Python/The Android App Market on Google Play/The Android App Market on Google Play.ipynb

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    "## 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>"
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   "source": [
    "# Read in dataset\n",
    "import pandas as pd\n",
    "apps_with_duplicates = pd.read_csv('datasets/apps.csv')"
   ]
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     "text": [
      "Total number of apps in the dataset =  9659\n"
     ]
    },
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       "    <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",
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       "      <th>3372</th>\n",
       "      <td>4256</td>\n",
       "      <td>The J-Notes: Jazz News</td>\n",
       "      <td>SPORTS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>7.2M</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone 10+</td>\n",
       "      <td>Sports</td>\n",
       "      <td>February 28, 2018</td>\n",
       "      <td>5.2.2</td>\n",
       "      <td>4.1 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9410</th>\n",
       "      <td>10585</td>\n",
       "      <td>FL House</td>\n",
       "      <td>PRODUCTIVITY</td>\n",
       "      <td>4.4</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Productivity</td>\n",
       "      <td>November 22, 2016</td>\n",
       "      <td>1.6.7</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5841</th>\n",
       "      <td>6873</td>\n",
       "      <td>PIO bv App</td>\n",
       "      <td>BUSINESS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>98M</td>\n",
       "      <td>10+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Business</td>\n",
       "      <td>August 1, 2018</td>\n",
       "      <td>2.6.0</td>\n",
       "      <td>4.1 and up</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9281</th>\n",
       "      <td>10453</td>\n",
       "      <td>Talkie Pro - Wi-Fi Calling, Chats, File Sharing</td>\n",
       "      <td>COMMUNICATION</td>\n",
       "      <td>4.5</td>\n",
       "      <td>201</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1,000+</td>\n",
       "      <td>Paid</td>\n",
       "      <td>$2.99</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Communication</td>\n",
       "      <td>January 6, 2018</td>\n",
       "      <td>Varies with device</td>\n",
       "      <td>Varies with device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1066</th>\n",
       "      <td>1295</td>\n",
       "      <td>Abs Workout - 30 Days Fitness App for Six Pack...</td>\n",
       "      <td>HEALTH_AND_FITNESS</td>\n",
       "      <td>4.6</td>\n",
       "      <td>299</td>\n",
       "      <td>11M</td>\n",
       "      <td>100,000+</td>\n",
       "      <td>Free</td>\n",
       "      <td>0</td>\n",
       "      <td>Everyone</td>\n",
       "      <td>Health &amp; Fitness</td>\n",
       "      <td>August 3, 2018</td>\n",
       "      <td>1.3.8</td>\n",
       "      <td>4.4 and up</td>\n",
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       "      Unnamed: 0                                                App  \\\n",
       "3372        4256                             The J-Notes: Jazz News   \n",
       "9410       10585                                           FL House   \n",
       "5841        6873                                         PIO bv App   \n",
       "9281       10453    Talkie Pro - Wi-Fi Calling, Chats, File Sharing   \n",
       "1066        1295  Abs Workout - 30 Days Fitness App for Six Pack...   \n",
       "\n",
       "                Category  Rating  Reviews  Size  Installs  Type  Price  \\\n",
       "3372              SPORTS     NaN        7  7.2M    1,000+  Free      0   \n",
       "9410        PRODUCTIVITY     4.4       29   NaN    1,000+  Free      0   \n",
       "5841            BUSINESS     NaN        2   98M       10+  Free      0   \n",
       "9281       COMMUNICATION     4.5      201   NaN    1,000+  Paid  $2.99   \n",
       "1066  HEALTH_AND_FITNESS     4.6      299   11M  100,000+  Free      0   \n",
       "\n",
       "     Content Rating            Genres       Last Updated         Current Ver  \\\n",
       "3372   Everyone 10+            Sports  February 28, 2018               5.2.2   \n",
       "9410       Everyone      Productivity  November 22, 2016               1.6.7   \n",
       "5841       Everyone          Business     August 1, 2018               2.6.0   \n",
       "9281       Everyone     Communication    January 6, 2018  Varies with device   \n",
       "1066       Everyone  Health & Fitness     August 3, 2018               1.3.8   \n",
       "\n",
       "             Android Ver  \n",
       "3372          4.1 and up  \n",
       "9410  Varies with device  \n",
       "5841          4.1 and up  \n",
       "9281  Varies with device  \n",
       "1066          4.4 and up  "
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    "# Drop duplicates\n",
    "apps = apps_with_duplicates.drop_duplicates()\n",
    "\n",
    "# Print the total number of apps\n",
    "print('Total number of apps in the dataset = ', apps['App'].count())\n",
    "\n",
    "# Have a look at a random sample of 5 rows\n",
    "n = 5\n",
    "apps.sample(n)"
   ]
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    "## 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>"
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    "# List of characters to remove\n",
    "chars_to_remove = ['+',',','M','$','k']\n",
    "# List of column names to clean\n",
    "cols_to_clean = ['Installs','Size','Price']\n",
    "\n",
    "# Loop for each column\n",
    "for 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]) "
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    "## 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>"
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      "Number of categories =  33\n"
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    "import plotly\n",
    "plotly.offline.init_notebook_mode(connected=True)\n",
    "import plotly.graph_objs as go\n",
    "\n",
    "# Print the total number of unique categories\n",
    "num_categories = len(apps['Category'].unique())\n",
    "print('Number of categories = ', num_categories)\n",
    "\n",
    "# Count the number of apps in each 'Category' and sort them in descending order\n",
    "num_apps_in_category = apps['Category'].value_counts().sort_values(ascending = False)\n",
    "\n",
    "data = [go.Bar(\n",
    "        x = num_apps_in_category.index, # index = category name\n",
    "        y = num_apps_in_category.values, # value = count\n",
    ")]\n",
    "\n",
    "plotly.offline.iplot(data)"
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    "## 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>"
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      "Average app rating =  4.173243045387994\n"
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          4,
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          4,
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          4,
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          4,
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          4,
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          3,
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          4.7,
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          4,
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          4,
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          4,
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          4,
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          4,
          4,
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          4,
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          4,
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          null,
          null,
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          5,
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          5,
          5,
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          4,
          4,
          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          4,
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          3.1,
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          4.5,
          3.2,
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Average rating of apps\n",
    "avg_app_rating = apps['Rating'].mean()\n",
    "print('Average app rating = ', avg_app_rating)\n",
    "\n",
    "# Distribution of apps according to their ratings\n",
    "data = [go.Histogram(\n",
    "        x = apps['Rating']\n",
    ")]\n",
    "\n",
    "# Vertical dashed line to indicate the average app rating\n",
    "layout = {'shapes': [{\n",
    "              'type' :'line',\n",
    "              'x0': avg_app_rating,\n",
    "              'y0': 0,\n",
    "              'x1': avg_app_rating,\n",
    "              'y1': 1000,\n",
    "              'line': { 'dash': 'dashdot'}\n",
    "          }]\n",
    "          }\n",
    "\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "dc": {
     "key": "32"
    },
    "deletable": false,
    "editable": false,
    "run_control": {
     "frozen": true
    },
    "tags": [
     "context"
    ]
   },
   "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>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "dc": {
     "key": "32"
    },
    "tags": [
     "sample_code"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VV19p1qxZevLJJzVixIjg9q1bt+rRRx9VZmamSkpKNGfOnESVEFL7cU/tZyLvTqR2cmY0B5AM0QzUTeeBuZ0lJKC8Xq9WrVql3NzcLtvXrVunjRs3Ki8vT2VlZZo8ebJOP/30uB27u7unQAvo+f8wIC6t47SgA30XbeaJlZDPoCoqKjR37lwNGjSow/YDBw5oyJAhGjBggLKzs3XRRRdp165dcT12NG3mv/+wJm6t47SgA30XbeaJFfc7qBdffFEDBw7U+PHjtX79+g77PB6P3G538Ot+/frJ4/F0+54ul6XCwvy41ei3I7eO9+RY0b6Py5UR15+ht0yqx6RaJLPqMakWyax6TKglUpt5ImqzLEv5edkRX5Obk6XCAbkRX5Mu4h5QmzZtkmVZeuedd1RdXa1ly5bpscceU1FRkQoKCtTQ0BB8bUNDQ4fACsfns+O6lHKGJQ0qCD1jebE7p0fHCjfzeef3MW05aJPqMakWyax6TKpFMqseE2oJt6JBhqWoaysq6v4aGGDbthpPtkR8TVOzV3V1kdezM024cxD3R3zPPvusnnnmGW3YsEGjR49WRUWFiorauk5GjBihQ4cOqa6uTi0tLXrvvfd04YUXxvX40bSZXz92cNxax2lBB/ou2swTKylt5q+88ooaGxtVWlqq8vJyLVq0SLZtq6SkRMXF8W0k6K7NvPPs5b3tvqMFHei7kt1m3tdYtm0bPymH1+vr0a18VXWt7n/9Y7X4wv9og905+v7w0/TWZ8eSEiwmPI5oz6R6TKpFMqsek2qRzKrHpFqk2OvpySO+Zq9P+4+eCLkvMP4pP8ulnDSbySLcOXDcQN2q6lrdV7W/27mwauqbO7SH0h4OwHSRxkE5afxTgOOmOqrccTDmiRppDwcAczguoHo7wzgzlAOAGRwXUL2dYZwZygHADI4LqMXjh8Y81T3t4QBgDscF1NTRxbpv6nnKdkVOqcHuHJWcP1iD3Tmy/v71iivPpUECAAzhuC4+Sdp9+HjEFnNLbV17b312LHjHVLnjoH6yeb8qdxxkHBPQCTP2h7f4+Q+06y+nWr8vOau/KudckMKKnMNxAdV5duFQAtFVU9+sn1btl2VZ8v699Y92c6AjZuwPr3M4SdKuv5zQ4uc/IKTiwHEB1dNZhFttSZ3GKgfazfv6Lx8gRZ6xv6//jnQOp+6291akBQsty1KzrbQbpBuJ4wIq1jFQndFuDrSJNGM/kqu7BQsnjRqkHAcN1nVck0SsHXyd0W4OtAn3u8DvCBLNcQHV01mEM622Oazao90cOIUZ+8O75Kz+PdqOnnFcQJVPGamS8yOHVCCOBrtztGrqebr36pG0mwNhTB1drBVXnsvvSAiVcy7oEkZ08cWPI2czDzBptmOTapHMqsekWiSz6jGpFsmsekyqRUrObOZNLa363Y7Pwu5P1wlj+8xs5lLo1s+AXJelZp/NWA4AMJzjAipSOElSk4/xTgCQDhwXUD0Zf8BYDgDpJNI4qMB+J42FclxA9RRjOQCki+7GQUnOGgvluC6+nmIsBwCYyXEB1ZPxB4zlAABzOS6gQo1LaC/XZTGWAwDSgCM/g6qcc0HIbr5Lzuqvj79oVJOvVTX1zfrJ5v1atXm/BtNyDiCCSMuNsBRJ4jgyoMK1mnfe1n7ZDVrOAYQSabkRSSxFkkCOe8QnxTbVfaDlHADai7TcSKR96D1H3kHFipZzAJ3FstwI15L4IKDaoeUcQGfF7hzVhAicwPUi0r546zxQNyvDkqvToNz8LGeMgZIc+ogvlqnuaTkHEEqk5UaSvRRJYKBu4D+XJZ2W7erwn1NmkZAcGlDhWs0vOau/BuSeumlsv+wGLecAQom03AhLkSRWQh7x+Xw+rVy5Up9//rksy9Lq1as1cuTI4P6nnnpKL7zwggYOHChJWr16tYYPHx6344fr4nvvLydkS2HbyqNtF6WtFOhbAmGE5EpIQG3btk2S9Nxzz2nnzp16+OGH9dhjjwX379mzRxUVFRozZkzcjx1pNvNIbeWRWknb/8WM9nUAnI/rQWIl5BHflClTtGbNGknSkSNH1L9/x8dte/fu1fr161VWVqYnnngirseOtsW8cytotO2itJUCCOB6kFgJ6+LLzMzUsmXLtGXLFv3iF7/osG/atGmaN2+eCgoKtGTJEm3btk2TJk0K+14ul6XCwvy411hb3xx830itpO2PHe3rOnO5MhLyM8TKpHpMqkUyqx6TapHMqseEWmK9HsTKsizl52UHv87NyVLhgNy4H8cUCW0zr6io0NKlSzVnzhy9+uqrys/Pl23buummm+R2ty3xO3HiRO3bty9iQPl8dkKWdi525wTfN1IraftjR/u6zpyyPHUimFSLZFY9JtUimVWPCbXEej1orydLvtu2rcaTLcGvm5q9qqvzR/iO9BDuHCTkEd9LL70UfHSXl5cny7KUkdF2KI/Ho+nTp6uhoUG2bWvnzp1x/Swq2hbzzq2g0baLJrutFIC5kn09CIyDCvyXnemcMU+hJOQO6sorr9Ty5ct14403qrW1VStWrNCWLVvU2Nio0tJS3XnnnVqwYIGys7N12WWXaeLEiXE7driJYqW2tvJwXXyBP3fXnRft6wA4X7KvB50XLJw0apD6OWRxwlAs27bt7l+WWl6vr0e38lXVtVr7+sdq8nX90XJdlnKyXDrR1Kpid46+P/w0vfXZsYS3lpvwOKI9k+oxqRbJrHpMqkUyqx6TapFir6cnj/iaWlr1ux2fBb+eNGqQTnNAQIU7B46b6qiqulY/2bxf4VK3yWerydcqqa0ldNPumuA+WssBwByOm0micsfBsOEUDVrLAcAMjguoeMwi3Pk9YpnNGADQO44LqHjMItz5PcK9J7OfA0DiOC6gFo8fqt5M5ktrOQCYwXFNEoGmhXh28dFaDsAEgXFQgXWgnLT2UyiOCyjpVKA8/tYhHTne1GFfq99W+wdz5//DAJVPGanuMJsxgFQLjINySnt5dxwZUJ3bwttrtaXjTafazGkXBwAzOe4zKCl0W3g4tIsDgJkcGVA9bf+mXRwAzOPIgOpp+zft4gBgHkcGVKi28HBoFwcAMzmySSJSF1+mJfXLyQy2mdMuDgBmcmRABWYer6lvVoYl+e3QS2wAAMzluIDq3GLu//tYXVrKAaQ7y7I04bxBjh+gG+C4z6AitZjTUg4gndm2LZcl5fRmPrc04riA6q5lnJZyAEgPjguo7lrGaSkHgPTguICK1GJOSzkApI+omiR++ctfdvg6KytLgwcP1jXXXKOsrKyEFBar9jOP08UHAOkrqoDav3+/cnJydPHFF2v37t06evSoioqK9Oabb+rBBx9MdI09Fph5vLAwX3V1jakuBwAQg6gC6sSJE/rd734nSZo7d64WLlyoBx98UGVlZQktLlYP/OFjbdpdE/w6LytDy684VxJrOgFAuogqoOrr6/X1119r4MCBOnbsmOrr6+X1etXU1NT9NydZ53CSpJNev+6r2q8MtS23ITEuCkD6sSxLlmXpWIsvuC0/y+XYtvOoAuqf//mfNWfOHBUUFKixsVErV67Ub3/7W82ePTvR9fXY7z+sCbndb0udR0cFxkURUADSgW3b2lpd22HbpFGDlOPQxQujCqhJkyZp4sSJ+vrrr/WNb3yjbTTzhAmJri0m/q6rvEfEuCgAMFNUAfXWW2/pqaeeUnPzqYv5008/nbCieiPQtRctxkUBgJmiCqh169ZpxYoVGjx4cKLr6bXrxw7u8hmU1BZc7T+DkhgXBQAmiyqgzjjjDH3ve99LdC1xUT5lpCTRxQcAaS6qgPrGN76hVatW6Vvf+pYsq61dpLS0NOzrfT6fVq5cqc8//1yWZWn16tUaOXJkcP/WrVv16KOPKjMzUyUlJZozZ04vf4yOzv+HAdry0Rc60dzW6XLS69eqzfslSSXnDw6GGADAXFEF1JlnnilJ+vLLL6N6023btkmSnnvuOe3cuVMPP/ywHnvsMUmS1+vVunXrtHHjRuXl5amsrEyTJ0/W6aefHkv9XVRV1+qnVfs7PMprL3BnRUgBgNkiBlRNTY0GDx6sadOm9ehNp0yZoh/84AeSpCNHjqh///7BfQcOHNCQIUM0YMAASdJFF12kXbt2aerUqT0sPbTKHQfDhlPA7z+sIaAAwHARA+q3v/2tli9frlWrVsmyLNl225Xfsqxuu/gyMzO1bNkybdmyRb/4xS+C2z0ej9xud/Drfv36yePxRHwvl8tSYWF+tz+MFF3buN9W1O8XLy5XRtKPGYlJ9ZhUi2RWPSbVIplVj0m1SMmpJyPD0vhRxcrKtJTjahv71C/Hpf65Zs2JGi8RA2r58uWSpJtvvlmTJ08Obt+8eXNUb15RUaGlS5dqzpw5evXVV5Wfn6+CggI1NDQEX9PQ0NAhsELx+eyo59QrdueoppuQyrCU9Dn6TJsX0KR6TKpFMqsek2qRzKrHpFqk2OspKop8/WvP77e146NaTRo1SHkZbf0A/ia/6pq8PT6uScKdg4gBtW3bNv3P//yPXn31VX3wwQeSJL/frz/+8Y+65pprwn7fSy+9pNraWt1yyy3Ky8uTZVnKyGhbAmPEiBE6dOiQ6urqlJ+fr/fee0+LFi2K9efqYvH4oRE/g5LaWtEBAGaLGFCjRo1SXV2dcnJyNGzYMEltj/e6+0zqyiuv1PLly3XjjTeqtbVVK1as0JYtW9TY2KjS0lKVl5dr0aJFsm1bJSUlKi6OX6t3oG38Z3/8NNjF1x5dfACQHiw78MFSBH6/P3gHJEl/+9vfNGjQoIQW1p7X64vp1rmwMF/z1r+tXX85Edx2yVn9VTnngg6vq6quTfj4KKc8jkgEk2qRzKrHpFoks+qJdy29vQ4k4xFfU0urfrfjM00aNUinOWj+vXDnIKoVdR955BF997vf1UUXXaRvf/vbuvnmm+NaXKIs+O1/dwgnSdr1lxNa/PwHwa+rqmu19o1PVFPfLFunZjmv6jQhIwDn4jpgpqgCauvWrdq+fbtmzJihzZs3x/WRXCK989nXIbe3D63KHQfV1NpxnvPALOcA+gauA2aKKqCKioqUnZ2thoYGnX322fJ607tjpL1wbenMcg70HVwHzBRVQA0ePDg488NDDz2k+vr6RNeVNOFmM2eWc6DvSJfrgGVZmnDeIOVnOefzp0giBlRra6veeOMNTZ8+Xd/73vd0zz33KCcnR0OHDk1Seb1z2fCBIbdfctapmS0Wjx+q3MyOp4FZzoG+JV2uA7Zty2XJsSvodhaxzXzp0qVyuVz68ssvdcUVV+jMM8/Uf/zHf2jBggXJqq9Xnr750m67+AJdOsxyDvRdXAfMFDGg/vznP+vFF19US0uLSkpKlJWVpaefflojRoxIVn0xeeAPH+v3H9YEFy7My8pQk9evYneOZvyfM7q8furoYv4iAn0c1wHzRAyogoICSVJ2drb8fr+efPJJFRYWJqWwWD3wh4+7LFh40tvWnRNoHZXEX0QAMFxUTRJS25pQpoeT1DZTeSS0jgJAeoh4B/Xpp5/qrrvukm3bwT8HPPTQQwkvLhb+bufFoHUUANJBxID6t3/7t+Cf586dm/Bi4iHD6j6kTGsdBQB0FTGgLr300mTVETfXjx3c5TOo9kxsHQUAdBXVku/pJDBTebguPlpHAaQry7KUndk3BulKPWiSSCflU0Zq5/83QQ/NHqv+OS6d9PplSzrp7br8BgCkC9u21dLad65jjruDCqiqrtVPX9uv9vM/Hm9q1ZrXPpZEmzkAmM6Rd1BS24jwTpMTS5K8fps2cwBIA44NqEit5LSZA4D5HBtQkVrJaTMHAPM5NqAWjx+qzBA/XVaGRZs5AKQBxwbU1NHFqpjV1sUXMCA3U/dePZIGCQBIA47t4pOka8//piacbf78gQAQjb42DsrRAdVeVXWtKnccVE19c3A6pMEM3AWQRgLjoPpl942Q6hMBVVVdq7VvfKKmv/edB2aYYPkNADCXYz+Daq9yx8FgOHXG8hsAYKY+EVDdjXtiXBQAmKdPBFR3454YFwUA5ukTAbV4/FDlhhoUJZbfAABT9YkmiUADBF18AJA+4h5QXq9XK1as0OHDh9XS0qJbb71Vl19+eXD/U089peYG50oAABKBSURBVBdeeEEDBw6UJK1evVrDhw+PdxmSpJd3H9GDr+9XbX0za0EBQJqJe0C9/PLLKiws1IMPPqi6ujrNnDmzQ0Dt2bNHFRUVGjNmTLwP3UFVda3WbvlETd627j1aygGkuwzLUn5W3xgDJSXgM6irr75at99+u6S2QWUuV8eTuXfvXq1fv15lZWV64okn4n34oModB4PhFEBLOYB05sqwlGOluorkifsdVL9+/SRJHo9Ht912m+64444O+6dNm6Z58+apoKBAS5Ys0bZt2zRp0qSI7+lyWSoszO9RHeFax2vrm3v8XvHgcmWk5LjhmFSPSbVIZtVjUi2SWfWYVIuUnHosq+fXwnSWkCaJo0eP6sc//rHmzZunGTNmBLfbtq2bbrpJbrdbkjRx4kTt27ev24Dy+WzV1TX2qIZid45qQoRUsTunx+8VD4WF+Sk5bjgm1WNSLZJZ9ZhUi2RWPSbVIsVeT1GRO+rX2nbPr4XpINw5iPsjvi+//FILFy7U3XffrdmzZ3fY5/F4NH36dDU0NMi2be3cuTNhn0UtHj9UuVkdfzxaygEgfcT9Durxxx/XiRMnVFlZqcrKSknSDTfcoJMnT6q0tFR33nmnFixYoOzsbF122WWaOHFivEuQ1NYI0S8/hy4+AEhTcQ+olStXauXKlWH3z5w5UzNnzoz3Ybuoqq7Vz7cdUN3JVknSSa8v4ccEAMSPIwfqVlXX6qdV+9Vqn9p2vKlVa177WBJt5gCQDhw51VHljoMdwinA67dpMweQtvy2rWMtPjWHuL45kSMDKtLs5MxcDiBd+fy2tn30NzX2kY8sHBlQkWYnZ+ZyAEgPjgyoxeOHKjPEaOusDIs2cwBIE45skgg0QbTv4huQm6m7Jo+gQQIA0oQjA6qqulY/++OnOtHc9pyWcAKA9OO4gKLFHACcwXGfQdFiDgDO4LiAosUcgFNlWJYmjRrUZ9aEclxA0WIOwKlcGZZOy3b1mTWhHBdQtJgDgDM4rkki0ARBFx8ApDfHBZTUFlJTRxcbt6AZACB6jnvEBwBwBgIKAGAkAgoAYCQCCgBgJAIKAGAkAgoAYCQCCgBgJAIKAGAkAgoAYCQCCgBgJAIKAGAkAgoAYCQCCgBgJAIKAGCkuC+34fV6tWLFCh0+fFgtLS269dZbdfnllwf3b926VY8++qgyMzNVUlKiOXPmxLuEDqqqa1W546Bq65tV7M7R4vFDWRcKANJA3APq5ZdfVmFhoR588EHV1dVp5syZwYDyer1at26dNm7cqLy8PJWVlWny5Mk6/fTT411GWy27j2jtG5+oqdUvSaqpb9baNz6RJEIKAAwX90d8V199tW6//XZJkm3bcrlcwX0HDhzQkCFDNGDAAGVnZ+uiiy7Srl274l1C0ENbPg6GU0BTq1+VOw4m7JgAgPiI+x1Uv379JEkej0e33Xab7rjjjuA+j8cjt9vd4bUej6fb93S5LBUW5ve4lqPHm0Jur61vjun9esPlykj6MSMxqR6TapHMqsekWiSz6jGpFik59VhWbNfCdJWQJd+PHj2qH//4x5o3b55mzJgR3F5QUKCGhobg1w0NDR0CKxyfz45p6fYzBuTqSIiQKnbnJH0peNOWnzepHpNqkcyqx6RaJLPqMakWKfZ6ioq6vwYG2HZs10LThTsHcX/E9+WXX2rhwoW6++67NXv27A77RowYoUOHDqmurk4tLS167733dOGFF8a7hKC7rhip3MyOP2JuZoYWjx+asGMCAOIj7ndQjz/+uE6cOKHKykpVVlZKkm644QadPHlSpaWlKi8v16JFi2TbtkpKSlRcnLhmhWvP/6YaGpvp4gOANGTZtm2nuojueL2+mG5rTXoEYFItkln1mFSLZFY9JtUimVWPSbVIyXnE5/P59fXXDd2/MM0k7REfAADxQEABAIxEQAEAjERAAQCMREABAIxEQAEAjJSQmSRMUFVdq8ffOqSjx5sY/wQAaciRAVVVXcss5gCQ5hz5iK9yx0FmMQeANOfIgKqtb+7RdgCAeRwZUMXunB5tBwCYx5EBtXj8UGYxB4A058gmiUAjBF18AJC+HHkHJbWF1P9d+gOtvuY8SdJPNu/XjPU7VVVdm+LKAADRcOQdVMDLu4/Qbg4Aacqxd1CS9NCWj2k3B4A05eiAOnq8KeR22s0BwHyODqgzBuSG3E67OQCYz9EBddcVI2k3B4A05egmiWvP/6YaGptVueOgauubaTcHgDTi6ICS2rr1CCQASD+OfsQHAEhfBBQAwEgEFADASAQUAMBIBBQAwEgEFADASAQUAMBICQuo3bt3a/78+V22P/XUU5o2bZrmz5+v+fPn67PPPktUCQCANJaQgbq/+tWv9PLLLysvL6/Lvj179qiiokJjxoxJxKEBAA6RkDuoIUOG6JFHHgm5b+/evVq/fr3Kysr0xBNPJOLwAAAHSMgd1FVXXaW//vWvIfdNmzZN8+bNU0FBgZYsWaJt27Zp0qRJEd/P5bJUWJjf4zpcroyYvi8RTKpFMqsek2qRzKrHpFoks+oxqRYpOfVYVmzXwnSV1Ln4bNvWTTfdJLfbLUmaOHGi9u3b121A+Xy26uoae3y8wsL8mL4vEUyqRTKrHpNqkcyqx6RaJLPqMakWKfZ6iorcUb/WtmO7Fpou3DlIahefx+PR9OnT1dDQINu2tXPnTj6LAgCElJQ7qFdeeUWNjY0qLS3VnXfeqQULFig7O1uXXXaZJk6cmIwSAABpxrJt2051Ed3xen084oszk+oxqRbJrHpMqkUyqx6TapGS84jP5/Pr668benwM0xnxiA8AgGgRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUAAAIxFQAAAjEVAAACMRUACQJvy2rWY71VUkDwEFAGnC57fV6PWluoykIaAAAEYioAAARiKgAABGykx1AYlSVV2rh//0mY41eiVJ/XNcWnr5OZo6ujjFlQEAopGwO6jdu3dr/vz5XbZv3bpVJSUlKi0t1fPPP5+QY1dV12rNax8Hw0mSTjT79NOq/aqqrk3IMQEA8ZWQO6hf/epXevnll5WXl9dhu9fr1bp167Rx40bl5eWprKxMkydP1umnnx7X41fuOCivv2svZqvdto+7KAAwX0ICasiQIXrkkUd0zz33dNh+4MABDRkyRAMGDJAkXXTRRdq1a5emTp0a8f1cLkuFhflRH7+2vjnivp68V7y4XBkpOW44JtVjUi2SWfWYVItkVj0m1SIlpx5XhqVv9M9V/9yshB7HFAkJqKuuukp//etfu2z3eDxyu93Br/v16yePx9Pt+/l8turqGqM+frE7RzVhQqrYndOj94qXwsL8lBw3HJPqMakWyax6TKpFMqsek2qRYq+nqMjd/YsCbMnf5FVdk7f716aRcOcgqV18BQUFamhoCH7d0NDQIbDiZfH4ocrKsLpsz7Ta9gEAzJfUgBoxYoQOHTqkuro6tbS06L333tOFF14Y9+NMHV2se68eqdPyT90G989xadXU8/j8CQDSRFLazF955RU1NjaqtLRU5eXlWrRokWzbVklJiYqLExMYU0cXq+yyYUY9AgAARC9hAXXmmWcG28hnzJgR3D558mRNnjw5UYcFADgEM0kAAIxEQAEAjERAAQCMREABAIxEQAEAjERAAQCMREABAIxEQAEAjERAAQCMZNm23XXhJAAAUow7KACAkQgoAICRCCgAgJEIKACAkQgoAICRCCgAgJEIKACAkZKy5Hsy+f1+3Xfffdq/f7+ys7N1//336+yzz056Hddff70KCgokta0uXFpaqn/913+Vy+XSuHHjtGTJkoTXsHv3bv3sZz/Thg0bdOjQIZWXl8uyLJ177rn6yU9+ooyMDP3yl7/Un/70J2VmZmrFihUaO3ZsUurZt2+fbrnlFg0dOlSSVFZWpmuuuSYp9Xi9Xq1YsUKHDx9WS0uLbr31Vp1zzjkpOT+hajnjjDNSdm58Pp9Wrlypzz//XJZlafXq1crJyUnJuQlVS2tra8rOTcBXX32lWbNm6cknn1RmZmbKf68czXaY119/3V62bJlt27b9v//7v/aPfvSjpNfQ1NRkX3fddR22XXvttfahQ4dsv99v/+M//qO9d+/ehNawfv16e/r06fYNN9xg27Zt33LLLfa7775r27Zt33vvvfYbb7xh79mzx54/f77t9/vtw4cP27NmzUpaPc8//7z9m9/8psNrklXPxo0b7fvvv9+2bds+duyYPXHixJSdn1C1pPLcbNmyxS4vL7dt27bfffdd+0c/+lHKzk2oWlJ5bmzbtltaWuzFixfbV155pf3pp5+m/PfK6Rz3iO/999/X+PHjJUkXXHCB9uzZk/QaPvroI508eVILFy7UggULtGvXLrW0tGjIkCGyLEvjxo3T22+/ndAahgwZokceeST49d69e3XppZdKkiZMmKC3335b77//vsaNGyfLsvTNb35TPp9PX3/9dVLq2bNnj/70pz/pxhtv1IoVK+TxeJJWz9VXX63bb79dkmTbtlwuV8rOT6haUnlupkyZojVr1kiSjhw5ov79+6fs3ISqJZXnRpIqKio0d+5cDRo0SFLqf6+cznEB5fF4go/WJMnlcqm1tTWpNeTm5mrRokX6zW9+o9WrV2v58uXKy8sL7u/Xr5/q6+sTWsNVV12lzMxTT3Bt25ZlWR2O3/lcJbKuzvWMHTtW99xzj5599lmdddZZevTRR5NWT79+/VRQUCCPx6PbbrtNd9xxR8rOT6haUnluJCkzM1PLli3TmjVrNGPGjJT+3elcSyrPzYsvvqiBAwcG/wEspf73yukcF1AFBQVqaGgIfu33+ztcGJNh2LBhuvbaa2VZloYNGya32626urrg/oaGBvXv3z+pNWVknPpfHTh+53PV0NAgt9udlHquuOIKjRkzJvjnffv2JbWeo0ePasGCBbruuus0Y8aMlJ6fzrWk+txIbXcKr7/+uu699141Nzd3OG6y/+60r2XcuHEpOzebNm3S22+/rfnz56u6ulrLli3rcGdkwu+V0zguoL7zne9o+/btkqQPPvhAI0eOTHoNGzdu1AMPPCBJqq2t1cmTJ5Wfn68///nPsm1bb775pi6++OKk1vStb31LO3fulCRt375dF198sb7zne/ozTfflN/v15EjR+T3+zVw4MCk1LNo0SJ9+OGHkqR33nlH3/72t5NWz5dffqmFCxfq7rvv1uzZsyWl7vyEqiWV5+all17SE088IUnKy8uTZVkaM2ZMSs5NqFqWLFmSsnPz7LPP6plnntGGDRs0evRoVVRUaMKECUb9XjmN47r4rrjiCr311luaO3eubNvW2rVrk17D7NmztXz5cpWVlcmyLK1du1YZGRlaunSpfD6fxo0bp/PPPz+pNS1btkz33nuvfv7zn2v48OG66qqr5HK5dPHFF6u0tFR+v1+rVq1KWj333Xef1qxZo6ysLJ1++ulas2aNCgoKklLP448/rhMnTqiyslKVlZWSpH/5l3/R/fffn/TzE6qW8vJyrV27NiXn5sorr9Ty5ct14403qrW1VStWrNCIESNS8ncnVC1nnHFGyv7ehGLa75XTsNwGAMBIjnvEBwBwBgIKAGAkAgoAYCQCCgBgJAIKAGAkx7WZA6Hs3LlTd9xxh8455xxJUnNzs2bMmKH58+cHX7N9+3YdPXpUpaWlqSoTQDsEFPqM7373u3r44YclSS0tLbr66qt13XXXBWf1mDBhQirLA9AJAYU+yePxKCMjQz/84Q911lln6fjx45o2bZoOHTqkpUuXqrKyUn/4wx/k8/lUVlamuXPnasOGDfqv//ovWZala665RgsWLEj1jwE4GgGFPuPdd9/V/PnzZVmWsrKydO+99+rXv/61pk+friuuuEIvvviiJGnfvn3avn27XnjhBfl8Pv385z/XJ598os2bN+vf//3fJUk333yzxo0bp+HDh6fyRwIcjYBCn9H+EV/Ar3/9aw0bNqzDts8//1xjx46Vy+WSy+VSeXm5Nm/erCNHjuiHP/yhJOn48eM6dOgQAQUkEF186PMCyyUEDB8+XPv27ZPf75fX69XNN9+s4cOH65xzztHTTz+tDRs2aNasWTrvvPNSVDHQN3AHBXQyevRojR8/XmVlZfL7/SorK9OoUaN02WWXqaysTC0tLRo7dqyKi4tTXSrgaEwWCwAwEo/4AABGIqAAAEYioAAARiKgAABGIqAAAEYioAAARiKgAABG+v8BvkfNcpAYjAEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "sns.set_style(\"darkgrid\")\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# Subset for categories with at least 250 apps\n",
    "large_categories = apps.groupby('Category').filter(lambda x: len(x) >= 250).reset_index()\n",
    "\n",
    "# Plot size vs. rating\n",
    "plt1 = sns.jointplot(x = large_categories['Size'], y = large_categories['Rating'], kind = 'hex')\n",
    "\n",
    "# Subset out apps whose type is 'Paid'\n",
    "paid_apps = apps[apps['Type'] == 'Paid']\n",
    "\n",
    "# Plot price vs. rating\n",
    "plt2 = sns.jointplot(x = paid_apps['Price'], y = paid_apps['Rating'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "dc": {
     "key": "39"
    },
    "deletable": false,
    "editable": false,
    "run_control": {
     "frozen": true
    },
    "tags": [
     "context"
    ]
   },
   "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>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "dc": {
     "key": "39"
    },
    "tags": [
     "sample_code"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>App</th>\n",
       "      <th>Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3327</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>most expensive app (H)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3465</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>💎 I'm rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3469</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich - Trump Edition</td>\n",
       "      <td>400.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4396</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4398</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I am Rich Plus</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4399</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am rich VIP</td>\n",
       "      <td>299.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4400</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I Am Rich Premium</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4401</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I am extremely Rich</td>\n",
       "      <td>379.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4402</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich!</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4403</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich(premium)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4406</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich Pro</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4408</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am rich (Most expensive app)</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4410</th>\n",
       "      <td>FAMILY</td>\n",
       "      <td>I Am Rich</td>\n",
       "      <td>389.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4413</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I am Rich</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4417</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>I AM RICH PRO PLUS</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8763</th>\n",
       "      <td>FINANCE</td>\n",
       "      <td>Eu Sou Rico</td>\n",
       "      <td>394.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8780</th>\n",
       "      <td>LIFESTYLE</td>\n",
       "      <td>I'm Rich/Eu sou Rico/أنا غني/我很有錢</td>\n",
       "      <td>399.99</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Category                                App   Price\n",
       "3327     FAMILY             most expensive app (H)  399.99\n",
       "3465  LIFESTYLE                         💎 I'm rich  399.99\n",
       "3469  LIFESTYLE           I'm Rich - Trump Edition  400.00\n",
       "4396  LIFESTYLE                          I am rich  399.99\n",
       "4398     FAMILY                     I am Rich Plus  399.99\n",
       "4399  LIFESTYLE                      I am rich VIP  299.99\n",
       "4400    FINANCE                  I Am Rich Premium  399.99\n",
       "4401  LIFESTYLE                I am extremely Rich  379.99\n",
       "4402    FINANCE                         I am Rich!  399.99\n",
       "4403    FINANCE                 I am rich(premium)  399.99\n",
       "4406     FAMILY                      I Am Rich Pro  399.99\n",
       "4408    FINANCE     I am rich (Most expensive app)  399.99\n",
       "4410     FAMILY                          I Am Rich  389.99\n",
       "4413    FINANCE                          I am Rich  399.99\n",
       "4417    FINANCE                 I AM RICH PRO PLUS  399.99\n",
       "8763    FINANCE                        Eu Sou Rico  394.99\n",
       "8780  LIFESTYLE  I'm Rich/Eu sou Rico/أنا غني/我很有錢  399.99"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Select a few popular app categories\n",
    "popular_app_cats = apps[apps.Category.isin(['GAME', 'FAMILY', 'PHOTOGRAPHY',\n",
    "                                            'MEDICAL', 'TOOLS', 'FINANCE',\n",
    "                                            'LIFESTYLE','BUSINESS'])]\n",
    "\n",
    "# Examine the price trend by plotting Price vs Category\n",
    "ax = sns.stripplot(x = popular_app_cats['Price'], y = popular_app_cats['Category'], jitter=True, linewidth=1)\n",
    "ax.set_title('App pricing trend across categories')\n",
    "\n",
    "# Apps whose Price is greater than 200\n",
    "apps_above_200 = popular_app_cats[['Category', 'App', 'Price']][popular_app_cats['Price'] > 200]\n",
    "apps_above_200"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "dc": {
     "key": "46"
    },
    "deletable": false,
    "editable": false,
    "run_control": {
     "frozen": true
    },
    "tags": [
     "context"
    ]
   },
   "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>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "dc": {
     "key": "46"
    },
    "tags": [
     "sample_code"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'App pricing trend across categories after filtering for junk apps')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select apps priced below $100\n",
    "apps_under_100 = popular_app_cats[popular_app_cats['Price']<100]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(15, 8)\n",
    "\n",
    "# Examine price vs category with the authentic apps\n",
    "ax = sns.stripplot(x='Price', y='Category', data=apps_under_100,\n",
    "                   jitter=True, linewidth=1)\n",
    "ax.set_title('App pricing trend across categories after filtering for junk apps')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "dc": {
     "key": "53"
    },
    "deletable": false,
    "editable": false,
    "run_control": {
     "frozen": true
    },
    "tags": [
     "context"
    ]
   },
   "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>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "dc": {
     "key": "53"
    },
    "tags": [
     "sample_code"
    ]
   },
   "outputs": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace0 = go.Box(\n",
    "    # Data for paid apps\n",
    "    y=apps[apps['Type'] == 'Paid']['Installs'],\n",
    "    name = 'Paid'\n",
    ")\n",
    "\n",
    "trace1 = go.Box(\n",
    "    # Data for free apps\n",
    "    y=apps[apps['Type'] == 'Free']['Installs'],\n",
    "    name = 'Free'\n",
    ")\n",
    "\n",
    "layout = go.Layout(\n",
    "    title = \"Number of downloads of paid apps vs. free apps\",\n",
    "    yaxis = dict(\n",
    "        type = 'log',\n",
    "        autorange = True\n",
    "    )\n",
    ")\n",
    "\n",
    "# Add trace0 and trace1 to a list for plotting\n",
    "data = [trace0,trace1]\n",
    "plotly.offline.iplot({'data': data, 'layout': layout})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "dc": {
     "key": "60"
    },
    "deletable": false,
    "editable": false,
    "run_control": {
     "frozen": true
    },
    "tags": [
     "context"
    ]
   },
   "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>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "dc": {
     "key": "60"
    },
    "tags": [
     "sample_code"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Sentiment Polarity Distribution')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Load user_reviews.csv\n",
    "reviews_df = pd.read_csv('datasets/user_reviews.csv')\n",
    "\n",
    "# Join and merge the two dataframe\n",
    "merged_df = pd.merge(apps, reviews_df, on = 'App', how = \"inner\")\n",
    "\n",
    "# Drop NA values from Sentiment and Translated_Review columns\n",
    "merged_df = merged_df.dropna(subset=['Sentiment', 'Translated_Review'])\n",
    "\n",
    "sns.set_style('ticks')\n",
    "fig, ax = plt.subplots()\n",
    "fig.set_size_inches(11, 8)\n",
    "\n",
    "# User review sentiment polarity for paid vs. free apps\n",
    "ax = sns.boxplot(x = 'Type', y = 'Sentiment_Polarity', data = merged_df)\n",
    "ax.set_title('Sentiment Polarity Distribution')"
   ]
  }
 ],
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