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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Profitable App Profiles for the App Store and Google Play Markets¶"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our aim in this project is to analyze mobile app that are profitable for the App Store and Google Play markets and help make data-driven decisions with respect to the kind of apps they build.\n",
    "\n",
    "Our analysis Analyze can help build apps that are free to download. Our main source of revenue consists of in-app ads. This means that our revenue for any given app is mostly influenced by the number of users that use our app. Our goal for this project is to analyze data to help company  understand what kinds of apps are likely to attract more users.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. import library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:50:13.515012Z",
     "start_time": "2020-04-09T11:50:12.071257Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from csv import reader"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Import dataset\n",
    "As of September 2018, there were almost 2 million iOS apps available on the App Store, and 2.1 million Android apps on Google Play. This data set I had from Kaggle link to them you can find below \n",
    "- [Android apps](https://dq-content.s3.amazonaws.com/350/googleplaystore.csv) \n",
    "- [IOS apps](https://dq-content.s3.amazonaws.com/350/AppleStore.csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:51:33.101457Z",
     "start_time": "2020-04-09T11:51:33.007710Z"
    }
   },
   "outputs": [],
   "source": [
    "#Android\n",
    "open_file = open('.../googleplaystore.csv')#data set-->https://dq-content.s3.amazonaws.com/350/googleplaystore.csv\n",
    "read_file = reader(open_file)\n",
    "android_data = list(read_file)\n",
    "android_header = android_data[0]\n",
    "android = android_data[1:]\n",
    "\n",
    "#IOS\n",
    "opened_file = open('.../AppleStore.csv')#data set-->https://dq-content.s3.amazonaws.com/350/AppleStore.csv\n",
    "read_file = reader(opened_file)\n",
    "ios = list(read_file)\n",
    "ios_header = ios[0]\n",
    "ios = ios[1:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make it easier to explore the data sets, I write a function named \" explore_data()\"  that I can use repeatedly to explore rows in a more readable way. You can  also find  an option function to show the number of rows and columns for any data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:51:40.089378Z",
     "start_time": "2020-04-09T11:51:40.078393Z"
    }
   },
   "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",
      "Number of rows: 10841\n",
      "Number of columns: 13\n"
     ]
    }
   ],
   "source": [
    "def explore_data(dataset, start, end,rows_and_columns=False):\n",
    "    dataset_silence = dataset[start:end]\n",
    "    for row in dataset_silence:\n",
    "        print(row)\n",
    "        print('\\n')\n",
    "    if rows_and_columns:\n",
    "        print('Number of rows:', len(dataset))\n",
    "        print('Number of columns:', len(dataset[0]))\n",
    "print(android_header)\n",
    "print('\\n')\n",
    "explore_data(android, 0, 3, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see 10,841 apps in Google Play and 13 columns. It that might be useful for the purpose of our analysis are: ['App', 'Category', 'Rating', 'Reviews','Installs', 'Type', 'Price','Genres']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:51:42.936006Z",
     "start_time": "2020-04-09T11:51:42.927068Z"
    }
   },
   "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",
      "Number of rows: 7197\n",
      "Number of columns: 16\n"
     ]
    }
   ],
   "source": [
    "print(ios_header)\n",
    "print('\\n')\n",
    "explore_data(ios, 0, 3, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see 7197 apps in Apple store and 16 columns. The columns that might be useful for the purpose of our analysis are: ['track_name', 'currency', 'price', 'rating_count_tot', 'rating_count_ver', and 'prime_genre']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Data cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-03-30T04:32:30.276237Z",
     "start_time": "2020-03-30T04:32:30.260616Z"
    }
   },
   "source": [
    "#### 3.1 Delating Wrong data\n",
    "we can see that one of the [discussions](https://www.kaggle.com/lava18/google-play-store-apps/discussion/66015) outlines an error for row 10472. Let's print this row and compare it against the header and another row that is correct."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:51:46.491571Z",
     "start_time": "2020-04-09T11:51:46.482647Z"
    }
   },
   "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",
      "['Life Made WI-Fi Touchscreen Photo Frame', '1.9', '19', '3.0M', '1,000+', 'Free', '0', 'Everyone', '', 'February 11, 2018', '1.0.19', '4.0 and up']\n",
      "\n",
      "\n",
      "['Xposed Wi-Fi-Pwd', 'PERSONALIZATION', '3.5', '1042', '404k', '100,000+', 'Free', '0', 'Everyone', 'Personalization', 'August 5, 2014', '3.0.0', '4.0.3 and up']\n"
     ]
    }
   ],
   "source": [
    "print(android_header)\n",
    "print('\\n')\n",
    "print(android[10472])\n",
    "print('\\n')\n",
    "print(android[10471])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:52:50.476554Z",
     "start_time": "2020-04-09T11:52:50.468010Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10841\n",
      "10840\n"
     ]
    }
   ],
   "source": [
    "print(len(android))\n",
    "#del android[10472]#use just one time\n",
    "print(len(android))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.2 Delate duplication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:52:57.401573Z",
     "start_time": "2020-04-09T11:52:56.664350Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number duplication app: 1181\n",
      "\n",
      "\n",
      "Number uniqe app: 9659\n"
     ]
    }
   ],
   "source": [
    "duplication = []\n",
    "uniqe_app = []\n",
    "for app in android:\n",
    "    title = app[0]\n",
    "    if title in uniqe_app:\n",
    "        duplication.append(title)\n",
    "    else:\n",
    "        uniqe_app.append(title)\n",
    "print('Number duplication app:', len(duplication))\n",
    "print('\\n')\n",
    "print('Number uniqe app:', len(uniqe_app))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I don't want to count certain apps more than once so I need to remove the duplicate entries and keep only one entry per app. \n",
    "\n",
    "Next step is:\n",
    "\n",
    "- Create a dictionary where each key is a unique app name, and the value is the highest number of reviews of that app\n",
    "- Use the dictionary to create a new data set, which will have only one entry per app (and select the apps with the highest number of reviews)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:52:57.665540Z",
     "start_time": "2020-04-09T11:52:57.644465Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exprcted lenght:  9659\n",
      "\n",
      "\n",
      "Currnent lenght:  9659\n"
     ]
    }
   ],
   "source": [
    "reviews_max = {}\n",
    "\n",
    "for app in android:\n",
    "    name = app[0]\n",
    "    n_reviews = float(app[3])\n",
    "    \n",
    "    if name in reviews_max and reviews_max[name] < n_reviews:\n",
    "        reviews_max[name] = n_reviews\n",
    "    else:\n",
    "        reviews_max[name]= n_reviews\n",
    "        \n",
    "        \n",
    "print('Exprcted lenght: ', len(uniqe_app))\n",
    "print('\\n')\n",
    "print('Currnent lenght: ', len(reviews_max))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's use the __reviews_max__ dictionary to remove the duplicates. For the duplicate cases, I'll only keep the entries with the highest number of reviews. In the code cell below:\n",
    "- I start by initializing __two empty lists, android_clean and already_added.__\n",
    "- I creat loop through the __android data__ set, and for every iteration:  \n",
    "     - I isolate the name of the app and the number of reviews.\n",
    "     - I add the current row (app) to the __android_clean__ list, and the app name (name) to the __already_added__ list if:\n",
    "         -The number of reviews of the current app matches the number of reviews of that app as described in the __reviews_max__ dictionary\n",
    "         \n",
    "The name of the app is not already in the __already_added__ list. I need to add this supplementary condition to account for those cases where the highest number of reviews of a duplicate app is the same for more than one entry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:52:59.819104Z",
     "start_time": "2020-04-09T11:52:59.128634Z"
    }
   },
   "outputs": [],
   "source": [
    "android_clean = []\n",
    "already_added = []\n",
    "\n",
    "for app in android:\n",
    "    name= app[0]\n",
    "    n_reviews = float(app[3])\n",
    "    \n",
    "    if (reviews_max[name] == n_reviews) and (name not in already_added):\n",
    "        android_clean.append(app)\n",
    "        already_added.append(name)\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### let's quickly explore the new data set, and confirm that the number of rows is 9,659."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:53:00.795328Z",
     "start_time": "2020-04-09T11:53:00.788431Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['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",
      "Number of rows: 9659\n",
      "Number of columns: 13\n"
     ]
    }
   ],
   "source": [
    "explore_data(android_clean, 0, 1, True)#--> \"function def abowe\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-03T04:57:10.452697Z",
     "start_time": "2020-04-03T04:57:09.616195Z"
    }
   },
   "source": [
    "#### 3.3 Renoving non-ENG app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:53:01.880395Z",
     "start_time": "2020-04-09T11:53:01.870431Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "def english_app(title):\n",
    "    non_ascii = 0\n",
    "    \n",
    "    for letter in title:\n",
    "        if ord(letter)>127:\n",
    "            non_ascii+=1\n",
    "            \n",
    "    if non_ascii>3:\n",
    "            \n",
    "        return False\n",
    "    else: \n",
    "        return True\n",
    "print(english_app('Instagram'))\n",
    "print(english_app('爱奇艺PPS -《欢乐颂2》电视剧热播'))\n",
    "print(english_app('Instachat '))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:53:03.561629Z",
     "start_time": "2020-04-09T11:53:03.488024Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "English app Google 9614 and IOS 6183\n",
      "Non English app Google 45 and IOS 1014\n"
     ]
    }
   ],
   "source": [
    "android_english = []\n",
    "android_non_eng = []\n",
    "\n",
    "for app in android_clean:\n",
    "    name= app[0]\n",
    "    if english_app(name):\n",
    "        android_english.append(app)\n",
    "    else:\n",
    "        android_non_eng.append(app)\n",
    "\n",
    "ios_english = []\n",
    "ios_non_eng = []\n",
    "        \n",
    "for app in ios:\n",
    "    name= app[1]\n",
    "    if english_app(name):\n",
    "        ios_english.append(app)\n",
    "    else:\n",
    "        ios_non_eng.append(app)\n",
    "        \n",
    "print('English app Google {} and IOS {}'.format(len(android_english),len(ios_english)))\n",
    "print('Non English app Google {} and IOS {}'.format(len(android_non_eng),len(ios_non_eng)))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__3.4 Isolating the Free Apps__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:53:04.547320Z",
     "start_time": "2020-04-09T11:53:04.527426Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finale data set Google App 8864, and IOS app 3222\n"
     ]
    }
   ],
   "source": [
    "android_final =[]\n",
    "ios_final = []\n",
    "\n",
    "for app in android_english:\n",
    "    price = app[7]\n",
    "    if price =='0':\n",
    "        android_final.append(app)\n",
    "\n",
    "for app in ios_english:\n",
    "    price = app[4]\n",
    "    if price =='0.0':\n",
    "        ios_final.append(app)\n",
    "print('Finale data set Google App {}, and IOS app {}'.format(len(android_final),len(ios_final)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To minimize risks and overhead, our validation strategy for an app idea is comprised of three steps:\n",
    "\n",
    "Build a minimal Android version of the app, and add it to Google Play.\n",
    "If the app has a good response from users, we develop it further.\n",
    "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": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:54:46.768535Z",
     "start_time": "2020-04-09T11:54:46.742914Z"
    }
   },
   "outputs": [],
   "source": [
    "def freq_table(dataset, index):\n",
    "    table = {}\n",
    "    total = 0\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",
    "    table_percent ={}\n",
    "    \n",
    "    for key in table:\n",
    "        percente = (table[key]/total)*100\n",
    "        table_percent[key] = percente\n",
    "    return table_percent\n",
    "\n",
    "def display_table (dataset,index):\n",
    "    table= freq_table(dataset, index)\n",
    "    table_display = []\n",
    "    for key in table:\n",
    "        key_val = (table[key],key)\n",
    "        table_display.append(key_val)\n",
    "        \n",
    "    table_sorted = sorted(table_display, reverse= True)\n",
    "    for entry in table_sorted:\n",
    "        print(entry[1],':', round(entry[0],2), '%')\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:54:49.127140Z",
     "start_time": "2020-04-09T11:54:49.110900Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FAMILY : 19.22 %\n",
      "GAME : 9.51 %\n",
      "TOOLS : 8.46 %\n",
      "BUSINESS : 4.58 %\n",
      "LIFESTYLE : 3.9 %\n",
      "PRODUCTIVITY : 3.89 %\n",
      "FINANCE : 3.7 %\n",
      "MEDICAL : 3.54 %\n",
      "SPORTS : 3.42 %\n",
      "PERSONALIZATION : 3.32 %\n",
      "COMMUNICATION : 3.25 %\n",
      "HEALTH_AND_FITNESS : 3.07 %\n",
      "PHOTOGRAPHY : 2.94 %\n",
      "NEWS_AND_MAGAZINES : 2.8 %\n",
      "SOCIAL : 2.66 %\n",
      "TRAVEL_AND_LOCAL : 2.34 %\n",
      "SHOPPING : 2.25 %\n",
      "BOOKS_AND_REFERENCE : 2.14 %\n",
      "DATING : 1.86 %\n",
      "VIDEO_PLAYERS : 1.78 %\n",
      "MAPS_AND_NAVIGATION : 1.4 %\n",
      "FOOD_AND_DRINK : 1.24 %\n",
      "EDUCATION : 1.13 %\n",
      "LIBRARIES_AND_DEMO : 0.94 %\n",
      "AUTO_AND_VEHICLES : 0.93 %\n",
      "ENTERTAINMENT : 0.88 %\n",
      "HOUSE_AND_HOME : 0.82 %\n",
      "WEATHER : 0.8 %\n",
      "EVENTS : 0.71 %\n",
      "PARENTING : 0.65 %\n",
      "ART_AND_DESIGN : 0.64 %\n",
      "COMICS : 0.62 %\n",
      "BEAUTY : 0.6 %\n"
     ]
    }
   ],
   "source": [
    "display_table(android_final,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-09T11:54:52.588156Z",
     "start_time": "2020-04-09T11:54:52.577826Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Games : 58.16 %\n",
      "Entertainment : 7.88 %\n",
      "Photo & Video : 4.97 %\n",
      "Education : 3.66 %\n",
      "Social Networking : 3.29 %\n",
      "Shopping : 2.61 %\n",
      "Utilities : 2.51 %\n",
      "Sports : 2.14 %\n",
      "Music : 2.05 %\n",
      "Health & Fitness : 2.02 %\n",
      "Productivity : 1.74 %\n",
      "Lifestyle : 1.58 %\n",
      "News : 1.33 %\n",
      "Travel : 1.24 %\n",
      "Finance : 1.12 %\n",
      "Weather : 0.87 %\n",
      "Food & Drink : 0.81 %\n",
      "Reference : 0.56 %\n",
      "Business : 0.53 %\n",
      "Book : 0.43 %\n",
      "Navigation : 0.19 %\n",
      "Medical : 0.19 %\n",
      "Catalogs : 0.12 %\n"
     ]
    }
   ],
   "source": [
    "display_table(ios_final,-5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that among the free English apps, more than a half (58.16%) are games. Entertainment apps are close to 8%, followed by photo and video apps, which are close to 5%. Only 3.66% of the apps are designed for education, followed by social networking apps which amount for 3.29% of the apps in our data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T05:44:04.515284Z",
     "start_time": "2020-04-04T05:44:04.437100Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tools : 8.449909747292418\n",
      "Entertainment : 6.069494584837545\n",
      "Education : 5.347472924187725\n",
      "Business : 4.580324909747293\n",
      "Productivity : 3.892148014440433\n",
      "Lifestyle : 3.892148014440433\n",
      "Finance : 3.7003610108303246\n",
      "Medical : 3.5424187725631766\n",
      "Sports : 3.463447653429603\n",
      "Personalization : 3.3167870036101084\n",
      "Communication : 3.2490974729241873\n",
      "Action : 3.1024368231046933\n",
      "Health & Fitness : 3.068592057761733\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 : 1.861462093862816\n",
      "Video Players & Editors : 1.782490974729242\n",
      "Casual : 1.7486462093862816\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 : 0.4399819494584838\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",
      "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;Brain Games : 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": [
    "display_table(android_final,-4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__The difference between the Genres and the Category columns is not crystal clear, but one thing we can notice is that the Genres column is much more granular (it has more categories). We're only looking for the bigger picture at the moment, so we'll only work with the Category column moving forward.__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Most Popular Apps by Genre on the App Store"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:06:09.124131Z",
     "start_time": "2020-04-04T06:06:09.077381Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Social Networking : 71548.35\n",
      "Photo & Video : 28441.54\n",
      "Games : 22788.67\n",
      "Music : 57326.53\n",
      "Reference : 74942.11\n",
      "Health & Fitness : 23298.02\n",
      "Weather : 52279.89\n",
      "Utilities : 18684.46\n",
      "Travel : 28243.8\n",
      "Shopping : 26919.69\n",
      "News : 21248.02\n",
      "Navigation : 86090.33\n",
      "Lifestyle : 16485.76\n",
      "Entertainment : 14029.83\n",
      "Food & Drink : 33333.92\n",
      "Sports : 23008.9\n",
      "Book : 39758.5\n",
      "Finance : 31467.94\n",
      "Education : 7003.98\n",
      "Productivity : 21028.41\n",
      "Business : 7491.12\n",
      "Catalogs : 4004.0\n",
      "Medical : 612.0\n"
     ]
    }
   ],
   "source": [
    "genre_ios = freq_table(ios_final,-5)\n",
    "for genre in genre_ios:\n",
    "    total=0\n",
    "    len_genre= 0\n",
    "    for app in ios_final:\n",
    "        genre_app = app[-5]\n",
    "        if genre_app ==genre:\n",
    "            n_rating = float(app[5])\n",
    "            total +=n_rating\n",
    "            len_genre +=1\n",
    "    avg_rating =round(total/len_genre,2)\n",
    "    print(genre, ':', avg_rating)     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T05:54:26.837845Z",
     "start_time": "2020-04-04T05:54:26.816266Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Social Networking': 3.2898820608317814,\n",
       " 'Photo & Video': 4.9658597144630665,\n",
       " 'Games': 58.16263190564867,\n",
       " 'Music': 2.0484171322160147,\n",
       " 'Reference': 0.5586592178770949,\n",
       " 'Health & Fitness': 2.0173805090006205,\n",
       " 'Weather': 0.8690254500310366,\n",
       " 'Utilities': 2.5139664804469275,\n",
       " 'Travel': 1.2414649286157666,\n",
       " 'Shopping': 2.60707635009311,\n",
       " 'News': 1.3345747982619491,\n",
       " 'Navigation': 0.186219739292365,\n",
       " 'Lifestyle': 1.5828677839851024,\n",
       " 'Entertainment': 7.883302296710118,\n",
       " 'Food & Drink': 0.8069522036002483,\n",
       " 'Sports': 2.1415270018621975,\n",
       " 'Book': 0.4345127250155183,\n",
       " 'Finance': 1.1173184357541899,\n",
       " 'Education': 3.662321539416512,\n",
       " 'Productivity': 1.7380509000620732,\n",
       " 'Business': 0.5276225946617008,\n",
       " 'Catalogs': 0.12414649286157665,\n",
       " 'Medical': 0.186219739292365}"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "freq_table(ios_final,-5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On average, navigation apps have the highest number of user reviews, but this figure is heavily influenced by Waze and Google Maps, which have close to half a million user reviews together:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:09:51.001717Z",
     "start_time": "2020-04-04T06:09:50.990059Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Waze - GPS Navigation, Maps & Real-time Traffic : 345046\n",
      "Google Maps - Navigation & Transit : 154911\n",
      "Geocaching® : 12811\n",
      "CoPilot GPS – Car Navigation & Offline Maps : 3582\n",
      "ImmobilienScout24: Real Estate Search in Germany : 187\n",
      "Railway Route Search : 5\n"
     ]
    }
   ],
   "source": [
    "for app in ios_final:\n",
    "    if app[-5]=='Navigation':\n",
    "        print(app[1],':',app[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Most Popular Apps by Genre on Google Play"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:28:33.947747Z",
     "start_time": "2020-04-04T06:28:33.934507Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1,000,000+ : 15.749097472924186\n",
      "100,000+ : 11.563628158844766\n",
      "10,000,000+ : 10.503158844765343\n",
      "10,000+ : 10.209837545126353\n",
      "1,000+ : 8.393501805054152\n",
      "100+ : 6.915613718411552\n",
      "5,000,000+ : 6.825361010830325\n",
      "500,000+ : 5.561823104693141\n",
      "50,000+ : 4.7721119133574\n",
      "5,000+ : 4.512635379061372\n",
      "10+ : 3.5424187725631766\n",
      "500+ : 3.2490974729241873\n",
      "50,000,000+ : 2.3014440433213\n",
      "100,000,000+ : 2.1322202166064983\n",
      "50+ : 1.917870036101083\n",
      "5+ : 0.78971119133574\n",
      "1+ : 0.5076714801444043\n",
      "500,000,000+ : 0.2707581227436823\n",
      "1,000,000,000+ : 0.22563176895306858\n",
      "0+ : 0.04512635379061372\n",
      "0 : 0.01128158844765343\n"
     ]
    }
   ],
   "source": [
    "display_table(android_final, 5) # the Installs columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:33:48.942953Z",
     "start_time": "2020-04-04T06:33:48.833260Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ART_AND_DESIGN : 1986335.09\n",
      "AUTO_AND_VEHICLES : 647317.82\n",
      "BEAUTY : 513151.89\n",
      "BOOKS_AND_REFERENCE : 8767811.89\n",
      "BUSINESS : 1704192.34\n",
      "COMICS : 817657.27\n",
      "COMMUNICATION : 38326063.2\n",
      "DATING : 854028.83\n",
      "EDUCATION : 1768500.0\n",
      "ENTERTAINMENT : 9146923.08\n",
      "EVENTS : 253542.22\n",
      "FINANCE : 1387692.48\n",
      "FOOD_AND_DRINK : 1924897.74\n",
      "HEALTH_AND_FITNESS : 4167457.36\n",
      "HOUSE_AND_HOME : 1331540.56\n",
      "LIBRARIES_AND_DEMO : 638503.73\n",
      "LIFESTYLE : 1437816.27\n",
      "GAME : 12914435.88\n",
      "FAMILY : 5180161.79\n",
      "MEDICAL : 123064.79\n",
      "SOCIAL : 23253652.13\n",
      "SHOPPING : 7036877.31\n",
      "PHOTOGRAPHY : 17840110.4\n",
      "SPORTS : 4274688.72\n",
      "TRAVEL_AND_LOCAL : 13984077.71\n",
      "TOOLS : 10801391.3\n",
      "PERSONALIZATION : 5201482.61\n",
      "PRODUCTIVITY : 16772838.59\n",
      "PARENTING : 542603.62\n",
      "WEATHER : 5074486.2\n",
      "VIDEO_PLAYERS : 24790074.18\n",
      "NEWS_AND_MAGAZINES : 9549178.47\n",
      "MAPS_AND_NAVIGATION : 4056941.77\n"
     ]
    }
   ],
   "source": [
    "cat_android = freq_table(android_final, 1)\n",
    "for cat in cat_android:\n",
    "    total =0\n",
    "    len_cat = 0\n",
    "    for app in android_final:\n",
    "        cat_app= app[1]\n",
    "        if cat_app ==cat:\n",
    "            n_installs = app[5]\n",
    "            n_installs = n_installs.replace(',', '')\n",
    "            n_installs = n_installs.replace('+', '')\n",
    "            total += float(n_installs)\n",
    "            len_cat += 1\n",
    "    avg_n_installs = round(total / len_cat,2)\n",
    "    print(cat, ':', avg_n_installs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:39:49.766635Z",
     "start_time": "2020-04-04T06:39:49.753336Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Messenger – Text and Video Chat for Free : 1,000,000,000+\n",
      "Gmail : 1,000,000,000+\n",
      "imo beta free calls and text : 100,000,000+\n",
      "imo free video calls and chat : 500,000,000+\n",
      "Android Messages : 100,000,000+\n",
      "Google Duo - High Quality Video Calls : 500,000,000+\n",
      "UC Browser - Fast Download Private & Secure : 500,000,000+\n",
      "Skype - free IM & video calls : 1,000,000,000+\n",
      "Who : 100,000,000+\n",
      "GO SMS Pro - Messenger, Free Themes, Emoji : 100,000,000+\n",
      "WhatsApp Messenger : 1,000,000,000+\n",
      "Google Chrome: Fast & Secure : 1,000,000,000+\n",
      "Firefox Browser fast & private : 100,000,000+\n",
      "Messenger Lite: Free Calls & Messages : 100,000,000+\n",
      "LINE: Free Calls & Messages : 500,000,000+\n",
      "Hangouts : 1,000,000,000+\n",
      "Kik : 100,000,000+\n",
      "KakaoTalk: Free Calls & Text : 100,000,000+\n",
      "Opera Mini - fast web browser : 100,000,000+\n",
      "Opera Browser: Fast and Secure : 100,000,000+\n",
      "Telegram : 100,000,000+\n",
      "Truecaller: Caller ID, SMS spam blocking & Dialer : 100,000,000+\n",
      "UC Browser Mini -Tiny Fast Private & Secure : 100,000,000+\n",
      "Viber Messenger : 500,000,000+\n",
      "WeChat : 100,000,000+\n",
      "Yahoo Mail – Stay Organized : 100,000,000+\n",
      "BBM - Free Calls & Messages : 100,000,000+\n"
     ]
    }
   ],
   "source": [
    "for app in android_final:\n",
    "    if app[1] == 'COMMUNICATION' and (app[5] == '1,000,000,000+'\n",
    "                                      or app[5] == '500,000,000+'\n",
    "                                      or app[5] == '100,000,000+'):\n",
    "        print(app[0],':',app[5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-04-04T06:51:04.725841Z",
     "start_time": "2020-04-04T06:51:04.711499Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cookpad - FREE recipe search makes fun cooking · musical making! : 10,000,000+\n",
      "DELISH KITCHEN - FREE recipe movies make food fun and easy! : 1,000,000+\n",
      "Delicious Recipes : 1,000,000+\n",
      "Tastely : 10,000,000+\n",
      "Pastry & Cooking (Without Net) : 1,000,000+\n",
      "McDonald's - McDonald's Japan : 10,000,000+\n",
      "Pyaterochka : 1,000,000+\n",
      "Refreshing app Free application that can use deal coupons : 1,000,000+\n",
      "Grubhub: Food Delivery : 5,000,000+\n",
      "hellofood - Food Delivery : 1,000,000+\n",
      "Domino's Pizza USA : 10,000,000+\n",
      "Chef - Recipes & Cooking : 5,000,000+\n",
      "Delivery Club-food delivery: pizza, sushi, burger, salad : 5,000,000+\n",
      "HungerStation : 1,000,000+\n",
      "Delivery yogi. : 10,000,000+\n",
      "Delivery trough - delivery trough delivery trough : 5,000,000+\n",
      "Dr. Oetker recipe ideas : 1,000,000+\n",
      "GialloZafferano: Recipes : 1,000,000+\n",
      "OpenRice : 1,000,000+\n",
      "Eat Fast Prepare \"Without Internet\" : 1,000,000+\n",
      "Cookbook Recipes : 5,000,000+\n",
      "My CookBook (Recipe Manager) : 1,000,000+\n",
      "Allrecipes Dinner Spinner : 5,000,000+\n",
      "Yummly Recipes & Shopping List : 1,000,000+\n",
      "Kitchen Stories - Recipes & Cooking : 1,000,000+\n",
      "Cookpad : 10,000,000+\n",
      "BigOven Recipes, Meal Planner, Grocery List & More : 1,000,000+\n",
      "Postmates Food Delivery: Order Eats & Alcohol : 1,000,000+\n",
      "Instacart: Grocery Delivery : 1,000,000+\n",
      "OpenTable: Restaurants Near Me : 5,000,000+\n",
      "Foursquare City Guide : 10,000,000+\n",
      "Eat24 Food Delivery & Takeout : 1,000,000+\n",
      "Pizza Hut : 10,000,000+\n",
      "DoorDash - Food Delivery : 1,000,000+\n",
      "Uber Eats: Local Food Delivery : 10,000,000+\n",
      "Seamless Food Delivery/Takeout : 1,000,000+\n",
      "Talabat: Food Delivery : 5,000,000+\n",
      "TheFork - Restaurants booking and special offers : 5,000,000+\n",
      "foodpanda - Local Food Delivery : 10,000,000+\n",
      "Zomato - Restaurant Finder and Food Delivery App : 10,000,000+\n",
      "Chick-fil-A : 5,000,000+\n",
      "BeyondMenu Food Delivery : 1,000,000+\n",
      "SONIC Drive-In : 1,000,000+\n",
      "McDonald's : 10,000,000+\n",
      "Wendy’s – Food and Offers : 1,000,000+\n",
      "Dunkin' Donuts : 1,000,000+\n",
      "SUBWAY® : 1,000,000+\n",
      "Panera Bread : 1,000,000+\n",
      "Starbucks : 10,000,000+\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for app in android_final:\n",
    "    if app[1] == 'FOOD_AND_DRINK' and (app[5] == '1,000,000+'\n",
    "                                            or app[5] == '5,000,000+'\n",
    "                                            or app[5] == '10,000,000+'\n",
    "                                            or app[5] == '50,000,000+'\n",
    "                                            or app[5] == '100,000,000+'):\n",
    "        print(app[0],':',app[5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}