkyYZwWs6duzMmjUrKSoqwjAMPB4PubltT+qQ4x8K5TAL0L//WTidTmbPfoeqqmrOOefcOqtGi4iIiIjUB8M+mavgyEnn8wUoLT16QZ76cMEFv8UwDFwuV3BvTL/fz+DBf+DKK6/Gtm1GjbqU6OhomjVrRmVlJevWrePGG8fRt++A4H0+/fRfzJr1TzweD9279+TKK/9EVNSRPWJnznyL996bSXJyMh6PB9u2cbvdNG3aFJ/Px7Zt28jLG8VZZw38r9+Lx1POo48+wIYN6wGDnJyW3HbbncTGxv3H50poiI+PbDD/74gcj9qpNHRqo9LQqY2eGho1Ov66Qwq0DVxDCrRQG2pN08QwDCzLwrZt3nnnw+D5srIynn76MdavX0tkZBRXXHE1ffv2P+HXyc/fzfr1a0lNTaN16zbMmDGdL75YQHh4OL///fn/rzD7Q6WlJdi2TUJC4km5nzQc+oKTUKB2Kg2d2qg0dGqjpwYF2hDW0AIt1K54GxHhoKZGTUcaLn3BSShQO5WGTm1UGjq10VPDjwVa7UMrJ8w0TSIiIuq7DBEREREROcUp0IqIiIiIiEhIUqAVERERERGRkKRAKyIiIiIiIiFJgVZERERERERCkgKtiIiIiIiIhCQFWhEREREREQlJCrQiIiIiIiISkhRoRUREREREJCQp0IqIiIiIiEhIUqAVERERERGRkKRAKyIiIiIiIiFJgVZERERERERCkgKtiIiIiIiIhCQFWhEREREREQlJCrQiIiIiIiISkhRoRUREREREJCQp0IqIiIiIiEhIMmzbtuu7CBEREREREZETpR5aERERERERCUkKtCIiIiIiIhKSFGhFREREREQkJCnQioiIiIiISEhSoBUREREREZGQpEArIiIiIiIiIclZ3wVIaLEsi0mTJrFp0ybCwsKYPHkyzZo1q++y5BTn8/m4/fbbyc/Px+v1Mnr0aHJycpg4cSKGYdCyZUvuueceTFO/4Un9OnDgAOeffz6vvPIKTqdTbVQalOeff5758+fj8/kYPnw4PXr0UBuVBsXn8zFx4kTy8/MxTZP77rtPf5eKemjlxPz73//G6/Xy9ttvM378eB566KH6LkmE999/n/j4eN58801efPFF7rvvPh588EHGjh3Lm2++iW3bfPrpp/VdppzifD4fd999N+Hh4QBqo9KgLFu2jJUrVzJ9+nSmTZvGnj171EalwVmwYAF+v5+33nqLG264gSeeeELtVBRo5cQsX76cvn37AtCpUyfWrl1bzxWJwKBBg7j55puDjx0OB+vWraNHjx4A9OvXj8WLF9dXeSIATJkyhWHDhpGSkgKgNioNyhdffEGrVq244YYbuO666xgwYIDaqDQ4zZs3JxAIYFkWHo8Hp9OpdioKtHJiPB4P0dHRwccOhwO/31+PFYlAVFQU0dHReDwexowZw9ixY7FtG8MwgufLy8vruUo5lc2aNYvExMTgD4KA2qg0KCUlJaxdu5Ynn3ySe++9lwkTJqiNSoMTGRlJfn4+5513HnfddRd5eXlqp6I5tHJioqOjqaioCD62LAunU81I6l9hYSE33HADl156KUOGDOGRRx4JnquoqCA2NrYeq5NT3TvvvINhGCxZsoQNGzZw2223UVxcHDyvNir1LT4+nuzsbMLCwsjOzsbtdrNnz57gebVRaQheffVV+vTpw/jx4yksLOSKK67A5/MFz6udnprUQysnpEuXLixcuBCAVatW0apVq3quSAT279/PqFGjuOWWW7jwwgsBaNu2LcuWLQNg4cKFdOvWrT5LlFPcG2+8weuvv860adNo06YNU6ZMoV+/fmqj0mB07dqVRYsWYds2e/fupaqqil69eqmNSoMSGxtLTEwMAHFxcfj9fn3fC4Zt23Z9FyGh4/Aqx5s3b8a2bR544AFatGhR32XJKW7y5MnMmzeP7Ozs4LE77riDyZMn4/P5yM7OZvLkyTgcjnqsUqRWXl4ekyZNwjRN7rrrLrVRaTAefvhhli1bhm3bjBs3joyMDLVRaVAqKiq4/fbbKSoqwufzMWLECNq3b692eopToBUREREREZGQpCHHIiIiIiIiEpIUaEVERERERCQkKdCKiIiIiIhISFKgFRERERERkZCkQCsiIiIiIiIhyVnfBYiIiMgvb9myZYwdO5acnBwAampqGDJkCHl5ecFrFi5cSGFhIZdcckl9lSkiIvKjFGhFREROUaeffjqPP/44AF6vl0GDBvGHP/yB2NhYAPr161ef5YmIiPxHCrQiIiKCx+PBNE1GjhxJRkYGBw8e5Le//S07duxgwoQJPPvss/z73/8mEAgwfPhwhg0bxrRp05gzZw6GYTB48GBGjBhR329DREROMQq0IiIip6ilS5eSl5eHYRi4XC7uuusuXnrpJYYMGcLAgQOZNWsWAOvXr2fhwoXMmDEDr9fLY489xpYtW5g7dy5vvvkmhmEwcuRI+vTpQ3Z2dj2/KxEROZUo0IqIiJyifjjk+LCXXnqJ5s2b1zn2/fff07FjRxwOBxEREdx5553MnTuXgoICRo4cCUBZWRk7d+5UoBURkV+UVjkWERGROgzDqPM4Ozub9evXY1kWPp+PK6+8kuzsbHJycvjHP/7BtGnTOP/882nVqlU9VSwiIqcq9dCKiIjIj2rTpg19+/Zl+PDhWJbF8OHDyc3NpVevXgwfPhyv10vHjh1JTU2t71JFROQUY9i2bdd3ESIiIiIiIiInSkOORUREREREJCQp0IqIiIiIiEhIUqAVERERERGRkKRAKyIiIiIiIiFJgVZERERERERCkgKtiIiIiIiIhCQFWhEREREREQlJCrQiIiIiIiISkv4XykPUM+EVijUAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select apps priced below $100\n",
    "apps_under_100 = popular_app_cats[popular_app_cats['Price'] < 100]\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Examine price vs category with the authentic apps (apps_under_100)\n",
    "ax = sns.stripplot(x = \"Price\", y = \"Category\", data = apps_under_100, jitter = True, linewidth = 1)\n",
    "ax.set_title('App pricing trend across categories after filtering for junk apps')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "522776a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "linkText": "Export to plot.ly",
        "plotlyServerURL": "https://plot.ly",
        "showLink": false
       },
       "data": [
        {
         "name": "Paid",
         "type": "box",
         "y": [
          100000,
          100000,
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          10000,
          1000,
          50,
          100,
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          500000,
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of downloads of paid apps vs. free apps\"},\"yaxis\":{\"autorange\":true,\"title\":{\"text\":\"Log number of downloads\"},\"type\":\"log\"}},                        {\"responsive\": true}                    ).then(function(){\n",
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       "            observer.disconnect();\n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace0 = go.Box(\n",
    "    # Data for paid apps\n",
    "    y = apps[apps['Type'] == \"Paid\"]['Installs'],\n",
    "    name = 'Paid'\n",
    ")\n",
    "\n",
    "trace1 = go.Box(\n",
    "    # Data for free apps\n",
    "    y = apps[apps['Type'] == \"Free\"]['Installs'],\n",
    "    name = 'Free'\n",
    ")\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = \"Number of downloads of paid apps vs. free apps\",\n",
    "    yaxis = dict(title = \"Log number of downloads\",\n",
    "                type = 'log',\n",
    "                autorange = True)\n",
    ")\n",
    "\n",
    "# Add trace0 and trace1 to a list for plotting\n",
    "data = [trace0, trace1]\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "463f7939",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sentiment Polarity Distribution')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load user_reviews.csv\n",
    "reviews_df = pd.read_csv(\"datasets/user_reviews.csv\")\n",
    "\n",
    "# Join the two dataframes\n",
    "merged_df = pd.merge(apps, reviews_df, on = \"App\")\n",
    "\n",
    "# Drop NA values from Sentiment and Review columns\n",
    "merged_df = merged_df.dropna(subset = ['Sentiment', 'Review'])\n",
    "\n",
    "sns.set_style('ticks')\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(11, 8)\n",
    "\n",
    "# User review sentiment polarity for paid vs. free apps\n",
    "ax = sns.boxplot(x = 'Type', y = 'Sentiment_Polarity', data = merged_df)\n",
    "ax.set_title('Sentiment Polarity Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "099cfb1d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}