Best money-making apps in the Google Play Market and AppStore

Introduction

There are many people use smartphones nowadays. Companies creating apps have to be proactive and inventive to impress client.

We work as data scientists for company that builds free to use apps. Our main revenue consist of in-app ads.

The goal of this project is to analyze datasets from App Store and Google Play Market and find app profiles that are:

  • Attractive for users
  • Free of charge
  • For English speaking audience

Dataset containing around 10.000 Android apps from the Google Play:Link

Dataset containing around 7.000 iOS apps from the App Store:Link

Explore datasets

In [1]:
# Open two data sets
# Turn both into lists of lists
from csv import reader

# AppStore data set
AppleFile=open('AppleStore.csv',encoding='utf8')
apple_apps=list(reader(AppleFile))

apple_header= apple_apps[0]  # Header of App Store dataset              
apple=apple_apps[1:]         # App Store dataset without header

# Google Play data set
GoogleFile=open('googleplaystore.csv',encoding='utf8')
google_apps=list(reader(GoogleFile))


google_header= google_apps[0] # Header of Google Play Market dataset  
google=google_apps[1:]        # Google Play Market dataset without header



# Explore_data function prints out rows of each dataset in readable way:
# Function shows quantity of rows and columns

def explore_data(dataset,start,end, rows_and_columns=False):
    
    dataset_slice= dataset[start:end]
    
    for row in dataset_slice:
        print(row,'\n')
        
    
    if rows_and_columns:
        print('Number of rows:',len(dataset))
        print('Number of columns',len(dataset[0]))


       

    

Print out several rows of Google Play Store data set to get the general information.

In [2]:
print(google_header)
explore_data(google,1,6,True)
['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver']
['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'] 

['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'] 

['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'] 

['Pixel Draw - Number Art Coloring Book', 'ART_AND_DESIGN', '4.3', '967', '2.8M', '100,000+', 'Free', '0', 'Everyone', 'Art & Design;Creativity', 'June 20, 2018', '1.1', '4.4 and up'] 

['Paper flowers instructions', 'ART_AND_DESIGN', '4.4', '167', '5.6M', '50,000+', 'Free', '0', 'Everyone', 'Art & Design', 'March 26, 2017', '1.0', '2.3 and up'] 

Number of rows: 10841
Number of columns 13

Now let's take a look at App Store data set:

In [3]:
print(apple_header)
explore_data(apple,1,6,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']
['389801252', 'Instagram', '113954816', 'USD', '0.0', '2161558', '1289', '4.5', '4.0', '10.23', '12+', 'Photo & Video', '37', '0', '29', '1'] 

['529479190', 'Clash of Clans', '116476928', 'USD', '0.0', '2130805', '579', '4.5', '4.5', '9.24.12', '9+', 'Games', '38', '5', '18', '1'] 

['420009108', 'Temple Run', '65921024', 'USD', '0.0', '1724546', '3842', '4.5', '4.0', '1.6.2', '9+', 'Games', '40', '5', '1', '1'] 

['284035177', 'Pandora - Music & Radio', '130242560', 'USD', '0.0', '1126879', '3594', '4.0', '4.5', '8.4.1', '12+', 'Music', '37', '4', '1', '1'] 

['429047995', 'Pinterest', '74778624', 'USD', '0.0', '1061624', '1814', '4.5', '4.0', '6.26', '12+', 'Social Networking', '37', '5', '27', '1'] 

Number of rows: 7197
Number of columns 16

Data Cleaning

Before entering into the analysis we do data cleaning including:

  • deleting wrong or incorrect data
  • removing duplicate data
  • modifying data (if needed) to reach the goal of analysis

1.Remove wrong data

The Google Play dataset has discussion section which contains one report about in the row 10472. This problem is about missing value in the column 'Category'.

To make sure that other rows in Google Play have the same length we need to execute following check.

In [4]:
errors_g=[]
i=0
for i in range(len(google)):
    
    if len(google[i])!=len(google_header): # Check if length of each entry does not coincide with length of the header
        print('Row ',i,' contains errors.')
        print(google[i])
        errors_g.append(i)                # In case of error saves the row number in list (errors_g)

for e in errors_g:                        # Loop over list (errors_g) 
    del google[e]                         # and delete rows containing failures from Google Play Market dataset
    print('Row ',e,' deleted')
Row  10472  contains errors.
['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']
Row  10472  deleted

Perform lenght-check for App Store dataset as well:

In [5]:
errors_a=[]
i=0
for i in range(len(apple)):
    if len(apple[i])!=len(apple_header):  # Check if length of each entry does not coincide with length of the header
        print('Row ',i,' contains errors.')
        print(apple[i])
        errors_a.append(i)                # In case of error saves the row number in list (errors_a)

        
for e in errors_a:                        # Loop over list (errors_a)
    del google[e]                         # and delete rows containing failures from App Store dataset
    print('Row ',e,' deleted')

2. Remove Duplicate Entries

Following examination of Google Play Store dataset reveals that it contains duplicate data.

For instance:

In [6]:
for item in google:
    name=item[0]
    
    if name=='KakaoTalk: Free Calls & Text':
        print(item)
['KakaoTalk: Free Calls & Text', 'COMMUNICATION', '4.3', '2546527', 'Varies with device', '100,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 3, 2018', 'Varies with device', 'Varies with device']
['KakaoTalk: Free Calls & Text', 'COMMUNICATION', '4.3', '2546527', 'Varies with device', '100,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 3, 2018', 'Varies with device', 'Varies with device']
['KakaoTalk: Free Calls & Text', 'COMMUNICATION', '4.3', '2546549', 'Varies with device', '100,000,000+', 'Free', '0', 'Everyone', 'Communication', 'August 3, 2018', 'Varies with device', 'Varies with device']

Let's count the quantity of duplicate and unique apps inGoogle Play Store dataset:

In [7]:
duplicate=[]
unique=[]

for item in google:      #Program loop over Google Play Store dataset
    name=item[0]
    if name in unique:  
        duplicate.append(name) # If entry has duplicates save in duplicate list
    else:
        unique.append(name) 
        
print('Number of duplicate apps: ',len(duplicate))
print()
print('Examples of duplicate apps: ', duplicate[0:17])
Number of duplicate apps:  1181

Examples of duplicate apps:  ['Quick PDF Scanner + OCR FREE', 'Box', 'Google My Business', 'ZOOM Cloud Meetings', 'join.me - Simple Meetings', 'Box', 'Zenefits', 'Google Ads', 'Google My Business', 'Slack', 'FreshBooks Classic', 'Insightly CRM', 'QuickBooks Accounting: Invoicing & Expenses', 'HipChat - Chat Built for Teams', 'Xero Accounting Software', 'MailChimp - Email, Marketing Automation', 'Crew - Free Messaging and Scheduling']

Duplicate entries of apps should be deleted to avoid multi-counting. To choose criteria for removal let's examine rows with duplicate data. The main difference is located in column 4 related to the number of reviews.

The higher the number of reviews, more recent data is.
Instead of removing rows randomly we keep only the row with highest review number.

Following this procedure for 'Google Allo' the entry with the highest review 347086 remains, any other will be removed.

['Google Allo', 'COMMUNICATION', '4.3', '346982', 'Varies with device', '10,000,000+', 'Free', '0', 'Everyone', 'Communication', 'January 23, 2018', 'Varies with device', '4.1 and up']

['Google Allo', 'COMMUNICATION', '4.3', '346980', 'Varies with device', '10,000,000+', 'Free', '0', 'Everyone', 'Communication', 'January 23, 2018', 'Varies with device', '4.1 and up']

['Google Allo', 'COMMUNICATION', '4.3', '347086', 'Varies with device', '10,000,000+', 'Free', '0', 'Everyone', 'Communication', 'January 23, 2018', 'Varies with device', '4.1 and up']

Using dictionary we create new list with dataset. New dataset will contain only one entry per app and for each app highest review.

In [8]:
# To get rid of duplicated data we create a dictionary {reviews_max} containing 
# unique apps in the format-   name : highest numbers of reviews.


reviews_max={}
for app in google:
    name=app[0]           
    n_reviews=float(app[3])       
    
    if name in reviews_max and reviews_max[name]<n_reviews:        # If name is in dictionary save the highest number of reviews                                                       
        reviews_max[name]=n_reviews                             
            
    if name not in reviews_max:                                 # Add name and reviews if it is not in the dictionary yet
        reviews_max[name]=n_reviews
        


# In android_clean list we keep only unique apps entries with highest reviews.    
android_clean=[]
already_added=[]

for app in google:
    name=app[0]            
    n_reviews=float(app[3])
    
    if n_reviews == reviews_max[name] and name not in already_added:    # If number of review  = max. review
        android_clean.append(app)                                    # save app in the android_clean list
        already_added.append(name)
        
print(len(android_clean))
9659

3. Non-english apps removal.

Our company uses English to develop apps. Thus in scope of this analysis we keep only apps for English-speaking audience. Exploring our datasets reveals that some apps are designed for non-English users. We remove those apps.

In [9]:
# Helper function ascii
# Checking number of unacceptable symbols contains string
# unacceptable symbols ASCII-code > 127

def ascii(any_string): 
    counter=0
    
    for char in any_string:              
        if ord(char) > 127:                # Calculates number of symbols with ASCII-code > 127
            counter += 1                   # (0-127, English letters, special symbols like !,#,?,@, etc.)
        
    if counter>3:                        
        return False
    else:
        return True
            
In [10]:
# Test ascii fuction
print(ascii('Flame - درب عقلك يوميا'))
print(ascii('বাংলা টিভি প্রো BD Bangla TV'))
print(ascii('Cъновник BG'))
print(ascii('Instachat 😜'))
print(ascii('Bonjour 2017 Abidjan CI ❤❤❤❤❤'))
False
False
False
True
False
In [11]:
# Separate Engish-based apps and save in lists eng_google and eng_apple

eng_google=[]
eng_apple=[]

for app in android_clean:       # Android_clean list (unique Android apps with highest rating)
    name=app[0]
    
    if ascii(name):             # If name does not contain > 3 symbols out of range 0-127 ===> save name in the eng_google
        eng_google.append(app)

        
        
for app in apple:               # Loop over apple list since it does not have duplicates and problems with length of entries
    name=app[1]
    
    if ascii(name):             # If name does not contain > 3 symbols out of range 0-127 ===> save name in the eng_apple
        eng_apple.append(app) 
        
print('Number of English apps in the Google Play Market dataset: ',len(eng_google))
print('Number of English apps in the App Store dataset: ',len(eng_apple))
Number of English apps in the Google Play Market dataset:  9614
Number of English apps in the App Store dataset:  6183

4. Isolation of Free Apps

To attract more users our goal is to focus on free to download and use apps. As mentioned in the introduction - our main source of income is in-built ads. In this section, we separate free apps and save them, while deleting non-free apps.

In [12]:
free_google=[]
free_apple=[]

for app in eng_google:
    price=app[7]
    
    if price=='0':
        free_google.append(app)
        
        
        
        
for app in eng_apple:
    price=app[4]
    
    if app[4]=='0.0':
        free_apple.append(app)
        


    
print('Quantity of free English apps in the Google Play Market dataset:',len(free_google))
print('Quantity of free English apps in the App Store dataset:',len(free_apple))
Quantity of free English apps in the Google Play Market dataset: 8864
Quantity of free English apps in the App Store dataset: 3222

Plan for analysis

So far we cleaned the data to prepare it for analysis. Before proceeding with analysis we choose a strategy to reach the goal and avoid large costs.

We will stick to the following plan:

  1. Find an app profile that seems to be attractive for users in both Google Play and App Store.

  2. Create version of the app and place it in the Google Play Store. In case of positive feedback we will develop app further.

  3. In case of positive profit, create version of the app for the App Store.

1. The Most Common Genres for each market

The Google Play Market dataset has a column genre. The App Store dataset has columns category and genre.

We will start by defining the most common genres or categories for each market.

In [13]:
# freq_table function return frequency table with percentages

def freq_table(dataset,index):
    freq_dict={}                          # Frequency table as dictionary
    
    for app in dataset:
        item=app[index]
        
        if item in freq_dict:            # If item is already in frequency table we add value
            freq_dict[item]+=1         
        else:
            freq_dict[item]=1            # Otherwise we create element of dictionary and define initial value
            
    for key in freq_dict:
         
        freq_dict[key]= round(freq_dict[key]/(len(dataset))*100,2)    # Calculate the percent of certain [key] in the dataset
        
    return freq_dict



# Display_table function returns dataset sorted in:
# - ascedning order (reverse=False)
# - descending order (reverse=True)

def display_table(dataset, index):
    table = freq_table(dataset, index)
    table_display = []
    
    for key in table:
        key_val_as_tuple = (table[key], key)
        table_display.append(key_val_as_tuple)

    table_sorted = sorted(table_display, reverse = True)
    for entry in table_sorted:
        print(entry[1], ':', entry[0])
        
  
    
In [14]:
# List of GENRES in the App Store sorted by percentages
display_table(free_apple,11)  
Games : 58.16
Entertainment : 7.88
Photo & Video : 4.97
Education : 3.66
Social Networking : 3.29
Shopping : 2.61
Utilities : 2.51
Sports : 2.14
Music : 2.05
Health & Fitness : 2.02
Productivity : 1.74
Lifestyle : 1.58
News : 1.33
Travel : 1.24
Finance : 1.12
Weather : 0.87
Food & Drink : 0.81
Reference : 0.56
Business : 0.53
Book : 0.43
Navigation : 0.19
Medical : 0.19
Catalogs : 0.12

The most common genre among English, free apps of the App Store is Games. The next common is Entertainment. The least common is Catalogs and Medical.

General impression is that most of the apps are created for entertainment ( games, social networking, video, shopping, etc.), but this does not imply that apps created for fun have the greatest amount of users.

58% of all apps are related to Gaming in particular. Based only on the analysis of common genres is hard to recommend an app profile.

In [15]:
# List of CATEGORIES in the Google Play Market sorted by percentages
display_table(free_google,1)
FAMILY : 18.91
GAME : 9.72
TOOLS : 8.46
BUSINESS : 4.59
LIFESTYLE : 3.9
PRODUCTIVITY : 3.89
FINANCE : 3.7
MEDICAL : 3.53
SPORTS : 3.4
PERSONALIZATION : 3.32
COMMUNICATION : 3.24
HEALTH_AND_FITNESS : 3.08
PHOTOGRAPHY : 2.94
NEWS_AND_MAGAZINES : 2.8
SOCIAL : 2.66
TRAVEL_AND_LOCAL : 2.34
SHOPPING : 2.25
BOOKS_AND_REFERENCE : 2.14
DATING : 1.86
VIDEO_PLAYERS : 1.79
MAPS_AND_NAVIGATION : 1.4
FOOD_AND_DRINK : 1.24
EDUCATION : 1.16
ENTERTAINMENT : 0.96
LIBRARIES_AND_DEMO : 0.94
AUTO_AND_VEHICLES : 0.93
HOUSE_AND_HOME : 0.82
WEATHER : 0.8
EVENTS : 0.71
PARENTING : 0.65
ART_AND_DESIGN : 0.64
COMICS : 0.62
BEAUTY : 0.6

The most common category of Google Play Market is Family. The next common is Game. The least common are Beauty and Comics.

If we explore Family thorougly, we can see that category includes mostly games apps for kids. It means that in reality games has a share of 28,63%

General impression is that apps designed for entertainment purposes are popular, but they are in balance with apps for practical purposes.

In [16]:
# List of GENRES in the Google Play Market sorted by percentages
display_table(free_google,9)
Tools : 8.45
Entertainment : 6.07
Education : 5.35
Business : 4.59
Productivity : 3.89
Lifestyle : 3.89
Finance : 3.7
Medical : 3.53
Sports : 3.46
Personalization : 3.32
Communication : 3.24
Action : 3.1
Health & Fitness : 3.08
Photography : 2.94
News & Magazines : 2.8
Social : 2.66
Travel & Local : 2.32
Shopping : 2.25
Books & Reference : 2.14
Simulation : 2.04
Dating : 1.86
Arcade : 1.85
Video Players & Editors : 1.77
Casual : 1.76
Maps & Navigation : 1.4
Food & Drink : 1.24
Puzzle : 1.13
Racing : 0.99
Role Playing : 0.94
Libraries & Demo : 0.94
Auto & Vehicles : 0.93
Strategy : 0.91
House & Home : 0.82
Weather : 0.8
Events : 0.71
Adventure : 0.68
Comics : 0.61
Beauty : 0.6
Art & Design : 0.6
Parenting : 0.5
Card : 0.45
Casino : 0.43
Trivia : 0.42
Educational;Education : 0.39
Board : 0.38
Educational : 0.37
Education;Education : 0.34
Word : 0.26
Casual;Pretend Play : 0.24
Music : 0.2
Racing;Action & Adventure : 0.17
Puzzle;Brain Games : 0.17
Entertainment;Music & Video : 0.17
Casual;Brain Games : 0.14
Casual;Action & Adventure : 0.14
Arcade;Action & Adventure : 0.12
Action;Action & Adventure : 0.1
Educational;Pretend Play : 0.09
Simulation;Action & Adventure : 0.08
Parenting;Education : 0.08
Entertainment;Brain Games : 0.08
Board;Brain Games : 0.08
Parenting;Music & Video : 0.07
Educational;Brain Games : 0.07
Casual;Creativity : 0.07
Art & Design;Creativity : 0.07
Education;Pretend Play : 0.06
Role Playing;Pretend Play : 0.05
Education;Creativity : 0.05
Role Playing;Action & Adventure : 0.03
Puzzle;Action & Adventure : 0.03
Entertainment;Creativity : 0.03
Entertainment;Action & Adventure : 0.03
Educational;Creativity : 0.03
Educational;Action & Adventure : 0.03
Education;Music & Video : 0.03
Education;Brain Games : 0.03
Education;Action & Adventure : 0.03
Adventure;Action & Adventure : 0.03
Video Players & Editors;Music & Video : 0.02
Sports;Action & Adventure : 0.02
Simulation;Pretend Play : 0.02
Puzzle;Creativity : 0.02
Music;Music & Video : 0.02
Entertainment;Pretend Play : 0.02
Casual;Education : 0.02
Board;Action & Adventure : 0.02
Video Players & Editors;Creativity : 0.01
Trivia;Education : 0.01
Travel & Local;Action & Adventure : 0.01
Tools;Education : 0.01
Strategy;Education : 0.01
Strategy;Creativity : 0.01
Strategy;Action & Adventure : 0.01
Simulation;Education : 0.01
Role Playing;Brain Games : 0.01
Racing;Pretend Play : 0.01
Puzzle;Education : 0.01
Parenting;Brain Games : 0.01
Music & Audio;Music & Video : 0.01
Lifestyle;Pretend Play : 0.01
Lifestyle;Education : 0.01
Health & Fitness;Education : 0.01
Health & Fitness;Action & Adventure : 0.01
Entertainment;Education : 0.01
Communication;Creativity : 0.01
Comics;Creativity : 0.01
Casual;Music & Video : 0.01
Card;Action & Adventure : 0.01
Books & Reference;Education : 0.01
Art & Design;Pretend Play : 0.01
Art & Design;Action & Adventure : 0.01
Arcade;Pretend Play : 0.01
Adventure;Education : 0.01

The most popular genre in the Google Play Market is Tools and the next popular is Entertainment.

It is very difficult to find out difference between Category and Genre. It seems that some categories and genres duplicate each other. Genre has more subсells than Categories. Right now we are trying to find general picture and will not use Categories in the analysis.

Summary:

Note: Only English apps are in scope of our analysis.

  1. App Store is dominated by apps designed for entertainment. Such genres as Games,Entertainment,Photo & Video have the lagrest share.

  2. Google Play Market has more even landscape, practical and funs apps are balanced. Apps for gaming are still in the majority.

We got the apps distribution by genres and categories, now we determine types of apps with the most users.

Google Play Market has the column installs, so it is possible to calculate average number of downloads for each genre.

In App Storecolumn installs is missing and we will take total number of user rating as a substitute. Total number is column rating_count_tot.

In [17]:
def freq_table_genre(dataset,index):
    freq_dict={}
    
    for app in dataset:
        item=app[index]
        if item in freq_dict:
            freq_dict[item]+=1
        else:
            freq_dict[item]=1
        
    return freq_dict


# Prime_genre shows-  genre: number of apps in Google Play Market
prime_genre=freq_table_genre(free_apple,11) 



# Get list_ratings with data in format-  genre: average number of user rating
list_ratings={} 

for genre in prime_genre:
    total=0
    len_genre=0
    
    for item in free_apple:
        genre_app=item[11]
        rating=item[5]
        
        if genre_app==genre:
            total+=float(rating)
            len_genre+=1
            
    average=(format(total/len_genre,'.2f'))
    list_ratings[genre]= float(average)


# Sort list_rating in descending order
table_display = []    
for key in list_ratings:
    key_val_as_tuple = (list_ratings[key], key)
    table_display.append(key_val_as_tuple)


table_sorted = sorted(table_display, reverse = True)
for entry in table_sorted:   
    print(entry[1], ':', entry[0])
       
        
Navigation : 86090.33
Reference : 74942.11
Social Networking : 71548.35
Music : 57326.53
Weather : 52279.89
Book : 39758.5
Food & Drink : 33333.92
Finance : 31467.94
Photo & Video : 28441.54
Travel : 28243.8
Shopping : 26919.69
Health & Fitness : 23298.02
Sports : 23008.9
Games : 22788.67
News : 21248.02
Productivity : 21028.41
Utilities : 18684.46
Lifestyle : 16485.76
Entertainment : 14029.83
Business : 7491.12
Education : 7003.98
Catalogs : 4004.0
Medical : 612.0

Navigation genre` has the highest rating. Meanwhile genre rating seems to be influenced by quite high ratings of following apps:

  • Waze - GPS Navigation, Maps & Real-time Traffic : 345046
  • Google Maps - Navigation & Transit : 154911

Excluding two apps above from the list will help us to see that Navigation is not very interesting for users.

In [18]:
length=0
total=0
for j in free_apple:
    name=j[1]
    genre=j[11]
    if genre=='Navigation' and name!='Waze - GPS Navigation, Maps & Real-time Traffic' and name!='Google Maps - Navigation & Transit':
        length+=1
        total+=float(j[5])
average=total/length
print('Navigation rating:',average)
Navigation rating: 4146.25

Reference is the next highest rating genre. Following apps skew the rating of genre because of their-own high rating:

  • Bible : 985920
  • Dictionary.com Dictionary & Thesaurus : 200047
  • Dictionary.com Dictionary & Thesaurus for iPad : 54175
In [19]:
length=0
total=0
for j in free_apple:
    name=j[1]
    genre=j[11]
    if genre=='Reference' and name!='Bible' and name!='Dictionary.com Dictionary & Thesaurus' and name!='Dictionary.com Dictionary & Thesaurus for iPad':
        length+=1
        total+=float(j[5])
average=total/length
print('Reference rating:',average)
Reference rating: 7254.4

At first sight the result of Social Networking is skewed by such a headliners as Facebook, Pinterest, WhatsApp etc. If we remove ratings of several "top apps" the rating of Social Networking remains rather high. That allows us to draw a conclusion that Social Networking is popular.

In [20]:
length=0
total=0
for j in free_apple:
    name=j[1]
    genre=j[11]
    if genre=='Social Networking' and name!='Facebook' and name!='Pinterest' and name!='WhatsApp'\
        and name!='Skype for iPhone' and name!='Messenger' and name!='Kik':
        length+=1
        total+=float(j[5])
average=total/length
print('Social Networking rating:',average)
Social Networking rating: 25365.09900990099

Let's see what happens to Food & Drink and Shopping if we remove some high-rated apps.

In [21]:
length=0
total=0
for j in free_apple:
    name=j[1]
    genre=j[11]
    if genre=='Food & Drink' and name!='Starbucks' and name!='Domino\'s Pizza USA' :
        length+=1
        total+=float(j[5])
average=total/length
print('Food & Drink rating:',average)
Food & Drink rating: 12675.083333333334
In [22]:
length=0
total=0
for j in free_apple:
    name=j[1]
    genre=j[11]
    if genre=='Shopping' and name!='Groupon - Deals, Coupons & Discount Shopping App ' and name!='Wish - Shopping Made Fun' \
        and name!='Wish - Shopping Made Fun':
        length+=1
        total+=float(j[5])
average=total/length
print('Shopping rating:',average)
Shopping rating: 25533.66265060241
In [23]:
#This helps to explore apps belonging to certain genre and its total rating(rating_count_tot)
for j in free_apple:
    genre=j[11]
    app=j[1]
    rating_count_tot=j[5]
    if genre=='Photo & Video':
        print(app,' : ',rating_count_tot)
Instagram  :  2161558
Snapchat  :  323905
YouTube - Watch Videos, Music, and Live Streams  :  278166
Pic Collage - Picture Editor & Photo Collage Maker  :  123433
Funimate video editor: add cool effects to videos  :  123268
musical.ly - your video social network  :  105429
Photo Collage Maker & Photo Editor - Live Collage  :  93781
Vine Camera  :  90355
Google Photos - unlimited photo and video storage  :  88742
Flipagram  :  79905
Mixgram - Picture Collage Maker - Pic Photo Editor  :  54282
Shutterfly: Prints, Photo Books, Cards Made Easy  :  51427
Pic Jointer – Photo Collage, Camera Effects Editor  :  51330
Color Pop Effects - Photo Editor & Picture Editing  :  45320
Photo Grid - photo collage maker & photo editor  :  40531
iSwap Faces LITE  :  39722
MOLDIV - Photo Editor, Collage & Beauty Camera  :  39501
Photo Editor by Aviary  :  39501
Photo Lab: Picture Editor, effects & fun face app  :  34585
Rookie Cam - Photo Editor & Filter Camera  :  33921
FotoRus -Camera & Photo Editor & Pic Collage Maker  :  32558
PicsArt Photo Studio: Collage Maker & Pic Editor  :  29078
Quik – GoPro Video Editor to edit clips with music  :  28654
Splice - Video Editor + Movie Maker by GoPro  :  28189
FreePrints – Photos Delivered  :  26060
Triller - Music Video & Film Maker  :  25683
Ghost Lens+Scary Photo Video Edit&Collage Maker  :  18316
Camera360 - Selfie Filter Camera, Photo Editor  :  16729
InstaMag - Free Pic and Photo Collage Maker  :  16221
Over— Edit Photos, Add Text & Captions to Pictures  :  16221
Photo Transfer App - Easy backup of photos+videos  :  15654
InstaSize: Photo Editor, Picture Effects & Collage  :  15605
Prisma: Photo Editor, Art Filters Pic Effects  :  15060
Filterra – Photo Editor, Effects for Pictures  :  14744
YouCam Makeup: Magic Makeup Selfie Cam  :  14188
MSQRD — Live Filters & Face Swap for Video Selfies  :  12982
Artisto – Video and Photo Editor with Art Filters  :  12963
InShot Video Editor Music, No Crop, Cut  :  12779
Layout from Instagram  :  12616
Face Swap App- Funny Face Changer Photo Effects  :  11977
Moments - private albums with friends and family  :  11955
VSCO  :  11174
Retrica - Selfie Camera with Filter, Sticker & GIF  :  11021
VivaVideo - Best Video Editor & Photo Movie Maker  :  10618
Prime Photos from Amazon  :  10511
Canva - Graphic Design & Photo Editing  :  9114
Photo Editor-  :  9095
Snapseed  :  8683
You Doodle - draw on photos & pictures, add text  :  8520
PIP Camera-Selfie Cam&Pic Collage&Photo Editor  :  8454
BeautyPlus - Selfie Camera for a Beautiful Image  :  7503
Baby Story - Pregnancy Pics Baby Milestones Photo  :  6700
Capture - Control Your GoPro Camera - Share Video  :  6542
Meitu  :  6478
Visage makeup editor plus photo teeth whitener  :  5767
Video & TV Cast for Chromecast: Best Browser to cast and stream webvideos and local videos on TV & Displays  :  5676
Adobe Photoshop Mix - Cut out, combine, create  :  5253
Collageable - Photo Collage Maker, Pic Grid Free  :  5112
Bazaart Photo Editor Pro and Picture Collage Maker  :  4909
InstaBeauty -Camera&Photo Editor&Pic Collage Maker  :  4818
YouCam Perfect - Photo & Selfie Editor  :  4293
PHHHOTO - Look Alive  :  4280
MuseCam - Edit Photos & Manual Camera  :  4267
VR Tube - Virtual Reality 360 Video Player  :  4142
Fyuse - 3D Photos  :  4126
MakeupPlus - Natural, Professional Makeup Looks  :  3987
LINE Camera - Photo editor, Animated Stamp, Filter  :  3978
Printicular Print Photos - 1 Hour Pickup  :  3909
Lumyer - augmented reality camera effects  :  3896
KODAK Kiosk Connect App  :  3711
Cool Wallpapers for Pokemon  :  3694
Pro Editor - Video Maker for FaceBook & Youtube  :  3668
Lomotif Music Video Editor - Add Music & Effects!  :  3507
Epson iPrint  :  2838
YouCam Fun - Live Selfie Video Filters  :  2522
A Color Story  :  2436
Boomerang from Instagram  :  2373
B612 - Trendy Filters, Selfiegenic Camera  :  2275
Polarr Photo Editor - Photo Editing Tools for All  :  2246
Retouch Vogue - Facetune Wrinkles & Pimples Makeup  :  2235
Kanvas - Express Yourself  :  2177
Easy Save - Repost your Instagram Photos & Videos  :  2159
Meitu HD  :  2150
Pixlr - Photo Collages, Effects, Overlays, Filters  :  2099
Patternator Pattern Maker Backgrounds & Wallpapers  :  2092
BeautyCam - AR Carnie selfie  :  2082
GIPHY. The GIF Search Engine for All the GIFs  :  2069
Adobe Photoshop Lightroom for iPad  :  2005
SuperPhoto - Photo Effects & Filters  :  1952
Solo Selfie  :  1799
Felt: Birthday & Greeting Cards & Thank You Card  :  1724
Perfect Image - Pic Collage Maker, Add Text to Photo, Cool Picture Editor  :  1646
InstaBoard  for Instagram - photos & videos repost  :  1571
Adobe Photoshop Lightroom for iPhone  :  1494
PhotoScan - scanner by Google Photos  :  1421
RealTimes: Video Maker  :  1274
Meipai  :  1190
POTO - Photo Collage Maker  :  1149
SNOW - Selfie, Motion sticker, Fun camera  :  1115
Bestie-Beauty Camera 360 & Portrait Selfie Editor  :  1035
Facetune 2  :  1009
Pitu  :  968
intoLive - Custom Live Photos wallpaper maker  :  938
LOL Movie: Change your face + voice!  :  849
Camcorder - Record VHS Home Videos  :  830
Anime Power FX  :  807
Squaready for Video - Convert Rectangle Movie Clip into Square Shape for Instagram  :  778
Canon PRINT Inkjet/SELPHY  :  689
Microsoft Pix Camera  :  678
Kwai - Share your video moments  :  668
Polaroid Print App - ZIP  :  631
Photo Quilt - Auto Collage Maker  :  599
Cymera - Photo & Beauty Editor & Collage  :  523
FACIE  :  514
Photo Editing Effects & Collage Maker - Effectshop  :  422
Pic-it Collage - Photo Collage Maker and Editor  :  415
Candy Camera  :  397
Microsoft Selfie  :  375
Color Pop Free - Selective Color Splash Effects and Black & White Photography Editor  :  352
SelfieCity  :  252
InstaSave for Instagram - Download & Repost your own Videos & Photos for Free  :  243
CATCHY Photos-Easter Bunny, Tooth Fairy and more..  :  228
SW/NG - Living Photos. Memories that Swing.  :  222
SlideStory - Create a slideshow movie and a snap video  :  220
April - Layouts, Photo Collage, and Poster Maker  :  165
PopCam Photo  :  160
Foodie - Delicious Camera for Food  :  144
FreeVRPlayer  :  134
Confetti - Geofilter Design Maker for Snapchat  :  120
Philm-Video&Photo Editor,REAL-TIME Magic Filter  :  103
Digital Domain  :  102
Homido 360 VR player  :  100
Best 9 for Instagram  :  88
VR Video World - Virtual Reality  :  88
FilmStory - For All Your Video Editing Needs  :  66
GIFYme - Create video loops and gifs with amazing filters for Whatsapp and Instagram  :  65
Kiosk Photo Transfer by Fujifilm  :  58
Pikazo – AI art that YOU control  :  56
lollicam - photo, video, and selfie camera  :  51
LOOKS - Real Makeup Camera  :  25
C CHANNEL -Watch tips & tricks videos for girls  :  21
in-capturing moments in life  :  16
Everfilter - transform your photos into artworks  :  15
GoSnaps - Share Screenshots for Pokémon GO  :  12
NightShooting  :  9
MixChannel  :  6
Simple Camera - Fast Minimal Design  :  3
SwapperFace - Face Swap Free, Live Mask Effects  :  2
LINE Moments - Capture Your Fun Moments  :  1
Video speed editor - VBooster  :  1
Video Smith - A Powerful video editing tool set  :  1
MeiCam -  Video Production Master  :  0
Instant X - Take instant-camera-like photo with double exposure and bulb mode  :  0
EOPAN  :  0
StageCameraHD  :  0
Pictalive for Live Photos - Create from videos  :  0
BlurEffect-Blur Photo & Video, Hide Face  :  0
camera for filter  :  0
Emojil - original emoji stamp, decoration camera  :  0
CelebrityDiagnosis!  :  0

Outputs

Following genres are skewed by strong market players:

  • Navigation - Waze, Google Map.
  • Reference - Bible, Dictionary.com Dictionary & Thesaurus.
  • Photo & Video- Instagram, Snapchat, YouTube.
  • Book - Kindle, Audible.
  • Food & Drink- Starbucks, Domino's Pizza USA.

Social Networking is influenced by Facebook, Pinterest, Skype, WhatsApp, Kik, but even without them genre seems to be popular. Creating app in such genre means buisness competition with leaders.

In spite of Pandora, Spotify and Shazam impact on Music ratings there are plenty of other relatively popular apps. We should take into consideration that people might not spend much time surfing in the Music apps, rather have them in the background while listening to the music.

Same pattern for Weather which has relatively high ratings. People do not tend to spend time in weather apps.

Games dominating the App Store in terms of numbers of apps. If we explore Games, we'll see there are plenty of app with very high ratings and average rating. Going this direction demands following analisys about the most popular genres of games.

Food & Drink, Finance, Travel- require additional activities, for instance: open a restaurant, get some experience in cooking, hiring finance professionals, etc.

Shopping seems to have potential. This genre still has a quite high rating even if we remove some highest-rated apps.

There is data about numbers of downloads for the Google Play Market. Since this data is open-ended we do not know exact number of installs. For example category 10.000+ includes all values greater than 10.000. We are going to use those values and consider 10.000+ as 10.000 or 200.000+ as 200.000.

In [24]:
# Prime_category is frequency table for each category  of the Google Play Market
prime_category=freq_table_genre(free_google,1)

inter_list={}
for category in prime_category:
    total=0
    len_category=0
    
    for item in free_google:
        cat_app=item[1]      # category of app 
        installs=item[5]     # number of dowloads
        
        if cat_app==category:
            installs=installs.replace('+','') # removing '+' from downloads value
            installs=installs.replace(',','') # removing ',' from downloads value
            total+=float(installs)
            len_category+=1
            
    average=total/len_category            # average number of downloads per category        
    inter_list[category]=average          # dictionary inter_list contains categories as keys and average number 
                                          # downloads as values


# Display_table_cat shows the dataset in descending order
def display_table_cat(dataset):
    
    table_display = []
    for key in dataset:
        key_val_as_tuple = (dataset[key], key)
        table_display.append(key_val_as_tuple)

    table_sorted = sorted(table_display, reverse = True)
    for entry in table_sorted:
        print(entry[1], ':', entry[0])
        
# Show inter_list in descending order
display_table_cat(inter_list)
COMMUNICATION : 38456119.167247385
VIDEO_PLAYERS : 24727872.452830188
SOCIAL : 23253652.127118643
PHOTOGRAPHY : 17840110.40229885
PRODUCTIVITY : 16787331.344927534
GAME : 15588015.603248259
TRAVEL_AND_LOCAL : 13984077.710144928
ENTERTAINMENT : 11640705.88235294
TOOLS : 10801391.298666667
NEWS_AND_MAGAZINES : 9549178.467741935
BOOKS_AND_REFERENCE : 8767811.894736841
SHOPPING : 7036877.311557789
PERSONALIZATION : 5201482.6122448975
WEATHER : 5074486.197183099
HEALTH_AND_FITNESS : 4188821.9853479853
MAPS_AND_NAVIGATION : 4056941.7741935486
FAMILY : 3695641.8198090694
SPORTS : 3638640.1428571427
ART_AND_DESIGN : 1986335.0877192982
FOOD_AND_DRINK : 1924897.7363636363
EDUCATION : 1833495.145631068
BUSINESS : 1712290.1474201474
LIFESTYLE : 1437816.2687861272
FINANCE : 1387692.475609756
HOUSE_AND_HOME : 1331540.5616438356
DATING : 854028.8303030303
COMICS : 817657.2727272727
AUTO_AND_VEHICLES : 647317.8170731707
LIBRARIES_AND_DEMO : 638503.734939759
PARENTING : 542603.6206896552
BEAUTY : 513151.88679245283
EVENTS : 253542.22222222222
MEDICAL : 120550.61980830671
In [28]:
# Helps to explore content of categories
for app in free_google:
    if app[1]=='BUSINESS':
        print(app[0],' : ', app[5])
Visual Voicemail by MetroPCS  :  10,000,000+
Indeed Job Search  :  50,000,000+
Uber Driver  :  10,000,000+
ADP Mobile Solutions  :  5,000,000+
Snag - Jobs Hiring Now  :  1,000,000+
Docs To Go™ Free Office Suite  :  50,000,000+
Google My Business  :  5,000,000+
OfficeSuite : Free Office + PDF Editor  :  100,000,000+
USPS MOBILE®  :  1,000,000+
Job Search by ZipRecruiter  :  1,000,000+
Google Primer  :  10,000,000+
Alba Heaven - Alvarez Job Portal Services  :  5,000,000+
SuperLivePro  :  1,000,000+
OfficeSuite Pro + PDF (Trial)  :  10,000,000+
My Space - Employment Center  :  1,000,000+
Box  :  10,000,000+
Polaris Office for LG  :  5,000,000+
Call Blocker  :  5,000,000+
Jobs in Alabama - Jobs in Alba  :  5,000,000+
Square Point of Sale - POS  :  5,000,000+
Plugin:AOT v5.0  :  100,000+
Kariyer.net  :  1,000,000+
SEEK Job Search  :  1,000,000+
Become a Job - Find a job or advertise  :  1,000,000+
ZOOM Cloud Meetings  :  10,000,000+
Easy Installer - Apps On SD  :  5,000,000+
IndiaMART: Search Products, Buy, Sell & Trade  :  5,000,000+
ViettelPost express delivery  :  100,000+
MyASUS - Service Center  :  10,000,000+
Job Korea - Career Jobs  :  1,000,000+
104 Looking for a job - looking for a job, looking for a job, looking for a part-time job, health checkup, resume, treatment room  :  1,000,000+
Myanmar 2D/3D  :  100,000+
Quick PDF Scanner + OCR FREE  :  5,000,000+
sABN  :  1,000,000+
ATI Cargoes and Transportation  :  100,000+
Secure Folder  :  50,000,000+
UPS Mobile  :  5,000,000+
Y! Mobile menu  :  100,000+
SignEasy | Sign and Fill PDF and other Documents  :  1,000,000+
Genius Scan - PDF Scanner  :  1,000,000+
Tiny Scanner - PDF Scanner App  :  10,000,000+
Fast Scanner : Free PDF Scan  :  10,000,000+
Mobile Doc Scanner (MDScan) Lite  :  1,000,000+
Zenefits  :  50,000+
FreshBooks Classic  :  100,000+
Insightly CRM  :  100,000+
QuickBooks Accounting: Invoicing & Expenses  :  1,000,000+
HipChat - Chat Built for Teams  :  500,000+
Xero Accounting Software  :  100,000+
MailChimp - Email, Marketing Automation  :  500,000+
Crew - Free Messaging and Scheduling  :  500,000+
Asana: organize team projects  :  1,000,000+
Google Analytics  :  1,000,000+
AdWords Express  :  1,000,000+
Accounting App - Zoho Books  :  100,000+
Invoice & Time Tracking - Zoho  :  100,000+
join.me - Simple Meetings  :  1,000,000+
Invoice 2go — Professional Invoices and Estimates  :  1,000,000+
Cisco Webex Meetings  :  10,000,000+
ScreenMeet. Easy Phone Meeting  :  100,000+
Cisco Webex Teams  :  100,000+
Microsoft Remote Desktop  :  5,000,000+
Start Meeting  :  50,000+
ClickMeeting Webinars  :  1,000,000+
BlueJeans for Android  :  500,000+
Skype for Business for Android  :  10,000,000+
Slack  :  5,000,000+
Verify - Receipts & Expenses  :  10,000+
R+F PULSE  :  10,000+
F-Secure Freedome for Business  :  50,000+
F-Gas Solutions  :  10,000+
ADMIRALTY H-Note  :  10,000+
M-Files  :  10,000+
Q MINDshare Mobile  :  10,000+
Q Operator  :  1,000+
U Pull It Auto Dismantler  :  10,000+
Vault-Hide SMS,Pics & Videos,App Lock,Cloud backup  :  50,000,000+
V-CUBE Seminar Mobile  :  100,000+
IRS W-9 form  :  10,000+
AC Freedom  :  100,000+
A/C REFRIGERANT CAPACITY  :  10,000+
Local Services ads by Google  :  1,000+
Google Ads  :  5,000,000+
Bing Ads  :  100,000+
Ivanti AE Agent  :  1,000+
AF Legendary 2017  :  50+
AF Our Time to Shine  :  100+
Safe Ag Systems™  :  100+
Border Ag & Energy  :  50+
Ag-Pro Companies  :  50+
West Central Ag  :  100+
United Ag Cooperative  :  5+
Ag Valley Cooperative  :  500+
Ag-Power  :  10+
i am rich  :  1,000+
Create apps fast with beautiful design and no code  :  1,000,000+
Resume Builder Free, 5 Minute CV Maker & Templates  :  1,000,000+
AO-EVENT  :  100+
AP Mobile 104  :  100+
AQ Service  :  10+
Augment - 3D Augmented Reality  :  1,000,000+
realcommercial.com.au  :  50,000+
Jobs in Canada - Emplois au Canada  :  1,000+
Job'Of - Emploi au Cameroun  :  10,000+
AirWatch Agent  :  5,000,000+
HCP Anywhere  :  5,000+
AirWatch Inbox  :  1,000,000+
Dynamics AX  :  10,000+
AX Timesheets App for Dynamics  :  10+
Workflow Approvals App AX 2012  :  100+
AY Recruitment  :  10+
AY EMLAK  :  10+
Ay Peruk  :  1+
AZ Mobile Gizmo  :  1,000+
BA4You  :  5,000+
BC browser  :  100+
Business Dictionary  :  500,000+
Upohar BD  :  1,000+
BD Online Shop  :  5,000+
Bf Light  :  1,000+
BF Family user  :  100+
XXX DISTILLERY  :  100,000+
Micro.bg Cloud POS System  :  100+
JOBS.bg  :  100,000+
Coomotaxi BH  :  5,000+
BH Táxi  :  5,000+
Microsoft Power BI–Business data analytics  :  100,000+
BI SmartLINK  :  5,000+
Sisense Mobile BI  :  1,000+
Propel BI APP  :  100+
BI Office  :  10,000+
Oracle BI Mobile  :  10,000+
Zoho Reports - Mobile BI  :  5,000+
BJ TIKET  :  10+
BJ Foods  :  10+
BJ Adams  :  5+
bk Group Mobile  :  50+
BK Arogyam Task Track  :  100+
BL Carrier  :  10+
Business Mitra (BM)  :  100+
BN Mi Banco  :  100,000+
2017 BN SM Sales Conference  :  100+
BN Habitat - Property Experts - Buy | Sell | Rent  :  50+
BP World Energy  :  10,000+
BP Service  :  100+
Bill Miller Bar-B-Q Store Ops  :  100+
BR Classified  :  50+
Mu Mobile BR  :  100+
Mu Elite BR  :  100+
Corporate B.S. Generator  :  10+
BT One Mobile secure access  :  10,000+
BT One Voice anywhere  :  10,000+
BT Find Address for Bluetooth  :  5,000+
BT Share It  :  500+
Ultimate Control BT  :  500+
Aegis BT  :  500+
BV Smart  :  1,000+
BV Forest  :  100+
BV Link  :  100+
BV MAAp  :  100+
PIO bv App  :  10+
Kovax Europe B.V.  :  500+
DHV accountancy BV  :  10+
BV Teknisk App  :  50+
BV Productions  :  1+
Allsetra B.V.  :  1,000+
PIO bv Transport App  :  5+
BW COMPANY FINDER  :  1,000+
BW eServices  :  10+
BX Mobile TMC for SAP B1  :  100+
BZ Reminder  :  1,000,000+
CA Service Management  :  10,000+
CA Mobile Authenticator  :  1,000+
CA Latam Partners  :  10+
CA Case Management  :  500+
CA UIM Mobile  :  1,000+
CA Clarity Mobile Time Manager  :  10,000+
Patchcord.ca Inc. App Launcher  :  10+
Viking CB Radios  :  1,000+
CB Mobile  :  100+
CB Land  :  100+
CD Events  :  100+
CD Roma's  :  100+
CD Ready  :  1,000+
CD-Zing  :  1,000+
CD Supply  :  5+
CE SmartApp.com  :  100+
Volvo CE Insider  :  1,000+
NetApp CE  :  100+
Merck CE  :  100+
CE Intelligence  :  5+
CH Kadels  :  1,000+
Valmet CI Tool  :  500+
RGN CI-Control  :  50+
CI View  :  100+
Ci - Logistics Group  :  50+
Majestic Cinema CI  :  5,000+
CI SA  :  10+
CJ Apps  :  10+
CJ the REALTOR  :  10+
CJ IT ApS  :  10+
CK Employee Portal  :  1,000+
Company Kitchen Inventory  :  1,000+
CL Clock  :  1,000+
MobileBiz Co - Cloud Invoice  :  10,000+
Websites.co.in Instant Website  :  10,000+
Good&Co: Career match tests  :  1,000,000+
CP ToolBox  :  1,000+
CP Plus Showcase  :  50,000+
CP Installer App  :  100+
CP Ready  :  1,000+
CP Cloud  :  100+
HR Team CQ Region Ed Qld  :  500+
CQ ESPM  :  5+
Create My App  :  10+
Global Shop  :  50+
CR Magazine  :  100+
NetClient CS  :  10,000+
CS  :  100+
Mobile CS  :  1,000+
Curriculum vitae App CV Builder Free Resume Maker  :  500,000+
Free Resume App  :  1,000,000+
CV Engineer - Free Resume Maker & CV Templates  :  10,000+
Curriculum Vitae  :  1,000,000+
Free resume builder CV maker templates PDF formats  :  1,000,000+
Resume Builder - Free CV Maker & Premium Templates  :  100,000+
Resume PDF Maker / CV Builder  :  500,000+
CV S ( CV Editor - Resume )  :  100,000+
CV Maker Pro  :  10,000+
HOW TO WRITE A CV  :  100,000+
CV EXAMPLES  :  100,000+
Resume Builder Free, CV Maker & Resume Templates  :  1,000,000+
Free Professional Resume Builder, CV, Cover Letter  :  50,000+
Free Resume Builder – CV Maker  :  5,000+
Resume App  :  1,000,000+
CV Builder  :  10,000+
Resume Maker:Free CV Maker,Templates Builder  :  100,000+
Resume Builder / CV Maker & Templates  :  5,000+
Resume ( CV Editor )  :  10,000+
Resume Maker - Creator  :  50,000+
CV Builder for Smart Resumes  :  1,000+
CV-Library Job Search  :  100,000+
CV Samples 2018  :  10,000+
CV (Curriculum Vitae / Resume) Maker  :  5,000+
Resume / CV  :  10,000+
VisualCV Resume Builder  :  100,000+
Resume Builder - Curriculum Vitae & Resume Maker  :  5,000+
CW Deposit  :  1,000+
Oracle CX Cloud Mobile  :  5,000+
CX North America  :  500+
Avaya CX  :  1,000+
CX Carrier Lite  :  10+
CX Capture  :  100+
CX Elevated  :  50+
FlexRelease CX  :  1,000+
Ambient CX  :  5+
QuestionPro - CX  :  50+
CX Network  :  0+
Cy-Fair Houston Chamber  :  5+
VAT check CY  :  100+
DB Stay Connected  :  1,000+
DB Customer Connect  :  10,000+
DB Pickles  :  100+
[email protected]  :  1,000+
DF Tracker  :  100+
DF-View  :  100+
ElejaOnline DF  :  50+
df-Vegetable  :  5+
DG Monitor  :  100+
DH-Security Camera  :  100+
dk Verk  :  500+
Ramdor DM Mobile  :  100+
DN Managed Mobility App  :  50+
DN Advanced Service Coder  :  10+
DN Premium Hookah Lounge  :  50+
PlayMotiv dn edition  :  500+
DN Diamonds  :  100+
DN Snacks  :  1+
PDF Reader - Scan、Edit & Share  :  10,000,000+
DQ Events  :  10,000+
ODTMobile v4  :  1,000+
DQT GPS  :  500+
ODTMobile  :  10,000+
DS-11 form  :  100+
SmartCircle Remote DS  :  500+
DS Vision  :  5+
DS - xR  :  10+
DS-82 form  :  100+
DT Fieldlink  :  500+
PAY DT  :  1+
DT Practice  :  500+
DW Mobile  :  10,000+
DW Spectrum™ IPVMS Mobile  :  10,000+
DW Spectrum™ IP VMS  :  10,000+
DW Witness  :  500+
DW Tech Tools  :  100+
DW Security  :  100+
ZAK DW  :  10+
VMAX IP Plus Mobile Client  :  1,000+
DY TECHNICAL GYAN  :  10+
EB-Link  :  100+
Debra Care Conference  :  50+
TANGEDCO Mobile App (Official)  :  500,000+
EB Kit  :  100+
EB Remote Deposit  :  10+
TNEB  :  100,000+
EB Cash Collections  :  5+
EC - Encumbrance Search - telangana state  :  10,000+
Ec Solutions Mobile  :  10+
Encumbrance Certificate - (Obsolete)  :  50,000+
EC Reps  :  100+
FILL EC  :  100+
EF Forms  :  50+
EF App  :  100+
EF Catalogues · Kataloge  :  500+
EG-Boost  :  1,000+
EG Mantenimiento  :  50+
EG CrossPad - ASPECT4  :  1,000+
EG CrossPad  :  1,000+
EG Retail  :  500+
EH Autolink  :  100+
Endress+Hauser Operations  :  10,000+
eHub  :  100,000+
NEMA ei  :  100+
Sensenuts eI  :  5+
Ej-buy  :  5+
EO Network  :  1,000+
EO Global  :  1,000+
EO SouthAsia  :  100+
EO Forum  :  100+
EO Events  :  10+
EO KOREA  :  50+
EO GSEA  :  10+
EO SA Benefits  :  10+
23rd QM BDE EO  :  10+
EO Hub  :  50+
EO  :  50+
4Eternity EO  :  10+
EP  :  100+
ES Task Manager (Task Killer )  :  10,000,000+
ES Anywhere  :  100+
ES Solar  :  100+
EU FTL Calculator  :  10,000+
CVRIA  :  10,000+
EURES - Your Job in Europe  :  50,000+
Autoroute.EU  :  1,000+
E.U. Trademark Search Tool  :  10+
EU VAT Checker  :  1,000+
Dotti EU  :  1,000+
EU FP7 Adventure  :  100+
VAT Checker for EU company  :  1,000+
Konferencija.eu  :  10+
EU GDPR RiskCalc  :  50+
EU Whoiswho  :  10+
Qserve EU MDR First Aid  :  100+
NativeScript Developer Day EU  :  100+
EU FP7 SAM  :  10+
eu sou franky  :  10,000+
EW Manager  :  10+
EW Gate  :  50+
EW Login  :  10+
EW Handbook  :  100+
Ex Service Taxis  :  1,000+
EY Events  :  10,000+
EY GlobalOne  :  1,000+
EY Conferences  :  1,000+
EY Africa  :  100+
EY Tax Briefing  :  100+
EY Digital Direct  :  5+
EY India Tax Insights  :  10,000+
EY India CFO Insights  :  5,000+
EY Digital Tax AR  :  100+
EY Divest  :  5+
EY Digi India Personal Tax  :  100+
EY Catalyst Reader  :  5+
EY EMEIA Diversity & Inclusion  :  500+
EY TaxLaw NL  :  100+
EY-Parthenon  :  5+
EY Oil & Gas  :  1,000+
EZ Thanks  :  10,000+
Ez Texting  :  10,000+
EZ View  :  50,000+
Facebook Face to Face Events  :  1,000,000+
Facebook Pages Manager  :  50,000,000+
Facebook Ads Manager  :  1,000,000+
FB Live  :  5,000+
EasyLive - FB Live Helper  :  500+
File Commander - File Manager/Explorer  :  100,000,000+
FE Mobile  :  10+
FE Connect Drive-Tech  :  100+
FG VOC  :  1,000+
FH App  :  100+
FK CLASSIC FOR YOU  :  10+
FL Tax-Verify  :  5,000+
Employ Florida Mobile  :  10,000+
FN  :  50+
Theme fo Oppo A30 Wallpaper & Icon  :  500+
RRIMS FO  :  100+
Neon Blue Gaming Wallpaper&Theme fo Lenovo K8 Note  :  500+
Custos F.O.  :  1+
FP-safe  :  100+
SCM FPS Status  :  10,000+
FQ Load Board for Transporters  :  100+
Fr Lupupa Sermons  :  100+
DICT.fr Mobile  :  10,000+
FieldBi FR Offline  :  100+
FR Forms  :  10+

It is interesting to investigate what happens to the downloads indicator if we remove some high-rated apps from account.

In [27]:
reduced = []

for app in free_google:
    index='COMMUNICATION'
    cat = app[1]
    installs = app[5]
    installs = installs.replace(',', '')
    installs = installs.replace('+', '')
    
    if ( cat == index) and (float(installs) < 100000000):  # Remove all apps over certain number of downloads
        reduced.append(float(installs))
        
print(index,'updated rating: ',sum(reduced) / len(reduced))
COMMUNICATION updated rating:  3603485.3884615386

Outputs

Distribution of applications by categories in the Google Play Market is different compared to App Store.

For instance:

  • 1)COMMUNICATION and SOCIAL are two different categories in Google Play Market. In App Store we have Social Networking genre.

  • 2)Photo & Video genre in App Store and in Google Play Market there are PHOTOGRAPHY and VIDEO_PLAYERS categories.

It should be taken into account that there are many categories dominated by few giants. For example:

  • SOCIAL- Facebook, Google+.
  • VIDEO_PLAYERS- YouTube, Motorola Gallery.
  • TOOLS - Google,Account Manager.

We are looking for categories apps that:

  • 1) Users spend plenty of time in.
  • 2) Have relatively high number of downloads after removing ratings of some top-rated apps.

There are list of such categories:

  • COMMUNICATION
  • VIDEO_PLAYERS
  • SOCIAL
  • GAME
  • SHOPPING

Conclusions and results

In this project, we analyzed apps in the Google Play Market and App Store to find app profiles that are attractive for users in both markets.

The distribution of applications by genre and category may create some obstacles to analysis in principle. We assume that the distribution is correct from the beginning.

The following categories have the potential to create applications:

  • Social Networking
  • Games
  • Shopping

It is clear that the market is full of competitive apps in principle. Creating an app in these categories may mean competition and attracting specialized developers.