Android.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 = ', len(apps))\n\n# Have a look at a random sample of 5 rows\nn = 5\napps.sample(n)","execution_count":3,"outputs":[{"output_type":"stream","text":"Total number of apps in the dataset =  9659\n","name":"stdout"},{"output_type":"execute_result","execution_count":3,"data":{"text/plain":"      Unnamed: 0                            App        Category  Rating  \\\n1181        1458           Yongqing fast search  HOUSE_AND_HOME     3.7   \n4581        5552                       Super AR          FAMILY     3.8   \n447          517  Christian Dating For Free App          DATING     3.9   \n359          405  mysms SMS Text Messaging Sync   COMMUNICATION     4.3   \n7598        8706  Latest DP and Status Pro 2018          FAMILY     4.7   \n\n      Reviews  Size    Installs  Type Price Content Rating         Genres  \\\n1181     1437   NaN    100,000+  Free     0       Everyone   House & Home   \n4581      410   28M     10,000+  Free     0           Teen  Entertainment   \n447      8722   13M    500,000+  Free     0     Mature 17+         Dating   \n359     37320  8.4M  1,000,000+  Free     0       Everyone  Communication   \n7598       19  5.7M      1,000+  Free     0       Everyone  Entertainment   \n\n           Last Updated         Current Ver         Android Ver  \n1181     August 2, 2018  Varies with device  Varies with device  \n4581  December 18, 2017                 2.1          4.0 and up  \n447       June 20, 2018                15.8          4.1 and up  \n359       July 30, 2018               6.5.1        4.0.3 and up  \n7598    January 5, 2018               1.0.4        4.0.3 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>1181</th>\n      <td>1458</td>\n      <td>Yongqing fast search</td>\n      <td>HOUSE_AND_HOME</td>\n      <td>3.7</td>\n      <td>1437</td>\n      <td>NaN</td>\n      <td>100,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>House &amp; Home</td>\n      <td>August 2, 2018</td>\n      <td>Varies with device</td>\n      <td>Varies with device</td>\n    </tr>\n    <tr>\n      <th>4581</th>\n      <td>5552</td>\n      <td>Super AR</td>\n      <td>FAMILY</td>\n      <td>3.8</td>\n      <td>410</td>\n      <td>28M</td>\n      <td>10,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Teen</td>\n      <td>Entertainment</td>\n      <td>December 18, 2017</td>\n      <td>2.1</td>\n      <td>4.0 and up</td>\n    </tr>\n    <tr>\n      <th>447</th>\n      <td>517</td>\n      <td>Christian Dating For Free App</td>\n      <td>DATING</td>\n      <td>3.9</td>\n      <td>8722</td>\n      <td>13M</td>\n      <td>500,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Mature 17+</td>\n      <td>Dating</td>\n      <td>June 20, 2018</td>\n      <td>15.8</td>\n      <td>4.1 and up</td>\n    </tr>\n    <tr>\n      <th>359</th>\n      <td>405</td>\n      <td>mysms SMS Text Messaging Sync</td>\n      <td>COMMUNICATION</td>\n      <td>4.3</td>\n      <td>37320</td>\n      <td>8.4M</td>\n      <td>1,000,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Communication</td>\n      <td>July 30, 2018</td>\n      <td>6.5.1</td>\n      <td>4.0.3 and up</td>\n    </tr>\n    <tr>\n      <th>7598</th>\n      <td>8706</td>\n      <td>Latest DP and Status Pro 2018</td>\n      <td>FAMILY</td>\n      <td>4.7</td>\n      <td>19</td>\n      <td>5.7M</td>\n      <td>1,000+</td>\n      <td>Free</td>\n      <td>0</td>\n      <td>Everyone</td>\n      <td>Entertainment</td>\n      <td>January 5, 2018</td>\n      <td>1.0.4</td>\n      <td>4.0.3 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":5,"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":7,"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":"edf0a8fc-a532-447f-ba85-2fe382a190b9"}],"layout":{},"config":{"showLink":true,"linkText":"Export to plot.ly","plotlyServerURL":"https://plot.ly"}},"text/html":"<div id=\"4d82a719-cd07-4bd7-a301-300c821cb695\" 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(\"4d82a719-cd07-4bd7-a301-300c821cb695\", [{\"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\": \"b723c036-41cb-42f0-b96c-0e5ece19557f\"}], {}, {\"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(\"4d82a719-cd07-4bd7-a301-300c821cb695\"));});</script>","text/vnd.plotly.v1+html":"<div id=\"4d82a719-cd07-4bd7-a301-300c821cb695\" 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(\"4d82a719-cd07-4bd7-a301-300c821cb695\", [{\"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\": \"b723c036-41cb-42f0-b96c-0e5ece19557f\"}], {}, {\"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(\"4d82a719-cd07-4bd7-a301-300c821cb695\"));});</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":9,"outputs":[{"output_type":"stream","text":"Average app rating =  4.173243045387994\n","name":"stdout"},{"output_type":"display_data","data":{"application/vnd.plotly.v1+json":{"data":[{"x":[4.1,3.9,4.7,4.5,4.3,4.4,3.8,4.1,4.4,4.7,4.4,4.4,4.2,4.6,4.4,3.2,4.7,4.5,4.3,4.6,4,4.1,4.7,null,4.7,4.8,4.7,4.1,3.9,4.1,4.2,4.1,4.5,4.2,4.7,3.8,4.7,4.1,4.7,4,4.2,4.5,4.4,3.8,4.2,4.7,4.6,4.2,4.3,4.2,4,3.8,4.6,3.9,4.3,4.9,4.4,4.2,4,3.9,4.6,4.9,4.3,4.6,4.9,3.9,4,4.3,3.9,4.2,4.8,3.6,4.2,4.8,4.8,4.6,4.5,4.3,4.5,4.9,3.9,4.4,4,4.3,3.7,4.4,4.3,3.2,4.6,4.6,4.5,3.7,4.6,4.6,4.6,4,4.4,4,4.7,4.9,4.7,3.9,3.9,4.2,4.6,4.3,4.7,4.7,4.8,4.2,4.3,4.5,4.1,null,4.2,4.5,4.4,4,4.1,4.1,4.4,4.6,4.5,null,3.9,4.4,null,4.6,3.8,null,null,4,4.3,4.5,null,4.1,3.7,4.7,4.2,4.6,4.5,4.6,4.4,4.2,4.5,4.5,4.5,4.5,4.4,4.5,4.6,4.8,3.9,4.6,4.2,4.1,4.7,4.2,4.3,3.3,4.6,4.8,4.7,null,4.1,4.6,4.1,4.6,4.7,4.5,3.9,4.4,4.3,4.2,4.5,4.4,3.4,4.9,4.6,4.4,null,4.4,4.4,4.4,3.5,null,4.4,4.1,4.3,4.4,4.3,4.3,4.1,4.4,4.3,3.9,4.8,4.5,4.4,4,4.3,4,4.2,4.5,4.2,4.2,4.6,4.1,4.6,3.1,3.9,4.3,4.1,4.4,4.1,4.1,4.5,4.4,4.4,4.3,4.4,4.6,4.2,4.4,4.7,3.8,3.9,null,4.3,4.4,4.7,4.5,4.2,4.7,4.8,4.2,4.3,4.4,4.1,3.8,4.3,3.8,3.5,4.1,4.6,4.3,4.5,4.1,4.5,4.6,4,4.2,4.4,4,4.2,4.2,4.1,3.8,3.9,3.9,4.5,4.5,4.6,4.7,4.7,4.8,3.9,4.1,4.4,4.6,4.5,4.7,4.4,4.5,3.9,3.2,3.2,4.1,4.5,4.2,4.2,3.7,4.5,4.6,4.5,null,4.7,4.4,3.5,3.3,4.5,4.4,4.2,5,4.4,4.7,4.4,4.4,4.6,4,4.4,4.3,4.3,4.4,4.3,4,4.3,4.3,4.4,4.3,4.3,4.3,4.3,4.3,4,4.5,4.3,3.7,4.5,3.9,4.4,3.6,4.4,4.2,4.4,4.1,4.4,4.3,4.2,4.2,4.4,4.4,3.9,4.2,4.4,4.6,4.3,4.3,4.4,3.7,4.3,3.9,4.5,3.7,4.3,4,4.1,4.2,4.2,4.1,4.4,4.1,4.3,4.3,4.5,4.3,4.2,4.2,4.5,4.3,4.3,4.3,4.2,4.6,4.2,4.5,4.1,4.2,4.1,4.3,4.1,4.2,4,4.2,4.2,4.3,4.4,4.2,4.4,4.2,4.8,4.4,4.4,4.4,4,4.5,4.4,4.1,4.2,4.5,4.3,4.5,4,4.2,4.5,4.6,4.1,4,4.2,4.6,4.1,4.3,4.2,4.3,4.1,4.6,4.2,2.6,null,null,null,3.5,4,4.1,3.7,4.1,4.2,4.5,4.4,4.2,4,4.1,3.1,4.4,4.2,4.1,3.9,4.3,4.4,3.5,4,3.3,4.5,4.4,4.1,3.9,3.9,3.6,4,3.6,3.4,4.2,4.1,3.4,3,4.6,4.1,3.9,1.9,3.5,2.5,3.9,3.4,3.5,4.4,3.8,4.2,2.5,2.8,4.1,4.2,3.5,4.3,3.3,4.1,4.2,3.5,4.2,4.4,4.1,4.2,4.3,3,4,3.3,4.1,3.7,4,4,4.1,3.3,4.4,4.3,3.4,4,3.6,4.2,3.5,4,4.1,4.4,4.2,4.1,4.2,3.9,4.1,3.9,4,4.2,4.5,3.9,3.6,4.4,3.5,4.4,4.8,4.6,4.7,4.8,null,2.7,5,null,4.8,5,4.8,null,4.9,3,null,null,4.7,null,null,1,null,null,null,null,null,null,null,5,4.7,null,5,null,null,null,5,null,null,null,null,3,4.1,null,null,null,null,null,null,null,5,3.7,4.5,4.2,null,null,null,4.3,null,4.4,3.4,4.7,4.8,4.7,3.5,4.7,3.8,2.9,null,4.7,4.6,4.7,4.6,4.7,null,4.5,4.7,4.8,4.6,4.6,4.6,4.2,4.9,3.8,4.2,4.4,4.4,4.3,4.5,4.4,4.6,3.9,4.4,4.3,4.4,4.2,4.4,4,4.2,3.8,4.5,4.7,4.5,4.3,4.2,4.3,4.7,4.7,4.6,4.5,4.4,4.6,4.5,4.5,4.4,4.4,4.2,4.5,4.1,4,4.1,4.3,4.3,4.3,4.6,4.1,4.6,4.7,4.7,4.3,4.7,4.6,4.6,4.6,4.3,4.2,4,4.5,4.2,4.1,4.4,4,4.5,4.4,4,4.2,4.3,4.2,4.5,4.2,4.6,4.2,4.7,4.4,4.4,4,4.6,4.4,4.3,4.1,4.2,4.3,4.3,4.3,4,4.2,4,4,3.8,4.1,3.9,4.1,4.5,4.4,4,4.4,4.5,4.3,4.5,4.2,3.5,4.8,4.4,4.1,4.9,4.7,4.7,4.7,4.4,4,4.2,4.3,4.5,3.5,4.2,3.1,4.6,4.2,4.3,4.3,4.1,3.8,3.4,4.3,4.4,4.4,4,3.7,3.9,4.5,4.4,4.3,4.2,4.2,4.5,4.7,4.5,4.5,3.4,4.2,4.3,4.2,4.6,4.1,4.2,4.2,4.3,4.4,3.9,4.1,4.3,4.6,3.6,4.3,4.3,4.1,4.1,4.2,3.9,4.2,3.7,4.5,3.7,3.8,4.3,3,4.1,4.2,4.1,3.9,4,4.4,4.2,4,3.9,4,4.2,4,4.3,3.9,4.5,4.1,4.5,3.6,3.8,3.7,3.8,3.7,4.1,3.7,3.9,3.9,3.9,4.1,3.9,4.2,4.3,4.6,4.3,4.6,4.5,4.6,3.9,4.2,4.4,4.2,4.3,4.6,4.3,4.5,4,4,4.5,4.5,4,4,4.2,4.4,4.6,null,4.6,4.1,4.6,4.4,4.6,4.9,4.5,4.6,4.7,4.3,null,null,4.2,4.3,5,4.4,5,4.5,null,null,null,4.5,4.8,4.4,5,null,3.7,null,4.1,null,4.8,null,null,4.6,4.4,4.4,3.6,3.7,3.8,4.2,4.2,4.2,3.3,3.4,4.3,4.2,4.7,4.1,4.7,4,3.6,4,3.6,4.3,4.2,4.2,4.1,4,4.1,4.4,4.7,4.5,4.3,4.6,4.3,4,4.5,4.5,3.6,4.2,4.1,3.5,4.4,4,4.5,4.2,4.6,4.2,4.8,4.5,4.2,4.3,4.4,4.4,4.6,4.6,4.6,4.4,4.3,4.2,4.2,3.8,4.5,4.6,4.6,4.7,4.6,4.6,3.8,4.3,4.3,4.5,4.6,4.6,4.7,4.5,4.4,3.9,4.5,4.6,4.1,4.5,4.4,4.5,4.6,4.2,4.4,4.1,3.9,4.5,3.7,4.1,4.4,4.6,4.3,4.3,4.4,4.3,4.4,4.1,4.4,4.2,4.3,4.3,3.9,4.1,4.1,4.2,4.5,4.7,4.4,4.6,4.6,4.3,4,4.4,4.6,4.2,4.1,3.6,null,4.1,4.6,null,4.7,4.7,4.7,4.7,4.1,3.4,3.8,3.7,4.2,3.1,3.5,4.7,4.5,4.2,4.3,4,4.5,4.6,4.7,4.1,4.3,3.8,4.4,4.3,4.2,4.3,3.8,4.3,3.7,4.5,3.6,4.8,3.3,4.7,4.6,4.6,3.4,4.6,4,4.1,4.5,4.4,4.5,4,4.1,4.5,4.6,4.1,4.5,4.6,4.5,4.3,3.6,4.4,4.6,4.1,4.3,3.9,4.1,4.3,4.7,4.6,4.4,4.2,4.5,4.2,4.5,4.5,4.3,4,4.8,4,4.9,4.8,4.9,4.8,4.4,3.3,4.7,4.6,4.8,4.8,4.8,4.5,4.4,4.5,4.5,4.5,4.8,3.9,4.6,4.5,4.5,4.7,4.7,4.4,4.2,3.9,4.2,4.4,4.6,4.6,4.2,4.5,4.7,4.5,4.5,3.7,4.5,4.6,4.6,4.7,4.5,4.5,4.6,4,4.3,4.4,4.5,4.2,4.6,4.9,4.5,4.6,4.5,4.6,4.6,4.5,4.5,4.4,3.9,4.6,4.4,4.5,4.5,4.4,4.4,4.4,4.2,4.5,4.5,4.4,4.3,4.6,4.6,4.9,4.4,4.3,4.1,4.6,4.8,4.5,4.7,4.6,4.3,4.6,4.3,4.6,4.6,4.5,4.6,4.6,4.5,4.1,4.5,4.6,4.5,4.8,4.8,4.5,4.1,4.4,4.2,4.5,4.3,4.6,4,4.6,4.6,4.4,4.7,4.4,4.4,4.4,4.5,4,4.6,4.1,4,4.4,4.4,4.1,3.5,4.3,4.5,4.2,4.5,4.1,4.5,3.7,4.3,4.5,4.6,4.7,4.6,4,4.4,4.8,4.2,4.1,4.4,4.3,4.5,4.8,4.2,4.5,4.1,4.1,4,4.3,4.5,null,4.6,3.7,3.7,4.2,4.5,4.3,3.9,4.6,4.3,4.4,4.6,4.5,3.8,null,4.4,4.7,3.4,4.3,4.3,4,4,3.8,null,4.3,3.6,3.8,4.5,4.6,null,4.5,4.7,4.3,3.7,null,4.2,3.4,3.9,4,4,4,4,4.1,3.9,4.4,4.4,4.3,4.1,3.9,4.4,4.6,null,4.1,null,null,3.8,4.6,3.5,4.7,4.3,4.5,4.4,3.4,4.3,null,4.3,4.6,4.6,nu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\"9e08ba48-1114-4939-a314-af3a4d8b5c12\"}], {\"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(\"0bdacee2-997b-44b1-8750-6685bd335e19\"));});</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# Subset for categories with at least 250 apps\nlarge_categories = apps.groupby('Category').filter(lambda x: len(x) >= 250).reset_index()\n\n# Plot size vs. rating\nplt1 = sns.jointplot(x = large_categories['Size'], y = large_categories['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":11,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x432 with 3 Axes>","image/png":"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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['Price'], y = popular_app_cats['Category'], 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":13,"outputs":[{"output_type":"execute_result","execution_count":13,"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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\n"},"metadata":{"needs_background":"light"}}]},{"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=apps_under_100['Price'], y=apps_under_100['Category'],\n                   jitter=True, linewidth=1)\nax.set_title('App pricing trend across categories after filtering for junk apps')","execution_count":15,"outputs":[{"output_type":"execute_result","execution_count":15,"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":{"needs_background":"light"}}]},{"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":17,"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":"f582b572-f8fc-41ec-9d16-b2c8ae0da0b6"},{"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\": \"f09807b5-06b7-4de3-9e08-38f26741249a\"}], {\"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(\"1bae11a3-f509-4b6a-bd2b-eb478816dc3f\"));});</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},"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)\nprint(merged_df.head())\n# User review sentiment polarity for paid vs. free apps\nax = sns.boxplot(x = reviews_df['Type'], y = reviews_df['Sentiment'], data = merged_df)\nax.set_title('Sentiment Polarity Distribution')","execution_count":19,"outputs":[{"output_type":"stream","text":"   Unnamed: 0                  App        Category  Rating  Reviews  Size  \\\n0           1  Coloring book moana  ART_AND_DESIGN     3.9      967  14.0   \n1           1  Coloring book moana  ART_AND_DESIGN     3.9      967  14.0   \n2           1  Coloring book moana  ART_AND_DESIGN     3.9      967  14.0   \n4           1  Coloring book moana  ART_AND_DESIGN     3.9      967  14.0   \n5           1  Coloring book moana  ART_AND_DESIGN     3.9      967  14.0   \n\n   Installs  Type  Price Content Rating                     Genres  \\\n0    500000  Free    0.0       Everyone  Art & Design;Pretend Play   \n1    500000  Free    0.0       Everyone  Art & Design;Pretend Play   \n2    500000  Free    0.0       Everyone  Art & Design;Pretend Play   \n4    500000  Free    0.0       Everyone  Art & Design;Pretend Play   \n5    500000  Free    0.0       Everyone  Art & Design;Pretend Play   \n\n       Last Updated Current Ver   Android Ver  \\\n0  January 15, 2018       2.0.0  4.0.3 and up   \n1  January 15, 2018       2.0.0  4.0.3 and up   \n2  January 15, 2018       2.0.0  4.0.3 and up   \n4  January 15, 2018       2.0.0  4.0.3 and up   \n5  January 15, 2018       2.0.0  4.0.3 and up   \n\n                                   Translated_Review Sentiment  \\\n0  A kid's excessive ads. The types ads allowed a...  Negative   \n1                                         It bad >:(  Negative   \n2                                               like   Neutral   \n4                           I love colors inspyering  Positive   \n5                                             I hate  Negative   \n\n   Sentiment_Polarity  Sentiment_Subjectivity  \n0              -0.250                1.000000  \n1              -0.725                0.833333  \n2               0.000                0.000000  \n4               0.500                0.600000  \n5              -0.800                0.900000  \n","name":"stdout"},{"output_type":"error","ename":"KeyError","evalue":"'Type'","traceback":["---------------------------------------------------------------------------","KeyError                                  Traceback (most recent call last)","/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)\n   3077             try:\n-> 3078                 return self._engine.get_loc(key)\n   3079             except KeyError:\n","pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()\n","pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()\n","pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()\n","pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()\n","KeyError: 'Type'","\nDuring handling of the above exception, another exception occurred:\n","KeyError                                  Traceback (most recent call last)","<ipython-input-19-ee3beac258da> in <module>\n     13 print(merged_df.head())\n     14 # User review sentiment polarity for paid vs. free apps\n---> 15 ax = sns.boxplot(x = reviews_df['Type'], y = reviews_df['Sentiment'], data = merged_df)\n     16 ax.set_title('Sentiment Polarity Distribution')\n","/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py in __getitem__(self, key)\n   2686             return self._getitem_multilevel(key)\n   2687         else:\n-> 2688             return self._getitem_column(key)\n   2689 \n   2690     def _getitem_column(self, key):\n","/usr/local/lib/python3.6/dist-packages/pandas/core/frame.py in _getitem_column(self, key)\n   2693         # get column\n   2694         if self.columns.is_unique:\n-> 2695             return self._get_item_cache(key)\n   2696 \n   2697         # duplicate columns & possible reduce dimensionality\n","/usr/local/lib/python3.6/dist-packages/pandas/core/generic.py in _get_item_cache(self, item)\n   2487         res = cache.get(item)\n   2488         if res is None:\n-> 2489             values = self._data.get(item)\n   2490             res = self._box_item_values(item, values)\n   2491             cache[item] = res\n","/usr/local/lib/python3.6/dist-packages/pandas/core/internals.py in get(self, item, fastpath)\n   4113 \n   4114             if not isna(item):\n-> 4115                 loc = self.items.get_loc(item)\n   4116             else:\n   4117                 indexer = np.arange(len(self.items))[isna(self.items)]\n","/usr/local/lib/python3.6/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance)\n   3078                 return self._engine.get_loc(key)\n   3079             except KeyError:\n-> 3080                 return self._engine.get_loc(self._maybe_cast_indexer(key))\n   3081 \n   3082         indexer = self.get_indexer([key], method=method, tolerance=tolerance)\n","pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()\n","pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_loc()\n","pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()\n","pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.get_item()\n","KeyError: 'Type'"]},{"output_type":"display_data","data":{"text/plain":"<Figure size 792x576 with 1 Axes>","image/png":"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\n"},"metadata":{}}]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 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