The Android App Market on Google Play.ipynb

{"cells":[{"metadata":{"dc":{"key":"4"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 1. Google Play Store apps and reviews\n<p>Mobile apps are everywhere. They are easy to create and can be lucrative. Because of these two factors, more and more apps are being developed. In this notebook, we will do a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. We'll look for insights in the data to devise strategies to drive growth and retention.</p>\n<p><img src=\"https://assets.datacamp.com/production/project_619/img/google_play_store.png\" alt=\"Google Play logo\"></p>\n<p>Let's take a look at the data, which consists of two files:</p>\n<ul>\n<li><code>apps.csv</code>: contains all the details of the applications on Google Play. There are 13 features that describe a given app.</li>\n<li><code>user_reviews.csv</code>: contains 100 reviews for each app, <a href=\"https://www.androidpolice.com/2019/01/21/google-play-stores-redesigned-ratings-and-reviews-section-lets-you-easily-filter-by-star-rating/\">most helpful first</a>. The text in each review has been pre-processed and attributed with three new features: Sentiment (Positive, Negative or Neutral), Sentiment Polarity and Sentiment Subjectivity.</li>\n</ul>"},{"metadata":{"dc":{"key":"4"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"# Read in dataset\nimport pandas as pd\napps_with_duplicates = pd.read_csv(\"datasets/apps.csv\")\n\n# Drop duplicates\napps = apps_with_duplicates.drop_duplicates()\n\n# Print the total number of apps\nprint('Total number of apps in the dataset = ', apps.count())\n\n# Have a look at a random sample of 5 rows\nn = 5\napps.sample(n)","execution_count":74,"outputs":[{"output_type":"stream","text":"Total number of apps in the dataset =  Unnamed: 0        9659\nApp               9659\nCategory          9659\nRating            8196\nReviews           9659\nSize              8432\nInstalls          9659\nType              9658\nPrice             9659\nContent Rating    9659\nGenres            9659\nLast Updated      9659\nCurrent Ver       9651\nAndroid Ver       9657\ndtype: int64\n","name":"stdout"},{"output_type":"execute_result","execution_count":74,"data":{"text/plain":"      Unnamed: 0                            App           Category  Rating  \\\n2099        2672                        Jiji.ng           SHOPPING     4.4   \n74            74     Tickets SDA 2019 + Exam RF  AUTO_AND_VEHICLES     4.8   \n1374        1672  Block Puzzle Classic Legend !               GAME     4.2   \n1970        2500              Blue CareOnDemand            MEDICAL     4.4   \n9268       10440      Forgotten Hill: Puppeteer               GAME     4.5   \n\n      Reviews  Size    Installs  Type Price Content Rating           Genres  \\\n2099    25714   12M  1,000,000+  Free     0       Everyone         Shopping   \n74       7021   17M    500,000+  Free     0       Everyone  Auto & Vehicles   \n1374    17039  4.9M  5,000,000+  Free     0       Everyone           Puzzle   \n1970      163   40M     10,000+  Free     0       Everyone          Medical   \n9268     2917   22M    100,000+  Free     0           Teen        Adventure   \n\n          Last Updated    Current Ver   Android Ver  \n2099     July 24, 2018        3.8.2.2  4.0.3 and up  \n74       July 27, 2018           1.79    4.0 and up  \n1374    April 13, 2018            2.9  2.3.3 and up  \n1970     June 29, 2018  10.4.1.015_05  4.0.3 and up  \n9268  October 30, 2017            2.6    2.3 and up  ","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>Unnamed: 0</th>\n      <th>App</th>\n      <th>Category</th>\n      <th>Rating</th>\n      <th>Reviews</th>\n      <th>Size</th>\n      <th>Installs</th>\n      <th>Type</th>\n      <th>Price</th>\n      <th>Content Rating</th>\n      <th>Genres</th>\n      <th>Last Updated</th>\n      <th>Current Ver</th>\n      <th>Android Ver</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2099</th>\n      <td>2672</td>\n      <td>Jiji.ng</td>\n      <td>SHOPPING</td>\n      <td>4.4</td>\n      <td>25714</td>\n      <td>12M</td>\n      <td>1,000,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Shopping</td>\n      <td>July 24, 2018</td>\n      <td>3.8.2.2</td>\n      <td>4.0.3 and up</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>74</td>\n      <td>Tickets SDA 2019 + Exam RF</td>\n      <td>AUTO_AND_VEHICLES</td>\n      <td>4.8</td>\n      <td>7021</td>\n      <td>17M</td>\n      <td>500,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Auto &amp; Vehicles</td>\n      <td>July 27, 2018</td>\n      <td>1.79</td>\n      <td>4.0 and up</td>\n    </tr>\n    <tr>\n      <th>1374</th>\n      <td>1672</td>\n      <td>Block Puzzle Classic Legend !</td>\n      <td>GAME</td>\n      <td>4.2</td>\n      <td>17039</td>\n      <td>4.9M</td>\n      <td>5,000,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Puzzle</td>\n      <td>April 13, 2018</td>\n      <td>2.9</td>\n      <td>2.3.3 and up</td>\n    </tr>\n    <tr>\n      <th>1970</th>\n      <td>2500</td>\n      <td>Blue CareOnDemand</td>\n      <td>MEDICAL</td>\n      <td>4.4</td>\n      <td>163</td>\n      <td>40M</td>\n      <td>10,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Medical</td>\n      <td>June 29, 2018</td>\n      <td>10.4.1.015_05</td>\n      <td>4.0.3 and up</td>\n    </tr>\n    <tr>\n      <th>9268</th>\n      <td>10440</td>\n      <td>Forgotten Hill: Puppeteer</td>\n      <td>GAME</td>\n      <td>4.5</td>\n      <td>2917</td>\n      <td>22M</td>\n      <td>100,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Teen</td>\n      <td>Adventure</td>\n      <td>October 30, 2017</td>\n      <td>2.6</td>\n      <td>2.3 and up</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"metadata":{"dc":{"key":"11"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 2. Data cleaning\n<p>The three features that we will be working with most frequently henceforth are <code>Installs</code>, <code>Size</code>, and <code>Price</code>. A careful glance of the dataset reveals that some of these columns mandate data cleaning in order to be consumed by code we'll write later. Specifically, the presence of special characters (<code>, $ +</code>) and letters (<code>M k</code>) in the <code>Installs</code>, <code>Size</code>, and <code>Price</code> columns make their conversion to a numerical data type difficult. Let's clean by removing these and converting each column to a numeric type.</p>"},{"metadata":{"dc":{"key":"11"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"# List of characters to remove\nchars_to_remove = [\"+\", \",\", \"M\", \"$\"]\n# List of column names to clean\ncols_to_clean = ['Installs', 'Size', 'Price']\n\n# Loop for each column\nfor col in cols_to_clean:\n    # Replace each character with an empty string\n    for char in chars_to_remove:\n        apps[col] = apps[col].str.replace(char, '')\n    # Convert col to numeric\n    apps[col] = pd.to_numeric(apps[col]) ","execution_count":76,"outputs":[]},{"metadata":{"dc":{"key":"18"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 3. Exploring app categories\n<p>With more than 1 billion active users in 190 countries around the world, Google Play continues to be an important distribution platform to build a global audience. For businesses to get their apps in front of users, it's important to make them more quickly and easily discoverable on Google Play. To improve the overall search experience, Google has introduced the concept of grouping apps into categories.</p>\n<p>This brings us to the following questions:</p>\n<ul>\n<li>Which category has the highest share of (active) apps in the market? </li>\n<li>Is any specific category dominating the market?</li>\n<li>Which categories have the fewest number of apps?</li>\n</ul>\n<p>We will see that there are <code>33</code> unique app categories present in our dataset. <em>Family</em> and <em>Game</em> apps have the highest market prevalence. Interestingly, <em>Tools</em>, <em>Business</em> and <em>Medical</em> apps are also at the top.</p>"},{"metadata":{"dc":{"key":"18"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"import plotly\nplotly.offline.init_notebook_mode(connected=True)\nimport plotly.graph_objs as go\n\n# Print the total number of unique categories\nnum_categories = len(apps['Category'].unique())\nprint('Number of categories = ', num_categories)\n\n# Count the number of apps in each 'Category' and sort them in descending order\nnum_apps_in_category = apps['Category'].value_counts().sort_values(ascending = False)\n\ndata = [go.Bar(\n        x = num_apps_in_category.index, # index = category name\n        y = num_apps_in_category.values, # value = count\n)]\n\nplotly.offline.iplot(data)","execution_count":78,"outputs":[{"output_type":"display_data","data":{"text/html":"<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>","text/vnd.plotly.v1+html":"<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"},"metadata":{}},{"output_type":"stream","text":"Number of categories =  33\n","name":"stdout"},{"output_type":"display_data","data":{"application/vnd.plotly.v1+json":{"data":[{"x":["FAMILY","GAME","TOOLS","BUSINESS","MEDICAL","PERSONALIZATION","PRODUCTIVITY","LIFESTYLE","FINANCE","SPORTS","COMMUNICATION","HEALTH_AND_FITNESS","PHOTOGRAPHY","NEWS_AND_MAGAZINES","SOCIAL","BOOKS_AND_REFERENCE","TRAVEL_AND_LOCAL","SHOPPING","DATING","VIDEO_PLAYERS","MAPS_AND_NAVIGATION","EDUCATION","FOOD_AND_DRINK","ENTERTAINMENT","AUTO_AND_VEHICLES","LIBRARIES_AND_DEMO","WEATHER","HOUSE_AND_HOME","EVENTS","ART_AND_DESIGN","PARENTING","COMICS","BEAUTY"],"y":[1832,959,827,420,395,376,374,369,345,325,315,288,281,254,239,222,219,202,171,163,131,119,112,102,85,84,79,74,64,64,60,56,53],"type":"bar","uid":"a91182b4-97d5-4d4e-8be1-879c9cedafe2"}],"layout":{},"config":{"showLink":true,"linkText":"Export to plot.ly","plotlyServerURL":"https://plot.ly"}},"text/html":"<div id=\"385c53d9-3e68-490e-8ccf-335051812e49\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"385c53d9-3e68-490e-8ccf-335051812e49\", [{\"x\": [\"FAMILY\", \"GAME\", \"TOOLS\", \"BUSINESS\", \"MEDICAL\", \"PERSONALIZATION\", \"PRODUCTIVITY\", \"LIFESTYLE\", \"FINANCE\", \"SPORTS\", \"COMMUNICATION\", \"HEALTH_AND_FITNESS\", \"PHOTOGRAPHY\", \"NEWS_AND_MAGAZINES\", \"SOCIAL\", \"BOOKS_AND_REFERENCE\", \"TRAVEL_AND_LOCAL\", \"SHOPPING\", \"DATING\", \"VIDEO_PLAYERS\", \"MAPS_AND_NAVIGATION\", \"EDUCATION\", \"FOOD_AND_DRINK\", \"ENTERTAINMENT\", \"AUTO_AND_VEHICLES\", \"LIBRARIES_AND_DEMO\", \"WEATHER\", \"HOUSE_AND_HOME\", \"EVENTS\", \"ART_AND_DESIGN\", \"PARENTING\", \"COMICS\", \"BEAUTY\"], \"y\": [1832, 959, 827, 420, 395, 376, 374, 369, 345, 325, 315, 288, 281, 254, 239, 222, 219, 202, 171, 163, 131, 119, 112, 102, 85, 84, 79, 74, 64, 64, 60, 56, 53], \"type\": \"bar\", \"uid\": \"ec77baf8-f8b7-450a-a63b-bafb6f0f5c8d\"}], {}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"385c53d9-3e68-490e-8ccf-335051812e49\"));});</script>","text/vnd.plotly.v1+html":"<div id=\"385c53d9-3e68-490e-8ccf-335051812e49\" style=\"height: 525px; width: 100%;\" class=\"plotly-graph-div\"></div><script type=\"text/javascript\">require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {};window.PLOTLYENV.BASE_URL=\"https://plot.ly\";Plotly.newPlot(\"385c53d9-3e68-490e-8ccf-335051812e49\", [{\"x\": [\"FAMILY\", \"GAME\", \"TOOLS\", \"BUSINESS\", \"MEDICAL\", \"PERSONALIZATION\", \"PRODUCTIVITY\", \"LIFESTYLE\", \"FINANCE\", \"SPORTS\", \"COMMUNICATION\", \"HEALTH_AND_FITNESS\", \"PHOTOGRAPHY\", \"NEWS_AND_MAGAZINES\", \"SOCIAL\", \"BOOKS_AND_REFERENCE\", \"TRAVEL_AND_LOCAL\", \"SHOPPING\", \"DATING\", \"VIDEO_PLAYERS\", \"MAPS_AND_NAVIGATION\", \"EDUCATION\", \"FOOD_AND_DRINK\", \"ENTERTAINMENT\", \"AUTO_AND_VEHICLES\", \"LIBRARIES_AND_DEMO\", \"WEATHER\", \"HOUSE_AND_HOME\", \"EVENTS\", \"ART_AND_DESIGN\", \"PARENTING\", \"COMICS\", \"BEAUTY\"], \"y\": [1832, 959, 827, 420, 395, 376, 374, 369, 345, 325, 315, 288, 281, 254, 239, 222, 219, 202, 171, 163, 131, 119, 112, 102, 85, 84, 79, 74, 64, 64, 60, 56, 53], \"type\": \"bar\", \"uid\": \"ec77baf8-f8b7-450a-a63b-bafb6f0f5c8d\"}], {}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"385c53d9-3e68-490e-8ccf-335051812e49\"));});</script>"},"metadata":{}}]},{"metadata":{"dc":{"key":"25"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 4. Distribution of app ratings\n<p>After having witnessed the market share for each category of apps, let's see how all these apps perform on an average. App ratings (on a scale of 1 to 5) impact the discoverability, conversion of apps as well as the company's overall brand image. Ratings are a key performance indicator of an app.</p>\n<p>From our research, we found that the average volume of ratings across all app categories is <code>4.17</code>. The histogram plot is skewed to the right indicating that the majority of the apps are highly rated with only a few exceptions in the low-rated apps.</p>"},{"metadata":{"dc":{"key":"25"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"# Average rating of apps\navg_app_rating = apps.Rating.mean()\nprint('Average app rating = ', avg_app_rating)\n\n# Distribution of apps according to their ratings\ndata = [go.Histogram(\n        x = apps['Rating']\n)]\n\n# Vertical dashed line to indicate the average app rating\nlayout = {'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\nplotly.offline.iplot({'data': data, 'layout': layout})","execution_count":80,"outputs":[{"output_type":"stream","text":"Average app rating =  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\"7df111ad-4cee-4913-a08b-34c5b0a9f8b1\"}], {\"shapes\": [{\"line\": {\"dash\": \"dashdot\"}, \"type\": \"line\", \"x0\": 4.173243045387994, \"x1\": 4.173243045387994, \"y0\": 0, \"y1\": 1000}]}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"824dc8d8-092f-404a-99bc-e139073aff22\"));});</script>"},"metadata":{}}]},{"metadata":{"dc":{"key":"32"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 5. Size and price of an app\n<p>Let's now examine 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>"},{"metadata":{"dc":{"key":"32"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"%matplotlib inline\nimport seaborn as sns\nsns.set_style(\"darkgrid\")\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\n# Plot size vs. rating\nplt1 = sns.jointplot(x = apps['Size'], y = apps['Rating'], kind = 'hex')\n\n# Subset out apps whose type is 'Paid'\npaid_apps = apps[apps['Type'] == 'Paid']\n\n# Plot price vs. rating\nplt2 = sns.jointplot(x = paid_apps['Price'], y = paid_apps['Rating'])","execution_count":82,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x432 with 3 Axes>","image/png":"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size 432x432 with 3 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\n"},"metadata":{}}]},{"metadata":{"dc":{"key":"39"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 6. Relation between app category and app price\n<p>So now comes the hard part. 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>"},{"metadata":{"dc":{"key":"39"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nfig, ax = plt.subplots()\nfig.set_size_inches(15, 8)\n\n# Select a few popular app categories\npopular_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\nax = sns.stripplot(x = popular_app_cats['Category'], y = popular_app_cats['Price'], jitter=True, linewidth=1)\nax.set_title('App pricing trend across categories')\n\n# Apps whose Price is greater than 200\napps_above_200 = popular_app_cats[['Category', 'App', 'Price']][popular_app_cats['Price'] > 200]\napps_above_200","execution_count":84,"outputs":[{"output_type":"execute_result","execution_count":84,"data":{"text/plain":"       Category                                App   Price\n3327     FAMILY             most expensive app (H)  399.99\n3465  LIFESTYLE                         💎 I'm rich  399.99\n3469  LIFESTYLE           I'm Rich - Trump Edition  400.00\n4396  LIFESTYLE                          I am rich  399.99\n4398     FAMILY                     I am Rich Plus  399.99\n4399  LIFESTYLE                      I am rich VIP  299.99\n4400    FINANCE                  I Am Rich Premium  399.99\n4401  LIFESTYLE                I am extremely Rich  379.99\n4402    FINANCE                         I am Rich!  399.99\n4403    FINANCE                 I am rich(premium)  399.99\n4406     FAMILY                      I Am Rich Pro  399.99\n4408    FINANCE     I am rich (Most expensive app)  399.99\n4410     FAMILY                          I Am Rich  389.99\n4413    FINANCE                          I am Rich  399.99\n4417    FINANCE                 I AM RICH PRO PLUS  399.99\n8763    FINANCE                        Eu Sou Rico  394.99\n8780  LIFESTYLE  I'm Rich/Eu sou Rico/أنا غني/我很有錢  399.99","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>"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x576 with 1 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3Llzc8ABB+TSSy9NXV1djjvuuJRKpWy99dY5+eSTU1NTk/PPPz933XVX6urqMnr06AwcOPBtj9vSUs78+UvaYmRYK8rlci768Q/z4P33pV9jJY/Or82OO+2WafdOztbdynlqUU36v3+7PDpzRjasaU65Wsq8ZfUZfuDn06ffVvnRuO9l806v5uVl9VlaqcnnDz8yQ/fdr72fFu/SlLv/kPMvOjelnqVU5ycbNmyYeXPnpmbjmlRermbvPT6RLx/+9dx2+2/zs5//JDUbl1KdW81HPjw4L7zwfObMfS7ZoJSaBTUZfcwp2W67Ae39lIC38fjjj+W0752S5cvKqVaTzvUNWVpdmKOPOT4f+tBHVvvYSqWSiy48P/dOvTvdu2yalxc9m899/ov51P8btpamB4C1p2fPhpVub5MrMFpaWjJmzJjW/1H4wQ9+kKOOOio77rhjxowZk0mTJqVXr16ZNm1axo8fnzlz5mTUqFGZMGFCW4wDhTJlyh/y/N/uybU7PJyOtdX8dX7nfGfyslz60ceyRZelWVou5aCpSzOy7/P5TO+5qVaTnz3xvkyYcEWqNfU5+0N/z/bdlmR5JTnpr33zi8suzo4f2yVNTRu291PjHWpubs4FF/0oc4fOTXmjcmrm1mTZLUuz4IAFqXapprS0lEk335Ztt94ul17+k8wd9nIqjZVkeTLtN1NTqa9kwf4LklJS90xdzvrR6fnZxVektra2vZ8asArVajXnnj0u3Wp6pdS5Jh/b7DOpKdXkxeZZOfecs/LT/7089fX1q3z8tGlT8/Cf/5p9+45KfU3HNG/4Sq781f9m8Ed3WOGKLQBYn7XJPTDOOOOMHHLIIdl4442TJDNmzMgOO+yQJNltt91yzz335P7778+QIUNSKpXSq1evlMvlzJs3ry3GgUKZ/sDU/L8ez6Rj7esXP728rEMGdmvOFl2WJklKpWRRS20+3Wtu68cHbD43yyvJRvWvZftur1+BVFeTDO89N411Lfnb32a0z5PhX/L3vz+abFRKeaNykqR+Tn2W9VuWapfXvyaqHatZ2HdBJk+5M9Ve1dfjRZLUJc3bNGd5h+VJ6fVNyzdfnqWV1/L883Pa46kA79Arr8zLggXz8+ryxdlqw8GpKb3+T7CNu/RLh1LnPPPM06t9/IMP/CW9N9g+9TWvLxnr0mHDbNqwVaZPf7jNZweAoljjV2BMnDgx3bt3z6677pqf/OQnSV7/X4dS6fV/bXfp0iWLFi3K4sWL09TU1Pq4N7Z37959tcevrS2lqWmDNT02rDW9tuiTJ55pTPJ6sOvRoSVPLumUcjWpLSV1pWo61VbyzJKO6df19agxa3GndKitZu6yurxarknn2td/oX1icacsq9amb9/evi/WIf37b5EsqCblJLVJpWslHf7RIammNUx0WdQl/T7UJzOefHiF7fVz61Mt/d/Kv9JrpVRfq2aLLTZNQ4OvASiqzp1rk1I1HWs3yIKlL2bjLv2SJC3l17Jk2cL07bvZan+Ob9Fnszz58F9aP65WK1nU8rKf/wC8p6zxgDFhwoSUSqVMnTo1f/vb33LssceucGVFc3NzGhsb07Vr1zQ3N6+wvaFh5etc3qxcrroHBuu03XbfN8fddH06pJIPNCzILS/2SrW+S4575IP5ZI/n8mhzY0q1HfL/Pbhljuj/fJaVS7nsyU3SuNEm6dunb775wGs5dPMX8+yrHXLV0xtni779sskmfXxfrEMaG3tk4HYfzl9uuz8Lt1qYDq90SN2CujRNbkrzFs3p/PwGaZzfmP/8z4Py0CMPZ9kdLVnUf2E6vtwpDc91TblcTuXhaiqdy+k2syl77T005XKtrwEouP32G55bb741f33xqbSUl2aDDk35x4L7ssuQj6emptNqv4d3GbJnJky4Lg+++Lts1GnzPNs8I009GtK37za+9wFY76zqHhhtdhPPJBkxYkROOeWUnHXWWTn88MNb74HxsY99LFtssUXOOuusXHbZZXn++efzX//1X7nxxhvf9phu4sn64KWXXswtN/06Lzz3ZD7woY9l9z32zh/uuj2PPHhfNu61RT417KDMmPFwfjPxiix9dUm2HzwkX/zSV7Ngwfz87GcX54nHpqdjfV122m2ffPbgEenQoUN7PyXepeXLl2fSpN/nvr/ck/f12CSf2OuT+dOf78v0Rx/KVv22yaf3OyDdujVl6dLX8rtbb879f/1TtujVN8OHfSYLFy7MjbdMzIJF87PHLntn1113b73KDSiuarWaqVOn5He/vSXz5s5LU7em7LnP3tl9971SU/P2q3rnzn05N910Q5556pkMGDggn/zkfu/qHUwAYF3RrgGjpqYmJ510UlpaWtK/f/+cdtppqa2tzXnnnZfJkyenUqnk+OOPz+DBg9/2mAIG71UPP/xgzj3zlAzpMT/lak2mzuuW40/6Qd7//m3bezQAAIA1pl0CRlsQMHgvqlar+e9RX8o3ek7LTj0WJUlunbNhrmvZNWPPuLCdpwMAAFhzVhUw2uRdSIA1q1wu55nnX86OGy1q3bZzjwV54qln23EqAACAtUfAgHVAbW1tNtu4e/487/9K5H1zG9N3817tOBUAAMDas8bfhQRY80qlUr74laPyvbPHZs+ec7O8WpPJL3fPsSd+q71HAwAAWCvcAwPWIS+88HymTp2Smpqa7LLLbtloox7tPRIAbeTBBx/InZMmpbauLp8YOjTbbvvB9h4JANYKN/EEAFhH3Pq7m3P1r67OVo0fS7Vazt8X3ptvjPpmdtxx5/YeDQDa3KoChiUkAAAFUqlUctWVv8rOmxyWpk7vS5I0duyZK6+4QsAA4D3NTTwBAApk+fLlaX51cRo7/t8ywaZOm+TluS+141QA0P4EDACAAunQoUP6brFlZi14sHXbE/Pvz4Dttm/HqQCg/bkHBgBAwTz11JP53iknpVNtYyqV5Ul9OaeOPT0bb/y+9h4NANqcm3gCAKxDWlpaMn36w6mrq8sHPzggtbW17T0SAKwVAgYAAABQeKsKGO6BAQAAABSegAEAAAAUnoABAAAAFJ6AAbCeWbp0acrlcnuPAQAAa1Rdew8AwJoxZ87snHP+DzPr77NS37E++w8/MAcdcGhKpVJ7jwYAAP82AQNgPVCpVHLK6aPzzObP5LUvvJqaxTWZ+Ptrs0nPTbPbbnu093gAAPBvs4QEYD3w5JNPZOHShXltwKtJTVJprOSV7V/JrXfe3N6jAQDAGiFgAKwHamvrknJ1hW2lcil1dfXtNBEAAKxZAgbAemCLLfrkfRttmoY/NaTUXErdnLo0PbRh/nPf/dt7NAAAWCNK1Wq1+va7FUdLSznz5y9p7zEACmfBgvm55Gfn58EHH0jXxoYcdtAXsvvH92rvsQAA4F3p2bNhpdsFDAAAAKAwVhUwLCEBAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACk/AAAAAAApPwAAAAAAKT8AAAAAACq+uLQ5aLpdz4oknZtasWSmVSjn11FOzfPnyfO1rX0vfvn2TJIceemg+9alP5fzzz89dd92Vurq6jB49OgMHDmyLkQAAAIB1WJsEjDvvvDNJcvXVV+e+++7Lueeemz333DOHH354Ro4c2brfjBkzMm3atIwfPz5z5szJqFGjMmHChLYYCQAAAFiHtUnA2HvvvbP77rsnSWbPnp3GxsZMnz49s2bNyqRJk9KnT5+MHj06999/f4YMGZJSqZRevXqlXC5n3rx56d69e1uMBQAAAKyj2iRgJEldXV2OPfbY3Hbbbfnxj3+cF154IQcddFAGDBiQiy66KBdccEEaGhrS1NTU+pguXbpk0aJFqw0YtbWlNDVt0FZjAwAAAAXUZgEjSc4444wcffTR+exnP5urr74673vf+5Ik++yzT8aOHZu99torzc3Nrfs3NzenoaFhtccsl6uZP39JW44NAAAAtJOePVfeBdrkXUiuv/76XHLJJUmSzp07p1Qq5Zvf/GYefvjhJMnUqVOz3XbbZdCgQZkyZUoqlUpmz56dSqVi+QgAAADwFqVqtVpd0wddsmRJjj/++Lz88stZvnx5vvKVr2TTTTfN2LFjU19fnx49emTs2LHp2rVrzjvvvEyePDmVSiXHH398Bg8evNpjt7SUXYEBAAAA66lVXYHRJgGjLQkYAAAAsP5aq0tIAAAAANYkAQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQNgHdfS0pIlS5a09xgAANCm6trioOVyOSeeeGJmzZqVUqmUU089NR07dsxxxx2XUqmUrbfeOieffHJqampy/vnn56677kpdXV1Gjx6dgQMHtsVIAOudcrmcn11+cSbd/vtUK9X023rLfPfbo9OjR8/2Hg0AANa4NgkYd955Z5Lk6quvzn333Zdzzz031Wo1Rx11VHbccceMGTMmkyZNSq9evTJt2rSMHz8+c+bMyahRozJhwoS2GAlgvXPjb67L7Q/emrmfmZtqh2qWPLwkp595cs4988L2Hg0AANa4NgkYe++9d3bfffckyezZs9PY2Jh77rknO+ywQ5Jkt912y913351+/fplyJAhKZVK6dWrV8rlcubNm5fu3bu3xVgA65Xb//C7zP/Q/FQ7V5MkSz60JHOumZ2XXnoxPXtu3M7TAQDAmtUmASNJ6urqcuyxx+a2227Lj3/849x9990plUpJki5dumTRokVZvHhxmpqaWh/zxvbVBYza2lKamjZoq7EB1hmdO3VKlr9pQyWpVqvZaKNGPycBAFjvtFnASJIzzjgjRx99dD772c9m6dKlrdubm5vT2NiYrl27prm5eYXtDQ0Nqz1muVzN/PluVgcwbOgBefaKZzOvfl4qnStpfKgxH9xu+9TUdPJzEgCAdVbPnivvAm3yLiTXX399LrnkkiRJ586dUyqVMmDAgNx3331JksmTJ2fw4MEZNGhQpkyZkkqlktmzZ6dSqVg+AvAOffzje+aIg/8r/R7sn163b5Z9+u+bY446ob3HAgCANlGqVqvVNX3QJUuW5Pjjj8/LL7+c5cuX5ytf+Uq23HLLnHTSSWlpaUn//v1z2mmnpba2Nuedd14mT56cSqWS448/PoMHD17tsVtayv5nEQAAANZTq7oCo00CRlsSMAAAAGD9tVaXkAAAAACsSQIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBjWq5q4AACAASURBVAAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHh1a/qALS0tGT16dJ577rksW7YsX//617Ppppvma1/7Wvr27ZskOfTQQ/OpT30q559/fu66667U1dVl9OjRGThw4JoeBwAAAFgPrPGAceONN6apqSlnnXVW5s+fn+HDh+fII4/M4YcfnpEjR7buN2PGjEybNi3jx4/PnDlzMmrUqEyYMGFNjwMAAACsB9Z4wNh3330zdOjQJEm1Wk1tbW2mT5+eWbNmZdKkSenTp09Gjx6d+++/P0OGDEmpVEqvXr1SLpczb968dO/efU2PBAAAAKzj1njA6NKlS5Jk8eLF+da3vpWjjjoqy5Yty0EHHZQBAwbkoosuygUXXJCGhoY0NTWt8LhFixa9bcCorS2lqWmDNT02AAAAUGBrPGAkyZw5c3LkkUfmsMMOy7Bhw7Jw4cI0NjYmSfbZZ5+MHTs2e+21V5qbm1sf09zcnIaGhrc9drlczfz5S9pibAAAAKCd9ey58jawxt+F5OWXX87IkSPz3e9+NwceeGCS5IgjjsjDDz+cJJk6dWq22267DBo0KFOmTEmlUsns2bNTqVQsHwEAAABWao1fgXHxxRdn4cKFufDCC3PhhRcmSY477rh8//vfT319fXr06JGxY8ema9euGTx4cA4++OBUKpWMGTNmTY8CAAAArCdK1Wq12t5DvBstLWVLSAAAAGA9tdaWkAAAAACsaQIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHgCBgAAAFB4AgYAAABQeAIGAAAAUHjvOGA8+eST+cMf/pDnn38+1Wq1LWcCAAAAWEHdO9npiiuuyG233ZYFCxZk+PDhefrppzNmzJi2ng0AAAAgyTu8AuPmm2/OZZddloaGhnzpS1/KQw891NZzAQAAALR6RwGjWq2mVCqlVColSTp06NCmQwEAAAC82TtaQrLffvvlc5/7XGbPnp2vfOUr2Xvvvdt6LgAAAIBWpeo7vCPn448/nr///e/p379/ttlmm7aea5VaWsqZP39Ju50fAAAAaDs9ezasdPs7ugLj2muvzaxZs3Lsscdm5MiR+c///M8MHz58pfu2tLRk9OjRee6557Js2bJ8/etfz1ZbbZXjjjsupVIpW2+9dU4++eTU1NTk/PPPz1133ZW6urqMHj06AwcO/NefIQAArMdeeunF/PLy/83f/jYjvXptls+NGJn3v3/b9h4LYK15R1dg7L///hk/fnzq6urS0tKSz3/+87nmmmtWuu+ECRMyc+bMnHDCCZk/f36GDx+ebbfdNocffnh23HHHjBkzJrvuumt69eqVM844I5dffnnmzJmTUaNGZcKECW87sCswAAB4r2lpacmRXx+ZHuUl2axjbeYtK+expclZZ5+fTTbZtL3HA1ijVnUFxju6iWdNTU3q6l6/WKO+vr71Zp4rs+++++bb3/52ktdv/llbW5sZM2Zkhx12SJLstttuueeee3L//fdnyJAhKZVK6dWrV8rlcubNm/eunhQAALwXPPDAn9OhvCzbdumQhrra9NmgQ3p3KOX2237X3qMBrDXvaAnJXnvtlcMOOywDBw7MjBkzsueee65y3y5duiRJFi9enG9961s56qijcsYZZ7RGjy5dumTRokVZvHhxmpqaVnjcokWL0r1799XOUltbSlPTBu9kbAAAWC/U1FTSoWbF/0Ssq1ZTLi/1b2PgPeMdBYxvfOMb2WOPPTJr1qzWJSGrM2fOnBx55JE57LDDMmzYsJx11lmtn2tubk5jY2O6du2a5ubmFbY3NKz8MpE3K5erlpAAAPCess02A/Liq8vyUk1tenasy+Ll5Tzdkhy2467+bQysd/6lJSTjx49Pkpx99tn57W9/m5kzZ+aWW27JOeecs8rHvPzyyxk5cmS++93v5sADD0ySfPCDH8x9992XJJk8eXIGDx6cQYMGZcqUKalUKpk9e3YqlcrbXn0BAADvRY2N3XL0MSdmZrlDbpu3NFMXlfPZw76QD3xgu/YeDWCtWe0VGJtsskmSpE+fPqmtrX1HB7z44ouzcOHCXHjhhbnwwguTJCeccEJOO+20nHPOOenfv3+GDh2a2traDB48OAcffHAqlUrGjBnzbz4VAABYf334w4Ny8U9/kfnzX0ljY7fU19e390gAa9U7eheSkSNH5tJLL10b87wt70ICAAAA669VLSF5R/fAaGxszO23355+/fqlpub1VSf9+vVbc9MBAAAArMbbBozFixfnmWeeyeWXX966rVQq5Re/+EWbDgYAAADwhtUGjCuuuCKXXnppamtr8+1vfzu77bbb2poLAAAAoNVq34XkN7/5TX73u9/lmmuuccUFAAAA0G5WGzA6dOiQDh06pHv37mlpaVlbMwEAAACsYLUB483ewZuVAAAAALSJ1b6N6s4775yddtop1Wo19957b3baaafWz5199tlrZcB/5m1UAQAAYP21qrdRXW3AmDZt2ioPuMMOO/z7U/0LBAwAAABYf/1LAaOIBAwAAABYf60qYLzje2AAAAAAtBcBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAovDYLGA899FBGjBiRJHnkkUey6667ZsSIERkxYkRuueWWJMn555+fAw88MIccckgefvjhthoFAAAAWMfVtcVBf/rTn+bGG29M586dkyQzZszI4YcfnpEjR7buM2PGjEybNi3jx4/PnDlzMmrUqEyYMKEtxgEAAADWcW0SMLbYYoucd955OeaYY5Ik06dPz6xZszJp0qT06dMno0ePzv33358hQ4akVCqlV69eKZfLmTdvXrp3777aY9fWltLUtEFbjA0AAAAUVJsEjKFDh+bZZ59t/XjgwIE56KCDMmDAgFx00UW54IIL0tDQkKamptZ9unTpkkWLFr1twCiXq5k/f0lbjA0AAAC0s549G1a6fa3cxHOfffbJgAEDWv/8yCOPpGvXrmlubm7dp7m5OQ0NKx8SAAAAeG9bKwHjiCOOaL1J59SpU7Pddttl0KBBmTJlSiqVSmbPnp1KpfK2V18AAAAA701tsoTkn51yyikZO3Zs6uvr06NHj4wdOzZdu3bN4MGDc/DBB6dSqWTMmDFrYxQAAABgHVSqVqvV9h7i3WhpKbsHBgAAAKyn2vUeGAAAAAD/DgEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAoPAEDAAAAKLw2CxgPPfRQRowYkSR56qmncuihh+awww7LySefnEqlkiQ5//zzc+CBB+aQQw7Jww8/3FajAAAAAOu4NgkYP/3pT3PiiSdm6dKlSZIf/OAHOeqoo3LllVemWq1m0qRJmTFjRqZNm5bx48fnnHPOyamnntoWowAAAADrgbq2OOgWW2yR8847L8ccc0ySZMaMGdlhhx2SJLvttlvuvvvu9OvXL0OGDEmpVEqvXr1SLpczb968dO/efbXHrq0tpalpg7YYGwAAACioNgkYQ4cOzbPPPtv6cbVaTalUSpJ06dIlixYtyuLFi9PU1NS6zxvb3y5glMvVzJ+/pC3GBgAAANpZz54NK92+Vm7iWVPzf6dpbm5OY2Njunbtmubm5hW2NzSsfEgAAADgvW2tBIwPfvCDue+++5IkkydPzuDBgzNo0KBMmTIllUols2fPTqVSedurLwAAAID3pjZZQvLPjj322Jx00kk555xz0r9//wwdOjS1tbUZPHhwDj744FQqlYwZM2ZtjAIAAACsg0rVarXa3kO8Gy0tZffAAAAAgPVUu94DAwAAAODfIWAAAAAAhSdgrMfK5XLWsRVCAAAAsFJr5SaerF1PPPGP/M8F5+XZpx5PQ9NGGfnFw7Pbrru391gAAADwLxMw1jOvvfZaxpx6Up7dZJc0f2x4Oiyekwt/ckk2ed8mef/7t23v8QAAAOBfYgnJeuYvf7k/SzfomeaNt09KNVnWsFle7vHhTLrzjvYeDQAAAP5lAsZ6pqamJqlWVthWSiU1tf6qAQAAWHf5rXY98+EPD0rnpa+kcc6fU1q+NJ1eeSIbvfRQ9tlzn/YeDQAAAP5lpeo69jYVLS3lzJ+/pL3HKLRnn306519ycZ74+9/SvecmOeILX8pHP7pje48FAAAAb6tnz4aVbhcwAAAAgMJYVcCwhAQAAAAoPAEDAAAAKDwBAwAAACg8AQMAAAAovLr2HgAAAN6rHn/873nyySfSt2+/bLXV+9t7HIBCEzAAAGAtq1arueC8s/PnaVPTo0NdXl62PB/5jx3zraO+m1Kp1N7jARSSJSQAALCWTZ/+cP7yp3uzW2N9Bm5Qk9261eevD0zLww8/2N6jARSWgAEAAGvZY4/NTM/aaupqXr/aoq5USs+aSh599G/tPBlAcQkYAACwlvXq1TsLqrWpVqtJXl9SsqBUl802693OkwEUl4ABAABr2Uc/umO6bbxJ/tRczj+al+bPzZV03Wjj7LDDTu09GkBhlapvZN91REtLOfPnL2nvMQAA4N+ybNmyTJ58Z/7+2MxsudX78/GP75mOHTvm6aefzF133p5KpZLd99g7ffv2b+9RAdaqnj0bVrpdwAAAgIK4//4/5Udn/yCbd6xJKdU8vbSab4z67+y00y7tPRrAWrOqgGEJCQAAFMTll16SgRvUZtsu9dmmS4d8pEttLr/skvYeC6AQBAwAACiIF156MRt1qG39uHuH2rw0d24qlUo7TgVQDAIGAAAUxJb9t8yzry1v/fi5V1vSb4s+qanxz3YAPwkBAKAgvvpf38oTy2ty/5JK7l9SyWMtNfmvI7/T3mMBFIKbeAIAQIG8+uqruf/+aalWq/mP/9ghG2ywQXuPBLBWeRcSAAAAoPC8CwkAAACwzhIwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwhMwAAAAgMITMAAAAIDCEzAAAACAwqtbmyfbf//907Vr1yRJ7969c/DBB+f0009PbW1thgwZkm9+85trcxwA/n/27jtAivL+4/h7Zna2l+uVgzvg6EgTEQVRUayxRI0xxsQSayy/qIktlmBvsfdYYo0NFEURsADSe+dod5TrdW/7Tvv9sXiEqNEkcHvg8+Ifd3Z27/O4beY7TxEEQRAEQRCE/USnFTASiQSWZfHaa691bDv11FN54oknKCkp4ZJLLmHdunUMGDCgsyIJgiAIgiAIgiAIgrCf6LQCxoYNG4jFYlx44YXous5VV11FMpmke/fuAIwZM4Z58+b9YAFDUSQyMtydEVkQBEEQBKFLsSyLRCKBw+FAkqR0xxEEQRCETtVpBQyn08lFF13EWWedRVVVFRdffDF+v7/jfo/Hw44dO37weQzDoq0tui+jCoIgCIIgdDlzv57Nyy+9SHuojfy8Qi674koGDhyU7liCIAiCsNfl5vq+c3unTeJZVlbGKaecgiRJlJWV4fP5aGtr67g/EonsUdAQBEEQBEEQUqqqKnnu2WcYnnkKZ/S9hZ7q4dx37520twfTHU0QBEEQOk2nFTDee+897rvvPgDq6+uJxWK43W62b9+OZVl8/fXXHHzwwZ0VRxAEQRAEYb8xZ/YseniHkOPujiRJFPv6ke8pY/HihemOJgiCIAidptOGkJx55pncdNNNnHPOOUiSxD333IMsy1x//fUYhsGYMWMYMmRIZ8URBEEQBEHYb9hUGxbGHttMS8dm69QF5QRBEAQhrSTLsqx0h/hPaJoh5sAQBEEQBOEnpba2hj9d/weG5pxArruUHe1r2RSeyzPP/g2XS0xuLgiCIBxYvm8ODFHAEARBEARB2A+sWbOKV19+meranfTu1YeLLr6Y7t1L0x1LEARBEPY6UcAQBEEQBEEQBEEQBKHLS/sqJIIgCIIgCIIgCIIgCP8tMfOTIAiCIAjCfmD9+rW89sor1NRWU17elwsu+h1FRcXpjiXsZV99OZNJ771FKBxm5MhD+e0FF+PxeNMdSxAEoUsQPTAEQRAEQRC6uNraGu65ayKZsX4cWXQhZl2AW2+5kXg8nu5owl60YMFc/v7iM5Qm2xnpgi1L5vLAfRPTHUsQBKHLEAUMQRCE/YBhGMybN4ennnuMD6e8TzgcSnckQRA60ZdfzqSHbwg9AgfhVgP0zTocny2HpUsXpTuasBd9/OH79HVI5DhseG0ygz02tm7ZTENDfbqjCYIgdAliCIkgCMJ+4OHH7mXZ5iUES4O4Kz1M+WQyjzzwFH5/IN3RBEHoBMlEEhl1j22KZCeZTKYpkbAvaFoSRZI6bkuAIkvidRYEQdhF9MAQBEHo4qqqKlm2eikNxzeQGJSg9YgWWrNb+PSzj9MdTRCETjJm7Di2hZfTGqvFsixqQhupj1Ry8MGHpDuasBcdOf44tiQtYoaJaVlsjuoEMrMpLu6W7miCIAhdguiBIQiC0MVVV+/EyrX2+MaO5kap3LE1faEEQehUvXuXc/5FF/LqKy8TT8TJCGRyw4234PP50x1N2IuOO+4kGuvr+eyzqRiGQVlpGTdfdxPSP/XKEARB+CmTLMuy0h3iP6FpBm1t0XTHEARB6DQNDQ1cde0lNJ3WiOW2wIScz3O4YMIlnHDCyemOJwhCJzIMg1gsisfjFSe1BzBN09A0Dbfbne4ogiAIaZGb6/vO7aIHhiAIQheXl5fHGaf/gkkfvoPezUBtsdEjt4zx4yekO5ogCJ1MURS83u8+qBMOHKqqoqrqt7Ynk0lef/VFZs/+Epti47gTTuaMM3+JLItR4YIg/DSIHhiCIAj7iZqaatatW0N+fgEDBw4WB6yCIAg/MU8+/jAbl86nn0vGtGBtzOKYU37OGWeek+5ogiAIe9X39cAQBQxBEARBEARB6OI0TeO8X5/JMdlO7LsK2EHNYJWu8sKLb6Q5nSAIwt4lhpAIQhdnGAbLly+lpqaafv3606dPv3RHEgRBEAShi7AsC8uykNg994ksgaHraUwlCILQuUQBQxC6gGQyyd23X0+yaSsDvW08+n4Wh4ydwPm/uzLd0QRBEIQuxrIsKiu3Egq1069ffxwOZ7ojCXuBZVls2lRBIpGgX78B35oDw263M3zYCNZXrKa/24ZpWWyImQw6aARr166hX7/+KIqSpvRCukUiYTZurCAnJ5eSku7pjiMI+4wYQiIIaRCLxYhEwmRn5yBJEjOmf8riyY/y8MC1yBKEdZlfLxnKrXc/TvfupemOKwiCIHQRsViUu+/8CzU7a3Hb/bTHm/jjDTcxePCQdEcT/gfBYBt33HYjodZmVFkmbkn8+bY76dWrfI/9IpEwTz3xV5YuW4IkSag2BZeiIEkSkt3J7RPvo7CwKE2tENJl7tzZPPfUE/TwF1MbaaDvgAH83/U3fOdEsIKwvxBzYAhCF2BZFm/8/XmmT/8EVbbw+TO46rpbmfHpZAZWv8HPuzV37DtxYz/6nnoDRx99bBoTC4IgCF3J66/9neWzN3BI/mlIkkx9eCvLWz/i+b+9gs0mOtburx5/9EGqVyxkgMeGJEnsiGnUOzN47MkXvnO5XE3TuPvOP2Ps2Ey5xw7A5ogGRaVMvPuhzo4vpFEkEubyiy/g1n4X0d1TgG7q3L/pNQ77+QSOP/6kdMcThP/a9xUwxBT2gtCJvvxyJmvnTuGNkSv58NBlnJ+9jAfuvoXiHuUsac/jm3JiwpBY3eamR4/StOYVBEEQupblS5fR0zcCSUodwuV7eyKjsnPnjjQnE/4Xq1Yuo4dT7ihWdHPaaGpuor09+J37q6rK+g3rKXXtvsJe5raxrmID+9m1SeF/VFGxgVJ/Md09BQDYZBtHZY9g1ZKlaU4mCPuGKGAIQidaOPszflVYRZZdR5Lg2II2MpQ43buXUqP24Pp1A3mlMp9LVg6l/5BR3+o6KgiCIPy05eTmEkw2dNxOGjFiiTCZmZlpTCX8r7Kys2nXzY7bMdNClmVcLvf3PibDHyCkGx23Q7pJwOf7zh4bwoErJyeX2mgjurl7MtedsXpy8vPSmEoQ9h3R11AQOpHb46OtZffVEtOCUBICgQzuuv8p5s6dTU31Dn7ZfxDDhx+cxqSCIAhCV3TW2b/gL7ffimYmcNn8VIYWM27cUQQCGemOJvwPzjn3fB556B7iRhKbBFWaxCmn/hy73f69j/nlub/l7y8+Q5mWRJKgMgm/+u0FnZha6Aq6d+9Beb9+PLD5dY7KGs6OeANftizjnp/9Nd3RhB9pw4Z1fP75dGRZZvz4CWIlwh8g5sAQhE60YcM6Hrr7Jv6v52ZKXAneqy1im2sIf7n3cXHFRBAEQfhRqqoqmfrRFIJtQUaPOYxx445GlkWn2v2JpmksWrSA+vpaBg4cTJ8+/Zg7dzYfTHoXy7I45bQzOOKIo2htbWH+/LlIEowePYbMzKw9nmflyuXMmPYxlmVxzHEnMWzYiDS1SEgnTdOYMWMaq5YsI7cgj5NOOY2CgsJ0xxJ+hFmzvuDFF5+lsDD1etXW1nL55VczevSYNCdLPzGJpyB0EStWLOPDd16muaWFocNHcfa5F+LxeNMdSxAEQRCEThCLxbjlpmtJtDXjw6Retyjt1YfNmyoodMgkUQhLChdcdDnPPv0o+fbU0qj1SYOb/zyR/v0HprkFgiDsLRdf/BvKykoJBAIAtLa2UlNTy9NPv5jWXF2BKGAIgiAIgiAIQppNmTKJzye9xXBPavnTmGEysyHMkbkefLZUsWJ9WKPWkOhntyjaNVFndUyjyZfLw48+k874giDsJaZpctZZP+PII4/s6EWn6zpz587lnXempDld+olVSARBEARBEAQhzTZuWEeObHYMHU2aFk5F7iheAOTbJWKxKAXO3dPVFThtbBerzQjCAUOWZcrL+1BbW9uxrba2lr59+6cxVdcnChiCIAiCIAiC0El6l/ejxZQ7lju1SxJx0yTyT6uQNGomTqeT+sTulSXq4zrdioo6Pa8gCPvOFVdcQ21tHWvWrGH16jU0NjZx6aVXpjtWlyaGkAiCIAiCIAhCJ4lGo9z0p2swwkF8lk69KVNUUsr2bVspVCWSkkLQkjn/wkt5/tknKLQrIEFd0uSGm25n0KCD0t0EQRD2omQyyapVK5AkiYMOGoqqqj/8oJ8AMQfGT4BpmixdupgVq1ZSVFDAkUeOx+PxpDuWIAiCIAj/orW1hakfT2HnjmoOGjKYY449/t8umbl06WJmffkldrud4088kd69+3RiWmFvaWxsYOrUD6nZuR1fIIvc3FwGDTqIgQMHs21bJUuWLMLr9TFmzBF4vT4aGhqYN28OkgSHHTaW3Ny8dDdBSAPLsli0aAHzZ8/G5XYz4cQTKSvrle5YgrBPiQLGT8BjTz7G3GWraAr0xZ9sJFtv5pEHH8HvD6Q7mrAXWJbFunVrWLt2Nbm5eRx22FgcDke6YwmCIAj/oU2bKrj91psp9gwg11PKttBKsrt5+cvEu79zSe0pH07mw/c/oJdvFAZJNgUX8n/XXsfw4QenIb3w32psbOCP111FgWLgkyxqDJlufQZw0y1/SXc0oYt77523mP3pDE7IHU1Yj/JJw3yuv+kWBg4cnO5ogrDPfF8Bw/adW4W00TSNVatWYFkWgwcP+dEnqDt37mDegvlUHfQ7LMVOCDAqpzH1k48555fn7tvQQqf4+4tPsfTr6RyVVceieBYfvf8Gd97/hFiCVRAOEHV1tWzZspmSkhK6dy9NdxxhHzEMxHCzcgAAIABJREFUg7vuvIMiT39GFp0CQHf/IKZXPUVFxXr69Ruwx/66rvPeu/9gXNEF+BzZAHjVbN56/XVRwNjPTP3oAwoUgwGeVPfwYsviq3Vr2Latih49StMbTuiyEok4Uz6YxH2Dfk+2IwOALHuA9958k4F335vmdILQ+UQBowupqanm5ttuJiZ7sGQZZ6KVibffRWlp2Q8+trp6B6a/EEvZ3f203VvC5qqqfZhY6Cw1NdXM/mo6b41cgddmYlk1/KUiyfRpUzn9jLPTHU8QhP+ApmnU1FSTk5PTUYD8x2svM+3jDym3TLbKMiMOPYzLrr6+Y1k14cCxaVMFpgZZvt2TMcqSjNeWTUND/bcKGPF4DE3X8NozO7ZlOPJZVdfYaZmFvaO2die+f/pIy5KE36HS0FDfUcCoq6tFlmXy8vLTE1LockKhEDbZRpZ9d4/qUk8hk3fMSWMqQUgfUcDoQp587hl2BgYTLDoEAG/9Sh576gkeefCvP/jYXr3Kkdt2IifDmHYvWBZZwY0MOXzcvo4tdIJt26oYmKnhtaVmKJckGB1oZPaWtWlOJgjCf2Lhwvk8+/jDuE2TdtPk5J+dziGHj2HG1A+5o7YWr2WRAO5fMI/lY5cwYsQh6Y4s7GWWZSErMpXBFZRlDEWRVSLJVhoiVQwYMOhb+3s8XvJyC9jWvobSQGryxq3BZQwcJLqO72+GjRjFRxvXU2xZyJJESDdojmn07duPlpZm7r37NurrajFNi+49Srnx5jvEMGCBrKxs3B43S1vXc3DWACzL4vPGJQw6aEi6owlCWogCRheyuWIt7cMu77gdzhvM9gWfYRgGiqL8m0dCTk4uZ/z8TN7/4O/EMnvjijVSnOVlwrHH7+vYQicoK+vJCy0qIU3BpxpYFswN5lF2sDiAFYT9RTAY5MlH7ufq+gbKdJ2gLPHwx5Npi4Q4KB7Hu2tKKgdwcGsba1etEAWMA1CfPv1wuR0YUZi6+XECjjwao9sYf+wEcnJyv7W/JElc/X9/4M6Jt7M9uhzdTGJzwv9deE8a0gv/i/HjJ7Bs8QK+qliH367SHNO46OIr8PsD3HnHzeiNtdgNjVbNpHLLJu69+3buvf/RH/38wWCQZcsW43Q6GT58pJgn6wAhyzJX/uE67r9nItOaFxLWosheO7edd3e6owlCWogCRheSkZ2HPVxHIqMUAHu4Dm8g60d3If7FmWczetRo1q5dTV5ePkOGDPvBwoewfygoKGT8hJO48AsYl93Ixlgm7Y4iLppwUrqjCYLwI61atZy+hkmZrgMQMC2OaGllS20NrU4nJvDNt/02n5eRhcVpyyrsfZqmMen9d5gzazYOhwvLYdBSE0K2w7m/Po9TTzsTy7L44INJTJk8iUQiQWZmFhdfdhlDhw7n+RdeYe3aVdjtDvr1G8DixQu4/557CEdCHDp6NGf/8lc4HM50N1P4N1RV5eZb76SqaiuNjQ306dOfQCCApmmsWL0SGRgacDLWpdKiGSzYsonNmzfRu3c5kJrv7I1XX2Tr1i2U9ezFr39zEd26lQCwcuVyHrz/TnKdKroFL0o27rrnIQoKCtPYYmFv6ddvAM++8Apr1qzG7XbTt29/McTwAGZZFtOnf8Inn3yMYeiMHz+BU075+Xee17W1tfL666+wevVK8vLy+dWvfkP//gPTkLrzKHfccccd6Q7xnzBNi3hcS3eMfSI3O4t1M97ENAwc4RoKq2fxu99eQFlZzx/9HIFAgN69+1BYWCS+2A4wBw09mPKBw2h29mTQ6OP47QWX43SKg1VB2F+0tDSzeN7XHB4K8c06E8u8XvIOH0trLMYyTUMzdKZnZLDZ7SHW2sKmzRspLumB1ysm693fPfv0kyyft44B/vEEpCJ2tFZw0cWXcO11N3TMe/HB5Pd59+23KXCVM6LgZNxk8d5nLzH4oIPIzc1j+/btTJ82jenTpzF92mf0dY+j2DmYtRuXs6ZiGWPGHpHmVgo/RkZGJsXF3Tp+wx984C6aaqvJtCsMCriQJAm3ImNaEDRh+IiRhEIh/nT9lbha6+ilmrQ11jF55gzGH3Mcqqpy+61/YqDdpLdLodgukUgm2LBzJ4ePOTK9jRX2GpvNRlFRMbm5ed+5WpFw4Pjoo8lMmvQuxcVF+P1+li5dTEtLC0OHDt9jP8MwuPHGP9DW1kpJSTcSiTgff/whI0YcQkZGRprS7z0ez3f3IhM9MLqQQw89nDuzc5g2YzqJRJzMAWOpqa1m48YN9OnTL93xhC6gT59+4r0gCPupgw4ayquZWbwVjTAqFGar3c5Cn4/7TziZs355LjNnfsbGVSuoqdxKj+YmRi1eyPZVK7np61nc/8jT5ObmpbsJwn8pFosyd+5sTux5DXbFBYAkyUye9B6hcDvRaIxDDx3Nhx9OwiY5OLjwZ0iSRIYzn5ge4rlnnmbIsGHM/nw2vX2H4jD9mPoWLCyyXEWMdJzG1NWP0tLSTFZWdppbK/wYra0tzJr1BbFYjBXLFtPbY6cpaXxrP3nXFde5c2eTKVv09qQma/epCuGIwdy5sxk16jCikQi5WbsP9oscNpZWbOicxgiCsFd99NEHlJf3xudLLSPat29fpk//hPPOu2CPXhjr1q0hFosydOhQALxeL4lEgmnTpnLppb9PS/bOIAoYXUx5eV/8/gDX33Ad7d4SojYfU6Z9xi9OP50zTj8z3fEEQRCE/5KiKNxx31957x+v8d7KFRR068Yd557fsdrASSedSnl5Xx697SauaGhEBoYnkuiyzGdTp/Dr83+X3gYI/zVNS/Uctcm7VwpLGHEaGuqZ98lKVMnFp1OnkkjG8Kt7Xl11KG6a64J8POUDjut1OT77rqVU7VmsbZxFsa8fsmTDpqjE4/HObZjwHwsGg3z++WdMeu8fFDoUFMvEtCzynTYqoxpbI0lKXCotSZ0dGlxy9AQgtRqNignsPnmxWSbRaBS73YEFhHQTv5q6vzmpU1T0w6vYCYLQ9cTjMVRV7bhts9nQdR3TNPcoYKT2s+/xWJvNRjQa7rSs6SAKGF3QW++8RX3mQFq7jQEglDeEd959heMnHN+x5J4gCIKw/wkEAlx06ZXfe39zczP5psk/DwAsiMepqqvd9+GEfcbvD9CjRxkbmr+mX/YYDFNndcMMBuUeTd/s0QCU+ocws+oFgvEGdrSvpZtvAHE9TEXzPPpmj2Z53TQ86u6lVAOOPKJaG5ZlsrltEf6Aj8LCou+LIHQBCxfO4/FHH0QxU0M9enpSh+FRTWdDKMkhmS7WhRKsbY+jyDLnnX8xJSXdATjkkNG8986bFNsNMlSFoGZQkzTp0aOUq6/8HQ5ZYm5LlDK3iiEp1Ghw629F0VMQ9keHHno4FRXr6N27N5IkUVVVxeDBQ/coagAMGjSEUChEU1MT2dnZJBIJ6urqOeOMc9KUvHOISRK6oC2VVUT9PTpuGw4/kitAfX1dGlMJgiAIe4uu6x1X5f/ZgAED2SxL1Oy6wpIE5mZmMvTQwzo5obC3XXv9n4h5a/loy8NMrXwEU9LJ9+ye48rvyEVCAQkWVn/I+xvu5dMtT1Lk60NZYBh+Rw6VbSuA1ARvm1oXYqDzwaYHqbXWcsNNf0aSpO99bwnppWkaTz35CIf4VCzLIM+5+xri0ICLpqTB181RWpIGNkVBURQmvf0al138G9avX0tGRia/u/gKlkYtZrYkWBQ2uOCiy/hw8ruUkOTITAejMl20Jg2aJJUHH35SDDntgizLIpGIY+1adeob4nMr/LMLL7yEgoIi5s+fz/z583G7vVx99bXf2s/lcnHjjbexc2c1CxcuZNmyZZxwwsmMGDEyDak7j2T96yeoi9M0g7a2aLpj7FNPP/cUH61tpKnH0QDYYs30WP8mL//tVVwuV5rTCYIgCP8tTdN46dknmDVnFqZlMnLYwVx2zXV79K6b9eVM/vbck5QgUWtZDB85iiv+8CexqtQBorW1BVVVee6Zp2nfqjAwZxwATdHtzN7+JhYmhqljV50MyDqCPtmHArC+6WvWN8/B78omloiQNKLIkoJuaFhY2GSVPn37sWnzBkzTZPiwkVx59TWi52YXEI1GeeiBu6hYu4rj8n0sbo0SUBX6eFNzVrQkdea1xDjt52cRCrWzdt4s+rpkVrbFaNNNzF1H6jZFpl//QVRsWIump+bLUCSJcTluvLbU94NlWXxUH+bttz8U3xldzJw5X/H6Ky/RFgpSnFfEJVdeRa9e5bz8wnN8NfuL1G/C8FFcduVV4nMrABAKtWMYBhkZmf92P9M0aW5uwu/3H1CrUeXm+r5zuyhgdEGtrS1cf8N1BBU/CdWPu7mCi86/iFGHHMrLr77M8hXLyczK5re/+hXDhh2c7riCIAjCj/T3F5+l6pOP+G1jEzbg3cwMzFGjue7mO/bYLxwOsWXLZvLy8sWwgANUXV0tt9z0J/y2fNBt1IQqyHZ349Din6PIKsvrplEdXk+3QB+QZOojmznr7HN45623GJR9DN39g9nevpqV9dM5qfc1LKiejG4mGN3tTBTJxqqmGWSW2bnxplvS3dSfvEcevpeqVUuoi8QZn+tFtyzmNkcJqDKqJFGf0OnrdbBNl3B7vPQyIqwNJbCATFVhoN+JaVnMb4kSMUwyVIURGS5sksTaUJy2pMG43NQJb0tSZ62u8vyLb4iVKrqQrVs3c/ftt3Jtr1/R01vMkpZ1vLjjY8aOPZLaZZu5tPR0VNnG69s/JVFi57obbk53ZGEfMk2TKVMmMX36p1iWxTHHHMdpp50pio7/4vsKGGIZ1S7I5XJx/ITjKcnyMahbNhf89kKGDBnKn27+E4uboLrbkTSYXlZ99gaDBgwgJyc33ZEFQfgvWJbFggXzePG1Z/l63iwCvgwKCgrTHUvYhx7/632UtIeY73LRrMiMD0d4IxTklH85cLHbHRQUFHbMQC4ceLxeHxOOO56EFWbuks9x2NyMKj4drz0LRbKR7+lJRctcTj37ZMoHlXHxJZcz+6uv8IR70DtrJLIkk+ksoDa8GafqobJtGaO7nYnHnoEi28h192D2uvf42SmnY7OJKc/SxTAMHnvsIQ7LSF0VXdueQJUlVAlq4qleFD6bTLbDhkeyCFoyip6kKakTMywOy/agyhI2WaI+oaGZMCzDhdemIEsSuQ4ba9oTGFg0JHU2xi0u/N3l9CgVE3h2JVM+mESv9mzG5A5FkiSK3Xlsjuxg+caVXN3zF+Q4MlBlGwP8ZTy/7G1OOfXn4mT2APb2228wffondO/enYyMAEuXLiYYDDJkyLB0R+tSvm8ZVTEHRhflcDgZO/ZITj75VIqKitm8eSMNre00dj8a3ZVNLLsPDfkjmfLJ1HRHFQThv/ThlPd57KUHWeCZx9f22dz76ERmz/ky3bGEfSQSCROPxVCx6KlpLLfbmZiZgWkY3P2XP7N8+ZLvfNzGjRt49ZUXeP/df9Dc3NTJqYV9yeVyc/TRx2JTVAxLw7R2L6NpWgamaeJwONi5YwdLly5GVmRM9lxq07B0ZElBkhQMS9/j8ZIkI8viUC+dJElCliQMy6Kv18FAv4PWpMHOhIlNkijz2OnmtlMRTtCYNCgt683WhIVhgSTBnt2kUz0qjH/qPG1ZIMkyO5OwPaaT0JJ8+ulH7NixvVPbKfx7NpsNDX2PbRoGsiyjmbu366aBLEmi98wB7tNPP6K8vJxAIIDf76e8vJzPPpv6rblRhO8mftX2E/F4HMvmSP2a7WIqTmKxWBpTCZ2hrq6WmTM/Y+XK5Zimme44wl5imibvTnqLpqOaSJYnSfZN0jKmmb/9/VkWL14gJvM6AM2a9SUDdB27BYucDmyWhSnJjI7F6bFkEY9OvJV3/vHaHo+ZOmUyD952I8bbb1L9+itcf/WlbN9elZ4GCPtEZmYWHrcXRbKzqOZDWuN1hJMtLKiehIyN9177gB1LInzwxsdUVGxgS3AhNaGNxPUwaxtnEdXa8Ntz8NozWVT9AW3xOkLJZpY1fMThhx3xrVnrhc4lyzJHHnUMy8M6m8IJYoaJpqj4PB5GZLgoddspcakcmummKalz+hlnc/jYIzEtUCWJhS1RwrpJu2YQ1g2SpsWqYJw2zSCimywLxlAkiUKbhWWalDpt6NWV3PjHq1m8eGG6my/sMu6o8XzVtIxFzWsIJsNMq53HtlgdE044iZe2f8T2SB11sWaeq5xEea8+NDY2pDuysJcZhsHSpYv54osZJBKJPXrG2Ww2ksnkDz5HMBjk008/4sUXn2XOnFk/6jEHItGnMI2amhppamqkrKxnx4Qr1dU7iUYj9OzZe4+uY/36DcChR3A3riWaMwAlGSKnfhFHHH9uuuILneCTqZN5981XGJUTZkbEheHJ59obJlJUVJzuaML/yDAMErEEpn93UcoIGIRDIR5+9T5cz7m57ZY7KSvrlcaUwt7U0txEVlLja5eTa1vb+GtmBj+LRJiwqxB9WDzOHe++jYmEy+Wivb2dT6ZM4tbGRrINkx22BK5EgrdffYk//nkiO3fuoKGhjoaGBvr06UvPnr2B1AFObW013bqV4PWKIShdhWVZTJ36AatWrWT06DFYlkVWVjYOhwNZkVBQCCdb+KLqZWRkLCxM06TQ1Z+kEaHYfRCb2+Yz7uijWLNqPku21WOz2dGMBJ9seQqH3Un/gf1ZuPkdDMNg7BFHct5vzk93swWgR49SZs5MEJQsTAtk1Y5NAZ9z93GeS5GQJZmnn3iYtpYmVFkiy67QmND5qjEMpK5hFZWUULNzB183RwBQZAXZMtkeMxiR4aLAmSpY5SV0Xv7bM4wcOarzGyx8S7duJVx3w8288crLvLDtQ/r07svt19xDQUEh7e1tPDD/dWKxKA7FwQC1J7f88TpO+fkZnH7GWT/43IlEnMrKreTm5pGdndMJrRH+U01Njdxyyx8xDB2n04VpmqxYsYLy8nK8Xi9VVVUccsjof9vzZtGiBfz1r/fhcrlIJpNMmzYVr9fLxIn3U19fi67rDBkyDJfL3YktSw8xiWcaGIbBE888yfx5XyN5MpFjQS6/9HI+nTGdLZWVSHY3Tknntptvo2fP3ScvW7du5oG/PkRTYwOmoSO7fCh6nPN/cyEnnHBSx3PHYlE8Hq/oftaFRaPRXdXWBC6X+zvHOba1tXLNFefz0vBVFLg0TAtuXFXGimCAo48+hgsuvlp0Dd6Pbdiwjj9P/BORIRESgxNggXOJE1utDaVdwXJb2MI2xo8/jst+d+WP/jyL74Cu6+uvZ/Pcw/dSpOucEI3yis/HVcF2eug6MUnisYCfWpsNE7AkCb9hEJZlbJaFDXBaFiFJAlnG7fcTDoUwLYsMwyAoKxR368bBhx7Ox1Mmky/L1FsmvzrvAk446dR0N/0nb9u2Sv50/bVYloXL5iOqt6NINgxTQ5IULEw8agZRrQ0ZG4Nzx7Oq6XN0M4kq25EkCUVSSRoxLCwuufQKDEPn1ZdfBis1TEQzEgS82UQT7YwdO46LL71c/EZ0AeFwiAsvPBfVMhkScKJIEmvb4yQkG92cCgM8NiRJoiqapNKwoWpxNN3giFwviiShmRZfNoYZmuFic3ucFsPkkEw3eY7UNci17TG2RlI99k7I92GTU9/7pmXxUV2Id9/9SLwPuqjKyi3cf/edOEwb7fEQCjL3H3QVXtVNa7KdG9Y8yf0PP0Z+fsH3/p4vXDifpx9/hCxnBs3RVg47fCwXX/57MX9GFzJ37hyeeOJh7HY7sVgMSZJwOBzE43EURUHXddxuNyeccDKnn/4LnM5vryKyePFCHnjgLnw+H5FIBFVVSSQSmKaJoijY7XaSySSyLHPJJb/n6KOPTUNL977vm8RT9MBIg9mzv2TuinVsG3oplmLHHqrlsScfI5HVi7ohl4Ik425Yw30P3cdzTz3f8aXVs2dvrrzsCibefz87+v0S0xnAFm/lldf/zpAhQ9m0eSN/e/lF4rEo/kAGV19xlZgMpotpaGjg6UfvYsPmragYGMi4XE7OOfcijplw4h77btmymb6ZOgWu1IGJLMHxBS3IWGxcPJP5g4Zz+OFHpKMZwv/IMAzufWgi4RFhnGuc2DfZkZKpwc6SLhE+MYyRbUASZk37nKGDhjF69JgffN4ZM6fx9zdeJBlPkJGdyf9d8UcGDBjUCS0SfiyfLFOpqqyw20lKEksdDnroOm95PVTbbPTWNCpVFcOCdkWhV1KjzqYQlWUipIoYR0UiGNEoM91ufhEKMzYeJwncZRpMq67mjuYmAqZFkyxz32svc9DQERQXd0t303/SbvvzTfjsWRxdeiE22U5TdDtfbnuVYn9/akIVHFt2MRnOfJJGjOlbn2NF42eYloFddlLs68fIop8BEptaFrG64XOeffYJbLKdnoFhDC04DoA1jV/SEq/hhNLfMmfRa8wbPIcxY8alt+ECVVWVSKbBwVlusu2pw+5RWW5mNoTZZinsiMRRJIgbe15PXNgSZViGC5cik+uwsaAlikSqF0aufffJqd+m4LUZSEBNXKO72w5ATVyntKS7KF50UZZl8eiDD3BG9jiOyBuGYRk8s+l9Ptj5Fb8uO5GkoSMZcOXvL8Zhd3DGGWdz+hln7VHIiETCPPbIg7hQaWhvJKB6WbN4GXMGfcWRR45PY+uEbzQ3N/P44w8xbNgwVFVl0aJFjBgxAo/Hg6ZpLF26lJKSErZv387MmZ/xwQfvA5CZmcnZZ/+ao446hkQizsMP35uaT0eWGTNmDLIsU19fz7p168jPz8fn85GTk8Pq1at57rknGTJk2AHdG0cUMNJg7sKFNGYPwVJSPzJJXyFxZzZJy4Yt3oYabSTpLSJYPZvGxkby8vI6Hrt02RJasgdiOgMA6M5MYlnlfP75dKZ+9hk7yk8n6SnA2VbJvQ/cy7NPPfeDawcLncOyLB6+9xYOk1eyXc7k+r47OSI3yNaIkz++/izFJT3o338gyWSSd956hVlfziARM4nqMg7F5K1teby7I/VlNCDQytIFs0QBYz+1Y8c2NDlJsn9q7gulUUFpUXCucqLn66niBYAdgr2DTProXZ5/5Wmi7REGDx3C7y/5PzIzs/Z4zg0b1vHi68/RfEwTRqZBcHuQu+67jReeeVWsJ99FFBYWEgIKdQOXBQ7TZJbLyZduF7JlYbMssKBY17ks2I7TsnjW78dpWdzQ3ELANPnS5WKOy8kZ4Qh+w+Bdr4dJHg8Fho7fMBieSBAwUydCOabJsHic5cuXigJGmsXjSQYXTsAmp373c9zd8aqZVLevJ89TRoYzHwC74qJP1qGsbvgCWZIxLJ2dofW0ba0j39OT6vAGLCzy3KXYZDu14U1UbliBiYFlGYDM5IoHkSWFJx9/lCFDhuHz+dPYciEzMwvLAuc/FRIcsoQFGLrBML+des2iOq7htcmMynSjyhIbQwmWtMYYk+2mVTMYlelCsyxWtsWZ1hDGb5Pp73OQMC3CuokswZr2OHXx1ISQ9QmdC8448XtSCZ0pkYjz5mt/Z/68ubgcTk449VQyMzNpbW5mbM+hACiSwslFY3how2ucVjyOW1Y9hWmZZKg+bMh8+O47ZGZncdRRx3Q876xZX6KYEtcO+DW9vN1YE9zCoxVvMn/OHFHA6CL+9ren8fl8+Hw+ampqyM7OxuPxAKCqKkVFRcTjcZxOJz179qSiooLS0lKcTicvvPA0Tz/9GJIkYVkWsiyTmZnZUZQMBoMoioKiKLS2tlJVVUVJSQk1NTWsXr3ygH4PiAJGGuRkZ+OoayHyzQbLREmGcUebcbduJuHvhqN9JzpGx5v8G1mZWXj0jQT/aZsjGaS6pprWnEEkvaklGOOZPUm0lbFkySKOOea4TmmX8O/V19fR2txAWWmEAX4H4/JSr2Ivb5wzCncyd9YM+vcfyEvPPUpk/XQeHVDJi1sLuGhxH4pdCUK6woNDK1Eki0cqiknU16W5RcJ/KxDIQAtpoAEqGPkGSquCFEuNg8fim8nmkYMyldu3EDw2iOkzWbR6AY1338yjDz6zx5WYr+Z8QahvO0ZWqvih9dAwthosW7aEsWOP7PQ2Ct9WX19HtmlyXijEJ243cVnm16EwfTSNRQ4Hn3rcVNpVrmkL4ts1utOQJE6NRMjaNYHv+FiML9wuXvb5+E0oxE6bwmKnkwZFISZJ3/pRb3Q4ODhTFLHTzcKkPdlMfaSS5XXTSBhREnoUu+wkqrVhWVbH5zmUbAZgYO6RdA8MpCFSxbK6Twm2LCDLVcSIwpNZWT+DtniqqNGaqMMm2ZAlhWCiEZtkJ9vVjbZELZdfehGvv/luOpv+k1dQUAgSVITiDMlwIQMbwwlUScKlSGyK6UhIuBSZQX4nTiV1ctLX52BrfYhZTRGcskSWqvBFU4S+PgfFLpWmhM78lihmqu6JzyYzOstDbVzDAvyqzNbNFcDP0th6AeDpxx5FrwpyY9mv2R6p4x9v/IOwFsU0TUJ6FL+aOtavj7egmQbXr3iMgYGe/LLHcbRrEV7YMhlJkpgy+f09ChjbqrZyZN4IevtKABic0ZthmX0JJuNpaafwbevWrcE0TSzLwuFwEIlECIfDuN1uZFkmFouhqirxeBzTNPH7/WiahtPpJJFIoCgK3bp1o7i4mFAoxPr168nKysLtdlNbW8vIkSNxu1NzXmzZsoX6+noM49vnjwcaUcBIg1NO+hlfffUHNElB8+TjrV+JobpRgNqhF2LZnEh6nJKVL7Fjxzb69RvQ8dgjjzyadye/T2LHLCK+7vjbNpJlS9K9ew+U6i17/B0jEWH79m2Ypim6EHYBqqqiGRY2CeLGnq9HzFBR7Q4SiQRz5n7N+4duwqca/GXQNt7ansMrlYW8dEgFJe7UbMO3DtzOeYv9exz0CvsP0zQxMfFO95IYnEAOy7gWu9ADOrIu4/nKQ6I8ga3RhqPCQXhkGCM3VZgIHxym+u2dvPTyc5yJitZVAAAgAElEQVR5xjkEAqneWA67HVnf830laTJ2u73T2yd8t1UrV4Cu83BGAL9pUmgY1NoUeug6x8ViVNhVNqoqm202VjpSQ0w0CZL/9Bm3gLgk4TJNPnO7MIBSTaNt19CUjarKQ4EAHsskLkm0+XyMHHlo2tospOTm5rK2fjaKJNMn61DCWhuNkSoMSyemR5iz/S3ApDlejWWZuNUA/XIOoyFSRUu8Bp89h4QeIWnEmLvjbQxTR5Yk4nqYbr5+DMk/loZIFRua51IfqaQusoVMZz7tiWZCoXbRCyONFEXhZ6eczidTJjOtPgSklj7NsiuUeewsbY0xLsfD8mCcb0aRJAyTqmgS04KIbpLvUdkR1wmoCr29DgBK3HZaNYPmhE7IsIgaJjVxjW4uFUWS2BCKY7c70tVsYZdwOMTS5Uu4rf9FPLnpHUJahLAWZUzeMHZG67ln7UucUTKesB7hH9tmkDATGKbJFeVn4VDsFLpyOK/0JF6pnEIyseeKE3n5BdSuWbfHtogeY8jQ0Z3ZROHfcDpdxOMx1qxZgyRJRKNRVqxYgWVZeL1egsEgsixjmibr169H13WysrKoqKhAURRcLhe9evXa9VxOwuEwmzdvxuVyYbPZOooXADk5OVRXVyNJEh9+OImDDx51wJ4jiEk80+DNN1/l/fff5scsiPmflB2+7/lyc/J47tmXDtg38f7k3ok3wI4FLGlx0XGJvcM3r/a3X0kZOLW4maGZEUZltfNBdQ7Pbin8juf4tiOOOJprrrnuf0wu7A2JRIJLLjmfcLgd80d9A6RYkoUkS2DsuV3a9a9jv13/viEj8/jjz4nhA11AVdVWbrz2Svy6TlBRsAGDE0mCskylauPweJw1qkqToqQGuf/LT/M3r/IeWyUJ1bI4JJEg3zD4yuWiTZJ2v7Msi+KCIh5/9qV93j7h37v+umuoqtpKhiOfULIJjz2L3hkj2N6+lqbYDqwf8X0gIWFX3OR5SrEsi5pQBWbHl4KEItnw2bOwyQ5aYtUo2DElnceffJqCgqJ920Dh39q0qYIbb7wWSH2WS5wKEd2kWd/9iZYAuwTZdoX6hEGGKpE0LcLGnp97jwQJUl8R37z6KuBUUvubFhQ5beyI60y86wH69x/YOY0UvlNbWyu/v/QiZMMiau0uQMjsPtqTkLCwsGNDkRViZgIJ8CguunsKsMkKq9o2f+/fkNjzPZKVlcVTT70oLmB0AW+//Qbvv/82hrH7AO6b87FvTsFVVcXpdBKJRDDNPX8LZFnG7/djmiYOhwNd12ltbe14nlGjRqHrOk1NTTQ1NREOp1Yscrnc/OUv99CrV3lnNHOf+b5JPNN+Wd40TW677TbOPvtszjvvPLZt25buSPvUxRefx7uT3ke3uTAcAaJ5g7FUN5asgmTDsrnQvAVEcwaArJJ05RDN7I0pq5goxD2FmLJKNKsPcX93TFklYc/EUBwYqhcUB4lAKfGscpBVkBQam5o56+xT2c9qVQeknXX1rA26ODY/SLk3jkcxKXEnOb6gFa+i41Z0CpwaJxS2kmPX8dlMip1Jjito5cuGDJ7bXMjpcwfwWlU+xxe00ssTI9uepNQdI1PVOCQziFM2KHPH8Nt0nLLBvDkzOeec09Ld9J+8cDjEL887jfZEG8niJJIioXfXMYoMJFXCyDWQFAmjwEAv1ZFsEmbABEfqB8zwpe7XemoY+QaoYMomlmJhqiZasYbWXUOySaBAaiSKxZV/uJjFixeku/k/eTfe8Adk06RdUVCAXMOgwaaQbRqowAKHg4iiMDqRoEg3cAMDNA1VkijXdPrqOk6gwDBwkprfImCa2IAJ0RjHRWOc196OIkkM1jQO0jRUWaa2vpbVq1els+kCUFm1GQmJ9mQj+d5euGw+VjRMRzOTlPgHokgqMjZcNj9lGcNw2wJ41Sxskh1ZslHoLcerZqVOcmQnYa0Frz0LBRWfmo0iKeS4S/Das2iN1yJLMiYahqWJOXC6gJtuvBYZyHMo5NkVquMGMQu6u2w4ZAmnnJqoW7OgLmHgkKFNs9AsCYcs0d1lw61IuBWJuAVOCVQ5dbvQoWACTkUmy27DALbtmgdj6tQP0tlsgdR5jqZr6FgEVC/jcoeT48jAr/pwynZy7Rk4ZJXhmf3ol1FG0tRxynaGZfajl6+EreFqtoZryHdkMcjfC7ukYpMUHLLKqKxB5Ngz8KkexuUOJ9eRSb4jCyukcf65vyAYDP5wQGGf+vTTjzAMo2MCzm/mrPD7/eTl5XX0vvB6vdjtdhwOB1lZWR37AoTDYWRZxrIs2tvbcbvdFBQUoCgKixYtYvny5ezYsQO3200gENg1NCVKc3Nzmlu/76R9CMnMmTNJJpO8/fbbrFixgvvuu49nnnkm3bH2CcuyaGxtR/PmI5k69Qf9BiQZyUhQtPR5Eu5cDIePlt4ngiQRjAcpXPkyDYN+hSO4jYxts7FpYRoHnEXCnxrv5t85D1/1InRnBqbqIZxRRqjoYACcrVvJ2jINS1Kw9ChffDGD8eMnpPN/wU9aXV0tLY31vDaqgkKXxoc7s/i8IZNHh21BlmBabYQ3tuXx8iEV2GSIGTLnLujLjf13MCQzSkhTOHdBXyxL4tXRG8h16FgWTFzbnTJPnK0RJ729cU4qbuWNbXkcnd9GXcxOq2ajKmLR1tYqJnRNo2uvvQpJkgj+PIhvmo/w+DB6Seog07HOgWO1g/iQOPFhqbGrSr2C9wsvybIkUkLCvsNO6KRQx1AS5wInjo0O9EydZO/UhKAA6jYV12IXckjGVEyww/0P3cV7b3+cnoYLAOjJJKokMToeZ67TSaZpckWwHQl4zzCZ7XYxsaWVgGliAU8F/BRpOofFE8xwu7i5tY2ZLhcb7SrFhoEGxGSZgGEy2evh8mA7n3g8nBMKcXg8AcASh4NXfV7uuOMm3n9/ajqb/5NWU1MNgCwrjOn2S/K9PQFY3zSX5tgORnc7g2CigRlbn2dCz0tx2jwYls7Myr8xPOdEltV/Qt+s0SysmcxJva/GrjgxLZMvq14hIrWhWxoH5R1Ln+xRqb8X2siS2o/RTQ3JknnjjVe57LIr09b+n7oVK5aiSDDI76SH287OmEbCSjA224P8zTKpTWFybTLNmoFDltAsixy7QsgwOSrHi02WMC2LOc0Ryj0O1rTHCagyh2e7WdIao6/PQfmuoSWNCZ3FrVEMC+bPn5fm1gvXX381IOGyOXhk+HU4FTu6afDnVU+RoXoxsTi37EQOyU71lPnDsoc5u/sEDs0ZDMBX9UuZ1bCUdi1Cv0AZ26N1mJhc3/83yEg8sfFtHh12HU7FgW4aTFzzAhMKD+W97TO5/fabePTRp9PYeiEUSg0bkySJ3NxcotEogUCAPn36ABCJRFi6dCl9+vRBkiSWLl1KUVERBQUFVFRUkJmZid/vp6ysjOrqanRdZ9iwYUiShKZpzJs3D0mSGDZsGD5fqrfC5s2b2blzJ88//ySHHHJgDiFNew+MpUuXMnbsWACGDh3KmjVr0pxo3wmF2kGxYahuojn9QUr977cUB7GMUhQ9SjS7X6r7MGA4AyTdOajRRmLZfbAlWpEso6N4AaT2B2JZ5dgjdUSz+3bcF88oQ9bjqIk2ZCPJzJmfdWJrhX+1bNkSil0JCncti7o+5GZ8fiu7lmynKuLkmPxWbLs+lS7FZGxOOxWh1Pg2n2pQ6olT7ouR60id+EoSjMsLsiHkZlxekPXtbo7IDbIx5OaI3DbCukJlxIldtvjiixmd3mZht+bWRvQcHctuIYdl9G56x33J0lSRIlm2u3upkZ8qVOiFOnI09aYwvbu7FuoFOiigtCloZVrHdq27hhyS0XN0ZENGTsgY8r+MPRE6nQ1w7Bru4bUshicSHcNCquwqZbpOYFfXUQkYFU+wxa4yPJFgm6piAsMTCapsNg6JJ6iz2RiaSGLDotKWuhZRqaqMSCQ6/ubwRIKELH9rOIrQuSZP3j2JZp6nrOO/u/sH0BJLFTcCjjxcqp+Y1g6AItko9vYlrLWQ5SqmOrSBfE9P7IoTAFmSKfEPwCbbSRpRSgK758oq9JaTMKKYlp4qhIjf/rT6+uvZGBYUOVUA2jSDIqeKvOtYT5Ul8hw27EpqZRK7LGOTJNw2mXyHDduugwRZkihwqP/f3p3GR1Hlaxz/VS/ZE2gMAUOiJERFEcWFQeQOKIzAh0VkE7wadHBXFAEZIstMgIAJIKOiAiouEwUkiKIo11FBHRmJA8igyKKgYUsIZoOk00m6u+6LJiVtADcgQZ/vm6RPV1VX1anl1L/OQoXPT4jd4MwwBzbDoKTGR4vDywaIDQnUyIhyGPVfyBc8h9zYDLjU1Zqww6MPOmx2rohtiyskmj3uQi5vcj4AftPPfk+xFcwA6BB7ITsr9tLOdR6by3bgNX04DAfnRp/FjvI9XNz4HMLsodZyL29yPnkV+XSMvYi9e3af+g0WS01NDTabDcMwiIyMpKKiAtM0g0aXjIyMJDQ0FLfbjc1mo2nTphw8eJCmTZvi8/lwu93W9AcPHiQuLs5qguJ0OnG5XBiGYQUvAJo1a4bNZrOamvwW1XsNjPLycqKivq/eaLfb8Xq9OBxHXzW73aBx44ijftfQxcSEgd+H4a0mvGQnh+L/EHgC9fsIO7iHmjAXYWV5eJoEOmux1bhxVhZRE96E0LJdeENisJlenBUHqIlsCkBY2S7AIKwsj5rwWELL8nDHXQhASHk+pt1JjSMcu9dD586dT9t991vQsWN7Xno+lNJqO41DfCRFevi0KJp+LYoBSIjwsGLfGQxrWYhhgNcP64qj6HRuoApglc9gjzuUSp+dQzU2op2Bh50NJVEkRXrYUBJFy0gPG0uiOCvCw8bSaCIdXhLCq9hTGUrPnt2V//UoKjKaQ0UHwQR/mB97od0KUjjyHZhOE+c+J1WNAw+gthIb+MFeZMcffvjBtsrADA88jNqL7RheA18jH459DmqSA0EMx34H/gg/jmIHps3EDDOxV9mV9/XMD9QYBtucIbStqubzkBA6Hq4p0aLGS254GJWGQfjhYMPmECctvF62OZ2c6fViA7aFOIn3+fgyxEkTn49tIU7CDwc9no6JxmGabHWG0K46EAjb5nQS6vdTZZy+983fgkGDBgQCyCaUegpwhQdGC9tf8Q2NQgMFU3dNGZU1Bwl3BjrlNU0/he5vaNmoHV8Vf0pK4/ZsOvAePr8Xu80R6AOj/Ctq/FWE2MIprPiGsxtdBEBR5R6ctlDC7FGU1xRzWfvLlP/1qFOnjvzrg/c4UOUlPtxJtMPG3soaUiJDMIxAzYqiah+NHIGHktgQO7sqfdbwqH7TxHZ4GMXvqr3Ehzmp9pkcqPbSygwh2mHjQLWXsx2Bh+Myrx8bUO4N9KyivK9fzrAQqtyVbC7bgc/0YTfsmKbJxpLtmKZJ0zAXWw9+ywWNkrEZNmJDG7O5bCdtG6cAsLlsBwnhcWw5+A0XNEom332Aan8Ne92FJETE8X7Bp3j9Phy2wHI3l+3kiti2vJP/CbFNmyr/61ltnxYVFRXExsbi8XgoKSmhcePGAHg8HqqqqggLC8M0TUpKSmjevDklJSVWJ54lJSVERkYSFRVFSUkJLVq0wDAMfD4fZWVl+P1+3G631aFncXExpmkSGRn5m83/eu/E8+GHH+biiy+mV6/AWNWdO3fmo48+Oub0p3snnkOHXkeV149pD6Um3IXH1YqIA5uxV5eD3w92O55GZ1MTHkvU/o34QmOoio4nqvBz8PvwxCQSWlFAedzF2L1uIr7bis8Zic3nwRsSjbPqIBWxrfHbQ4na/18Mvw8wMUyTV5e+oY4869nwmwdhrz5Iv/givjoUxvrSaC6IcXOpq5y39jWhtMZBclQlV55xiNWFjcj3hJASWUn7M8p5t6AxXtPguyonjZw+escXse1QBJvLImgVVcnX5RH8MbaU1YUuUqIr2VEehtcfyG8vdl7JURXy+rR/fwF33f9nzFATb5wX514n1edWQw2E7AwJpBU4qU6uxh/uJ3RbKL4YH/aywLCqvigfdredqtaBUUtC8kLw2/0Yh/O4ulU1OCBke0ig00+fAV4wbAbDb76TPn361fMe+H37859voLK0FANoW1XFVyEhJHi9nFPj5eOwUCpsNiJNk06VHr5xOvjK6eTySg+fhodzQXUV0abJf0JDOaumhjynk/gaL8UOOx7DIKGmhl1OJ3bTxDQMOnk8GCb8KzwMPzBpahYXXnhRfe+C37WBA3tjO9xBXyvX5VT7Kskr20TTiJY0CY/n65J1+Pw1xITGkhBzAXsPbaPa68bn91LtrySpUTsK3XmY+GjZ6GL2V3xDiWcffr+fxuHNKavaz9kxbXHYQ9lZsgGf6cUAfKZXzYfqmWmaXD+4D4YJZ0U4AZNdlV4aOew0C3Owt7IGr2ni8ZnYD/fGWNsfRqjNIMRmEB/uZL/Hi8fvx+c3CbMZVJkQYbcR47Sxu7KGhDAnTpvBt+5qODy0au9r+3PzzbfV8x74fdu16xvGjhqJ3WYjLrQJVza9mPXFWyiqKsXt9RAf0ZT9nmK6xF2K1/Sxev86nDYHV8Vdhs/08fGB/xLlCMdm2Dg/Jok1BzYCEGIP4eq4y/m0+AuchoNOTdvxWck2SqsPEm4Pp8DzHbPnPKkOfOvZrbemUlpajGEYOBwOK6ARGxtLeHi4NWpIQkIC3333HVVVVcTGxpKfn49hGBiHg5dxcXHY7Xby8/OJiYnB5XJRUFBAdXW19WwXHx+Px+PhwIED+P1+srOXEBFxeg+neqxOPOs9gPHOO++wevVqMjMz2bhxI0888QTPPvvsMac/3QMYACNH3sUuq1rXkX0HH+v/X6d5XDPmzHn6mLVa5NQxTZOpUyfx+X/X4+f7XA7ujTrw+chK/7bD0x15RNgPT1O7DOOI+Y+c7ozYOObPf/FEb4r8Anv27GLkA/cERg74uaf3L7gk2LDxl79MpEMHDanWEIwZM4Jvd+4Iysojz334/rw+0pFh56MdAj8cocS6Xths3HffWK666qpftd5yYgwc2Bv4fsQBDn8KOHI0CttRRiX5/qgJzB88z7GW9cory3XvbwB8Ph8jRtxBYWFBUPpPvaz/khLhnXfeS/fuvX7mXHIy5OV9w+jRgX5obNjqjEJms64Jgb9HfoZAh9yB/468dgTm8x/+XPu/gQEGPPXUAuLimp38jZMfNXHiOLZsObVdJMyb9xxNm57++d9gAxh+v5/09HS2bw9UpZo+fbo13u3R/BYCGCIiIiIiIiJydA02gPFzKYAhIiIiIiIi8tt1rACGOigWERERERERkQZPAQwRERERERERafAUwBARERERERGRBk8BDBERERERERFp8BTAEBEREREREZEGTwEMEREREREREWnwFMAQERERERERkQZPAQwRERERERERafAUwBARERERERGRBk8BDBERERERERFp8BTAEBEREREREZEGTwEMEREREREREWnwFMAQERERERERkQZPAQwRERERERERafAUwBARERERERGRBk8BDBERERERERFp8BTAEBEREREREZEGTwEMEREREREREWnwDNM0zfpeCRERERERERGR41ENDBERERERERFp8BTAEBEREREREZEGTwEMEREREREREWnwFMAQERERERERkQZPAQwRERERERERafAUwBARERERERGRBk8BDBERERERERFp8Bz1vQK/Jbm5uTzwwAOkpKRgmibV1dWkp6fzj3/8g169etG5c2dr2k6dOrFmzRo8Hg/p6ekUFhZSWVlJ06ZNmTx5Mi6Xi9TUVNLT0/nuu++45557WLFiBWeeeSYAs2bNIjk5mQEDBnDhhRdyySWXBK3LrFmzaNq0KVlZWWzfvp3q6mrCw8P529/+RmJiInl5eUybNg2v10t5eTnt27dnzJgx2GyKaZ0Ie/bs4dprr6VNmzZWWocOHVi0aBFr1qxhzpw5fPjhhyxevBiHI3AaXn/99cyePZuEhAQAnnnmGV588UXef/99QkNDAUhLS6O8vJwnnnjCWm7tsQSwbt06nnzySbxeL263mwEDBnDjjTcGHZu1XC4Xjz/++EnfF78Hubm5LF68mL///e9WWlpamnXe//AcbdWqFenp6T/73HW73WRkZACwceNGLrroImw2GwMGDGD27Nm8/PLLnHXWWQCsWrWKp59+mpdffpnOnTtbx0itOXPmsGLFCuLi4qy0K6+8krvvvvuE7x8Jtnv3bmbOnElBQQFhYWGEhYUxduxYzjnnHADuuusuTNNk/vz51jxdu3YlKSmJBQsWWGnPP/88mZmZbNu2TfnZgB3rfjBixAj69evHpZdeyt/+9jfru/POO48hQ4YwZcoUKy0jI4NVq1axatUq5syZQ2xsLDfccEPQ9R/g/vvvp02bNtx5550AlJeXM3DgQB577DFat259Crb29y03N5dhw4Yxe/ZsevfubaX37duXNm3a8Omnn3LmmWcGlbXGjRtHRUVFUPnR6/UybNgwevXqBQTf59977z1efPFFADweD7feeis9e/a0lpeens7GjRt5/fXXrbTa8mSrVq1O6vafzn5YTqqqqqJv375s3rz5mGV4gLVr1/LUU09hmiY1NTX06NGDW265he3btx/1fn3rrbfSpUsXFi5cyIoVK6wy4G233UaXLl0AcLvd/P3vf2fjxo2EhYUBMGzYMK655po661lRUUFCQgKzZs0iJCQEgLfffpvx48fzzjvv0KxZM6DuPb+mpoZRo0bRoUMHunbtysqVK62y5o4dO0hPTyctLY0RI0bw+uuv06hRIwCys7NZv349jz766EnKid+OzMxMNm/ezIEDB/B4PCQmJuJyuRg7diwzZsygtLSUmpoaWrduzYMPPkhUVBRw7GPKMIxjnstPP/00//73v/F6vRiGwbhx47jwwgvrY7NPCQUwTrArrrjCeoj5+OOPeeyxx3C5XMec/tVXXyU2NpbMzEwAXnjhBZ588kkmTpwYNF1ISAgPPfQQzz//PIZhBH3XqFEjsrOz6yz7ww8/pLCwkOeffx4I3PSmT5/O3LlzmT17NjfddBOdO3fGNE1GjBjB+++/zzXXXPOrtl++l5KSUidfFi1aZP2/d+9e5s+fz7333nvU+d944w169erFW2+9xYABA6z09evX8/rrr3PdddcFTb97924yMjJ49tlniY2NxePxMGzYMBITEwkNDQ06NuXUOtY5+kvO3drpu3btynPPPWcVOAzDYPz48WRnZ3Pw4EFmzJjBM888g91uP+Z63XLLLdxwww0nYhPlJ6qsrOTuu+9m6tSpVvBq06ZNTJkyhezsbPbt24fb7cbr9bJ7924SExOteQsLCykuLqZJkyZA4DipLVSC8rMhO9r9YP369Zx77rmsXbuW8vJyq/DauHFj1q1bh9frxeFw4PP5+Pzzz3/S76SnpzNw4EC6detGSkoKM2bMYMiQIQpenELJycm89dZbVgBj27ZtVFZWWt8fed2ulZubG3SPrqioIDU1laSkJM4//3xrug0bNvDCCy8wf/58IiMjKSkpYciQIaSkpJCSkkJlZaV1XOXm5tKhQ4dTsMW/HUfmQXV1NT179jzuubN9+3aysrKYP38+cXFxeL1e0tPTWbBgAbfddtsx79eLFy+28jI0NJSSkhLuuOMOGjVqRLt27Rg/fjyXXnopEyZMAKC4uJhbb72V9u3b11lPgDFjxrBq1SorkJWTk0NqaipLlizhvvvus6Y78h6xY8cOHnzwQV577bVjbl+bNm0YNGgQGRkZzJw5k127drFw4UJeeeWVn71vf4/S0tIAWLZsGTt37uTBBx/E4/EwePBgMjIyuPjiiwF47bXXGDNmDPPnz//RY+povv76a1atWsWiRYswDIMtW7Ywbtw43njjjVO2raeaXrefRAcPHrQKmscSGxvLmjVrWLVqFeXl5aSmploH/JGuuOIKGjVqxMsvv/yTf9/lcvHFF1/w9ttvU1xcTLdu3Xjssces333ttddYv349Xq+XRx99lD/96U8/bwPlV7ntttt48803+fLLL+t8l5uby1lnncXQoUPr5Pno0aOZM2cOBQUFQenLly/nuuuuIzY2FoCwsDAWLFhAp06dTt5GyElxvHP3WK677jpcLheLFy8mKyuLu+66K+jhVxqG1atXc8UVVwTVvLnooov4xz/+AQSC2t26daNfv34sXLgwaN4ePXrwf//3f0Cg8HnWWWfhdDpP3crLCZWTk0OPHj245pprgt6WOxwO/vCHP1hveD/++GOuvPLKn7TMJk2aMGnSJCZOnEhubi579uzhz3/+80lZfzm61q1bs2/fPg4dOgQEXkb07dv3Zy0jMjKSIUOGWOd7rZycHG6++WYiIyOBwL0iJyfHehu7cuVKOnbsSP/+/X9WeVHqKi8vx2azWTUkjmbx4sXceeedVq0Gh8NBWlrajz7gv/TSS0yYMMEKaLhcLkaMGMGiRYs4cOAA33zzDcOGDbOmb9KkCcuWLaNx48Z1llVdXU1hYaEVzN69ezdlZWXcfvvtLF++nJqamqOuQ2lpKREREcffCQRqBH777bd8+OGHpKenM3nyZGJiYn50Pjm6Dz74gPbt21vBC4D+/ftTUlLC7t27f9ExFR0dzb59+1i6dCn79+/n/PPPZ+nSpSd9W+qTamCcYGvXriU1NZXq6mq2bt3Kk08+yYoVK+pMV1uLokePHhiGwdKlS3nooYc499xzmThxIuedd16dedLT0xk8eDB//OMfg9LLyspITU21PsfFxfHII49w0UUXMXXqVJYsWUJGRgbNmzcnLS2NP/zhD4wbN46FCxcye/Zstm/fTpcuXfjrX/+qi9IJ9PXXXwfly6xZs4K+j4iIYOrUqaSlpdW50OTk5DB48GCSk5MJCQnhv//9r3Wxa9asGSNHjmTChAlB1ckLCwvrvCmIjvkKctYAAAxlSURBVI62/q89Nmt16dLlmNFcObF+eI7WVu37Jefu8UyePJkhQ4bQtm3bOjV0juaFF17g7bfftj7fddddCnidZHv27LGa+QDcfffdlJeXWzVuVqxYwSuvvILD4aB3796MHDnSqkLcp08fJk2axP/+7/9aD0Xvv/++tSzlZ8P1w/tBZmYm69evJyMjg5SUFO69915uuukm6/s+ffqQk5NDly5dWLFiBXfffTfLly//Sb/VtWtX3n33XR566CHrjZycWt27d+ef//wnAwYMYNOmTdx+++3k5+cDMHz4cKsJic1ms5qD/NAZZ5zB5s2bg9IKCwvrBKaPrIWVk5PDlClTrGaK+/fvt5oQyI+rLScZhoHT6WTSpEmsXLmSmTNn8swzz1jTlZWVAYFgwaBBg4KWERUVRWVlJX6//5jNsktKSuq84ExMTGTfvn3s3bs3KI8ff/xx/vOf/1BWVsY999yDy+Wy1rOoqAibzcb1119Px44dAVi6dCkDBw4kJiaGdu3a8e6771pNkWrvETabjZiYGKZOnWr9zpHHZWVlJeHh4QDY7XaysrJITU2lf//+P1oOkePbvXt3UBmgVkJCAvv27fvRY+pomjVrxty5c3nppZd48sknCQsLY9SoUfTo0eOkbENDoADGCXZkta6dO3cydOhQunXrRnV1ddB0Xq8XgM8++4yOHTvSvXt3fD4fy5cv56GHHmLZsmV1lu1yuRg/fjzjxo3j0ksvtdKPVQ1969atJCUlMXv2bEzTZM2aNTzwwAOsWbOGtWvXcsstt3DLLbdQUVFBVlYWTz311FFrf8gvc7Qqwz/Uvn17rrzyyqC362VlZXz00UcUFxeTnZ1NeXk5L730UlC09tprr+W9994LekMbHx9fp1bG1q1brQuempDUn5/bhOR45+7xHkaaNGnCZZddZhVWfoyaHJx6zZs354svvrA+z507Fwj0gfPBBx9QUVHBmDFjAPD7/bz55psMHjwYwOoDKT8/nw0bNvDAAw8ELVv52XD98H6wcOFC/H6/1VfFgQMH+OSTT6yHkMsuu4zJkydTUlJCaWkpLVq0+Fm/d9111+HxePTwWk/69u1Leno6iYmJXH755UHfHa0JydHs27eP5s2bB6XFx8eTn58f9LJi/fr1xMbG4vV6+eqrr6wmyYZhsGjRojrXCTm2o5WTVq5cydixY+v0gQGBB8e9e/dywQUXWN+Vl5cTEhJy3D7loqKiKC0tDapRkZeXx5lnnknz5s3Zu3evlX7//fcDgZdgbrcbl8tlrWdJSQnDhw+3+k7z+Xy8+eabtGjRglWrVlFWVsZLL71klQmOd4848ris7QOjVnJyMsnJyfTv3//YO09+kmbNmrFp06Y66Xl5ecTHx/+iYyovL4+oqCgefvhhAD7//HNuv/12OnTocNRaO78FakJyEtVW5b/gggt49913rfR169ZZne+89dZbVvTdbrdz3nnnWZ3wHE1tR27Ha7NW65NPPuHxxx/H7/djGAbnnHMO4eHhGIbBzJkz+fTTT4FAVcWkpKTj/q6cPKNGjeKjjz4iLy8PCFQ3HThwIM899xwLFixgyZIlrFmzhuLi4qD50tPTee6556ioqAC+f2NXO11FRQV//etfOXDgwKndIPnVjnfuyumtW7dufPLJJ2zcuNFKy8vLo6CggJUrV5KRkcGCBQtYsGABjz76aJ1mJL169SIzM5NLLrlEx8NpbOnSpcybN8/K64kTJwZV+TcMgy5dupCenq7mnaehxMRE3G432dnZXHvttT97/vLycnJycoI65wQYMGAACxYswO12A1BUVMT48eOprKwkJyeHUaNGWcfUiy++yKuvvlrnBZqcODfccANz5861ylk1NTVMmzaNoUOHHne+m266iYyMDCtvioqKeOKJJxg6dCjNmzcnISEh6Hpw6NAhtmzZUuea73K5mDlzJhMnTqSwsJAPP/yQCy+8kOzsbBYsWMDSpUspKipi69atJ3jL5Zfq1q0b//73v4OCGDk5ObhcLhITE3/RMbVt2zamTJliHU9JSUnExMQctw+0051qYJxgtdW6bDYbFRUVpKWl0bdvX6ZPn06/fv2IjIzE6XRavYs/8MADTJ06lX79+hEeHk5ERATTpk077m9MmDCBtWvXWp9/WA0dAv0kpKamkpWVRb9+/YiKisJmszFjxgwAHn30UTIyMsjMzCQkJISEhISgaKucOqGhoUyfPt26OOXk5Fj5BBAeHk737t1ZsmRJ0HxNmjQhLS3N6gQ0ISGBsWPHMmLECOx2OxUVFQwaNIguXbqQm5tbpwkJBEY6qa2eLr/OmjVrgjpbTUpK+tF5fsm5+0uUlpYGrdvw4cOBuk0OkpKSgkY+kBMvMjKSuXPn8sgjjzBr1iy8Xi92u520tDQyMzP5n//5H2vayy67jKqqKjZs2GCl9ezZk2nTpgX1mVBL+Xl62Lx5M6ZpWqPOQKA56cMPP2w1M4DAW/xBgwYdNw+Pdm736dPn5Ky4/Cy9evVi+fLlJCUlsXv3biv9yKr6EBhdIiYmJqj86PP5uO+++0hOTg5a5iWXXML111/P8OHDcTgceDweRo8eTXJyMitWrAjqtC8+Pp7WrVvzzjvvADBy5EjrRVWHDh0YN27cydz834U2bdowatQoRo0ahc/nw+v1cs011/xo89zU1FR8Ph833ngjDocDwzC45557rNrVWVlZzJkzhxtuuAG73Y7b7aZnz5707t2bzz77LGhZKSkppKamWgGR2hp7tQYNGsTLL78cNEKV1J/IyEjmzZvH9OnTKS0txefzcd555zF79mzgpx1TRzuXd+zYwaBBg4iIiMA0Tf7yl78ENSP/rTFM0zTreyVERERERERERI5HTUhEREREREREpMFTAENEREREREREGjwFMERERERERESkwVMAQ0REREREREQaPAUwRERERERERKTB0zCqIiIicsJ99dVXzJw5k8rKStxuN126dOG+++7DMIw60+7bt4+tW7fStWvXelhTEREROV2oBoaIiIicUAcPHmT06NGMHz+e7OxslixZwvbt21m8ePFRp1+7di0bNmw4xWspIiIipxvVwBAREZET6v3336dDhw60bNkSALvdTlZWFk6nkwkTJlBQUEBhYSFdu3bl/vvv5+mnn8bj8XDJJZeQkJBARkYGAI0bN2b69OlERUUxefJkvvjiC2JjY9m7dy9z584FYPz48fh8PgzDYOLEibRu3Zqrr76a5ORkWrVqxerVq8nJyaFx48YsXLiQiooKbr/99vraNSIiIvIrKIAhIiIiJ1RhYSGJiYlBaZGRkezZs4d27doxePBgqqqq6Ny5M6NGjeKOO+5g586ddOvWjeuvv57p06eTkpJCTk4Ozz77LG3btqW0tJSlS5dSXFxM9+7dAZgxYwbDhg3jT3/6E1u2bGH8+PEsW7aM/Px8li1bhsvlIioqirfeeosbb7yRN954gyeeeKI+domIiIicAApgiIiIyAkVHx/Pl19+GZS2e/duCgoK+Pzzz1m7di1RUVFUV1fXmXfHjh1MnjwZgJqaGlq2bElkZCTt2rUDoEmTJiQnJ1vTtm/fHoDzzz+fgoICAFwuFy6XC4CBAwcyevRo2rdvT2xsLLGxsSdno0VEROSkUx8YIiIickJdffXV/Otf/2LXrl1AIBCRmZnJli1biI6O5pFHHmH48OF4PB5M08Rms+H3+wFISkoiKyuL7Oxsxo4dy1VXXcU555zDxo0bASgrK+Pbb78FoFWrVqxbtw6ALVu2WMEJm+374k2LFi2Ijo5m3rx5DBo06FTtAhERETkJDNM0zfpeCREREflt+eKLL5gxYwamaVJRUcHVV19Nz549GTNmDNHR0YSEhJCfn8+LL75IUVERo0aN4v777+fss88mKysLr9eLYRhMmzaNli1bMmXKFCtIsWnTJnJycqipqWHSpElUV1fj9XqZOHEibdu2pVOnTqxZs8Zal3/+859kZGSwevVq7HZ7Pe4VERER+TUUwBAREZEGbceOHWzdupXevXtTUlJCnz59WL16NSEhIT9p/pUrV7J9+3ZGjhx5ktdURERETiYFMERERKRBc7vdjBkzhqKiInw+HzfddBP9+/f/SfPOnj2b3Nxc5s2bZ/WLISIiIqcnBTBEREREREREpMFTJ54iIiIiIiIi0uApgCEiIiIiIiIiDZ4CGCIiIiIiIiLS4CmAISIiIiIiIiINngIYIiIiIiIiItLg/T9dDQgFSlwPrgAAAABJRU5ErkJggg==\n"},"metadata":{}}]},{"metadata":{"dc":{"key":"46"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 7. 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>\n<p>Let's filter out these junk apps and re-do our visualization. The distribution of apps under \\$20 becomes clearer.</p>"},{"metadata":{"dc":{"key":"46"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"# Select apps priced below $100\napps_under_100 = popular_app_cats[popular_app_cats['Price'] < 100]\n\nfig, ax = plt.subplots()\nfig.set_size_inches(15, 8)\n\n# Examine price vs category with the authentic apps\nax = sns.stripplot(x = popular_app_cats['Category'], y = popular_app_cats['Price'], data=apps_under_100,\n                   jitter=True, linewidth=1)\nax.set_title('App pricing trend across categories after filtering for junk apps')","execution_count":86,"outputs":[{"output_type":"execute_result","execution_count":86,"data":{"text/plain":"Text(0.5, 1.0, 'App pricing trend across categories after filtering for junk apps')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x576 with 1 Axes>","image/png":"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\n"},"metadata":{}}]},{"metadata":{"dc":{"key":"53"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 8. Popularity of paid apps vs free apps\n<p>For apps in the Play Store today, there are five types of pricing strategies: free, freemium, paid, paymium, and subscription. Let's focus on free and paid apps only. Some characteristics of free apps are:</p>\n<ul>\n<li>Free to download.</li>\n<li>Main source of income often comes from advertisements.</li>\n<li>Often created by companies that have other products and the app serves as an extension of those products.</li>\n<li>Can serve as a tool for customer retention, communication, and customer service.</li>\n</ul>\n<p>Some characteristics of paid apps are:</p>\n<ul>\n<li>Users are asked to pay once for the app to download and use it.</li>\n<li>The user can't really get a feel for the app before buying it.</li>\n</ul>\n<p>Are paid apps installed as much as free apps? It turns out that paid apps have a relatively lower number of installs than free apps, though the difference is not as stark as I would have expected!</p>"},{"metadata":{"dc":{"key":"53"},"tags":["sample_code"],"trusted":true},"cell_type":"code","source":"trace0 = go.Box(\n    # Data for paid apps\n    y=apps[apps['Type'] == 'Paid']['Installs'],\n    name = 'Paid'\n)\n\ntrace1 = go.Box(\n    # Data for free apps\n    y=apps[apps['Type'] == 'Free']['Installs'],\n    name = 'Free'\n)\n\nlayout = go.Layout(\n    title = \"Number of downloads of paid apps vs. free apps\",\n    yaxis = dict(\n        type = 'log',\n        autorange = True\n    )\n)\n\n# Add trace0 and trace1 to a list for plotting\ndata =[trace0,trace1]\nplotly.offline.iplot({'data': data, 'layout': layout})","execution_count":90,"outputs":[{"output_type":"display_data","data":{"application/vnd.plotly.v1+json":{"data":[{"name":"Paid","y":[100000,100000,100000,10000,1000,50,100,100,100,1000,1000,500000,100000,100000,100000,10000,50000,100000,10000,100000,100000,100000,100000,100000,100000,100000,100000,100000,100000,5000,5000,1000,500,100000,10000,10000,1000,1000,1000,100,100,1000,5000,5000,1000,10000,10000,5000,1000,10000,10000,50000,10000000,1000000,100000,10000,10000,10000,10000,10000,5000,5000,100000,50000,1000,10000,50000,1000,1000,10000,1000,1000,1000,100,5000,5000,500,1000,10000,1000,100,1000,500,5000,1000,500,1000,5000,10000,1000,10000,100,1000,5000,10000,1000,1000,100,50000,1000,1000,5000,5000,1000,10000,50,1000,10000,1000,1000,500,500,1000,5000,1000,100,1,50,10,1,1000000,100000,100000,50000,1000000,1000000,10000,10000,100000,100000,100000,100,100,5000,1000,100,1000,500,50000,10000,10000,10000000,100000,100000,100000,10000,10,100000,500000,5,10,10,500,5000,1000,1000,100,100,5000,5000,500,5000,10,500,100,5000,500,100,10000,50000,1,1000000,10,10000,500,1000,100,1000,10000,10000,100000,1000,5000,100000,10000,1000,10000,1000,10000,100000,1000,5000,10000,10000,10000,10000,100,100,5000,100,5,100,1000,100,10,500,1,100,10000,10,0,100,100,1,100,5000,500,10,5000,100,50,1000,50000,100000,100000,50000,100,1000,1000,100,10000,100000,10000,5000,5000,10000,1000,10000,5000,10000,100000,50,50000,50000,10000,500,1000,10000,5000,10000,1000,10000,5000,50,10000,1000,100000,10000,50000,1000,1000000,10000,100,10,50000,10000,500000,1000,10000,10000,50000,10000,10000,100000,1000,10000,5000,100,1000,10000,1000,10,100000,1000,5000,100,500,5000,1,100,5000,1000,100,500,50000,100,10,100,50,10,50,10,10,0,10000,100000,10000,10000,50000,1000,1000,5000,1000,10000,5000,1000,10000,10000,5000,5000,1000,100000,100000,1000,1000,10,100,500,100,5,10,0,10,1000000,1,1000,1000000,50000,500000,1000000,100000,100000,100000,10000,1000,5000,100,1000,100,10000,100000,1000,10,1,1,10,1,1000,1000,1000,500,1000,1,5,100,10,0,5000,1000,1000,100,50,50000,10,50,100000,100000,1000,1000,1000,5000,50000,500,5000,10,100000,50000,10000,100,100000,50000,100000,50000,1,10,500,100,100,10000,50,5,10,100,50,100,500,10000,500,1000,500,1000,1000,10,5000,1000,100000,1000,1000,100,10,1000,1000,100,1000,50,1000,1,1000000,100000,5000,0,50000,10,50,1000,1000,10000,10,5,500,100000,1000,1000,100000,1000,500000,10000,100,1000,1000,1000,100,100,100,500,500,10000,100,1000,10000,10000,100,50,1000,1,1000,1000,1000,10,5000,500,50000,5,1000,50,10,10,1000,1000000,100000,10000,10000,50000,1000,10000,10,10,5,1000000,100,10,10,10,100000,10000,10000,100,10000,100000,100000,100000,10000,10000,50000,10000,10000,5000,100,100,1000,10,100,10,500,100,100,100,500000,100,10,10,100,100,1000,50,100,100,50000,1000,1000,100,100,5000,100,100,10000,5000,5000,100,10,10,1,1000,500,10000,1000,100000,10,10,10,1000,10,1000,1,5,10,100000,100000,10000,10000,500,50,500,10,10,1,50000,50,5000,10,10000,10,10,10,100,100,10000,50,1000,100,10,500000,1000,1,50000,10,1000,5,50,5000,10000,10,5000,1000,50000,50000,10000,10000,100000,10000,100000,100000,100000,1000,10000,500,50000,100000,100,1000,10000,50000,100000,50000,1000000,100,50,10000,10,50,1000000,100000,1000,10000,100000,5000,10000,1000,100,10000,5000,100000,100,10,500,50,50,50,10,100,50,500,10000,10000,10,1,1,1000000,500000,1000000,1000000,5,1000,1000,500,100,10000,1000,50,0,50000,50,10000,1000,500000,1000,100000,10000,1000,10000,1000,5000,1000,100000,10000,1000,100,100,1000000,500,50000,1000,50,100,100000,50,500,0,100000,10,500000,500,50000,1000,10000,0,10,0,100,10000,0,1000000,10000,100000,100000,500000,10000,50000,5000,5000,1000,5000,5000,5000,5000,50,100,500,100000,100,50000,100,10000,10000,10000,1000,1000,1000,100,5000,100,100000,10000,1000,1000,5000,5000,100000,10,10,10,10,10,10,5,10,50,100000,1000000,100,1,100,1000,10000,10000,50],"type":"box","uid":"c81fa6e5-15ec-4bff-b6fb-63d885b8afff"},{"name":"Free","y":[10000,500000,5000000,50000000,100000,50000,50000,1000000,1000000,10000,1000000,1000000,10000000,100000,100000,5000,500000,10000,5000000,10000000,100000,100000,500000,100000,50000,10000,500000,100000,10000,100000,100000,50000,100000,100000,10000,100000,500000,5000000,10000,500000,10000,100000,10000000,100000,10000,10000000,100000,100000,100000,100000,1000000,100000,1000000,100000,100000,100000,50000,100000,100000,100000,10000,100000,1000000,100000,100000,10000,50000,5000000,100000,5000000,5000000,500000,10000000,100000,500000,50000,100000,1000000,100000,1000000,50000,1000000,500000,100000,1000000,1000000,100000,100000,1000000,100000,100000,1000000,1000000,1000000,1000000,500000,500000,100000,500000,1000000,100000,500000,1000000,500000,100000,1000000,50000,1000000,10000,1000000,100000,10000,50000,100000,10000,10000,10000,10000000,500000,1000000,50000,10000,1000000,50000,500000,500000,100000,10000,5000,10000,10000,100000,5000,100000,10000,10000,1000000,50000,10000,100000000,50000,100000,10000000,100000000,10000000,10000000,10000000,100000,100000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100000, 1000, 5000, 10000, 10000, 5000, 50000, 1000000, 1000, 1000, 10, 50000, 1, 100000, 100000, 500, 100, 100000, 1000, 100, 10, 10, 1, 10, 100000, 10000, 10000, 1000, 10000000, 50000, 10000000, 50000, 50000, 500, 50000, 50000, 50000, 1000000, 500000, 1000, 100000, 1000000, 1000000, 100000, 5000, 1000, 10000, 1000000, 100000, 100, 500, 100, 50000, 1000000, 100, 100, 1000, 10000, 50000, 500000, 100, 100000, 10000, 5000, 1000, 50, 10, 100, 10000, 100, 5000000, 5000, 10000, 10000, 100000, 5000, 100000, 1000, 500, 10, 5000, 100, 1000, 1000, 10000000], \"type\": \"box\", \"uid\": \"5a49280a-0ad1-4df5-a356-e7343ad4743c\"}], {\"title\": \"Number of downloads of paid apps vs. free apps\", \"yaxis\": {\"autorange\": true, \"type\": \"log\"}}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"2f9d1faf-8daf-45ee-b7c5-b8ae28327ea5\"));});</script>"},"metadata":{}}]},{"metadata":{"dc":{"key":"60"},"deletable":false,"editable":false,"run_control":{"frozen":true},"tags":["context"]},"cell_type":"markdown","source":"## 9. Sentiment analysis of user reviews\n<p>Mining user review data to determine how people feel about your product, brand, or service can be done using a technique called sentiment analysis. User reviews for apps can be analyzed to identify if the mood is positive, negative or neutral about that app. For example, positive words in an app review might include words such as 'amazing', 'friendly', 'good', 'great', and 'love'. Negative words might be words like 'malware', 'hate', 'problem', 'refund', and 'incompetent'.</p>\n<p>By plotting sentiment polarity scores of user reviews for paid and free apps, we observe that free apps receive a lot of harsh comments, as indicated by the outliers on the negative y-axis. Reviews for paid apps appear never to be extremely negative. This may indicate something about app quality, i.e., paid apps being of higher quality than free apps on average. The median polarity score for paid apps is a little higher than free apps, thereby syncing with our previous observation.</p>\n<p>In this notebook, we analyzed over ten thousand apps from the Google Play Store. We can use our findings to inform our decisions should we ever wish to create an app ourselves.</p>"},{"metadata":{"dc":{"key":"60"},"tags":["sample_code"],"trusted":true,"collapsed":true},"cell_type":"code","source":"# Load user_reviews.csv\nreviews_df = pd.read_csv('datasets/user_reviews.csv')\n\n# Join and merge the two dataframe\nmerged_df = pd.merge(apps, reviews_df, on = App, how = \"inner\")\n\n# Drop NA values from Sentiment and Translated_Review columns\nmerged_df = merged_df.dropna(subset=['Sentiment', 'Translated_Review'])\n\nsns.set_style('ticks')\nfig, ax = plt.subplots()\nfig.set_size_inches(11, 8)\n\n# User review sentiment polarity for paid vs. free apps\nax = sns.boxplot(x = ..., y = ..., data = ...)\nax.set_title('Sentiment Polarity Distribution')","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.6.7","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":2}