Dataquest.io Guided Project 1 - Profitable App Profiles for the App Store and Google Play Markets

Description: Sources: https://www.kaggle.com/lava18/google-play-store-apps/home https://www.kaggle.com/ramamet4/app-store-apple-data-set-10k-apps/home Goal: finding application characteristics most likely to maximize revenue from application

Defining explore function. Will be useful to take a look at source databases.

In [1]:
import operator
#importing operator library to sort dictionaries

def explore_data(dataset, start, end, rows_and_columns=False):
    dataset_slice = dataset[start:end]    
    for row in dataset_slice:
        print(row)
        print('\n') # adds a new (empty) line after each row

    if rows_and_columns:
        print('Number of rows:', len(dataset))
        print('Number of columns:', len(dataset[0]))

Importing source datasets and transforming them to list variables.

In [2]:
def sum_column(table, C):
    result = sum(row[C] for row in table)
    return result
In [3]:
apple_open=open('AppleStore.csv',encoding="utf8")
google_open=open('googleplaystore.csv',encoding="utf8")
import csv
apple_read=csv.reader(apple_open)
google_read=csv.reader(google_open)
google_list=list(google_read)
apple_list=list(apple_read)

Exploration of datasets using created explore_data function.

In [4]:
explore_data(google_list,0,2,True)

['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver']


['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']


Number of rows: 10842
Number of columns: 13

Google Store application dataset offes below structure:

Variable Explanation
App unique identifier.Variable name. String
Category type of app. String
Rating App rating. Float from 0 to 10
Reviews Number of reviews. Integer
Size Size in Megabytes. String
Installs Number of installs range. String.
Type 'Free' or 'Paid'. String
Price Price in dollars. 0 for free apps.
Content Rating Age limit to use app. String
Genres Genre of app. String
Last updated Date of last update. String
Current Ver current version. String
Android Ver Min Android ver to use this app. String
In [5]:
explore_data(apple_list,0,2,True)

['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']


['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1']


Number of rows: 7198
Number of columns: 16

Apple Store application dataset offes below structure:

Variable Explanation
id unique application number. Key. Integer
track_name name of application. String
size_bytes size of app in bytes. Integer
currency currency of app price. String
price price of app. 0 for free apps. Float.
rating_count_tot total number of ratings. Integer
rating_count_ver aaa
user_rating Rating of users. Float from 0 to 10.
user_rating_ver aaa
ver application version. Float.
cont_rating Content Rating on 5 star scale. String
prime_genre App Genre. String
sup_devices.num number of supported devices. Integer
ipadSc_urls.num aaa
lang.num number of supported languages. Integer
vpp_lic aaa

II Data cleansing a) Preparing function to detect outliers and incorrect values.

In [6]:
#Dataset - name of dataset
#variable - case-sensitive name of variable in dataset
def variable_desc(dataset,variable):
    header=dataset[0]
    index_temp=int(header.index(variable))
    dict_temp={}
    for temp in dataset[1:]:
        b=str(temp[index_temp])
        if b in dict_temp:
            dict_temp[b] += 1
        else:
            dict_temp[b] = 1

    sorted_dict = list(sorted(dict_temp.items(), key=operator.itemgetter(1), reverse=True))
    print('Variable analysed: ' + variable)
    print('Number of distinct values:', len(sorted_dict))
    for row in sorted_dict:
        print(row)
In [7]:
variable_desc(google_list,'Category')

Variable analysed: Category
Number of distinct values: 34
('FAMILY', 1972)
('GAME', 1144)
('TOOLS', 843)
('MEDICAL', 463)
('BUSINESS', 460)
('PRODUCTIVITY', 424)
('PERSONALIZATION', 392)
('COMMUNICATION', 387)
('SPORTS', 384)
('LIFESTYLE', 382)
('FINANCE', 366)
('HEALTH_AND_FITNESS', 341)
('PHOTOGRAPHY', 335)
('SOCIAL', 295)
('NEWS_AND_MAGAZINES', 283)
('SHOPPING', 260)
('TRAVEL_AND_LOCAL', 258)
('DATING', 234)
('BOOKS_AND_REFERENCE', 231)
('VIDEO_PLAYERS', 175)
('EDUCATION', 156)
('ENTERTAINMENT', 149)
('MAPS_AND_NAVIGATION', 137)
('FOOD_AND_DRINK', 127)
('HOUSE_AND_HOME', 88)
('AUTO_AND_VEHICLES', 85)
('LIBRARIES_AND_DEMO', 85)
('WEATHER', 82)
('ART_AND_DESIGN', 65)
('EVENTS', 64)
('COMICS', 60)
('PARENTING', 60)
('BEAUTY', 53)
('1.9', 1)

b) Function to find duplicates among primary key

In [8]:
print(google_list[10473])
del google_list[10473]
print(google_list[10473])

['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']
['osmino Wi-Fi: free WiFi', 'TOOLS', '4.2', '134203', '4.1M', '10,000,000+', 'Free', '0', 'Everyone', 'Tools', 'August 7, 2018', '6.06.14', '4.4 and up']
In [9]:
#Dataset - name of dataset
#variable - case-sensitive name of primary key variable in dataset
#output dataset - clean list based on primary key
#max_var - variable that we will use to deduplicate (we will take
# only max values)

def duplicates(dataset,primary_key,max_var):
    print('Length of input dataset - ' + str(len(dataset)))
    header=dataset[0]
    index_temp=int(header.index(primary_key))
    print('Index of primary key - ' + primary_key + ' : ' + str(index_temp))
    index_max=int(header.index(max_var))
    print('Index of variable used for deduplication - ' + max_var + ' : ' + str(index_max))
    dict_temp={}  
    clean_list=[]
    clean_list.append(header)
    for temp in dataset[1:]:   
        b=str(temp[index_temp])
        c=float(temp[index_max])
        if b in dict_temp and dict_temp[b] < c:
            dict_temp[b] = c
        if b not in dict_temp:
            dict_temp[b] = c
    print('Length of dictionary: ' + str(len(dict_temp)))
    deduped_list=[]
    already_added=[]
    deduped_list.append(header)
    for tempo in dataset[1:]:
        name=str(tempo[index_temp])
        d=float(tempo[index_max])
        if name not in already_added and d==dict_temp[name]:
            deduped_list.append(tempo)
            already_added.append(name)
    print('Length of deduplicated end-dataset: ' + str(len(deduped_list)))
    return deduped_list
In [10]:
google_dedup=duplicates(google_list,'App','Reviews')

Length of input dataset - 10841
Index of primary key - App : 0
Index of variable used for deduplication - Reviews : 3
Length of dictionary: 9659
Length of deduplicated end-dataset: 9660
In [11]:
#Source dataset
for a in google_list:
    if a[0]=='Microsoft Outlook':
        print(a)

['Microsoft Outlook', 'PRODUCTIVITY', '4.3', '3252896', '50M', '100,000,000+', 'Free', '0', 'Everyone', 'Productivity', 'August 2, 2018', '2.2.194', '4.4 and up']
['Microsoft Outlook', 'PRODUCTIVITY', '4.3', '3249518', '50M', '100,000,000+', 'Free', '0', 'Everyone', 'Productivity', 'August 2, 2018', '2.2.194', '4.4 and up']
In [12]:
#Dataset cleaned from app name duplicates
for a in google_dedup:
    if a[0]=='Microsoft Outlook':
        print(a)

['Microsoft Outlook', 'PRODUCTIVITY', '4.3', '3252896', '50M', '100,000,000+', 'Free', '0', 'Everyone', 'Productivity', 'August 2, 2018', '2.2.194', '4.4 and up']
In [13]:
apple_dedup=duplicates(apple_list,'id','rating_count_tot')
#No duplicates in apple_list dataset

Length of input dataset - 7198
Index of primary key - id : 0
Index of variable used for deduplication - rating_count_tot : 5
Length of dictionary: 7197
Length of deduplicated end-dataset: 7198
In [14]:
#Noneng - function returning list of english names from list potentially containing non-english names
#Recognition of non-english name - more than 3 non-ASCII characters 
#Dataset - name of dataset
#primary_key - case-sensitive name name containing non-english entries
#prnt - if prnt=1 then function prints all non-eng app names
def noneng(dataset,primary_key,prnt=0):
    print('Records in input dataset - ' + str(len(dataset)))
    header=dataset[0]
    index_temp=int(header.index(primary_key))
    print('Index of primary key - ' + primary_key + ' : ' + str(index_temp))
    list_noneng=[]
    clean_list=[]
    clean_list.append(header)
    for a in dataset[1:]:
        b=str(a[index_temp])
        c=0    
        for character in b:
            if ord(character)>127 and b not in list_noneng:
                c += 1
                if c>3 and b not in list_noneng:
                    list_noneng.append(b)
        if b not in list_noneng:
            clean_list.append(a)
    print('Number of records in english-app end-dataset: ' + str(len(clean_list)))
    if prnt==1:
        print('List of non-english apps')
        print(str(list_noneng))
    return clean_list
In [15]:
google_noneng=noneng(google_dedup,'App',1)

Records in input dataset - 9660
Index of primary key - App : 0
Number of records in english-app end-dataset: 9615
List of non-english apps
['Flame - درب عقلك يوميا', 'သိင်္ Astrology - Min Thein Kha BayDin', 'РИА Новости', 'صور حرف H', 'L.POINT - 엘포인트 [ 포인트, 멤버십, 적립, 사용, 모바일 카드, 쿠폰, 롯데]', 'RMEduS - 음성인식을 활용한 R 프로그래밍 실습 시스템', 'AJ렌터카 법인 카셰어링', 'Al Quran Free - القرآن (Islam)', '中国語 AQリスニング', '日本AV历史', 'Ay Yıldız Duvar Kağıtları', 'বাংলা টিভি প্রো BD Bangla TV', 'Cъновник BG', 'CSCS BG (в български)', '뽕티비 - 개인방송, 인터넷방송, BJ방송', 'BL 女性向け恋愛ゲーム◆俺プリクロス', 'SecondSecret ‐「恋を読む」BLノベルゲーム‐', 'BL 女性向け恋愛ゲーム◆ごくメン', 'あなカレ【BL】無料ゲーム', '감성학원 BL 첫사랑', 'BQ-መጽሐፍ ቅዱሳዊ ጥያቄዎች', 'BS Calendar / Patro / पात्रो', 'Vip视频免费看-BT磁力搜索', 'Билеты ПДД CD 2019 PRO', 'Offline Jízdní řády CG Transit', 'Bonjour 2017 Abidjan CI ❤❤❤❤❤', 'CK 初一 十五', 'الفاتحون Conquerors', 'DG ग्राम / Digital Gram Panchayat', 'DM הפקות', 'DW فارسی By dw-arab.com', 'لعبة تقدر تربح DZ', 'বাংলাflix', 'RPG ブレイジング ソウルズ アクセレイト', '英漢字典 EC Dictionary', 'ECナビ×シュフー', 'أحداث وحقائق | خبر عاجل في اخبار العالم', 'EG SIM CARD (EGSIMCARD, 이지심카드)', 'パーリーゲイツ公式通販｜EJ STYLE（イージェイスタイル）', 'FAHREDDİN er-RÂZİ TEFSİRİ', "I'm Rich/Eu sou Rico/أنا غني/我很有錢", 'AÖF Ev İdaresi 1. Sınıf', 'Ey Sey Storytime រឿងនិទានតាឥសី', '哈哈姆特不EY', 'FP Разбитый дисплей']
In [16]:
apple_noneng=noneng(apple_dedup,'track_name')

Records in input dataset - 7198
Index of primary key - track_name : 1
Number of records in english-app end-dataset: 6184
In [17]:
variable_desc(google_noneng,'Price')

Variable analysed: Price
Number of distinct values: 92
('0', 8864)
('$0.99', 145)
('$2.99', 124)
('$1.99', 73)
('$4.99', 70)
('$3.99', 56)
('$1.49', 45)
('$5.99', 26)
('$2.49', 25)
('$9.99', 19)
('$399.99', 11)
('$6.99', 10)
('$14.99', 9)
('$4.49', 9)
('$7.99', 7)
('$3.49', 7)
('$5.49', 5)
('$29.99', 5)
('$19.99', 5)
('$8.99', 5)
('$6.49', 5)
('$11.99', 3)
('$1.00', 3)
('$24.99', 3)
('$2.00', 3)
('$12.99', 3)
('$7.49', 2)
('$10.00', 2)
('$16.99', 2)
('$39.99', 2)
('$1.70', 2)
('$17.99', 2)
('$13.99', 2)
('$8.49', 2)
('$9.00', 1)
('$79.99', 1)
('$10.99', 1)
('$1.50', 1)
('$15.99', 1)
('$33.99', 1)
('$74.99', 1)
('$3.95', 1)
('$3.88', 1)
('$25.99', 1)
('$400.00', 1)
('$3.02', 1)
('$1.76', 1)
('$4.84', 1)
('$4.77', 1)
('$1.61', 1)
('$2.50', 1)
('$1.59', 1)
('$1.29', 1)
('$5.00', 1)
('$299.99', 1)
('$379.99', 1)
('$37.99', 1)
('$18.99', 1)
('$389.99', 1)
('$19.90', 1)
('$1.75', 1)
('$14.00', 1)
('$4.85', 1)
('$46.99', 1)
('$109.99', 1)
('$154.99', 1)
('$3.08', 1)
('$2.59', 1)
('$4.80', 1)
('$1.96', 1)
('$19.40', 1)
('$3.90', 1)
('$4.59', 1)
('$15.46', 1)
('$3.04', 1)
('$4.29', 1)
('$2.60', 1)
('$3.28', 1)
('$4.60', 1)
('$28.99', 1)
('$2.95', 1)
('$2.90', 1)
('$1.97', 1)
('$200.00', 1)
('$89.99', 1)
('$2.56', 1)
('$30.99', 1)
('$3.61', 1)
('$394.99', 1)
('$1.26', 1)
('$1.20', 1)
('$1.04', 1)
In [18]:
variable_desc(apple_noneng,'price')

Variable analysed: price
Number of distinct values: 34
('0.0', 3222)
('2.99', 669)
('0.99', 641)
('1.99', 610)
('4.99', 375)
('3.99', 266)
('6.99', 165)
('9.99', 76)
('5.99', 43)
('7.99', 30)
('14.99', 15)
('19.99', 13)
('8.99', 8)
('24.99', 8)
('13.99', 6)
('29.99', 6)
('15.99', 4)
('17.99', 3)
('11.99', 3)
('59.99', 3)
('39.99', 2)
('16.99', 2)
('49.99', 2)
('20.99', 1)
('12.99', 1)
('74.99', 1)
('249.99', 1)
('27.99', 1)
('22.99', 1)
('18.99', 1)
('99.99', 1)
('21.99', 1)
('34.99', 1)
('299.99', 1)
In [19]:
#free - function returning free applications from a super-set of paid and free applications
#Recognition of non-english name - more than 3 non-ASCII characters 
#Dataset - name of dataset
#primary_key - case-sensitive name name containing non-english entries
#prnt - if prnt=1 then function prints all non-eng app names
def free(dataset,primary_key):
    print('Records in input dataset - ' + str(len(dataset)))
    header=dataset[0]
    index_temp=int(header.index(primary_key))
    print('Index of primary key - ' + primary_key + ' : ' + str(index_temp))
    paid_apps=[]
    free_apps=[]
    free_apps.append(header)
    for a in dataset[1:]:
        b=str(a[index_temp])  
        if b != '0' and b != '0.0':
            paid_apps.append(b)
        else:
            free_apps.append(a)
    print('Number of records in free app end-dataset: ' + str(len(free_apps)))
    return free_apps
In [20]:
free_google=free(google_noneng,'Price')

Records in input dataset - 9615
Index of primary key - Price : 7
Number of records in free app end-dataset: 8865
In [21]:
free_apple=free(apple_noneng,'price')

Records in input dataset - 6184
Index of primary key - price : 4
Number of records in free app end-dataset: 3223

Build a minimal Android version of the app, and add it to Google Play.

If the app has a good response from users, we then develop it further. If the app is profitable after six months, we also build an iOS version of the app and add it to the App Store. Variables we are going to inspect:

Google datasetRating SizeContent Rating *Genre

In [22]:
#Dataset - name of dataset
#variable - case-sensitive name of variable in dataset
def freq(dataset,variable):
    header=dataset[0]
    index_temp=int(header.index(variable))
    dict_temp={}
    for temp in dataset[1:]:
        b=str(temp[index_temp])
        if b in dict_temp:
            dict_temp[b] += 1
        else:
            dict_temp[b] = 1

    sorted_dict = list(sorted(dict_temp.items(), key=operator.itemgetter(1), reverse=True))
    total=sum_column(sorted_dict,1)  
    print('Variable analysed: ' + variable)
    print('Number of distinct values:', len(sorted_dict))
    print('Total observations: ', total)
    for row in sorted_dict:
        print(row, ", Fraction of total:", round(row[1]/total*100,1),'%')
In [23]:
freq(free_apple,'prime_genre')

Variable analysed: prime_genre
Number of distinct values: 23
Total observations:  3222
('Games', 1874) , Fraction of total: 58.2 %
('Entertainment', 254) , Fraction of total: 7.9 %
('Photo & Video', 160) , Fraction of total: 5.0 %
('Education', 118) , Fraction of total: 3.7 %
('Social Networking', 106) , Fraction of total: 3.3 %
('Shopping', 84) , Fraction of total: 2.6 %
('Utilities', 81) , Fraction of total: 2.5 %
('Sports', 69) , Fraction of total: 2.1 %
('Music', 66) , Fraction of total: 2.0 %
('Health & Fitness', 65) , Fraction of total: 2.0 %
('Productivity', 56) , Fraction of total: 1.7 %
('Lifestyle', 51) , Fraction of total: 1.6 %
('News', 43) , Fraction of total: 1.3 %
('Travel', 40) , Fraction of total: 1.2 %
('Finance', 36) , Fraction of total: 1.1 %
('Weather', 28) , Fraction of total: 0.9 %
('Food & Drink', 26) , Fraction of total: 0.8 %
('Reference', 18) , Fraction of total: 0.6 %
('Business', 17) , Fraction of total: 0.5 %
('Book', 14) , Fraction of total: 0.4 %
('Navigation', 6) , Fraction of total: 0.2 %
('Medical', 6) , Fraction of total: 0.2 %
('Catalogs', 4) , Fraction of total: 0.1 %
In [24]:
freq(free_google,'Category')

Variable analysed: Category
Number of distinct values: 33
Total observations:  8864
('FAMILY', 1676) , Fraction of total: 18.9 %
('GAME', 862) , Fraction of total: 9.7 %
('TOOLS', 750) , Fraction of total: 8.5 %
('BUSINESS', 407) , Fraction of total: 4.6 %
('LIFESTYLE', 346) , Fraction of total: 3.9 %
('PRODUCTIVITY', 345) , Fraction of total: 3.9 %
('FINANCE', 328) , Fraction of total: 3.7 %
('MEDICAL', 313) , Fraction of total: 3.5 %
('SPORTS', 301) , Fraction of total: 3.4 %
('PERSONALIZATION', 294) , Fraction of total: 3.3 %
('COMMUNICATION', 287) , Fraction of total: 3.2 %
('HEALTH_AND_FITNESS', 273) , Fraction of total: 3.1 %
('PHOTOGRAPHY', 261) , Fraction of total: 2.9 %
('NEWS_AND_MAGAZINES', 248) , Fraction of total: 2.8 %
('SOCIAL', 236) , Fraction of total: 2.7 %
('TRAVEL_AND_LOCAL', 207) , Fraction of total: 2.3 %
('SHOPPING', 199) , Fraction of total: 2.2 %
('BOOKS_AND_REFERENCE', 190) , Fraction of total: 2.1 %
('DATING', 165) , Fraction of total: 1.9 %
('VIDEO_PLAYERS', 159) , Fraction of total: 1.8 %
('MAPS_AND_NAVIGATION', 124) , Fraction of total: 1.4 %
('FOOD_AND_DRINK', 110) , Fraction of total: 1.2 %
('EDUCATION', 103) , Fraction of total: 1.2 %
('ENTERTAINMENT', 85) , Fraction of total: 1.0 %
('LIBRARIES_AND_DEMO', 83) , Fraction of total: 0.9 %
('AUTO_AND_VEHICLES', 82) , Fraction of total: 0.9 %
('HOUSE_AND_HOME', 73) , Fraction of total: 0.8 %
('WEATHER', 71) , Fraction of total: 0.8 %
('EVENTS', 63) , Fraction of total: 0.7 %
('PARENTING', 58) , Fraction of total: 0.7 %
('ART_AND_DESIGN', 57) , Fraction of total: 0.6 %
('COMICS', 55) , Fraction of total: 0.6 %
('BEAUTY', 53) , Fraction of total: 0.6 %
In [25]:
freq(free_google,'Genres')

Variable analysed: Genres
Number of distinct values: 114
Total observations:  8864
('Tools', 749) , Fraction of total: 8.4 %
('Entertainment', 538) , Fraction of total: 6.1 %
('Education', 474) , Fraction of total: 5.3 %
('Business', 407) , Fraction of total: 4.6 %
('Lifestyle', 345) , Fraction of total: 3.9 %
('Productivity', 345) , Fraction of total: 3.9 %
('Finance', 328) , Fraction of total: 3.7 %
('Medical', 313) , Fraction of total: 3.5 %
('Sports', 307) , Fraction of total: 3.5 %
('Personalization', 294) , Fraction of total: 3.3 %
('Communication', 287) , Fraction of total: 3.2 %
('Action', 275) , Fraction of total: 3.1 %
('Health & Fitness', 273) , Fraction of total: 3.1 %
('Photography', 261) , Fraction of total: 2.9 %
('News & Magazines', 248) , Fraction of total: 2.8 %
('Social', 236) , Fraction of total: 2.7 %
('Travel & Local', 206) , Fraction of total: 2.3 %
('Shopping', 199) , Fraction of total: 2.2 %
('Books & Reference', 190) , Fraction of total: 2.1 %
('Simulation', 181) , Fraction of total: 2.0 %
('Dating', 165) , Fraction of total: 1.9 %
('Arcade', 164) , Fraction of total: 1.9 %
('Video Players & Editors', 157) , Fraction of total: 1.8 %
('Casual', 156) , Fraction of total: 1.8 %
('Maps & Navigation', 124) , Fraction of total: 1.4 %
('Food & Drink', 110) , Fraction of total: 1.2 %
('Puzzle', 100) , Fraction of total: 1.1 %
('Racing', 88) , Fraction of total: 1.0 %
('Libraries & Demo', 83) , Fraction of total: 0.9 %
('Role Playing', 83) , Fraction of total: 0.9 %
('Auto & Vehicles', 82) , Fraction of total: 0.9 %
('Strategy', 81) , Fraction of total: 0.9 %
('House & Home', 73) , Fraction of total: 0.8 %
('Weather', 71) , Fraction of total: 0.8 %
('Events', 63) , Fraction of total: 0.7 %
('Adventure', 60) , Fraction of total: 0.7 %
('Comics', 54) , Fraction of total: 0.6 %
('Art & Design', 53) , Fraction of total: 0.6 %
('Beauty', 53) , Fraction of total: 0.6 %
('Parenting', 44) , Fraction of total: 0.5 %
('Card', 40) , Fraction of total: 0.5 %
('Casino', 38) , Fraction of total: 0.4 %
('Trivia', 37) , Fraction of total: 0.4 %
('Educational;Education', 35) , Fraction of total: 0.4 %
('Board', 34) , Fraction of total: 0.4 %
('Educational', 33) , Fraction of total: 0.4 %
('Education;Education', 30) , Fraction of total: 0.3 %
('Word', 23) , Fraction of total: 0.3 %
('Casual;Pretend Play', 21) , Fraction of total: 0.2 %
('Music', 18) , Fraction of total: 0.2 %
('Entertainment;Music & Video', 15) , Fraction of total: 0.2 %
('Puzzle;Brain Games', 15) , Fraction of total: 0.2 %
('Racing;Action & Adventure', 15) , Fraction of total: 0.2 %
('Casual;Brain Games', 12) , Fraction of total: 0.1 %
('Casual;Action & Adventure', 12) , Fraction of total: 0.1 %
('Arcade;Action & Adventure', 11) , Fraction of total: 0.1 %
('Action;Action & Adventure', 9) , Fraction of total: 0.1 %
('Educational;Pretend Play', 8) , Fraction of total: 0.1 %
('Entertainment;Brain Games', 7) , Fraction of total: 0.1 %
('Simulation;Action & Adventure', 7) , Fraction of total: 0.1 %
('Board;Brain Games', 7) , Fraction of total: 0.1 %
('Parenting;Education', 7) , Fraction of total: 0.1 %
('Art & Design;Creativity', 6) , Fraction of total: 0.1 %
('Educational;Brain Games', 6) , Fraction of total: 0.1 %
('Casual;Creativity', 6) , Fraction of total: 0.1 %
('Parenting;Music & Video', 6) , Fraction of total: 0.1 %
('Education;Pretend Play', 5) , Fraction of total: 0.1 %
('Education;Creativity', 4) , Fraction of total: 0.0 %
('Role Playing;Pretend Play', 4) , Fraction of total: 0.0 %
('Education;Brain Games', 3) , Fraction of total: 0.0 %
('Entertainment;Creativity', 3) , Fraction of total: 0.0 %
('Educational;Creativity', 3) , Fraction of total: 0.0 %
('Adventure;Action & Adventure', 3) , Fraction of total: 0.0 %
('Role Playing;Action & Adventure', 3) , Fraction of total: 0.0 %
('Educational;Action & Adventure', 3) , Fraction of total: 0.0 %
('Entertainment;Action & Adventure', 3) , Fraction of total: 0.0 %
('Puzzle;Action & Adventure', 3) , Fraction of total: 0.0 %
('Education;Action & Adventure', 3) , Fraction of total: 0.0 %
('Education;Music & Video', 3) , Fraction of total: 0.0 %
('Casual;Education', 2) , Fraction of total: 0.0 %
('Music;Music & Video', 2) , Fraction of total: 0.0 %
('Simulation;Pretend Play', 2) , Fraction of total: 0.0 %
('Puzzle;Creativity', 2) , Fraction of total: 0.0 %
('Sports;Action & Adventure', 2) , Fraction of total: 0.0 %
('Board;Action & Adventure', 2) , Fraction of total: 0.0 %
('Entertainment;Pretend Play', 2) , Fraction of total: 0.0 %
('Video Players & Editors;Music & Video', 2) , Fraction of total: 0.0 %
('Comics;Creativity', 1) , Fraction of total: 0.0 %
('Lifestyle;Pretend Play', 1) , Fraction of total: 0.0 %
('Art & Design;Pretend Play', 1) , Fraction of total: 0.0 %
('Entertainment;Education', 1) , Fraction of total: 0.0 %
('Arcade;Pretend Play', 1) , Fraction of total: 0.0 %
('Art & Design;Action & Adventure', 1) , Fraction of total: 0.0 %
('Strategy;Action & Adventure', 1) , Fraction of total: 0.0 %
('Music & Audio;Music & Video', 1) , Fraction of total: 0.0 %
('Health & Fitness;Education', 1) , Fraction of total: 0.0 %
('Casual;Music & Video', 1) , Fraction of total: 0.0 %
('Travel & Local;Action & Adventure', 1) , Fraction of total: 0.0 %
('Tools;Education', 1) , Fraction of total: 0.0 %
('Parenting;Brain Games', 1) , Fraction of total: 0.0 %
('Video Players & Editors;Creativity', 1) , Fraction of total: 0.0 %
('Health & Fitness;Action & Adventure', 1) , Fraction of total: 0.0 %
('Trivia;Education', 1) , Fraction of total: 0.0 %
('Lifestyle;Education', 1) , Fraction of total: 0.0 %
('Card;Action & Adventure', 1) , Fraction of total: 0.0 %
('Books & Reference;Education', 1) , Fraction of total: 0.0 %
('Simulation;Education', 1) , Fraction of total: 0.0 %
('Puzzle;Education', 1) , Fraction of total: 0.0 %
('Adventure;Education', 1) , Fraction of total: 0.0 %
('Role Playing;Brain Games', 1) , Fraction of total: 0.0 %
('Strategy;Education', 1) , Fraction of total: 0.0 %
('Racing;Pretend Play', 1) , Fraction of total: 0.0 %
('Communication;Creativity', 1) , Fraction of total: 0.0 %
('Strategy;Creativity', 1) , Fraction of total: 0.0 %
In [26]:
#searches for maximum value of variables that can be converted to float type
def max_value(dataset,variable):
    header=dataset[0]
    index_temp=int(header.index(variable))
    values_list = [float(e[index_temp]) for e in dataset[1:]]
    result = max(values_list)
    print('Maximum value for ' + str(variable) + ' : ' + str(result))
In [27]:
max_value(free_google,'Reviews')
#na reviews dziala dobrze ale na skategoryzowanych nie, 
#czy mozna to lepiej zrobic

Maximum value for Reviews : 78158306.0
In [28]:
#WHERE function - returns rows equal to 'where' condition
def print_where(dataset,variable,condition):
    header=dataset[0]
    index_temp=int(header.index(variable))
    for a in dataset:
        if a[index_temp]==condition:
            print(a)
In [29]:
print_where(free_google,'Reviews','78158306')

['Facebook', 'SOCIAL', '4.1', '78158306', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'August 3, 2018', 'Varies with device', 'Varies with device']
In [30]:
freq(free_google,'Installs')

Variable analysed: Installs
Number of distinct values: 21
Total observations:  8864
('1,000,000+', 1394) , Fraction of total: 15.7 %
('100,000+', 1024) , Fraction of total: 11.6 %
('10,000,000+', 935) , Fraction of total: 10.5 %
('10,000+', 904) , Fraction of total: 10.2 %
('1,000+', 744) , Fraction of total: 8.4 %
('100+', 613) , Fraction of total: 6.9 %
('5,000,000+', 605) , Fraction of total: 6.8 %
('500,000+', 493) , Fraction of total: 5.6 %
('50,000+', 423) , Fraction of total: 4.8 %
('5,000+', 400) , Fraction of total: 4.5 %
('10+', 314) , Fraction of total: 3.5 %
('500+', 288) , Fraction of total: 3.2 %
('50,000,000+', 204) , Fraction of total: 2.3 %
('100,000,000+', 189) , Fraction of total: 2.1 %
('50+', 170) , Fraction of total: 1.9 %
('5+', 70) , Fraction of total: 0.8 %
('1+', 45) , Fraction of total: 0.5 %
('500,000,000+', 24) , Fraction of total: 0.3 %
('1,000,000,000+', 20) , Fraction of total: 0.2 %
('0+', 4) , Fraction of total: 0.0 %
('0', 1) , Fraction of total: 0.0 %
In [31]:
print_where(free_google,'Installs','1,000,000,000+')

['Google Play Books', 'BOOKS_AND_REFERENCE', '3.9', '1433233', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Books & Reference', 'August 3, 2018', 'Varies with device', 'Varies with device']
['WhatsApp Messenger', 'COMMUNICATION', '4.4', '69119316', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 3, 2018', 'Varies with device', 'Varies with device']
['Messenger – Text and Video Chat for Free', 'COMMUNICATION', '4.0', '56646578', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 1, 2018', 'Varies with device', 'Varies with device']
['Skype - free IM & video calls', 'COMMUNICATION', '4.1', '10484169', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 3, 2018', 'Varies with device', 'Varies with device']
['Google Chrome: Fast & Secure', 'COMMUNICATION', '4.3', '9643041', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 1, 2018', 'Varies with device', 'Varies with device']
['Gmail', 'COMMUNICATION', '4.3', '4604483', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 2, 2018', 'Varies with device', 'Varies with device']
['Hangouts', 'COMMUNICATION', '4.0', '3419513', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Communication', 'July 21, 2018', 'Varies with device', 'Varies with device']
['Subway Surfers', 'GAME', '4.5', '27725352', '76M', '1,000,000,000+', 'Free', '0', 'Everyone 10+', 'Arcade', 'July 12, 2018', '1.90.0', '4.1 and up']
['Facebook', 'SOCIAL', '4.1', '78158306', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'August 3, 2018', 'Varies with device', 'Varies with device']
['Google+', 'SOCIAL', '4.2', '4831125', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 26, 2018', 'Varies with device', 'Varies with device']
['Instagram', 'SOCIAL', '4.5', '66577446', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']
['Google Photos', 'PHOTOGRAPHY', '4.5', '10859051', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Photography', 'August 6, 2018', 'Varies with device', 'Varies with device']
['Maps - Navigate & Explore', 'TRAVEL_AND_LOCAL', '4.3', '9235373', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Travel & Local', 'July 31, 2018', 'Varies with device', 'Varies with device']
['Google Street View', 'TRAVEL_AND_LOCAL', '4.2', '2129707', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Travel & Local', 'August 6, 2018', 'Varies with device', 'Varies with device']
['Google', 'TOOLS', '4.4', '8033493', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Tools', 'August 3, 2018', 'Varies with device', 'Varies with device']
['Google Drive', 'PRODUCTIVITY', '4.4', '2731211', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Everyone', 'Productivity', 'August 6, 2018', 'Varies with device', 'Varies with device']
['YouTube', 'VIDEO_PLAYERS', '4.3', '25655305', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Video Players & Editors', 'August 2, 2018', 'Varies with device', 'Varies with device']
['Google Play Movies & TV', 'VIDEO_PLAYERS', '3.7', '906384', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Video Players & Editors', 'August 6, 2018', 'Varies with device', 'Varies with device']
['Google Play Games', 'FAMILY', '4.3', '7168735', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Entertainment', 'July 16, 2018', 'Varies with device', 'Varies with device']
['Google News', 'NEWS_AND_MAGAZINES', '3.9', '878065', '13M', '1,000,000,000+', 'Free', '0', 'Teen', 'News & Magazines', 'August 1, 2018', '5.2.0', '4.4 and up']
In [32]:
max_value(free_apple,'rating_count_tot')

Maximum value for rating_count_tot : 2974676.0
In [33]:
print_where(free_apple,'rating_count_tot','2974676')

['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1']
In [34]:
max_value(free_apple,'user_rating')

Maximum value for user_rating : 5.0
In [35]:
print_where(free_apple,'user_rating','5.0')

['487119327', 'Head Soccer', '121319424', 'USD', '0.0', '481564', '8518', '5.0', '5.0', '5.4.1', '4+', 'Games', '40', '4', '11', '1']
['930574573', 'Sniper 3D Assassin: Shoot to Kill Gun Game', '157851648', 'USD', '0.0', '386521', '10332', '5.0', '5.0', '1.17.6', '17+', 'Games', '40', '5', '9', '1']
['698255242', 'Geometry Dash Lite', '69076992', 'USD', '0.0', '370370', '2650', '5.0', '4.5', '2.11', '4+', 'Games', '37', '4', '1', '1']
['436491861', "Domino's Pizza USA", '105743360', 'USD', '0.0', '258624', '2481', '5.0', '4.5', '4.2.0', '4+', 'Food & Drink', '37', '5', '2', '1']
['887947640', 'CSR Racing 2', '1944321024', 'USD', '0.0', '257100', '2025', '5.0', '5.0', '1.11.3', '4+', 'Games', '37', '5', '11', '1']
['600674056', "Pictoword: Fun 2 Pics Guess What's the Word Trivia", '126216192', 'USD', '0.0', '186089', '1010', '5.0', '4.5', '2.4.2', '4+', 'Games', '37', '5', '1', '1']
['606190854', 'Iron Force', '124666880', 'USD', '0.0', '141634', '1655', '5.0', '4.0', '2.4.1', '17+', 'Games', '38', '5', '12', '1']
['635573390', 'Sniper Shooter: Gun Shooting Games', '113509376', 'USD', '0.0', '134080', '451', '5.0', '5.0', '5.0.4', '12+', 'Games', '37', '5', '1', '1']
['381471023', 'Flashlight Ⓞ', '42027008', 'USD', '0.0', '130450', '1010', '5.0', '4.5', '2.1.2', '4+', 'Utilities', '40', '0', '22', '1']
['448639966', 'Pic Collage - Picture Editor & Photo Collage Maker', '109210624', 'USD', '0.0', '123433', '1521', '5.0', '5.0', '7.12.17', '12+', 'Photo & Video', '37', '5', '12', '1']
['392988420', 'Zappos: shop shoes & clothes, fast free shipping', '70325248', 'USD', '0.0', '103655', '39452', '5.0', '5.0', '3.9.0', '4+', 'Shopping', '37', '4', '1', '1']
['519817714', 'Credit Karma: Free Credit Scores, Reports & Alerts', '95494144', 'USD', '0.0', '101679', '181', '5.0', '5.0', '4.11.1', '4+', 'Finance', '37', '0', '1', '1']
['1093190533', "PewDiePie's Tuber Simulator", '266766336', 'USD', '0.0', '90851', '535', '5.0', '5.0', '1.9.1', '9+', 'Games', '37', '5', '17', '1']
['539124565', 'We Heart It - Fashion, wallpapers, quotes, tattoos', '79953920', 'USD', '0.0', '90414', '44', '5.0', '4.0', '8.3.0', '12+', 'Social Networking', '37', '5', '31', '1']
['962194608', 'Google Photos - unlimited photo and video storage', '160215040', 'USD', '0.0', '88742', '1145', '5.0', '5.0', '2.17.0', '4+', 'Photo & Video', '37', '5', '75', '1']
['1031002863', 'Color Therapy Adult Coloring Book for Adults', '135236608', 'USD', '0.0', '84062', '1450', '5.0', '4.5', '2.0', '4+', 'Book', '37', '4', '2', '1']
['962969578', 'Blackbox - think outside the box', '100392960', 'USD', '0.0', '80058', '444', '5.0', '5.0', '1.3.10', '4+', 'Games', '37', '0', '1', '1']
['993492744', 'Egg, Inc.', '53579776', 'USD', '0.0', '79074', '8442', '5.0', '5.0', '1.5', '4+', 'Games', '38', '4', '1', '1']
['959619034', 'Flight Pilot Simulator 3D: Flying Game For Free', '142512128', 'USD', '0.0', '60360', '6551', '5.0', '4.5', '1.3.4', '4+', 'Games', '38', '5', '1', '1']
['792595594', 'Logos Quiz -Guess the most famous brands, new fun!', '72567808', 'USD', '0.0', '58640', '2023', '5.0', '5.0', '2.0', '4+', 'Games', '38', '2', '1', '1']
['875063456', 'Elevate - Brain Training and Games', '196350976', 'USD', '0.0', '58092', '436', '5.0', '5.0', '4.0.1', '4+', 'Education', '37', '5', '31', '1']
['1141762073', 'Tricky Test 2™: Genius Brain?', '134669312', 'USD', '0.0', '45578', '19952', '5.0', '5.0', '5.1', '4+', 'Games', '38', '5', '1', '1']
['1068095192', 'Gin Rummy Plus - Multiplayer Online Card Game', '178644992', 'USD', '0.0', '36355', '304', '5.0', '4.5', '2.4.1', '12+', 'Games', '38', '5', '1', '1']
['1068378177', 'Yu-Gi-Oh! Duel Links', '185152512', 'USD', '0.0', '35570', '937', '5.0', '4.5', '1.6.0', '9+', 'Games', '37', '5', '11', '1']
['457517348', 'FotoRus -Camera & Photo Editor & Pic Collage Maker', '119500800', 'USD', '0.0', '32558', '147', '5.0', '4.5', '7.0.4', '4+', 'Photo & Video', '38', '5', '3', '1']
['973005664', 'Arrow Ambush', '25895936', 'USD', '0.0', '32020', '192', '5.0', '4.0', '1.8', '4+', 'Games', '38', '2', '1', '1']
['805845189', 'Crazy Kitchen', '196248576', 'USD', '0.0', '30704', '67', '5.0', '4.5', '4.1.2', '4+', 'Games', '38', '5', '1', '1']
['979401801', 'Browser and File Manager for Documents', '42198016', 'USD', '0.0', '27750', '27213', '5.0', '5.0', '2.0.1', '17+', 'Utilities', '37', '4', '5', '1']
['518158653', 'FreePrints – Photos Delivered', '112790528', 'USD', '0.0', '26060', '0', '5.0', '0.0', '2.11.3', '4+', 'Photo & Video', '37', '5', '1', '1']
['1162255664', 'SMILE Inc.', '137533440', 'USD', '0.0', '25859', '839', '5.0', '4.5', '1.11', '12+', 'Games', '37', '5', '1', '1']
['994905763', 'Triller - Music Video & Film Maker', '87287808', 'USD', '0.0', '25683', '186', '5.0', '4.5', '4.2.2', '12+', 'Photo & Video', '37', '5', '1', '1']
['1060704812', 'Castle Crush: Epic Strategy Game', '106132480', 'USD', '0.0', '23148', '684', '5.0', '5.0', '2.5.0', '12+', 'Games', '37', '5', '11', '1']
['544118997', 'Shopular Coupons, Weekly Deals for Target, Walmart', '52582400', 'USD', '0.0', '22729', '997', '5.0', '5.0', '6.80', '4+', 'Shopping', '37', '4', '1', '1']
['1045165396', 'Vlogger Go Viral - Clicker Game & Vlog Simulator', '100562944', 'USD', '0.0', '21977', '563', '5.0', '5.0', '1.17', '4+', 'Games', '38', '5', '7', '1']
['635966718', 'Memrise: learn languages', '83949568', 'USD', '0.0', '20383', '138', '5.0', '4.5', '2.2.22', '4+', 'Education', '37', '5', '24', '1']
['916281743', 'Sugar Smash: Book of Life', '128648192', 'USD', '0.0', '20254', '71', '5.0', '4.5', '3.32.162', '4+', 'Games', '37', '4', '16', '1']
['860011430', 'Ghost Lens+Scary Photo Video Edit&Collage Maker', '102500352', 'USD', '0.0', '18316', '756', '5.0', '4.5', '3.91', '12+', 'Photo & Video', '40', '5', '3', '1']
['1016673544', 'ipsy - Makeup, subscription and beauty tips', '35611648', 'USD', '0.0', '17489', '729', '5.0', '5.0', '2.0.0', '4+', 'Lifestyle', '37', '5', '1', '1']
['908989995', 'Bruh-Button', '52343808', 'USD', '0.0', '17487', '157', '5.0', '4.0', '2.1', '17+', 'Entertainment', '37', '5', '1', '1']
['608847384', 'X-War: Clash of Zombies', '42917888', 'USD', '0.0', '17254', '237', '5.0', '4.5', '5.4', '9+', 'Games', '40', '5', '3', '1']
['527219710', 'Sworkit - Custom Workouts for Exercise & Fitness', '143166464', 'USD', '0.0', '16819', '348', '5.0', '5.0', '5.4.1', '4+', 'Health & Fitness', '37', '5', '12', '1']
['1025707485', 'VPN Proxy Master - Unlimited WiFi security VPN', '27117568', 'USD', '0.0', '13674', '0', '5.0', '0.0', '2.4.2', '4+', 'Productivity', '37', '1', '9', '1']
['955286870', 'CPlus for Craigslist app - mobile classifieds', '120219648', 'USD', '0.0', '13345', '2788', '5.0', '5.0', '3.0.0', '17+', 'Catalogs', '37', '5', '1', '1']
['1137893020', 'Artisto – Video and Photo Editor with Art Filters', '55673856', 'USD', '0.0', '12963', '979', '5.0', '5.0', '1.17', '4+', 'Photo & Video', '37', '3', '8', '1']
['493145008', 'Headspace', '121170944', 'USD', '0.0', '12819', '1326', '5.0', '5.0', '2.13.2', '4+', 'Health & Fitness', '37', '0', '1', '1']
['997362197', 'InShot Video Editor Music, No Crop, Cut', '55851008', 'USD', '0.0', '12779', '3366', '5.0', '5.0', '1.19.1', '4+', 'Photo & Video', '37', '0', '9', '1']
['723134859', 'Ebates: Cash Back, Coupons & Rebate Shopping App', '108079104', 'USD', '0.0', '12617', '99', '5.0', '4.5', '4.15.0', '4+', 'Shopping', '37', '5', '5', '1']
['836767708', 'Wayfair - Shop Furniture, Home Decor, Daily Sales', '165069824', 'USD', '0.0', '12578', '146', '5.0', '5.0', '4.24.2', '4+', 'Shopping', '37', '5', '3', '1']
['1066752474', 'Solitaire Ⓞ', '68179968', 'USD', '0.0', '12077', '1373', '5.0', '5.0', '1.0.228', '4+', 'Games', '40', '2', '15', '1']
['1058528141', 'War Machines: 3D Multiplayer Tank Shooting Game', '163080192', 'USD', '0.0', '11325', '172', '5.0', '4.5', '2.0.6', '12+', 'Games', '38', '5', '9', '1']
['888251661', 'Bee Brilliant', '199310336', 'USD', '0.0', '11151', '152', '5.0', '5.0', '1.42.0', '4+', 'Games', '38', '5', '30', '1']
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['1068266222', 'TraptionBakery', '46557184', 'USD', '0.0', '17', '17', '5.0', '5.0', '1.0', '9+', 'Games', '37', '2', '1', '1']
['1057124368', 'LINE RUSH !', '130563072', 'USD', '0.0', '15', '2', '5.0', '5.0', '1.4.4', '9+', 'Games', '43', '0', '3', '1']
['1005030039', 'Mon Espace - Pôle emploi', '111504384', 'USD', '0.0', '11', '0', '5.0', '0.0', '4.2', '4+', 'Business', '37', '5', '1', '1']
['1183260922', "Room Escape Game - Santa's Room", '143346688', 'USD', '0.0', '10', '10', '5.0', '5.0', '1.0', '4+', 'Games', '40', '0', '1', '1']
['1174727122', 'Book - room escape game -', '71790592', 'USD', '0.0', '10', '10', '5.0', '5.0', '1.0', '4+', 'Games', '37', '0', '1', '1']
['1068766238', 'Free QR Code Reader simply to scan a QR Code', '12190720', 'USD', '0.0', '10', '6', '5.0', '5.0', '2.1', '4+', 'Productivity', '38', '3', '2', '1']
['563764220', 'minne - shopping handmade item', '80129024', 'USD', '0.0', '8', '0', '5.0', '0.0', '7.11.0', '4+', 'Shopping', '37', '0', '2', '1']
['1125806960', 'Escape the Cake Café', '33091584', 'USD', '0.0', '7', '7', '5.0', '5.0', '1.0.1', '4+', 'Games', '40', '0', '2', '1']
['1125318904', 'Dice Crush', '180950016', 'USD', '0.0', '7', '1', '5.0', '5.0', '1.0.3', '4+', 'Games', '40', '5', '2', '1']
['1170395210', 'Room Escape Game - Pictures Room Esacpe', '88484864', 'USD', '0.0', '6', '2', '5.0', '5.0', '1.1', '4+', 'Games', '40', '0', '1', '1']
['1068100966', 'Pirates Kids Room Escape', '166528000', 'USD', '0.0', '6', '6', '5.0', '5.0', '1.0', '4+', 'Games', '40', '4', '1', '1']
['632460897', '鬼とび', '9931776', 'USD', '0.0', '6', '1', '5.0', '5.0', '1.1.3', '4+', 'Games', '40', '3', '2', '1']
['1102346079', 'Brake or Break', '82316288', 'USD', '0.0', '5', '3', '5.0', '5.0', '1.4.1', '9+', 'Games', '38', '5', '1', '1']
['723322796', 'FizzUp – Online Fitness Trainer', '124125184', 'USD', '0.0', '5', '0', '5.0', '0.0', '1.21.2', '4+', 'Health & Fitness', '38', '5', '2', '1']
['1188375727', 'Escape the Sweet Shop Series', '90898432', 'USD', '0.0', '3', '3', '5.0', '5.0', '1.0', '4+', 'Games', '40', '0', '2', '1']
['1048899002', 'Simple Camera - Fast Minimal Design', '74435584', 'USD', '0.0', '3', '3', '5.0', '5.0', '3.0.1', '4+', 'Photo & Video', '37', '5', '2', '1']
['1175547625', 'Escape a Crepe House', '32714752', 'USD', '0.0', '3', '3', '5.0', '5.0', '1.0', '4+', 'Games', '40', '0', '2', '1']
['1142223652', 'ROAD -escape game-', '74856448', 'USD', '0.0', '2', '2', '5.0', '5.0', '1.0', '4+', 'Games', '40', '5', '1', '1']
['1082215066', 'Escape Game : Escape from Okinawa', '36832256', 'USD', '0.0', '2', '2', '5.0', '5.0', '1.0.0', '4+', 'Games', '38', '0', '2', '1']
['1121196185', 'Soccer Cup Championship 2016', '68205568', 'USD', '0.0', '2', '2', '5.0', '5.0', '1.2', '4+', 'Games', '38', '5', '1', '1']
['1021877189', 'a. - Physical Simulation Puzzle Game', '49728512', 'USD', '0.0', '2', '2', '5.0', '5.0', '1.0.8', '4+', 'Games', '40', '4', '2', '1']
['1095317943', 'Survivor: Prologue', '55823360', 'USD', '0.0', '2', '2', '5.0', '5.0', '1.0.7', '12+', 'Games', '37', '5', '4', '1']
['1085401990', 'SLAAAASH ! -Cut and Smash ! refreshing Puzzle-', '47260672', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.0.5', '4+', 'Games', '40', '0', '2', '1']
['1156413671', 'LINE Moments - Capture Your Fun Moments', '133572608', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.2.1', '4+', 'Photo & Video', '37', '0', '6', '1']
['887910620', 'DelusionCreatureGacha', '50221056', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.0', '4+', 'Games', '40', '2', '1', '1']
['1013551921', 'Video Smith - A Powerful video editing tool set', '39056384', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.2', '4+', 'Photo & Video', '37', '0', '2', '1']
['1115245945', 'Smart Matches ~ Puzzles with Matchsticks', '28306432', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.1', '4+', 'Games', '37', '4', '15', '1']
['1151496004', 'Jeremstar box', '43215872', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.5.1', '9+', 'Entertainment', '37', '1', '1', '1']
['968213298', 'Bike Race Level 100', '98312192', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.7.1', '9+', 'Games', '40', '5', '2', '1']
['588287777', 'Baidu Videos', '142116864', 'USD', '0.0', '1', '1', '5.0', '5.0', '7.8.5', '17+', 'Entertainment', '38', '0', '2', '1']
['1124568844', 'Frantic Ball', '196617216', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.0.2', '4+', 'Games', '37', '5', '1', '1']
['966802035', 'LINE FIGHTERS', '136356864', 'USD', '0.0', '1', '1', '5.0', '5.0', '1.0.7', '4+', 'Games', '38', '5', '4', '1']
['1090731387', 'Versus - Multiplayer Game (2 players)', '60761088', 'USD', '0.0', '1', '1', '5.0', '5.0', '2.1.2', '4+', 'Games', '37', '5', '4', '1']

Analysis results

  1. 'Games' is the most dominant free Apple prime genre with 1874 applications, 'Entertainment' is second with 254 applications
  2. 'Family' is the most dominant free Google category with 1676 applications, 'Game' is second with 862 applications
  3. 'Tools' is the most dominant free Google genre with 749 applications, 'Entertainment' is second with 538 applications
  4. Most of applications are designed for entertainment purposes - if we want to create a succesfull free application based on genre and category a game that can be enjoyed by whole family would be the right choice
  5. For Google free apps most reviews and downloads are for communication apps like Facebook, messenger, hangouts and also tools like google photos, youtube etc.
  6. For Apple free apps as well biggest number of reviews is for Facebook, however there are a lot of games with top user ratings (5.0)
  7. All above points suggest that the best course of action would be to design a game for family - possibly allowing easy in-game comms within the community

Next step: calculate average rating for each genre

In [46]:
def avg_by(dataset,variable,sum_variable):
    header=dataset[0]
    index_temp=int(header.index(variable))
    index_sum=int(header.index(sum_variable))
    dict_temp={}

    for temp in dataset[1:]:
        genre_app=str(temp[index_temp])
        if genre_app not in dict_temp:
            dict_temp[genre_app] = 1
            total=0
            len_genre=0
            for temp2 in dataset[1:]:
                if genre_app==str(temp2[index_temp]):
                    add=temp2[index_sum]
                    add = add.replace('+','')
                    add = float(add.replace(',',''))
                    total += add
                    len_genre += 1
            result=float(total/len_genre)
            dict_temp[genre_app]=result
    sorted_dict = list(sorted(dict_temp.items(), key=operator.itemgetter(1), reverse=True))
    print(sorted_dict)
In [47]:
avg_by(free_google,'Genres','Installs')

[('Communication', 38456119.167247385), ('Adventure;Action & Adventure', 35333333.333333336), ('Video Players & Editors', 24947335.796178345), ('Social', 23253652.127118643), ('Arcade', 22888365.48780488), ('Casual', 19569221.602564104), ('Puzzle;Action & Adventure', 18366666.666666668), ('Photography', 17840110.40229885), ('Educational;Action & Adventure', 17016666.666666668), ('Productivity', 16787331.344927534), ('Racing', 15910645.681818182), ('Travel & Local', 14051476.145631067), ('Casual;Action & Adventure', 12916666.666666666), ('Action', 12603588.872727273), ('Strategy', 11199902.530864198), ('Tools', 10802461.246995995), ('Lifestyle;Pretend Play', 10000000.0), ('Casual;Music & Video', 10000000.0), ('Tools;Education', 10000000.0), ('Card;Action & Adventure', 10000000.0), ('Adventure;Education', 10000000.0), ('Role Playing;Brain Games', 10000000.0), ('News & Magazines', 9549178.467741935), ('Music', 9445583.333333334), ('Educational;Pretend Play', 9375000.0), ('Puzzle;Brain Games', 9280666.666666666), ('Word', 9094458.695652174), ('Racing;Action & Adventure', 8816666.666666666), ('Books & Reference', 8767811.894736841), ('Puzzle', 8302861.91), ('Video Players & Editors;Music & Video', 7500000.0), ('Shopping', 7036877.311557789), ('Role Playing;Action & Adventure', 7000000.0), ('Casual;Pretend Play', 6957142.857142857), ('Entertainment;Music & Video', 6413333.333333333), ('Action;Action & Adventure', 5888888.888888889), ('Entertainment', 5602792.775092937), ('Education;Brain Games', 5333333.333333333), ('Casual;Creativity', 5333333.333333333), ('Role Playing;Pretend Play', 5275000.0), ('Personalization', 5201482.6122448975), ('Weather', 5074486.197183099), ('Music;Music & Video', 5050000.0), ('Sports;Action & Adventure', 5050000.0), ('Video Players & Editors;Creativity', 5000000.0), ('Adventure', 4922785.333333333), ('Simulation;Action & Adventure', 4857142.857142857), ('Education;Education', 4759517.0), ('Board', 4759209.117647059), ('Sports', 4596842.615635179), ('Educational;Brain Games', 4433333.333333333), ('Health & Fitness', 4188821.9853479853), ('Maps & Navigation', 4056941.7741935486), ('Entertainment;Creativity', 4000000.0), ('Role Playing', 3965645.421686747), ('Card', 3815462.5), ('Trivia', 3475712.7027027025), ('Simulation', 3475484.08839779), ('Casino', 3427910.5263157897), ('Entertainment;Brain Games', 3314285.714285714), ('Arcade;Action & Adventure', 3190909.1818181816), ('Board;Action & Adventure', 3000000.0), ('Entertainment;Pretend Play', 3000000.0), ('Education;Creativity', 2875000.0), ('Educational;Creativity', 2333333.3333333335), ('Entertainment;Action & Adventure', 2333333.3333333335), ('Art & Design', 2122850.9433962265), ('Education;Music & Video', 2033333.3333333333), ('Food & Drink', 1924897.7363636363), ('Education;Pretend Play', 1800000.0), ('Educational;Education', 1737143.142857143), ('Business', 1712290.1474201474), ('Casual;Brain Games', 1425916.6666666667), ('Lifestyle', 1412998.3449275363), ('Finance', 1387692.475609756), ('House & Home', 1331540.5616438356), ('Parenting;Music & Video', 1118333.3333333333), ('Entertainment;Education', 1000000.0), ('Casual;Education', 1000000.0), ('Arcade;Pretend Play', 1000000.0), ('Education;Action & Adventure', 1000000.0), ('Strategy;Action & Adventure', 1000000.0), ('Parenting;Brain Games', 1000000.0), ('Health & Fitness;Action & Adventure', 1000000.0), ('Racing;Pretend Play', 1000000.0), ('Strategy;Creativity', 1000000.0), ('Dating', 854028.8303030303), ('Comics', 831873.1481481482), ('Puzzle;Creativity', 750000.0), ('Auto & Vehicles', 647317.8170731707), ('Libraries & Demo', 638503.734939759), ('Education', 550185.4430379746), ('Simulation;Pretend Play', 550000.0), ('Beauty', 513151.88679245283), ('Art & Design;Pretend Play', 500000.0), ('Music & Audio;Music & Video', 500000.0), ('Strategy;Education', 500000.0), ('Communication;Creativity', 500000.0), ('Parenting', 467977.5), ('Parenting;Education', 452857.14285714284), ('Educational', 411184.8484848485), ('Board;Brain Games', 407142.85714285716), ('Art & Design;Creativity', 285000.0), ('Events', 253542.22222222222), ('Medical', 120550.61980830671), ('Art & Design;Action & Adventure', 100000.0), ('Health & Fitness;Education', 100000.0), ('Travel & Local;Action & Adventure', 100000.0), ('Lifestyle;Education', 100000.0), ('Puzzle;Education', 100000.0), ('Comics;Creativity', 50000.0), ('Books & Reference;Education', 1000.0), ('Simulation;Education', 500.0), ('Trivia;Education', 100.0)]
In [48]:
avg_by(free_apple,'prime_genre','rating_count_tot')

[('Navigation', 86090.33333333333), ('Reference', 74942.11111111111), ('Social Networking', 71548.34905660378), ('Music', 57326.530303030304), ('Weather', 52279.892857142855), ('Book', 39758.5), ('Food & Drink', 33333.92307692308), ('Finance', 31467.944444444445), ('Photo & Video', 28441.54375), ('Travel', 28243.8), ('Shopping', 26919.690476190477), ('Health & Fitness', 23298.015384615384), ('Sports', 23008.898550724636), ('Games', 22788.6696905016), ('News', 21248.023255813954), ('Productivity', 21028.410714285714), ('Utilities', 18684.456790123455), ('Lifestyle', 16485.764705882353), ('Entertainment', 14029.830708661417), ('Business', 7491.117647058823), ('Education', 7003.983050847458), ('Catalogs', 4004.0), ('Medical', 612.0)]

Final thou

  1. For google store free apps most installed genre's are Communication, Adventure: Action & adventure and Video Players & Editors
  2. For apple free apps most installed genre's are Navigation, Reference & Social Networking
  3. With a strong emphasis on communication & social networking I believe this further strenghtens the point that designed app should combine fun & communiucation at one place. Maybe some messenger-like app with built in simple mini-games.