Notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# My Analysis on Profitable App Profiles for the App Store and Google Play Markets\n",
    "<p> <img src= \"https://th.bing.com/th/id/R.a596c49ca2cc35b17afb8f7bb409d6e9?rik=FEj0zMShEH1Dmg&riu=http%3a%2f%2fwww.androidblogg.com%2fwp-content%2fuploads%2f2020%2f05%2fstore.png&ehk=DxTAb1otCmYQT6SjtlNtOqZqIBUus28lxDLpZEYRmqo%3d&risl=&pid=ImgRaw&r=0\"></p>\n",
    "\n",
    "## The goal for this project is to analyze data and find mobile app profiles that are profitable for the App Store and Google Play markets and likely to attract more users.\n",
    "\n",
    "## I'm going to use two data sets for this project:\n",
    "* [A dataset](https://www.kaggle.com/lava18/google-play-store-apps) containing data of about 10,000 Apps from Google Play; the data was collected in August 2018. The data can be found on [Here]( https://www.kaggle.com/lava18/google-play-store-apps), on Kaggle.\n",
    "\n",
    "* [A dataset](https://www.kaggle.com/datasets/ramamet4/app-store-apple-data-set-10k-apps) containing data of about 7,000 Apps from App Store; the data was collected in August 2018. The data can be found on [Here]( https://www.kaggle.com/lava18/google-play-store-apps), on Kaggle.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# I Start by opening the two data sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open(\"AppleStore.csv\", encoding='utf8')\n",
    "from csv import reader\n",
    "read_file = reader(file)\n",
    "Applestore_data = list(read_file)\n",
    "\n",
    "file = open(\"googleplaystore.csv\", encoding='utf8')\n",
    "from csv import reader\n",
    "read_file = reader(file)\n",
    "Playstore_data = list(read_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## In the cell below I define a function named explore_data() that can be used repeatedly to explore rows in a more readable way, and i also added a feature to show the number of rows and columns for any data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "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')\n",
    "\n",
    "    if rows_and_columns:\n",
    "        print('Number of rows:', len(dataset))\n",
    "        print('Number of columns:', len(dataset[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using the function to Explore the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "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",
      "Number of rows: 10842\n",
      "Number of columns: 13\n"
     ]
    }
   ],
   "source": [
    "print(Playstore_data[0])#Prints the header row from the dataset\n",
    "print(\"\\n\")\n",
    "explore_data(Playstore_data, 1,3,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "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",
      "Number of rows: 7198\n",
      "Number of columns: 16\n"
     ]
    }
   ],
   "source": [
    "print(Applestore_data[0])#Prints the header row from the dataset\n",
    "print(\"\\n\")\n",
    "explore_data(Applestore_data, 1,3,True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Cleansing\n",
    "<p> <img src =\"https://www.expertcallers.com/blog/wp-content/uploads/2020/04/data-cleansing-services.jpg\" width = \"80%\" align=\"center\"></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On going through the Google Play data set dedicated discussion section, an error for row 10472, which is row 10473 in the data set, was outlined in one of the discussions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12\n",
      "13\n"
     ]
    }
   ],
   "source": [
    "print(len(Playstore_data[10473]))\n",
    "print(len(Playstore_data[10500]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the cell above i compared the length of row 10473 with another row to see the difference between the lengths.\n",
    "\n",
    "Below I'm now using a built in function `del()`, to delete that incomplete row."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10841\n"
     ]
    }
   ],
   "source": [
    "del(Playstore_data[10473])\n",
    "print (len(Playstore_data))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From exploring the data i also noticed that some apps have some duplicate entries in the `Playstore_data`<br>\n",
    "Example Below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Google My Business', 'BUSINESS', '4.4', '70991', 'Varies with device', '5,000,000+', 'Free', '0', 'Everyone', 'Business', 'July 24, 2018', '2.19.0.204537701', '4.4 and up']\n",
      "['Google My Business', 'BUSINESS', '4.4', '70991', 'Varies with device', '5,000,000+', 'Free', '0', 'Everyone', 'Business', 'July 24, 2018', '2.19.0.204537701', '4.4 and up']\n",
      "['Google My Business', 'BUSINESS', '4.4', '70991', 'Varies with device', '5,000,000+', 'Free', '0', 'Everyone', 'Business', 'July 24, 2018', '2.19.0.204537701', '4.4 and up']\n"
     ]
    }
   ],
   "source": [
    "for rows in Playstore_data:\n",
    "    if rows[0] == \"Google My Business\":\n",
    "        print (rows)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I don't want to count certain apps more than once when analyzing the data, So im removing the duplicate entries and keeping only one entry per app.\n",
    "But rather than removing duplicates randomly, I'll keep only the row with the highest number of review.\n",
    " _The higher the number of reviews, the more recent the data should be._"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Removing Duplicate apps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1181\n",
      "9659\n"
     ]
    }
   ],
   "source": [
    "duplicate_apps = []\n",
    "unique_apps = []\n",
    "for row in Playstore_data[1:]:\n",
    "    x = row[0]\n",
    "    if x in unique_apps:\n",
    "        duplicate_apps.append(x)\n",
    "    else:\n",
    "        unique_apps.append(x)\n",
    "print(len(duplicate_apps))\n",
    "print(len(unique_apps))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Quick PDF Scanner + OCR FREE', 'Box', 'Google My Business']\n"
     ]
    }
   ],
   "source": [
    "print(duplicate_apps[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9659\n"
     ]
    }
   ],
   "source": [
    "reviews_max = {}\n",
    "for rows in Playstore_data[1:]:\n",
    "    names = rows[0]\n",
    "    n_reviews = float(rows[3])\n",
    "    if names in reviews_max and reviews_max[names] < n_reviews:\n",
    "        reviews_max[names] = n_reviews\n",
    "    elif names not in reviews_max:\n",
    "        reviews_max[names] = n_reviews\n",
    "print(len(reviews_max))\n",
    "# print(reviews_max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "android_clean = []\n",
    "already_added = []\n",
    "\n",
    "for rows in Playstore_data[1:]:\n",
    "    name = rows[0]\n",
    "    n_reviews = float(rows[3])\n",
    "    if n_reviews == reviews_max[name] and name not in already_added:\n",
    "        android_clean.append(rows)\n",
    "        already_added.append(name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "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",
      "['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",
      "Number of rows: 9659\n",
      "Number of columns: 13\n"
     ]
    }
   ],
   "source": [
    "explore_data(android_clean, 0, 3, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## After removing the duplicates from the Playstore_data, im left with **9659 rows** and **13 Column** in the **android_clean** dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From exploring the both dataset android_clean and Applestore_data, i also noticed that there are some Non-English apps with names that suggest they are not designed for an English-speaking audience. But the analysis is only the only apps that are designed for an English-speaking audience, so I am removing them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "English text usually includes letters from the English alphabet, numbers composed of digits from 0 to 9, punctuation marks (., !, ?, ;, etc.), and other symbols (+, *, /, etc.).<br>\n",
    "All these characters that are specific to English texts are encoded using the ASCII standard. Each ASCII character has a corresponding number between 0 and 127 associated with it.\n",
    "So im using that advantage to build a function `is_eng()` that checks an app name and tells us whether it contains non-ASCII characters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To minimize the impact of data loss, i'll tune the function to only remove an app if its name has more than three characters with corresponding numbers falling outside the ASCII range. \n",
    "<br>\n",
    "This means all English apps with up to three emoji or other special characters will still be labeled as English. The function is still not perfect, but it should be fairly effective."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def is_eng(x):\n",
    "    x = str(x)\n",
    "    z = 0\n",
    "    for y in x:\n",
    "        if ord(y) > 127:\n",
    "            z += 1\n",
    "    if z > 3:\n",
    "        return False\n",
    "    else:\n",
    "        return True\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(is_eng('Docs To Go™ Free Office Suite'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the cell below, i am now using the `is_eng()` function to filter out the non-English apps for both data sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9614\n"
     ]
    }
   ],
   "source": [
    "English_apps_android = []\n",
    "for row in android_clean:\n",
    "    name = row[0]\n",
    "    if is_eng(name):\n",
    "        English_apps_android.append(row)\n",
    "print(len(English_apps_android))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6183\n"
     ]
    }
   ],
   "source": [
    "English_apps_apple = []\n",
    "for row in Applestore_data[1:]:\n",
    "    name = row[1]\n",
    "    if is_eng(name):\n",
    "        English_apps_apple.append(row)\n",
    "print(len(English_apps_apple))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### After filtering out the Non-English apps, I'm now Left with 9614 Android apps and 6183 iOS Apps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " These datasets still have to go through one more layer of filtering because the datasets contain both free and non-free apps; and for the analysis, i'll need to isolate only the free apps. That will be the last step in the data cleaning process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8864\n"
     ]
    }
   ],
   "source": [
    "Free_Eng_android = []\n",
    "for row in English_apps_android:\n",
    "    price = row[7]\n",
    "    if price == \"0.0\" or price == \"0\":\n",
    "        Free_Eng_android.append(row)\n",
    "print(len(Free_Eng_android))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3222\n"
     ]
    }
   ],
   "source": [
    "Free_Eng_apple = []\n",
    "for row in English_apps_apple:\n",
    "    price = row[4]\n",
    "    if price == \"0.0\" or price == \"0\":\n",
    "        Free_Eng_apple.append(row)\n",
    "print(len(Free_Eng_apple))\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## So far in the Data Cleaning process, i have been able to:\n",
    "\n",
    "* Remove inaccurate data\n",
    "* Remove duplicate app entries\n",
    "* Remove non-English apps\n",
    "* Isolate the Free Apps\n",
    "<br>\n",
    "\n",
    "Which leaves me with **_8864_ Android apps** and **_3222_ iOS apps**, which should be enough for the analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " <img src =\"https://th.bing.com/th/id/OIP.Hhhcsrwe6mvnWqvOjelUqgHaEK?pid=ImgDet&rs=1\" align =\"center\" width =\"80%\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  _The aim of this analysis is to determine the kinds of apps that are likely to attract more users both in the App Store and Google Playstore._"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PHASE 1 \n",
    "## Most Common Apps by Genre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I begin the analysis by getting a sense of the most common genres for each market, that is; app categories that are popular on both markets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For that im going to need to build two functions that will be used to analyze the Data sets:\n",
    "\n",
    "* The function `freq_table()` that will generate frequency tables of any column in the dataset.\n",
    "* Another function `display_table` that will be used to display the percentages in a descending order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creates the Frequency Table\n",
    "def freq_table(dataset,column):\n",
    "    frequency_table = {}\n",
    "    total = 0\n",
    "    for row in dataset:\n",
    "        total +=1\n",
    "        x = row[column]\n",
    "        if x in frequency_table:\n",
    "            frequency_table[x] += 1\n",
    "        else:\n",
    "            frequency_table[x] = 1\n",
    "    table_percentages = {}\n",
    "    for key in frequency_table:\n",
    "        percentage = (frequency_table[key] / total) * 100\n",
    "        table_percentages[key] = percentage \n",
    "    \n",
    "    return table_percentages\n",
    "            \n",
    "#Displays the table in Descending Order\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",
    "    from prettytable import PrettyTable\n",
    "\n",
    "    myTable = PrettyTable([\"GENRE\",  \"Frequency(%)\"])\n",
    " \n",
    "    for rows in table_sorted:\n",
    "        myTable.add_row([rows[1],rows[0]])\n",
    "    return myTable\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I am now generating a frequency table for the prime_genre column of the App Store Data set using the function `freq_table` i defined above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Social Networking': 3.2898820608317814, 'Photo & Video': 4.9658597144630665, 'Games': 58.16263190564867, 'Music': 2.0484171322160147, 'Reference': 0.5586592178770949, 'Health & Fitness': 2.0173805090006205, 'Weather': 0.8690254500310366, 'Utilities': 2.5139664804469275, 'Travel': 1.2414649286157666, 'Shopping': 2.60707635009311, 'News': 1.3345747982619491, 'Navigation': 0.186219739292365, 'Lifestyle': 1.5828677839851024, 'Entertainment': 7.883302296710118, 'Food & Drink': 0.8069522036002483, 'Sports': 2.1415270018621975, 'Book': 0.4345127250155183, 'Finance': 1.1173184357541899, 'Education': 3.662321539416512, 'Productivity': 1.7380509000620732, 'Business': 0.5276225946617008, 'Catalogs': 0.12414649286157665, 'Medical': 0.186219739292365}\n"
     ]
    }
   ],
   "source": [
    "table = freq_table(Free_Eng_apple,11)\n",
    "print(table)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The display_table function will now be used to display them in descending order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------------+---------------------+\n",
      "|       GENRE       |     Frequency(%)    |\n",
      "+-------------------+---------------------+\n",
      "|       Games       |  58.16263190564867  |\n",
      "|   Entertainment   |  7.883302296710118  |\n",
      "|   Photo & Video   |  4.9658597144630665 |\n",
      "|     Education     |  3.662321539416512  |\n",
      "| Social Networking |  3.2898820608317814 |\n",
      "|      Shopping     |   2.60707635009311  |\n",
      "|     Utilities     |  2.5139664804469275 |\n",
      "|       Sports      |  2.1415270018621975 |\n",
      "|       Music       |  2.0484171322160147 |\n",
      "|  Health & Fitness |  2.0173805090006205 |\n",
      "|    Productivity   |  1.7380509000620732 |\n",
      "|     Lifestyle     |  1.5828677839851024 |\n",
      "|        News       |  1.3345747982619491 |\n",
      "|       Travel      |  1.2414649286157666 |\n",
      "|      Finance      |  1.1173184357541899 |\n",
      "|      Weather      |  0.8690254500310366 |\n",
      "|    Food & Drink   |  0.8069522036002483 |\n",
      "|     Reference     |  0.5586592178770949 |\n",
      "|      Business     |  0.5276225946617008 |\n",
      "|        Book       |  0.4345127250155183 |\n",
      "|     Navigation    |  0.186219739292365  |\n",
      "|      Medical      |  0.186219739292365  |\n",
      "|      Catalogs     | 0.12414649286157665 |\n",
      "+-------------------+---------------------+\n"
     ]
    }
   ],
   "source": [
    "\n",
    "print(display_table(Free_Eng_apple,11))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get a clearer picture,\n",
    "The frequency table will now be used to plot a Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Matplotlib is building the font cache; this may take a moment.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels =[]\n",
    "sizes = []\n",
    "small_label = \"others\"\n",
    "sizes_small = 0\n",
    "for x,y in table.items():\n",
    "    labels.append(x)\n",
    "    sizes.append(y)\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "Colors = ['green','blue','purple','brown','teal']\n",
    "plt.figure(figsize=(8,8))\n",
    "plt.barh(labels,sizes, color=Colors)\n",
    "plt.title('Most Popular Genres in the Apple Store', fontsize=17)\n",
    "plt.xlabel('FREQUENCY', fontsize=14)\n",
    "plt.ylabel('GENRES', fontsize=14)\n",
    "#plt.xticks(fontsize=30)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this it can be seen that among the free English apps, more than a half (58.1%) are games. Entertainment apps are close to 8%, followed by photo and video apps, which amount for close to 5% of the apps in our data set.\n",
    "The general impression is that the App Store (at least the part containing free English apps) is dominated by apps that are designed for fun (games, entertainment, photo and video, social networking, sports, music, etc.), while apps with practical purposes (education, shopping, utilities, productivity, lifestyle, etc.) are more rare. \n",
    "However, the fact that fun apps are the most numerous doesn't also imply that they also have the greatest number of users — _The demand might not be the same as the Supply._\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Repeating the same process for the Category column of the Google Play data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---------------------+--------------------+\n",
      "|        GENRE        |    Frequency(%)    |\n",
      "+---------------------+--------------------+\n",
      "|        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",
      "+---------------------+--------------------+\n"
     ]
    }
   ],
   "source": [
    "table = freq_table(Free_Eng_android,1)\n",
    "print(display_table(Free_Eng_android,1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels =[]\n",
    "sizes = []\n",
    "for x,y in table.items():\n",
    "    labels.append(x)\n",
    "    sizes.append(y)\n",
    "Colors = ['green','blue','purple','brown','teal']\n",
    "plt.figure(figsize=(10,12))\n",
    "plt.barh(labels,sizes, color=Colors,align='center',)\n",
    "plt.title('Most Popular Category in the Play Store', fontsize=20)\n",
    "plt.xlabel('FREQUENCY', fontsize=15)\n",
    "plt.ylabel('CATEGORY', fontsize=15)\n",
    "#plt.xticks(rotation=90,fontsize=9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Things seem significantly different on Google Play Store: there are not that many apps designed for fun, A good number of apps are designed for practical purposes (family, tools, business, lifestyle, productivity, etc.)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, inspecting the Genre Column of the Google Play Store dataset which seem to be related to the Category Column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---------------------------------------+----------------------+\n",
      "|                 GENRE                 |     Frequency(%)     |\n",
      "+---------------------------------------+----------------------+\n",
      "|                 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",
      "+---------------------------------------+----------------------+\n"
     ]
    }
   ],
   "source": [
    "print(display_table(Free_Eng_android,-4))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There's no clear difference between the Genres and the Category columns of the Play Store Dataset, but one thing is that the Genres column is more granular and has more categories than the Categories Columns. <br>\n",
    "But because Im looking for the bigger picture at the moment, I'll only work with the Category column moving forward."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### _Up to this point, its safe enough to say that the App Store is dominated by apps designed for fun, while Google Play shows a more balanced landscape of both practical and for-fun apps._  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PHASE TWO\n",
    "# Most Popular Apps by Genre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The way im going to find out what genres have the most users is to calculate the average number of installs for each app genre. <br>For the Google Play data set, this information can be found in the Installs column, but it is missing for the App Store data set. <br>As a workaround, I'll take the total number of user ratings as a proxy, which can be found in the rating_count_tot column."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I'm starting with calculating the average number of user ratings per app genre on the App Store."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+-------------------+--------------------+\n",
      "|       GENRE       |  Average Ratings   |\n",
      "+-------------------+--------------------+\n",
      "|     Navigation    | 86090.33333333333  |\n",
      "|     Reference     | 74942.11111111111  |\n",
      "| Social Networking | 71548.34905660378  |\n",
      "|       Music       | 57326.530303030304 |\n",
      "|      Weather      | 52279.892857142855 |\n",
      "|        Book       |      39758.5       |\n",
      "|    Food & Drink   | 33333.92307692308  |\n",
      "|      Finance      | 31467.944444444445 |\n",
      "|   Photo & Video   |    28441.54375     |\n",
      "|       Travel      |      28243.8       |\n",
      "|      Shopping     | 26919.690476190477 |\n",
      "|  Health & Fitness | 23298.015384615384 |\n",
      "|       Sports      | 23008.898550724636 |\n",
      "|       Games       |  22788.6696905016  |\n",
      "|        News       | 21248.023255813954 |\n",
      "|    Productivity   | 21028.410714285714 |\n",
      "|     Utilities     | 18684.456790123455 |\n",
      "|     Lifestyle     | 16485.764705882353 |\n",
      "|   Entertainment   | 14029.830708661417 |\n",
      "|      Business     | 7491.117647058823  |\n",
      "|     Education     | 7003.983050847458  |\n",
      "|      Catalogs     |       4004.0       |\n",
      "|      Medical      |       612.0        |\n",
      "+-------------------+--------------------+\n"
     ]
    }
   ],
   "source": [
    "table = freq_table(Free_Eng_apple,-5)\n",
    "avg_rating = {}\n",
    "for names in table:\n",
    "    total = 0\n",
    "    len_genre = 0\n",
    "    for rows in Free_Eng_apple:\n",
    "        genre_app = rows[-5]\n",
    "        if genre_app == names:\n",
    "            float_genre = float(rows[5])\n",
    "            total += float_genre\n",
    "            len_genre += 1\n",
    "    avg_genre_rating = total /len_genre\n",
    "    avg_rating[names]=avg_genre_rating\n",
    "table_display = []\n",
    "for key in avg_rating:\n",
    "    key_val_as_tuple = (avg_rating[key], key)\n",
    "    table_display.append(key_val_as_tuple)\n",
    "    table_sorted = sorted(table_display, reverse = True)\n",
    "from prettytable import PrettyTable\n",
    "myTable = PrettyTable([\"GENRE\",  \"Average Ratings\"])\n",
    " \n",
    "for key in table_sorted:\n",
    "    myTable.add_row([key[1],key[0]])\n",
    "print( myTable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On an average, Navigation apps have the highest number of user reviews.."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From exploring the apps under the navigation genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "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 Free_Eng_apple:\n",
    "    if app[-5] == 'Navigation':\n",
    "        print(app[1], ':', app[5]) # print name and number of ratings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "i can see that close to half a million user reviews on Google Maps and Waze have heavily influenced the average rating of this genre(Navigation)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Moving over to the second most highest rating: Reference Genre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bible : 985920\n",
      "Dictionary.com Dictionary & Thesaurus : 200047\n",
      "Dictionary.com Dictionary & Thesaurus for iPad : 54175\n",
      "Google Translate : 26786\n",
      "Muslim Pro: Ramadan 2017 Prayer Times, Azan, Quran : 18418\n",
      "New Furniture Mods - Pocket Wiki & Game Tools for Minecraft PC Edition : 17588\n",
      "Merriam-Webster Dictionary : 16849\n",
      "Night Sky : 12122\n",
      "City Maps for Minecraft PE - The Best Maps for Minecraft Pocket Edition (MCPE) : 8535\n",
      "LUCKY BLOCK MOD ™ for Minecraft PC Edition - The Best Pocket Wiki & Mods Installer Tools : 4693\n",
      "GUNS MODS for Minecraft PC Edition - Mods Tools : 1497\n",
      "Guides for Pokémon GO - Pokemon GO News and Cheats : 826\n",
      "WWDC : 762\n",
      "Horror Maps for Minecraft PE - Download The Scariest Maps for Minecraft Pocket Edition (MCPE) Free : 718\n",
      "VPN Express : 14\n",
      "Real Bike Traffic Rider Virtual Reality Glasses : 8\n",
      "教えて!goo : 0\n",
      "Jishokun-Japanese English Dictionary & Translator : 0\n"
     ]
    }
   ],
   "source": [
    "for app in Free_Eng_apple:\n",
    "    if app[-5] == 'Reference':\n",
    "        print(app[1], ':', app[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, this genre seems to show some potential,even tho the Bible and Dictionary.com apps skewed up the average rating.<br> It fits well with the fact that the App Store is dominated by for-fun apps as seen in the First Phase of the analysis, which suggests the market might be a bit saturated with for-fun apps, which means that a practical app might have more of a chance to stand out among the huge number of apps on the App Store."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On to the next Dataset; the Google Play Dataset.\n",
    "## Most Popular Apps by Genre on Google Play"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the Google Play market, data about the number of installs were given, which helps to get a clearer picture about genre popularity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'10,000+': 10.198555956678701,\n",
       " '5,000,000+': 6.825361010830325,\n",
       " '50,000,000+': 2.3014440433213,\n",
       " '100,000+': 11.552346570397113,\n",
       " '50,000+': 4.7721119133574,\n",
       " '1,000,000+': 15.726534296028879,\n",
       " '10,000,000+': 10.548285198555957,\n",
       " '5,000+': 4.512635379061372,\n",
       " '500,000+': 5.561823104693141,\n",
       " '1,000,000,000+': 0.22563176895306858,\n",
       " '100,000,000+': 2.1322202166064983,\n",
       " '1,000+': 8.393501805054152,\n",
       " '500,000,000+': 0.2707581227436823,\n",
       " '500+': 3.2490974729241873,\n",
       " '100+': 6.915613718411552,\n",
       " '50+': 1.917870036101083,\n",
       " '10+': 3.5424187725631766,\n",
       " '1+': 0.5076714801444043,\n",
       " '5+': 0.78971119133574,\n",
       " '0+': 0.04512635379061372,\n",
       " '0': 0.01128158844765343}"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "freq_table(Free_Eng_android, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One problem with this data is that is not precise. For instance, I can't tell whether an app with 100,000+ installs has 100,000 installs or 200,000.\n",
    "I'm going to leave the numbers as they are, which means that an app with 100,000+ installs has 100,000 installs, and an app with 1,000,000+ installs has 1,000,000 installs, and so on."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To compute the average number of installs for each genre (category), I will need to remove the commas and the plus characters and convert each install number to `float`. Which would be done in the loop below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---------------------+--------------------+\n",
      "|        GENRE        |    Frequency(%)    |\n",
      "+---------------------+--------------------+\n",
      "|    COMMUNICATION    | 38456119.167247385 |\n",
      "|    VIDEO_PLAYERS    | 24727872.452830188 |\n",
      "|        SOCIAL       | 23253652.127118643 |\n",
      "|     PHOTOGRAPHY     | 17840110.40229885  |\n",
      "|     PRODUCTIVITY    | 16787331.344927534 |\n",
      "|         GAME        | 15588015.603248259 |\n",
      "|   TRAVEL_AND_LOCAL  | 13984077.710144928 |\n",
      "|    ENTERTAINMENT    | 11640705.88235294  |\n",
      "|        TOOLS        | 10801391.298666667 |\n",
      "|  NEWS_AND_MAGAZINES | 9549178.467741935  |\n",
      "| BOOKS_AND_REFERENCE | 8767811.894736841  |\n",
      "|       SHOPPING      | 7036877.311557789  |\n",
      "|   PERSONALIZATION   | 5201482.6122448975 |\n",
      "|       WEATHER       | 5074486.197183099  |\n",
      "|  HEALTH_AND_FITNESS | 4188821.9853479853 |\n",
      "| MAPS_AND_NAVIGATION | 4056941.7741935486 |\n",
      "|        FAMILY       | 3695641.8198090694 |\n",
      "|        SPORTS       | 3638640.1428571427 |\n",
      "|    ART_AND_DESIGN   | 1986335.0877192982 |\n",
      "|    FOOD_AND_DRINK   | 1924897.7363636363 |\n",
      "|      EDUCATION      | 1833495.145631068  |\n",
      "|       BUSINESS      | 1712290.1474201474 |\n",
      "|      LIFESTYLE      | 1437816.2687861272 |\n",
      "|       FINANCE       | 1387692.475609756  |\n",
      "|    HOUSE_AND_HOME   | 1331540.5616438356 |\n",
      "|        DATING       | 854028.8303030303  |\n",
      "|        COMICS       | 817657.2727272727  |\n",
      "|  AUTO_AND_VEHICLES  | 647317.8170731707  |\n",
      "|  LIBRARIES_AND_DEMO |  638503.734939759  |\n",
      "|      PARENTING      | 542603.6206896552  |\n",
      "|        BEAUTY       | 513151.88679245283 |\n",
      "|        EVENTS       | 253542.22222222222 |\n",
      "|       MEDICAL       | 120550.61980830671 |\n",
      "+---------------------+--------------------+\n"
     ]
    }
   ],
   "source": [
    "table = freq_table(Free_Eng_android,1)\n",
    "table_2 = {}\n",
    "#Remove characters from strings\n",
    "for cat in table:\n",
    "    total = 0\n",
    "    len_category = 0\n",
    "    for rows in Free_Eng_android:\n",
    "        category = rows[1]\n",
    "        if category == cat:\n",
    "            inst = rows[5]\n",
    "            inst =inst.replace(\"+\",\"\")\n",
    "            inst =inst.replace(\",\" ,\"\")\n",
    "            inst = float(inst)\n",
    "            total += inst\n",
    "            len_category += 1\n",
    "    avg_inst = total / len_category\n",
    "    table_2[cat] = avg_inst\n",
    "#Sorts table in Descending Order    \n",
    "table_display = []\n",
    "for key in table_2:\n",
    "    key_val_as_tuple = (table_2[key], key)\n",
    "    table_display.append(key_val_as_tuple)\n",
    "    table_sorted = sorted(table_display, reverse = True)\n",
    "#Displays a Fancy Table    \n",
    "from prettytable import PrettyTable\n",
    "myTable = PrettyTable([\"GENRE\",  \"Average Installs\"])\n",
    "for rows in table_sorted:\n",
    "    myTable.add_row([rows[1],rows[0]])\n",
    "    \n",
    "print(myTable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On average, communication apps have the most installs: 38,456,119. This number is heavily skewed up by a few apps that have over one billion installs (WhatsApp, Facebook Messenger, Skype, Google Chrome, Gmail, and Hangouts), and a few others with over 100 and 500 million installs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WhatsApp Messenger : 1,000,000,000+\n",
      "imo beta free calls and text : 100,000,000+\n",
      "Android Messages : 100,000,000+\n",
      "Google Duo - High Quality Video Calls : 500,000,000+\n",
      "Messenger – Text and Video Chat for Free : 1,000,000,000+\n",
      "imo free video calls and chat : 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",
      "LINE: Free Calls & Messages : 500,000,000+\n",
      "Google Chrome: Fast & Secure : 1,000,000,000+\n",
      "Firefox Browser fast & private : 100,000,000+\n",
      "UC Browser - Fast Download Private & Secure : 500,000,000+\n",
      "Gmail : 1,000,000,000+\n",
      "Hangouts : 1,000,000,000+\n",
      "Messenger Lite: Free Calls & Messages : 100,000,000+\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 Free_Eng_android:\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": "markdown",
   "metadata": {},
   "source": [
    "The same pattern can be found in the **Video Players** category, which is the runner-up with 24,727,872 installs. The market is dominated by apps like Youtube, Google Play Movies & TV, or MX Player.<br> The pattern is repeated for **Social Apps** (where we have giants like Facebook, Instagram, Google+, etc.), **Photography apps** (Google Photos and other popular photo editors), or **Productivity Apps** (Microsoft Word, Dropbox, Google Calendar, Evernote, etc.).<br>\n",
    "The main issue with these Genres(Category) is that these app genres might seem more popular than they really are, and these niches seem to be dominated by a few giants who are hard to compete against.<br>\n",
    "The **Game** genre seems pretty popular, but this part of the market seems a bit saturated as seen in the first phase, so it's best to come up with a different app recommendation.\n",
    "\n",
    "The **Books and Reference** genre looks fairly popular as well, with an average number of installs of 8,767,811. It's interesting to explore this in more depth, because this genre has some potential to work well on the App Store, and the aim is to recommend an app genre that shows potential for being profitable on both the App Store and Google Play.\n",
    "\n",
    "Taking a look at some of the apps from this genre(**Books and Reference genre**) and their number of installs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E-Book Read - Read Book for free : 50,000+\n",
      "Download free book with green book : 100,000+\n",
      "Wikipedia : 10,000,000+\n",
      "Cool Reader : 10,000,000+\n",
      "Free Panda Radio Music : 100,000+\n",
      "Book store : 1,000,000+\n",
      "FBReader: Favorite Book Reader : 10,000,000+\n",
      "English Grammar Complete Handbook : 500,000+\n",
      "Free Books - Spirit Fanfiction and Stories : 1,000,000+\n",
      "Google Play Books : 1,000,000,000+\n",
      "AlReader -any text book reader : 5,000,000+\n",
      "Offline English Dictionary : 100,000+\n",
      "Offline: English to Tagalog Dictionary : 500,000+\n",
      "FamilySearch Tree : 1,000,000+\n",
      "Cloud of Books : 1,000,000+\n",
      "Recipes of Prophetic Medicine for free : 500,000+\n",
      "ReadEra – free ebook reader : 1,000,000+\n",
      "Anonymous caller detection : 10,000+\n",
      "Ebook Reader : 5,000,000+\n",
      "Litnet - E-books : 100,000+\n",
      "Read books online : 5,000,000+\n",
      "English to Urdu Dictionary : 500,000+\n",
      "eBoox: book reader fb2 epub zip : 1,000,000+\n",
      "English Persian Dictionary : 500,000+\n",
      "Flybook : 500,000+\n",
      "All Maths Formulas : 1,000,000+\n",
      "Ancestry : 5,000,000+\n",
      "HTC Help : 10,000,000+\n",
      "English translation from Bengali : 100,000+\n",
      "Pdf Book Download - Read Pdf Book : 100,000+\n",
      "Free Book Reader : 100,000+\n",
      "eBoox new: Reader for fb2 epub zip books : 50,000+\n",
      "Only 30 days in English, the guideline is guaranteed : 500,000+\n",
      "Moon+ Reader : 10,000,000+\n",
      "SH-02J Owner's Manual (Android 8.0) : 50,000+\n",
      "English-Myanmar Dictionary : 1,000,000+\n",
      "Golden Dictionary (EN-AR) : 1,000,000+\n",
      "All Language Translator Free : 1,000,000+\n",
      "Azpen eReader : 500,000+\n",
      "URBANO V 02 instruction manual : 100,000+\n",
      "Bible : 100,000,000+\n",
      "C Programs and Reference : 50,000+\n",
      "C Offline Tutorial : 1,000+\n",
      "C Programs Handbook : 50,000+\n",
      "Amazon Kindle : 100,000,000+\n",
      "Aab e Hayat Full Novel : 100,000+\n",
      "Aldiko Book Reader : 10,000,000+\n",
      "Google I/O 2018 : 500,000+\n",
      "R Language Reference Guide : 10,000+\n",
      "Learn R Programming Full : 5,000+\n",
      "R Programing Offline Tutorial : 1,000+\n",
      "Guide for R Programming : 5+\n",
      "Learn R Programming : 10+\n",
      "R Quick Reference Big Data : 1,000+\n",
      "V Made : 100,000+\n",
      "Wattpad 📖 Free Books : 100,000,000+\n",
      "Dictionary - WordWeb : 5,000,000+\n",
      "Guide (for X-MEN) : 100,000+\n",
      "AC Air condition Troubleshoot,Repair,Maintenance : 5,000+\n",
      "AE Bulletins : 1,000+\n",
      "Ae Allah na Dai (Rasa) : 10,000+\n",
      "50000 Free eBooks & Free AudioBooks : 5,000,000+\n",
      "Ag PhD Field Guide : 10,000+\n",
      "Ag PhD Deficiencies : 10,000+\n",
      "Ag PhD Planting Population Calculator : 1,000+\n",
      "Ag PhD Soybean Diseases : 1,000+\n",
      "Fertilizer Removal By Crop : 50,000+\n",
      "A-J Media Vault : 50+\n",
      "Al-Quran (Free) : 10,000,000+\n",
      "Al Quran (Tafsir & by Word) : 500,000+\n",
      "Al Quran Indonesia : 10,000,000+\n",
      "Al'Quran Bahasa Indonesia : 10,000,000+\n",
      "Al Quran Al karim : 1,000,000+\n",
      "Al-Muhaffiz : 50,000+\n",
      "Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+\n",
      "Al-Quran 30 Juz free copies : 500,000+\n",
      "Koran Read &MP3 30 Juz Offline : 1,000,000+\n",
      "Hafizi Quran 15 lines per page : 1,000,000+\n",
      "Quran for Android : 10,000,000+\n",
      "Surah Al-Waqiah : 100,000+\n",
      "Hisnul Al Muslim - Hisn Invocations & Adhkaar : 100,000+\n",
      "Satellite AR : 1,000,000+\n",
      "Audiobooks from Audible : 100,000,000+\n",
      "Kinot & Eichah for Tisha B'Av : 10,000+\n",
      "AW Tozer Devotionals - Daily : 5,000+\n",
      "Tozer Devotional -Series 1 : 1,000+\n",
      "The Pursuit of God : 1,000+\n",
      "AY Sing : 5,000+\n",
      "Ay Hasnain k Nana Milad Naat : 10,000+\n",
      "Ay Mohabbat Teri Khatir Novel : 10,000+\n",
      "Arizona Statutes, ARS (AZ Law) : 1,000+\n",
      "Oxford A-Z of English Usage : 1,000,000+\n",
      "BD Fishpedia : 1,000+\n",
      "BD All Sim Offer : 10,000+\n",
      "Youboox - Livres, BD et magazines : 500,000+\n",
      "B&H Kids AR : 10,000+\n",
      "B y H Niños ES : 5,000+\n",
      "Dictionary.com: Find Definitions for English Words : 10,000,000+\n",
      "English Dictionary - Offline : 10,000,000+\n",
      "Bible KJV : 5,000,000+\n",
      "Borneo Bible, BM Bible : 10,000+\n",
      "MOD Black for BM : 100+\n",
      "BM Box : 1,000+\n",
      "Anime Mod for BM : 100+\n",
      "NOOK: Read eBooks & Magazines : 10,000,000+\n",
      "NOOK Audiobooks : 500,000+\n",
      "NOOK App for NOOK Devices : 500,000+\n",
      "Browsery by Barnes & Noble : 5,000+\n",
      "bp e-store : 1,000+\n",
      "Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+\n",
      "BR Ambedkar Biography & Quotes : 10,000+\n",
      "BU Alsace : 100+\n",
      "Catholic La Bu Zo Kam : 500+\n",
      "Khrifa Hla Bu (Solfa) : 10+\n",
      "Kristian Hla Bu : 10,000+\n",
      "SA HLA BU : 1,000+\n",
      "Learn SAP BW : 500+\n",
      "Learn SAP BW on HANA : 500+\n",
      "CA Laws 2018 (California Laws and Codes) : 5,000+\n",
      "Bootable Methods(USB-CD-DVD) : 10,000+\n",
      "cloudLibrary : 100,000+\n",
      "SDA Collegiate Quarterly : 500+\n",
      "Sabbath School : 100,000+\n",
      "Cypress College Library : 100+\n",
      "Stats Royale for Clash Royale : 1,000,000+\n",
      "GATE 21 years CS Papers(2011-2018 Solved) : 50+\n",
      "Learn CT Scan Of Head : 5,000+\n",
      "Easy Cv maker 2018 : 10,000+\n",
      "How to Write CV : 100,000+\n",
      "CW Nuclear : 1,000+\n",
      "CY Spray nozzle : 10+\n",
      "BibleRead En Cy Zh Yue : 5+\n",
      "CZ-Help : 5+\n",
      "Modlitební knížka CZ : 500+\n",
      "Guide for DB Xenoverse : 10,000+\n",
      "Guide for DB Xenoverse 2 : 10,000+\n",
      "Guide for IMS DB : 10+\n",
      "DC HSEMA : 5,000+\n",
      "DC Public Library : 1,000+\n",
      "Painting Lulu DC Super Friends : 1,000+\n",
      "Dictionary : 10,000,000+\n",
      "Fix Error Google Playstore : 1,000+\n",
      "D. H. Lawrence Poems FREE : 1,000+\n",
      "Bilingual Dictionary Audio App : 5,000+\n",
      "DM Screen : 10,000+\n",
      "wikiHow: how to do anything : 1,000,000+\n",
      "Dr. Doug's Tips : 1,000+\n",
      "Bible du Semeur-BDS (French) : 50,000+\n",
      "La citadelle du musulman : 50,000+\n",
      "DV 2019 Entry Guide : 10,000+\n",
      "DV 2019 - EDV Photo & Form : 50,000+\n",
      "DV 2018 Winners Guide : 1,000+\n",
      "EB Annual Meetings : 1,000+\n",
      "EC - AP & Telangana : 5,000+\n",
      "TN Patta Citta & EC : 10,000+\n",
      "AP Stamps and Registration : 10,000+\n",
      "CompactiMa EC pH Calibration : 100+\n",
      "EGW Writings 2 : 100,000+\n",
      "EGW Writings : 1,000,000+\n",
      "Bible with EGW Comments : 100,000+\n",
      "My Little Pony AR Guide : 1,000,000+\n",
      "SDA Sabbath School Quarterly : 500,000+\n",
      "Duaa Ek Ibaadat : 5,000+\n",
      "Spanish English Translator : 10,000,000+\n",
      "Dictionary - Merriam-Webster : 10,000,000+\n",
      "JW Library : 10,000,000+\n",
      "Oxford Dictionary of English : Free : 10,000,000+\n",
      "English Hindi Dictionary : 10,000,000+\n",
      "English to Hindi Dictionary : 5,000,000+\n",
      "EP Research Service : 1,000+\n",
      "Hymnes et Louanges : 100,000+\n",
      "EU Charter : 1,000+\n",
      "EU Data Protection : 1,000+\n",
      "EU IP Codes : 100+\n",
      "EW PDF : 5+\n",
      "BakaReader EX : 100,000+\n",
      "EZ Quran : 50,000+\n",
      "FA Part 1 & 2 Past Papers Solved Free – Offline : 5,000+\n",
      "La Fe de Jesus : 1,000+\n",
      "La Fe de Jesús : 500+\n",
      "Le Fe de Jesus : 500+\n",
      "Florida - Pocket Brainbook : 1,000+\n",
      "Florida Statutes (FL Code) : 1,000+\n",
      "English To Shona Dictionary : 10,000+\n",
      "Greek Bible FP (Audio) : 1,000+\n",
      "Golden Dictionary (FR-AR) : 500,000+\n",
      "Fanfic-FR : 5,000+\n",
      "Bulgarian French Dictionary Fr : 10,000+\n",
      "Chemin (fr) : 1,000+\n",
      "The SCP Foundation DB fr nn5n : 1,000+\n"
     ]
    }
   ],
   "source": [
    "for app in Free_Eng_android:\n",
    "    if app[1] == 'BOOKS_AND_REFERENCE':\n",
    "        print(app[0], ':', app[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The **Book and Reference** genre includes a variety of apps: software for processing and reading ebooks, various collections of libraries, dictionaries, etc. Let me check if there are extremely popular apps that skew the average:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Google Play Books : 1,000,000,000+\n",
      "Bible : 100,000,000+\n",
      "Amazon Kindle : 100,000,000+\n",
      "Wattpad 📖 Free Books : 100,000,000+\n",
      "Audiobooks from Audible : 100,000,000+\n"
     ]
    }
   ],
   "source": [
    "for app in Free_Eng_android:\n",
    "    if app[1] == 'BOOKS_AND_REFERENCE' 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": "markdown",
   "metadata": {},
   "source": [
    "However, it looks like there is only one very popular app \"Google Play Books\" which has over a billion installs, so this market still shows potential.<br> In the cell below, im trying get some app ideas based on the kind of apps that are somewhere in the middle in terms of popularity that is; between 1,000,000 and 100,000,000 downloads):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wikipedia : 10,000,000+\n",
      "Cool Reader : 10,000,000+\n",
      "Book store : 1,000,000+\n",
      "FBReader: Favorite Book Reader : 10,000,000+\n",
      "Free Books - Spirit Fanfiction and Stories : 1,000,000+\n",
      "AlReader -any text book reader : 5,000,000+\n",
      "FamilySearch Tree : 1,000,000+\n",
      "Cloud of Books : 1,000,000+\n",
      "ReadEra – free ebook reader : 1,000,000+\n",
      "Ebook Reader : 5,000,000+\n",
      "Read books online : 5,000,000+\n",
      "eBoox: book reader fb2 epub zip : 1,000,000+\n",
      "All Maths Formulas : 1,000,000+\n",
      "Ancestry : 5,000,000+\n",
      "HTC Help : 10,000,000+\n",
      "Moon+ Reader : 10,000,000+\n",
      "English-Myanmar Dictionary : 1,000,000+\n",
      "Golden Dictionary (EN-AR) : 1,000,000+\n",
      "All Language Translator Free : 1,000,000+\n",
      "Aldiko Book Reader : 10,000,000+\n",
      "Dictionary - WordWeb : 5,000,000+\n",
      "50000 Free eBooks & Free AudioBooks : 5,000,000+\n",
      "Al-Quran (Free) : 10,000,000+\n",
      "Al Quran Indonesia : 10,000,000+\n",
      "Al'Quran Bahasa Indonesia : 10,000,000+\n",
      "Al Quran Al karim : 1,000,000+\n",
      "Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+\n",
      "Koran Read &MP3 30 Juz Offline : 1,000,000+\n",
      "Hafizi Quran 15 lines per page : 1,000,000+\n",
      "Quran for Android : 10,000,000+\n",
      "Satellite AR : 1,000,000+\n",
      "Oxford A-Z of English Usage : 1,000,000+\n",
      "Dictionary.com: Find Definitions for English Words : 10,000,000+\n",
      "English Dictionary - Offline : 10,000,000+\n",
      "Bible KJV : 5,000,000+\n",
      "NOOK: Read eBooks & Magazines : 10,000,000+\n",
      "Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+\n",
      "Stats Royale for Clash Royale : 1,000,000+\n",
      "Dictionary : 10,000,000+\n",
      "wikiHow: how to do anything : 1,000,000+\n",
      "EGW Writings : 1,000,000+\n",
      "My Little Pony AR Guide : 1,000,000+\n",
      "Spanish English Translator : 10,000,000+\n",
      "Dictionary - Merriam-Webster : 10,000,000+\n",
      "JW Library : 10,000,000+\n",
      "Oxford Dictionary of English : Free : 10,000,000+\n",
      "English Hindi Dictionary : 10,000,000+\n",
      "English to Hindi Dictionary : 5,000,000+\n"
     ]
    }
   ],
   "source": [
    "for app in Free_Eng_android:\n",
    "    if app[1] == 'BOOKS_AND_REFERENCE' 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",
    "        print(app[0], ':', app[5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the Output above,this Genre(Category) seems to be dominated by software for processing and reading ebooks, as well as various collections of libraries and dictionaries, so it's probably not a good idea to build similar apps since there'll be some significant competition.\n",
    "\n",
    "But i also noticed that there are quite a few apps built around the book Quran, which implies that building an app around a popular book can be profitable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CONCLUSION"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this project, I analyzed data about the App Store and Google Play mobile apps to recommend an app profile that can be profitable for both markets, and I have been able to conclude that:\n",
    "\n",
    "**Taking a popular book (perhaps a more recent book) and turning it into an app could be profitable for both the Google Play and the App Store markets**, but these markets are already full of libraries so some special features may need to be added to the app besides the raw version of the book, which might include daily quotes from the book, an audio version of the book, quizzes on the book, or a forum where people can discuss the book, etc."
   ]
  }
 ],
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