Profitable App Profiles for the App Store and Google Play Markets.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# App Project - Dataquest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Analyst :\n",
    "\n",
    "We only build apps that are free to download and install, and our main source of revenue consists of in-app ads. This means our revenue for any given app is mostly influenced by the number of users who use our app — the more users that see and engage with the ads, the better. Our goal for this project is to analyze data to help our developers understand what type of apps are likely to attract more users.\n",
    "\n",
    "**This project is a part of dataquest's Data Scientist Path**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Collecting the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from csv import reader\n",
    "\n",
    "# Dataset for The Apple Store\n",
    "opened_file = open('AppleStore.csv')\n",
    "read_file = reader(opened_file)\n",
    "apple = list(read_file)\n",
    "apple_header = apple[0]\n",
    "apple = apple[1:]\n",
    "\n",
    "# Dataset for The Google Play Store\n",
    "opened_file = open('googleplaystore.csv')\n",
    "read_file = reader(opened_file)\n",
    "android = list(read_file)\n",
    "android_header = android[0]\n",
    "android = android[1:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Pre-defined function\n",
    "def explore_data(dataset, start, end, rows_and_columns=False):\n",
    "    dataset_slice = dataset[start:end]    \n",
    "    for row in dataset_slice:\n",
    "        print(row)\n",
    "        print('\\n') # adds a new (empty) line after each row\n",
    "\n",
    "    if rows_and_columns:\n",
    "        print('Number of rows:', len(dataset))\n",
    "        print('Number of columns:', len(dataset[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['id', 'track_name', 'size_bytes', 'currency', 'price', 'rating_count_tot', 'rating_count_ver', 'user_rating', 'user_rating_ver', 'ver', 'cont_rating', 'prime_genre', 'sup_devices.num', 'ipadSc_urls.num', 'lang.num', 'vpp_lic']\n",
      "\n",
      "\n",
      "['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1']\n",
      "\n",
      "\n",
      "['389801252', 'Instagram', '113954816', 'USD', '0.0', '2161558', '1289', '4.5', '4.0', '10.23', '12+', 'Photo & Video', '37', '0', '29', '1']\n",
      "\n",
      "\n",
      "['529479190', 'Clash of Clans', '116476928', 'USD', '0.0', '2130805', '579', '4.5', '4.5', '9.24.12', '9+', 'Games', '38', '5', '18', '1']\n",
      "\n",
      "\n",
      "['420009108', 'Temple Run', '65921024', 'USD', '0.0', '1724546', '3842', '4.5', '4.0', '1.6.2', '9+', 'Games', '40', '5', '1', '1']\n",
      "\n",
      "\n",
      "['284035177', 'Pandora - Music & Radio', '130242560', 'USD', '0.0', '1126879', '3594', '4.0', '4.5', '8.4.1', '12+', 'Music', '37', '4', '1', '1']\n",
      "\n",
      "\n",
      "Number of rows: 7197\n",
      "Number of columns: 16\n"
     ]
    }
   ],
   "source": [
    "print(apple_header)\n",
    "print('\\n')\n",
    "explore_data(apple,0,5,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver']\n",
      "\n",
      "\n",
      "['Photo Editor & Candy Camera & Grid & ScrapBook', 'ART_AND_DESIGN', '4.1', '159', '19M', '10,000+', 'Free', '0', 'Everyone', 'Art & Design', 'January 7, 2018', '1.0.0', '4.0.3 and up']\n",
      "\n",
      "\n",
      "['Coloring book moana', 'ART_AND_DESIGN', '3.9', '967', '14M', '500,000+', 'Free', '0', 'Everyone', 'Art & Design;Pretend Play', 'January 15, 2018', '2.0.0', '4.0.3 and up']\n",
      "\n",
      "\n",
      "['U Launcher Lite – FREE Live Cool Themes, Hide Apps', 'ART_AND_DESIGN', '4.7', '87510', '8.7M', '5,000,000+', 'Free', '0', 'Everyone', 'Art & Design', 'August 1, 2018', '1.2.4', '4.0.3 and up']\n",
      "\n",
      "\n",
      "['Sketch - Draw & Paint', 'ART_AND_DESIGN', '4.5', '215644', '25M', '50,000,000+', 'Free', '0', 'Teen', 'Art & Design', 'June 8, 2018', 'Varies with device', '4.2 and up']\n",
      "\n",
      "\n",
      "['Pixel Draw - Number Art Coloring Book', 'ART_AND_DESIGN', '4.3', '967', '2.8M', '100,000+', 'Free', '0', 'Everyone', 'Art & Design;Creativity', 'June 20, 2018', '1.1', '4.4 and up']\n",
      "\n",
      "\n",
      "Number of rows: 10841\n",
      "Number of columns: 13\n"
     ]
    }
   ],
   "source": [
    "print(android_header)\n",
    "print('\\n')\n",
    "explore_data(android,0,5,True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use these columns in our analysis : Category, price, rating, reviews, genre, etc.\n",
    "This is the [link](https://www.kaggle.com/ramamet4/app-store-apple-data-set-10k-apps/home) to the Apple Store Dataset documentation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Life Made WI-Fi Touchscreen Photo Frame',\n",
       " '1.9',\n",
       " '19',\n",
       " '3.0M',\n",
       " '1,000+',\n",
       " 'Free',\n",
       " '0',\n",
       " 'Everyone',\n",
       " '',\n",
       " 'February 11, 2018',\n",
       " '1.0.19',\n",
       " '4.0 and up']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# App with no rating\n",
    "android[10472] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Removing that row\n",
    "del android[10472]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some duplicates that we need to remove. Based on the example below, we will choose the fourth column as a criterion, keeping only the app with the highest number of reviews."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Instagram', 'SOCIAL', '4.5', '66577313', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']\n",
      "['Instagram', 'SOCIAL', '4.5', '66577446', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']\n",
      "['Instagram', 'SOCIAL', '4.5', '66577313', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']\n",
      "['Instagram', 'SOCIAL', '4.5', '66509917', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']\n"
     ]
    }
   ],
   "source": [
    "for app in android:\n",
    "    name = app[0]\n",
    "    if name == 'Instagram':\n",
    "        print(app)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of duplicate apps:  1181\n",
      "Number of unique apps:  9659\n"
     ]
    }
   ],
   "source": [
    "# Calculating the number of duplicates\n",
    "duplicate=[] \n",
    "unique=[] \n",
    "\n",
    "for app in android:\n",
    "    name=app[0]\n",
    "    if name in unique:\n",
    "        duplicate.append(name)\n",
    "    else:\n",
    "        unique.append(name)\n",
    "            \n",
    "print('Number of duplicate apps: ', len(duplicate))\n",
    "print('Number of unique apps: ', len(unique))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will create a dictionary with unique app names as keys, and the corresponding value is the highest number of reviews."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "reviews_max={}\n",
    "\n",
    "for app in android:\n",
    "    name=app[0]\n",
    "    n_reviews=float(app[3]) #Reviews is the fourth column\n",
    "    \n",
    "    if name in reviews_max and reviews_max[name]<n_reviews:\n",
    "        reviews_max[name]=n_reviews\n",
    "    elif name not in reviews_max:\n",
    "        reviews_max[name]=n_reviews\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9659\n"
     ]
    }
   ],
   "source": [
    "print(len(reviews_max)) #We expect 9,659 entries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we'll remove the duplicate rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "android_clean=list() #Stores clean data\n",
    "already_added=list() #Stores app names\n",
    "\n",
    "for app in android:\n",
    "    name=app[0]\n",
    "    n_reviews=float(app[3])\n",
    "    \n",
    "    if name not in already_added and n_reviews == reviews_max[name]:\n",
    "        android_clean.append(app)\n",
    "        already_added.append(name)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9659\n"
     ]
    }
   ],
   "source": [
    "print(len(android_clean)) #Expexted 9,659 entries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are interested in english apps only, so we will remove an foreign app.\n",
    "We can detect non-english apps using ASCII (American Standard Code for Information Interchange).\n",
    "English letter fall in between 0 and 127, any character less than 0 or greater that 127 is a non-english character."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Function to detect non-english names\n",
    "def is_english_non_edited(string):\n",
    "    for character in string:\n",
    "        if ord(character) > 127:\n",
    "            return False\n",
    "    return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Testing the function\n",
    "is_english_non_edited('爱奇艺PPS -《欢乐颂2》电视剧热播')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "is_english_non_edited('Docs To Go™ Free Office Suite')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "is_english_non_edited('Instachat 😜')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can lose some data because certain characters used in an english app return 'False'.\n",
    "That's why we'll only remove apps with more than three foreign characters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Edited function\n",
    "def is_english(string):\n",
    "    non_ascii = 0\n",
    "    \n",
    "    for character in string:\n",
    "        if ord(character) > 127:\n",
    "            non_ascii += 1\n",
    "    \n",
    "    if non_ascii > 3:\n",
    "        return False\n",
    "    else:\n",
    "        return True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Testing the edited version\n",
    "is_english('Docs To Go™ Free Office Suite')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "is_english('Instachat 😜')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "is_english('爱奇艺PPS -《欢乐颂2》电视剧热播')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we will remove any non-english app from both our datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "android_english=list()\n",
    "apple_english=list()\n",
    "\n",
    "for app in android_clean:\n",
    "    name=app[0]\n",
    "    if is_english(name):\n",
    "        android_english.append(app)\n",
    "\n",
    "for app in apple:\n",
    "    name=app[1]\n",
    "    if is_english(name):\n",
    "        apple_english.append(app)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9614\n",
      "6183\n"
     ]
    }
   ],
   "source": [
    "# Let's see how many apps we have left\n",
    "print(len(android_english))\n",
    "print(len(apple_english))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We only want free apps. Therfore, we'll remove any non-free app from our datasets. This is the last data cleaning step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "android_apps=list() \n",
    "apple_apps=list() \n",
    "\n",
    "for app in android_english:\n",
    "    try:\n",
    "        price=float(app[7])\n",
    "    except:\n",
    "        price=float(app[7][1:])\n",
    "    if price == 0.0:\n",
    "        android_apps.append(app)\n",
    "\n",
    "for app in apple_english:\n",
    "    try:\n",
    "        price=float(app[4])\n",
    "    except:\n",
    "        price=float(app[4][1:])\n",
    "    if price == 0.0:\n",
    "        apple_apps.append(app)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8864\n",
      "3222\n"
     ]
    }
   ],
   "source": [
    "print(len(android_apps))\n",
    "print(len(apple_apps))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To minimize risks and overhead, our validation strategy for an app idea is comprised of three steps:\n",
    "\n",
    "1. Build a minimal Android version of the app, and add it to Google Play.\n",
    "2. If the app has a good response from users, we develop it further.\n",
    "3. If the app is profitable after six months, we build an iOS version of the app and add it to the App Store."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver']\n"
     ]
    }
   ],
   "source": [
    "print(android_header)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use 'Genres' and 'Category' to generate a frequency table for android apps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['id', 'track_name', 'size_bytes', 'currency', 'price', 'rating_count_tot', 'rating_count_ver', 'user_rating', 'user_rating_ver', 'ver', 'cont_rating', 'prime_genre', 'sup_devices.num', 'ipadSc_urls.num', 'lang.num', 'vpp_lic']\n"
     ]
    }
   ],
   "source": [
    "print(apple_header)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For iOS apps, we can use 'prime_genre'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Helper function\n",
    "def display_table(dataset, index):\n",
    "    table = freq_table(dataset, index)\n",
    "    table_display = []\n",
    "    for key in table:\n",
    "        key_val_as_tuple = (table[key], key)\n",
    "        table_display.append(key_val_as_tuple)\n",
    "\n",
    "    table_sorted = sorted(table_display, reverse = True)\n",
    "    for entry in table_sorted:\n",
    "        print(entry[1], ':', entry[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Function de generate frequency tables\n",
    "def freq_table(dataset, index):\n",
    "    table = {}\n",
    "    total = 0\n",
    "    \n",
    "    for row in dataset:\n",
    "        total += 1\n",
    "        value = row[index]\n",
    "        if value in table:\n",
    "            table[value] += 1\n",
    "        else:\n",
    "            table[value] = 1\n",
    "    \n",
    "    table_percentages = {}\n",
    "    for key in table:\n",
    "        percentage = (table[key] / total) * 100\n",
    "        table_percentages[key] = percentage\n",
    "    \n",
    "    return table_percentages\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Games : 55.64595660749507\n",
      "Entertainment : 8.234714003944774\n",
      "Photo & Video : 4.117357001972387\n",
      "Social Networking : 3.5256410256410255\n",
      "Education : 3.2544378698224854\n",
      "Shopping : 2.983234714003945\n",
      "Utilities : 2.687376725838264\n",
      "Lifestyle : 2.3175542406311638\n",
      "Finance : 2.0710059171597637\n",
      "Sports : 1.947731755424063\n",
      "Health & Fitness : 1.8737672583826428\n",
      "Music : 1.6518737672583828\n",
      "Book : 1.6272189349112427\n",
      "Productivity : 1.5285996055226825\n",
      "News : 1.4299802761341223\n",
      "Travel : 1.3806706114398422\n",
      "Food & Drink : 1.0601577909270217\n",
      "Weather : 0.7642998027613412\n",
      "Reference : 0.4930966469428008\n",
      "Navigation : 0.4930966469428008\n",
      "Business : 0.4930966469428008\n",
      "Catalogs : 0.22189349112426035\n",
      "Medical : 0.19723865877712032\n"
     ]
    }
   ],
   "source": [
    "# Frequency table for prime_genre\n",
    "display_table(apple_apps,11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most common genre : Games.\n",
    "Second most common : Entertainment.\n",
    "The most common apps are for no practical purposes.\n",
    "\n",
    "Recommended app : Games more than 55% of the free anglish app market."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tools : 8.449909747292418\n",
      "Entertainment : 6.069494584837545\n",
      "Education : 5.347472924187725\n",
      "Business : 4.591606498194946\n",
      "Productivity : 3.892148014440433\n",
      "Lifestyle : 3.892148014440433\n",
      "Finance : 3.7003610108303246\n",
      "Medical : 3.531137184115524\n",
      "Sports : 3.463447653429603\n",
      "Personalization : 3.3167870036101084\n",
      "Communication : 3.2378158844765346\n",
      "Action : 3.1024368231046933\n",
      "Health & Fitness : 3.0798736462093865\n",
      "Photography : 2.944494584837545\n",
      "News & Magazines : 2.7978339350180503\n",
      "Social : 2.6624548736462095\n",
      "Travel & Local : 2.3240072202166067\n",
      "Shopping : 2.2450361010830324\n",
      "Books & Reference : 2.1435018050541514\n",
      "Simulation : 2.0419675090252705\n",
      "Dating : 1.861462093862816\n",
      "Arcade : 1.8501805054151623\n",
      "Video Players & Editors : 1.7712093862815883\n",
      "Casual : 1.7599277978339352\n",
      "Maps & Navigation : 1.3989169675090252\n",
      "Food & Drink : 1.2409747292418771\n",
      "Puzzle : 1.128158844765343\n",
      "Racing : 0.9927797833935018\n",
      "Role Playing : 0.9363718411552346\n",
      "Libraries & Demo : 0.9363718411552346\n",
      "Auto & Vehicles : 0.9250902527075812\n",
      "Strategy : 0.9138086642599278\n",
      "House & Home : 0.8235559566787004\n",
      "Weather : 0.8009927797833934\n",
      "Events : 0.7107400722021661\n",
      "Adventure : 0.6768953068592057\n",
      "Comics : 0.6092057761732852\n",
      "Beauty : 0.5979241877256317\n",
      "Art & Design : 0.5979241877256317\n",
      "Parenting : 0.4963898916967509\n",
      "Card : 0.45126353790613716\n",
      "Casino : 0.42870036101083037\n",
      "Trivia : 0.41741877256317694\n",
      "Educational;Education : 0.39485559566787\n",
      "Board : 0.3835740072202166\n",
      "Educational : 0.3722924187725632\n",
      "Education;Education : 0.33844765342960287\n",
      "Word : 0.2594765342960289\n",
      "Casual;Pretend Play : 0.236913357400722\n",
      "Music : 0.2030685920577617\n",
      "Racing;Action & Adventure : 0.16922382671480143\n",
      "Puzzle;Brain Games : 0.16922382671480143\n",
      "Entertainment;Music & Video : 0.16922382671480143\n",
      "Casual;Brain Games : 0.13537906137184114\n",
      "Casual;Action & Adventure : 0.13537906137184114\n",
      "Arcade;Action & Adventure : 0.12409747292418773\n",
      "Action;Action & Adventure : 0.10153429602888085\n",
      "Educational;Pretend Play : 0.09025270758122744\n",
      "Simulation;Action & Adventure : 0.078971119133574\n",
      "Parenting;Education : 0.078971119133574\n",
      "Entertainment;Brain Games : 0.078971119133574\n",
      "Board;Brain Games : 0.078971119133574\n",
      "Parenting;Music & Video : 0.06768953068592057\n",
      "Educational;Brain Games : 0.06768953068592057\n",
      "Casual;Creativity : 0.06768953068592057\n",
      "Art & Design;Creativity : 0.06768953068592057\n",
      "Education;Pretend Play : 0.056407942238267145\n",
      "Role Playing;Pretend Play : 0.04512635379061372\n",
      "Education;Creativity : 0.04512635379061372\n",
      "Role Playing;Action & Adventure : 0.033844765342960284\n",
      "Puzzle;Action & Adventure : 0.033844765342960284\n",
      "Entertainment;Creativity : 0.033844765342960284\n",
      "Entertainment;Action & Adventure : 0.033844765342960284\n",
      "Educational;Creativity : 0.033844765342960284\n",
      "Educational;Action & Adventure : 0.033844765342960284\n",
      "Education;Music & Video : 0.033844765342960284\n",
      "Education;Brain Games : 0.033844765342960284\n",
      "Education;Action & Adventure : 0.033844765342960284\n",
      "Adventure;Action & Adventure : 0.033844765342960284\n",
      "Video Players & Editors;Music & Video : 0.02256317689530686\n",
      "Sports;Action & Adventure : 0.02256317689530686\n",
      "Simulation;Pretend Play : 0.02256317689530686\n",
      "Puzzle;Creativity : 0.02256317689530686\n",
      "Music;Music & Video : 0.02256317689530686\n",
      "Entertainment;Pretend Play : 0.02256317689530686\n",
      "Casual;Education : 0.02256317689530686\n",
      "Board;Action & Adventure : 0.02256317689530686\n",
      "Video Players & Editors;Creativity : 0.01128158844765343\n",
      "Trivia;Education : 0.01128158844765343\n",
      "Travel & Local;Action & Adventure : 0.01128158844765343\n",
      "Tools;Education : 0.01128158844765343\n",
      "Strategy;Education : 0.01128158844765343\n",
      "Strategy;Creativity : 0.01128158844765343\n",
      "Strategy;Action & Adventure : 0.01128158844765343\n",
      "Simulation;Education : 0.01128158844765343\n",
      "Role Playing;Brain Games : 0.01128158844765343\n",
      "Racing;Pretend Play : 0.01128158844765343\n",
      "Puzzle;Education : 0.01128158844765343\n",
      "Parenting;Brain Games : 0.01128158844765343\n",
      "Music & Audio;Music & Video : 0.01128158844765343\n",
      "Lifestyle;Pretend Play : 0.01128158844765343\n",
      "Lifestyle;Education : 0.01128158844765343\n",
      "Health & Fitness;Education : 0.01128158844765343\n",
      "Health & Fitness;Action & Adventure : 0.01128158844765343\n",
      "Entertainment;Education : 0.01128158844765343\n",
      "Communication;Creativity : 0.01128158844765343\n",
      "Comics;Creativity : 0.01128158844765343\n",
      "Casual;Music & Video : 0.01128158844765343\n",
      "Card;Action & Adventure : 0.01128158844765343\n",
      "Books & Reference;Education : 0.01128158844765343\n",
      "Art & Design;Pretend Play : 0.01128158844765343\n",
      "Art & Design;Action & Adventure : 0.01128158844765343\n",
      "Arcade;Pretend Play : 0.01128158844765343\n",
      "Adventure;Education : 0.01128158844765343\n"
     ]
    }
   ],
   "source": [
    "# Frequency table for Genres\n",
    "display_table(android_apps,9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most common apps : Tools and Entertainement.\n",
    "They are more practical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FAMILY : 18.907942238267147\n",
      "GAME : 9.724729241877256\n",
      "TOOLS : 8.461191335740072\n",
      "BUSINESS : 4.591606498194946\n",
      "LIFESTYLE : 3.9034296028880866\n",
      "PRODUCTIVITY : 3.892148014440433\n",
      "FINANCE : 3.7003610108303246\n",
      "MEDICAL : 3.531137184115524\n",
      "SPORTS : 3.395758122743682\n",
      "PERSONALIZATION : 3.3167870036101084\n",
      "COMMUNICATION : 3.2378158844765346\n",
      "HEALTH_AND_FITNESS : 3.0798736462093865\n",
      "PHOTOGRAPHY : 2.944494584837545\n",
      "NEWS_AND_MAGAZINES : 2.7978339350180503\n",
      "SOCIAL : 2.6624548736462095\n",
      "TRAVEL_AND_LOCAL : 2.33528880866426\n",
      "SHOPPING : 2.2450361010830324\n",
      "BOOKS_AND_REFERENCE : 2.1435018050541514\n",
      "DATING : 1.861462093862816\n",
      "VIDEO_PLAYERS : 1.7937725631768955\n",
      "MAPS_AND_NAVIGATION : 1.3989169675090252\n",
      "FOOD_AND_DRINK : 1.2409747292418771\n",
      "EDUCATION : 1.1620036101083033\n",
      "ENTERTAINMENT : 0.9589350180505415\n",
      "LIBRARIES_AND_DEMO : 0.9363718411552346\n",
      "AUTO_AND_VEHICLES : 0.9250902527075812\n",
      "HOUSE_AND_HOME : 0.8235559566787004\n",
      "WEATHER : 0.8009927797833934\n",
      "EVENTS : 0.7107400722021661\n",
      "PARENTING : 0.6543321299638989\n",
      "ART_AND_DESIGN : 0.6430505415162455\n",
      "COMICS : 0.6204873646209386\n",
      "BEAUTY : 0.5979241877256317\n"
     ]
    }
   ],
   "source": [
    "# Frequency table for Category\n",
    "display_table(android_apps,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Family and Games are the most common app genres."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most common apps are : Games and Entertainment."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One way to find out what genres are the most popular (have the most users) is to calculate the average number of installs for each app genre. For the Google Play data set, we can find this information in the Installs column, but this information is missing for the App Store data set. As a workaround, we'll take the total number of user ratings as a proxy, which we can find in the rating_count_tot app."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Social Networking  :  71548.34905660378\n",
      "Health & Fitness  :  23298.015384615384\n",
      "Catalogs  :  4004.0\n",
      "Weather  :  52279.892857142855\n",
      "Utilities  :  18684.456790123455\n",
      "Travel  :  28243.8\n",
      "Navigation  :  86090.33333333333\n",
      "Entertainment  :  14029.830708661417\n",
      "Productivity  :  21028.410714285714\n",
      "News  :  21248.023255813954\n",
      "Photo & Video  :  28441.54375\n",
      "Business  :  7491.117647058823\n",
      "Lifestyle  :  16485.764705882353\n",
      "Music  :  57326.530303030304\n",
      "Finance  :  31467.944444444445\n",
      "Medical  :  612.0\n",
      "Reference  :  74942.11111111111\n",
      "Games  :  22788.6696905016\n",
      "Education  :  7003.983050847458\n",
      "Book  :  39758.5\n",
      "Shopping  :  26919.690476190477\n",
      "Food & Drink  :  33333.92307692308\n",
      "Sports  :  23008.898550724636\n"
     ]
    }
   ],
   "source": [
    "# for App Store\n",
    "ft_prime_genre = freq_table(apple_apps,11)\n",
    "\n",
    "for genre in ft_prime_genre:\n",
    "    total=0\n",
    "    len_genre=0\n",
    "    for app in apple_apps:\n",
    "        genre_app = app[11]\n",
    "        \n",
    "        if genre_app == genre:\n",
    "            n_ratings = float(app[5])\n",
    "            total+= n_ratings\n",
    "            len_genre+=1\n",
    "    average = total/len_genre\n",
    "    print(genre,' : ',str(average))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The recommended app is : Social networking"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NEWS_AND_MAGAZINES  :  9549178.467741935\n",
      "TRAVEL_AND_LOCAL  :  13984077.710144928\n",
      "WEATHER  :  5074486.197183099\n",
      "SHOPPING  :  7036877.311557789\n",
      "COMMUNICATION  :  38456119.167247385\n",
      "SOCIAL  :  23253652.127118643\n",
      "BUSINESS  :  1712290.1474201474\n",
      "EVENTS  :  253542.22222222222\n",
      "PHOTOGRAPHY  :  17840110.40229885\n",
      "FINANCE  :  1387692.475609756\n",
      "HOUSE_AND_HOME  :  1331540.5616438356\n",
      "PRODUCTIVITY  :  16787331.344927534\n",
      "FAMILY  :  3695641.8198090694\n",
      "COMICS  :  817657.2727272727\n",
      "MAPS_AND_NAVIGATION  :  4056941.7741935486\n",
      "VIDEO_PLAYERS  :  24727872.452830188\n",
      "GAME  :  15588015.603248259\n",
      "LIBRARIES_AND_DEMO  :  638503.734939759\n",
      "SPORTS  :  3638640.1428571427\n",
      "BOOKS_AND_REFERENCE  :  8767811.894736841\n",
      "HEALTH_AND_FITNESS  :  4188821.9853479853\n",
      "ART_AND_DESIGN  :  1986335.0877192982\n",
      "PARENTING  :  542603.6206896552\n",
      "ENTERTAINMENT  :  11640705.88235294\n",
      "MEDICAL  :  120550.61980830671\n",
      "AUTO_AND_VEHICLES  :  647317.8170731707\n",
      "EDUCATION  :  1833495.145631068\n",
      "LIFESTYLE  :  1437816.2687861272\n",
      "FOOD_AND_DRINK  :  1924897.7363636363\n",
      "TOOLS  :  10801391.298666667\n",
      "BEAUTY  :  513151.88679245283\n",
      "PERSONALIZATION  :  5201482.6122448975\n",
      "DATING  :  854028.8303030303\n"
     ]
    }
   ],
   "source": [
    "# for Google Store\n",
    "ft_category = freq_table(android_apps,1)\n",
    "\n",
    "for category in ft_category:\n",
    "    total=0\n",
    "    len_category=0\n",
    "    for app in android_apps:\n",
    "        category_app = app[1]\n",
    "        \n",
    "        if category_app == category:\n",
    "            n_install = float(app[5].replace('+','').replace(',',''))\n",
    "            total+=n_install\n",
    "            len_category+=1\n",
    "    average = total/len_category\n",
    "    print(category,' : ',str(average))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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