This project is designed to analyze data to help developers of Android and iOS mobile apps to understand which types of applications have the potential to attract more users on Google Play and App Store.
As of September 2018, there were approximately 2 million iOS apps available on the App Store, and 2.1 million Android apps on Google Play.
Collecting data for over four million apps requires a significant amount of time and money, so we'll try to analyze a sample of data instead. To avoid spending resources with collecting new data ourselves, we should first try to see whether we can find any relevant existing data at no cost. Luckily, these are two data sets that seem suitable for our purpose:
A data set containing data about approximately ten thousand Android apps from Google Play. You can download the data set directly from this link.
A data set containing data about approximately seven thousand iOS apps from the App Store. You can download the data set directly from this link.
Let's import our datasets.
import csv
# The iOS dataset
ios_file = open('AppleStore.csv')
ios_read = csv.reader(ios_file)
ios_rows = list(ios_read)
ios_header = ios_rows[0]
ios = ios_rows[1:]
# The Android dataset
android_file = open('googleplaystore.csv')
android_read = csv.reader(android_file)
android_rows = list(android_read)
android_header = android_rows[0]
android = android_rows[1:]
This a function that will help us to explore the datasets. This will save us time as we need to explore the datasets frequently during the analysis.
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]))
Let's explore our datasets to understand their contents. We will do so by printing the first few rows of each dataset. We will also identify the columns that will help us with our analysis.
Let us start with iOS dataset.
print(ios_header, '\n')
explore_data(ios, 1, 3, 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'] Number of rows: 7197 Number of columns: 16
So, the App store has 7197 apps and 16 columns. The columns that will help us in our analysis are: 'track_name'
, 'currency'
, 'price'
, 'rating_count_tot'
, 'prime_genre'
. Some of the column names are not self explanatory but the details of each column can be found in this documentation.
Now let's take a look at the Google Play dataset.
print(android_header, '\n')
explore_data(android, 1, 3, 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'] Number of rows: 10841 Number of columns: 13
The Google Play has 10841 apps with some interesting columns that will help us to analyze the data like: 'App'
, 'Category'
, 'Rating'
, 'Reviews'
, 'Type'
, 'Genres'
, etc.
The Google Play dataset has a dedicated discussion section, and we can see that one of the discussions describes an error for a certain row.
Let us find out the row index with the missing data and print it out to see the missing data.
print(android_header, '\n')
print('The length of the header:', len(android_header),'\n')
for row in android:
if len(row) != len(android_header):
print('The length of row with missing information:', len(row), '\n')
print('The index of row with missing information:', android.index(row), '\n')
print('The row with missing iformation is: \n', row)
['App', 'Category', 'Rating', 'Reviews', 'Size', 'Installs', 'Type', 'Price', 'Content Rating', 'Genres', 'Last Updated', 'Current Ver', 'Android Ver'] The length of the header: 13 The length of row with missing information: 12 The index of row with missing information: 10472 The row with missing iformation is: ['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']
As seen, the row is missing the 'category column'
of the data. So, we are going to delete it to clean our data.
print(len(android))
del android[10472] # don't run this more than once
print(len(android))
10841 10840
If we explore the Google Play data set long enough or look at the discussions section, we'll notice some apps have duplicate entries. For instance, Instagram has four entries:
for app in android:
name = app[0]
if name == 'Instagram':
print(app)
['Instagram', 'SOCIAL', '4.5', '66577313', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device'] ['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'] ['Instagram', 'SOCIAL', '4.5', '66577313', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device'] ['Instagram', 'SOCIAL', '4.5', '66509917', 'Varies with device', '1,000,000,000+', 'Free', '0', 'Teen', 'Social', 'July 31, 2018', 'Varies with device', 'Varies with device']
Now that we know the Google Play dataset has duplicate entries, let's count the number of duplicates in the dataset.
duplicate_apps = []
unique_apps = []
for app in android:
name = app[0]
if name in unique_apps:
duplicate_apps.append(name)
else:
unique_apps.append(name)
print('The number of duplicate apps in the dataset:', len(duplicate_apps), '\n')
print('Examples of duplicate apps:', duplicate_apps[:6])
The number of duplicate apps in the dataset: 1181 Examples of duplicate apps: ['Quick PDF Scanner + OCR FREE', 'Box', 'Google My Business', 'ZOOM Cloud Meetings', 'join.me - Simple Meetings', 'Box']
Looking at the Instagram duplicates above, we can see that the number of reviews are different. It is most likely that the row with highest number of reviews is the latest row.So, we are going to keep this row in all our duplicated apps.
After we remove the 1181 duplicates, we should be left with 9659 based on the following formular:
print('Expected length:', len(android) - 1181 )
Expected length: 9660
Let us assign the row with highest user rating to each application so that we have unique apps with highest number of rating. We will check the length of our dataset again.
reviews_max = {}
for app in android:
name = app[0]
n_reviews = float(app[3])
if name in reviews_max and reviews_max[name] < n_reviews:
reviews_max[name] = n_reviews
if name not in reviews_max:
reviews_max[name] = n_reviews
print(len(reviews_max))
9659
We have it! It is 9659. So we are doing good.
Now, we will use the above dictionary to remove the duplicate rows.
android_clean = [] #This will store our new cleaned dataset
already_added = [] # This will store app names
for app in android:
name = app[0]
n_reviews = float(app[3])
if n_reviews == reviews_max[name] and name not in already_added:
android_clean.append(app)
already_added.append(name)
Now, let's explore the new dataset to make sure it has 9659 entries.
explore_data(android_clean, 0, 3, True)
We have remove the duplicates in our Google Play dataset.
print(ios[813][1])
print(ios[6731][1])
print('\n')
print(android_clean[4412][0])
print(android_clean[7940][0])
We are not interested in keeping this types of applications, so we are going to remove them.
To remove non-english apps, we should use a function that will detect non-english letters based on ASCII standard.
def eng_only(a_string):
for character in a_string:
if ord(character) > 127:
return False
return True
print(eng_only('Instagram'))
print(eng_only('爱奇艺PPS -《欢乐颂2》电视剧热播'))
print(eng_only('Instachat 😜'))
As seen above, our function 'eng_only'
classified 'Instachat 😜'
as non-english because it contain emoji. Emojis have ASCII number that are more than 127. Let's see it below:
print(ord('😜'))
In order to reduce data loss, we are going to modify our function to claasy all apps that have 3 characters that are bigger than 127. In this way, we will be able to capture names with 3 emojis.
def eng_only(a_string):
non_ascii = 0
for character in a_string:
if ord(character) > 127:
non_ascii += 1
if non_ascii > 3:
return False
else:
return True
print(eng_only('Docs To Go™ Free Office Suite'))
print(eng_only('Instachat 😜'))
print(eng_only('爱奇艺PPS -《欢乐颂2》电视剧热播'))
True True False
So now lets use our new function to remove all non-english apps from our datasets.
# Removing non-english apps from Google Play Store
android_english = []
for app in android_clean:
name = app[0]
if eng_only(name):
android_english.append(app)
#Removing non-english apps from App Store
ios_english = []
for app in ios:
name = app[1]
if eng_only(name):
ios_english.append(app)
print(explore_data(android_english, 0, 2, True))
print('\n')
print(explore_data(ios_english, 0, 2, True))
['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'] ['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'] Number of rows: 9614 Number of columns: 13 None ['284882215', 'Facebook', '389879808', 'USD', '0.0', '2974676', '212', '3.5', '3.5', '95.0', '4+', 'Social Networking', '37', '1', '29', '1'] ['389801252', 'Instagram', '113954816', 'USD', '0.0', '2161558', '1289', '4.5', '4.0', '10.23', '12+', 'Photo & Video', '37', '0', '29', '1'] Number of rows: 6183 Number of columns: 16 None
We are left with 9614 apps in Google Play Store and 6183 apps in App Store.
Since we are solely focused on apps that are free, we are going to isolate them in a separate list so that our analysis will begin.
# Getting free android apps
android_free = []
for app in android_english:
price = app[7]
if price == '0':
android_free.append(app)
# Getting free iOS apps
ios_free = []
for app in ios_english:
price = app[4]
if price == '0.0':
ios_free.append(app)
print(len(android_free))
print(len(ios_free))
8864 3222
So now we realized that we have 8864 free apps in Google Play Store and 3222 in App Store.
To minimize risks and overhead, our validation strategy for an app idea will have three steps:
Remember that our goal is to add app to both Google Play and App Store, we need to find profiles that are successful in both markets. For instance, a profile that works well for both markets might be a productivity app that makes use of gamification.
Let's begin the analysis by determining the most common genres for each market. For this, we'll build a frequency table for the 'prime_genre'
column of the App Store data set, and the 'Genres'
and 'Category'
columns of the Google Play data set.
We'll build two functions we can use to analyze the frequency tables:
def freq_table(dataset, index):
freq_dict = {}
total = 0
for row in dataset:
total += 1
column = row[index]
if column in freq_dict:
freq_dict[column] += 1
else:
freq_dict[column] = 1
freq_percentages = {}
for key in freq_dict:
percentage = (freq_dict[key] / total) * 100
freq_percentages[key] = percentage
return freq_percentages
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])
We start by examining the frequency table for the 'prime_genre'
column of the App Store data set.
display_table(ios_free, -5) # Prime_Genre
Games : 58.16263190564867 Entertainment : 7.883302296710118 Photo & Video : 4.9658597144630665 Education : 3.662321539416512 Social Networking : 3.2898820608317814 Shopping : 2.60707635009311 Utilities : 2.5139664804469275 Sports : 2.1415270018621975 Music : 2.0484171322160147 Health & Fitness : 2.0173805090006205 Productivity : 1.7380509000620732 Lifestyle : 1.5828677839851024 News : 1.3345747982619491 Travel : 1.2414649286157666 Finance : 1.1173184357541899 Weather : 0.8690254500310366 Food & Drink : 0.8069522036002483 Reference : 0.5586592178770949 Business : 0.5276225946617008 Book : 0.4345127250155183 Navigation : 0.186219739292365 Medical : 0.186219739292365 Catalogs : 0.12414649286157665
We can see that among the free English apps, more than a half (58.16%) are games. Entertainment apps are close to 8%, followed by photo and video apps, which are close to 5%. Only 3.66% of the apps are designed for education, followed by social networking apps which amount for 3.29% of the apps in our data set.
The general impression is that App Store (at least the part containing free English apps) is dominated by apps that are designed for fun (games, entertainment, photo and video, social networking, sports, music, etc.), while apps with practical purposes (education, shopping, utilities, productivity, lifestyle, etc.) are more rare. However, the fact that fun apps are the most numerous doesn't also imply that they also have the greatest number of users — the demand might not be the same as the offer.
Let's continue by examining the 'Category'
and 'Genres'
columns of the Google Play data set (two columns which seem to be related).
display_table(android_free, 1) # Category
FAMILY : 18.907942238267147 GAME : 9.724729241877256 TOOLS : 8.461191335740072 BUSINESS : 4.591606498194946 LIFESTYLE : 3.9034296028880866 PRODUCTIVITY : 3.892148014440433 FINANCE : 3.7003610108303246 MEDICAL : 3.531137184115524 SPORTS : 3.395758122743682 PERSONALIZATION : 3.3167870036101084 COMMUNICATION : 3.2378158844765346 HEALTH_AND_FITNESS : 3.0798736462093865 PHOTOGRAPHY : 2.944494584837545 NEWS_AND_MAGAZINES : 2.7978339350180503 SOCIAL : 2.6624548736462095 TRAVEL_AND_LOCAL : 2.33528880866426 SHOPPING : 2.2450361010830324 BOOKS_AND_REFERENCE : 2.1435018050541514 DATING : 1.861462093862816 VIDEO_PLAYERS : 1.7937725631768955 MAPS_AND_NAVIGATION : 1.3989169675090252 FOOD_AND_DRINK : 1.2409747292418771 EDUCATION : 1.1620036101083033 ENTERTAINMENT : 0.9589350180505415 LIBRARIES_AND_DEMO : 0.9363718411552346 AUTO_AND_VEHICLES : 0.9250902527075812 HOUSE_AND_HOME : 0.8235559566787004 WEATHER : 0.8009927797833934 EVENTS : 0.7107400722021661 PARENTING : 0.6543321299638989 ART_AND_DESIGN : 0.6430505415162455 COMICS : 0.6204873646209386 BEAUTY : 0.5979241877256317
The landscape seems significantly different on Google Play: there are not that many apps designed for fun, and it seems that a good number of apps are designed for practical purposes (family, tools, business, lifestyle, productivity, etc.).
However, if we investigate this further, we can see that the family category (which accounts for almost 19% of the apps) means mostly games for kids.
Even so, practical apps seem to have a better representation on Google Play compared to App Store. This picture is also confirmed by the frequency table we see for the Genres column:
display_table(android_free, 9) # Genres
Tools : 8.449909747292418 Entertainment : 6.069494584837545 Education : 5.347472924187725 Business : 4.591606498194946 Productivity : 3.892148014440433 Lifestyle : 3.892148014440433 Finance : 3.7003610108303246 Medical : 3.531137184115524 Sports : 3.463447653429603 Personalization : 3.3167870036101084 Communication : 3.2378158844765346 Action : 3.1024368231046933 Health & Fitness : 3.0798736462093865 Photography : 2.944494584837545 News & Magazines : 2.7978339350180503 Social : 2.6624548736462095 Travel & Local : 2.3240072202166067 Shopping : 2.2450361010830324 Books & Reference : 2.1435018050541514 Simulation : 2.0419675090252705 Dating : 1.861462093862816 Arcade : 1.8501805054151623 Video Players & Editors : 1.7712093862815883 Casual : 1.7599277978339352 Maps & Navigation : 1.3989169675090252 Food & Drink : 1.2409747292418771 Puzzle : 1.128158844765343 Racing : 0.9927797833935018 Role Playing : 0.9363718411552346 Libraries & Demo : 0.9363718411552346 Auto & Vehicles : 0.9250902527075812 Strategy : 0.9138086642599278 House & Home : 0.8235559566787004 Weather : 0.8009927797833934 Events : 0.7107400722021661 Adventure : 0.6768953068592057 Comics : 0.6092057761732852 Beauty : 0.5979241877256317 Art & Design : 0.5979241877256317 Parenting : 0.4963898916967509 Card : 0.45126353790613716 Casino : 0.42870036101083037 Trivia : 0.41741877256317694 Educational;Education : 0.39485559566787 Board : 0.3835740072202166 Educational : 0.3722924187725632 Education;Education : 0.33844765342960287 Word : 0.2594765342960289 Casual;Pretend Play : 0.236913357400722 Music : 0.2030685920577617 Racing;Action & Adventure : 0.16922382671480143 Puzzle;Brain Games : 0.16922382671480143 Entertainment;Music & Video : 0.16922382671480143 Casual;Brain Games : 0.13537906137184114 Casual;Action & Adventure : 0.13537906137184114 Arcade;Action & Adventure : 0.12409747292418773 Action;Action & Adventure : 0.10153429602888085 Educational;Pretend Play : 0.09025270758122744 Simulation;Action & Adventure : 0.078971119133574 Parenting;Education : 0.078971119133574 Entertainment;Brain Games : 0.078971119133574 Board;Brain Games : 0.078971119133574 Parenting;Music & Video : 0.06768953068592057 Educational;Brain Games : 0.06768953068592057 Casual;Creativity : 0.06768953068592057 Art & Design;Creativity : 0.06768953068592057 Education;Pretend Play : 0.056407942238267145 Role Playing;Pretend Play : 0.04512635379061372 Education;Creativity : 0.04512635379061372 Role Playing;Action & Adventure : 0.033844765342960284 Puzzle;Action & Adventure : 0.033844765342960284 Entertainment;Creativity : 0.033844765342960284 Entertainment;Action & Adventure : 0.033844765342960284 Educational;Creativity : 0.033844765342960284 Educational;Action & Adventure : 0.033844765342960284 Education;Music & Video : 0.033844765342960284 Education;Brain Games : 0.033844765342960284 Education;Action & Adventure : 0.033844765342960284 Adventure;Action & Adventure : 0.033844765342960284 Video Players & Editors;Music & Video : 0.02256317689530686 Sports;Action & Adventure : 0.02256317689530686 Simulation;Pretend Play : 0.02256317689530686 Puzzle;Creativity : 0.02256317689530686 Music;Music & Video : 0.02256317689530686 Entertainment;Pretend Play : 0.02256317689530686 Casual;Education : 0.02256317689530686 Board;Action & Adventure : 0.02256317689530686 Video Players & Editors;Creativity : 0.01128158844765343 Trivia;Education : 0.01128158844765343 Travel & Local;Action & Adventure : 0.01128158844765343 Tools;Education : 0.01128158844765343 Strategy;Education : 0.01128158844765343 Strategy;Creativity : 0.01128158844765343 Strategy;Action & Adventure : 0.01128158844765343 Simulation;Education : 0.01128158844765343 Role Playing;Brain Games : 0.01128158844765343 Racing;Pretend Play : 0.01128158844765343 Puzzle;Education : 0.01128158844765343 Parenting;Brain Games : 0.01128158844765343 Music & Audio;Music & Video : 0.01128158844765343 Lifestyle;Pretend Play : 0.01128158844765343 Lifestyle;Education : 0.01128158844765343 Health & Fitness;Education : 0.01128158844765343 Health & Fitness;Action & Adventure : 0.01128158844765343 Entertainment;Education : 0.01128158844765343 Communication;Creativity : 0.01128158844765343 Comics;Creativity : 0.01128158844765343 Casual;Music & Video : 0.01128158844765343 Card;Action & Adventure : 0.01128158844765343 Books & Reference;Education : 0.01128158844765343 Art & Design;Pretend Play : 0.01128158844765343 Art & Design;Action & Adventure : 0.01128158844765343 Arcade;Pretend Play : 0.01128158844765343 Adventure;Education : 0.01128158844765343
The difference between the 'Genres'
and the 'Category'
columns is not crystal clear, but one thing we can notice is that the 'Genres'
column is much more granular (it has more categories). We're only looking for the bigger picture at the moment, so we'll only work with the 'Category'
column moving forward.
Up to this point, we found that the App Store is dominated by apps designed for fun, while Google Play shows a more balanced landscape of both practical and for-fun apps. Now we'd like to get an idea about the kind of apps that have most users.
One way to find out what genres are the most popular (have the most users) is to calculate the average number of installs for each app genre. For the Google Play data set, we can find this information in the Installs column, but for the App Store data set this information is missing. As a workaround, we'll take the total number of user ratings as a proxy, which we can find in the rating_count_tot app.
Below, we calculate the average number of user ratings per app genre on the App Store:
prime_column = freq_table(ios_free, -5)
for genre in prime_column:
total = 0
len_genre = 0
for row in ios_free:
genre_app = row[-5]
if genre_app == genre:
user_rating = float(row[5])
total += user_rating
len_genre += 1
avg_user_rating = total/len_genre
print(genre, ':', avg_user_rating)
Social Networking : 71548.34905660378 Photo & Video : 28441.54375 Games : 22788.6696905016 Music : 57326.530303030304 Reference : 74942.11111111111 Health & Fitness : 23298.015384615384 Weather : 52279.892857142855 Utilities : 18684.456790123455 Travel : 28243.8 Shopping : 26919.690476190477 News : 21248.023255813954 Navigation : 86090.33333333333 Lifestyle : 16485.764705882353 Entertainment : 14029.830708661417 Food & Drink : 33333.92307692308 Sports : 23008.898550724636 Book : 39758.5 Finance : 31467.944444444445 Education : 7003.983050847458 Productivity : 21028.410714285714 Business : 7491.117647058823 Catalogs : 4004.0 Medical : 612.0
On average, navigation apps have the highest number of user reviews, but this figure is heavily influenced by Waze and Google Maps, which have close to half a million user reviews together:
for app in ios_free:
if app[-5] == 'Navigation':
print(app[1], ':', app[5]) # Print the name and user rating
Waze - GPS Navigation, Maps & Real-time Traffic : 345046 Google Maps - Navigation & Transit : 154911 Geocaching® : 12811 CoPilot GPS – Car Navigation & Offline Maps : 3582 ImmobilienScout24: Real Estate Search in Germany : 187 Railway Route Search : 5
The same pattern applies to social networking apps, where the average number is heavily influenced by a few giants like Facebook, Pinterest, Skype, etc. Same applies to music apps, where a few big players like Pandora, Spotify, and Shazam heavily influence the average number.
Our aim is to find popular genres, but navigation, social networking or music apps might seem more popular than they really are. The average number of ratings seem to be skewed by very few apps which have hundreds of thousands of user ratings, while the other apps may struggle to get past the 10,000 threshold. We could get a better picture by removing these extremely popular apps for each genre and then rework the averages, but we'll leave this level of detail for later.
Reference apps have 74,942 user ratings on average, but it's actually the Bible and Dictionary.com which skew up the average rating:
for app in ios_free:
if app[-5] == 'Reference':
print(app[1], ':', app[5]) # Print the name and user rating
Bible : 985920 Dictionary.com Dictionary & Thesaurus : 200047 Dictionary.com Dictionary & Thesaurus for iPad : 54175 Google Translate : 26786 Muslim Pro: Ramadan 2017 Prayer Times, Azan, Quran : 18418 New Furniture Mods - Pocket Wiki & Game Tools for Minecraft PC Edition : 17588 Merriam-Webster Dictionary : 16849 Night Sky : 12122 City Maps for Minecraft PE - The Best Maps for Minecraft Pocket Edition (MCPE) : 8535 LUCKY BLOCK MOD ™ for Minecraft PC Edition - The Best Pocket Wiki & Mods Installer Tools : 4693 GUNS MODS for Minecraft PC Edition - Mods Tools : 1497 Guides for Pokémon GO - Pokemon GO News and Cheats : 826 WWDC : 762 Horror Maps for Minecraft PE - Download The Scariest Maps for Minecraft Pocket Edition (MCPE) Free : 718 VPN Express : 14 Real Bike Traffic Rider Virtual Reality Glasses : 8 教えて!goo : 0 Jishokun-Japanese English Dictionary & Translator : 0
However, this niche seems to show some potential. One thing we could do is take another popular book and turn it into an app where we could add different features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes about the book, etc. On top of that, we could also embed a dictionary within the app, so users don't need to exit our app to look up words in an external app.
This idea seems to fit well with the fact that the App Store is dominated by for-fun apps. This suggests the market might be a bit saturated with for-fun apps, which means a practical app might have more of a chance to stand out among the huge number of apps on the App Store.
Now let's analyze the Google Play market a bit.
For the Google Play market, we actually have data about the number of installs, so we should be able to get a clearer picture about genre popularity. However, the install numbers don't seem precise enough — we can see that most values are open-ended (100+, 1,000+, 5,000+, etc.):
display_table(android_free, 5) # the Installs columns
1,000,000+ : 15.726534296028879 100,000+ : 11.552346570397113 10,000,000+ : 10.548285198555957 10,000+ : 10.198555956678701 1,000+ : 8.393501805054152 100+ : 6.915613718411552 5,000,000+ : 6.825361010830325 500,000+ : 5.561823104693141 50,000+ : 4.7721119133574 5,000+ : 4.512635379061372 10+ : 3.5424187725631766 500+ : 3.2490974729241873 50,000,000+ : 2.3014440433213 100,000,000+ : 2.1322202166064983 50+ : 1.917870036101083 5+ : 0.78971119133574 1+ : 0.5076714801444043 500,000,000+ : 0.2707581227436823 1,000,000,000+ : 0.22563176895306858 0+ : 0.04512635379061372 0 : 0.01128158844765343
One problem with this data is that is not precise. For instance, we don't know whether an app with 100,000+ installs has 100,000 installs, 200,000, or 350,000. However, we don't need very precise data for our purposes — we only want to get an idea which app genres attract the most users, and we don't need perfect precision with respect to the number of users.
We're going to leave the numbers as they are, which means that we'll consider that an app with 100,000+ installs has 100,000 installs, and an app with 1,000,000+ installs has 1,000,000 installs, and so on.
To perform computations, however, we'll need to convert each install number to float — this means that we need to remove the commas and the plus characters, otherwise the conversion will fail and raise an error. We'll do this directly in the loop below, where we also compute the average number of installs for each genre (category).
category_column = freq_table(android_free, 1)
for category in category_column:
total = 0
len_category = 0
for row in android_free:
category_app = row[1]
if category_app == category:
n_installs = row[5]
n_installs = n_installs.replace('+', '')
n_installs = n_installs.replace(',', '')
total += float(n_installs)
len_category += 1
avg_n_installs = total/len_category
print(category, ':', avg_n_installs)
ART_AND_DESIGN : 1986335.0877192982 AUTO_AND_VEHICLES : 647317.8170731707 BEAUTY : 513151.88679245283 BOOKS_AND_REFERENCE : 8767811.894736841 BUSINESS : 1712290.1474201474 COMICS : 817657.2727272727 COMMUNICATION : 38456119.167247385 DATING : 854028.8303030303 EDUCATION : 1833495.145631068 ENTERTAINMENT : 11640705.88235294 EVENTS : 253542.22222222222 FINANCE : 1387692.475609756 FOOD_AND_DRINK : 1924897.7363636363 HEALTH_AND_FITNESS : 4188821.9853479853 HOUSE_AND_HOME : 1331540.5616438356 LIBRARIES_AND_DEMO : 638503.734939759 LIFESTYLE : 1437816.2687861272 GAME : 15588015.603248259 FAMILY : 3695641.8198090694 MEDICAL : 120550.61980830671 SOCIAL : 23253652.127118643 SHOPPING : 7036877.311557789 PHOTOGRAPHY : 17840110.40229885 SPORTS : 3638640.1428571427 TRAVEL_AND_LOCAL : 13984077.710144928 TOOLS : 10801391.298666667 PERSONALIZATION : 5201482.6122448975 PRODUCTIVITY : 16787331.344927534 PARENTING : 542603.6206896552 WEATHER : 5074486.197183099 VIDEO_PLAYERS : 24727872.452830188 NEWS_AND_MAGAZINES : 9549178.467741935 MAPS_AND_NAVIGATION : 4056941.7741935486
On average, communication apps have the most installs: 38,456,119. This number is heavily skewed up by a few apps that have over one billion installs (WhatsApp, Facebook Messenger, Skype, Google Chrome, Gmail, and Hangouts), and a few others with over 100 and 500 million installs:
for app in android_free:
if app[1] == 'COMMUNICATION' and (app[5] == '1,000,000,000+'
or app[5] == '500,000,000+'
or app[5] == '100,000,000+'):
print(app[0], ':', app[5])
WhatsApp Messenger : 1,000,000,000+ imo beta free calls and text : 100,000,000+ Android Messages : 100,000,000+ Google Duo - High Quality Video Calls : 500,000,000+ Messenger – Text and Video Chat for Free : 1,000,000,000+ imo free video calls and chat : 500,000,000+ Skype - free IM & video calls : 1,000,000,000+ Who : 100,000,000+ GO SMS Pro - Messenger, Free Themes, Emoji : 100,000,000+ LINE: Free Calls & Messages : 500,000,000+ Google Chrome: Fast & Secure : 1,000,000,000+ Firefox Browser fast & private : 100,000,000+ UC Browser - Fast Download Private & Secure : 500,000,000+ Gmail : 1,000,000,000+ Hangouts : 1,000,000,000+ Messenger Lite: Free Calls & Messages : 100,000,000+ Kik : 100,000,000+ KakaoTalk: Free Calls & Text : 100,000,000+ Opera Mini - fast web browser : 100,000,000+ Opera Browser: Fast and Secure : 100,000,000+ Telegram : 100,000,000+ Truecaller: Caller ID, SMS spam blocking & Dialer : 100,000,000+ UC Browser Mini -Tiny Fast Private & Secure : 100,000,000+ Viber Messenger : 500,000,000+ WeChat : 100,000,000+ Yahoo Mail – Stay Organized : 100,000,000+ BBM - Free Calls & Messages : 100,000,000+
Again, the main concern is that these app genres might seem more popular than they really are. Moreover, these niches seem to be dominated by a few giants who are hard to compete against.
The game genre seems pretty popular, but previously we found out this part of the market seems a bit saturated, so we'd like to come up with a different app recommendation if possible.
The books and reference genre looks fairly popular as well, with an average number of installs of 8,767,811. It's interesting to explore this in more depth, since we found this genre has some potential to work well on the App Store, and our aim is to recommend an app genre that shows potential for being profitable on both the App Store and Google Play.
Let's take a look at some of the apps from this genre and their number of installs:
for app in android_free:
if app[1] == 'BOOKS_AND_REFERENCE':
print(app[0], ':', app[5])
E-Book Read - Read Book for free : 50,000+ Download free book with green book : 100,000+ Wikipedia : 10,000,000+ Cool Reader : 10,000,000+ Free Panda Radio Music : 100,000+ Book store : 1,000,000+ FBReader: Favorite Book Reader : 10,000,000+ English Grammar Complete Handbook : 500,000+ Free Books - Spirit Fanfiction and Stories : 1,000,000+ Google Play Books : 1,000,000,000+ AlReader -any text book reader : 5,000,000+ Offline English Dictionary : 100,000+ Offline: English to Tagalog Dictionary : 500,000+ FamilySearch Tree : 1,000,000+ Cloud of Books : 1,000,000+ Recipes of Prophetic Medicine for free : 500,000+ ReadEra – free ebook reader : 1,000,000+ Anonymous caller detection : 10,000+ Ebook Reader : 5,000,000+ Litnet - E-books : 100,000+ Read books online : 5,000,000+ English to Urdu Dictionary : 500,000+ eBoox: book reader fb2 epub zip : 1,000,000+ English Persian Dictionary : 500,000+ Flybook : 500,000+ All Maths Formulas : 1,000,000+ Ancestry : 5,000,000+ HTC Help : 10,000,000+ English translation from Bengali : 100,000+ Pdf Book Download - Read Pdf Book : 100,000+ Free Book Reader : 100,000+ eBoox new: Reader for fb2 epub zip books : 50,000+ Only 30 days in English, the guideline is guaranteed : 500,000+ Moon+ Reader : 10,000,000+ SH-02J Owner's Manual (Android 8.0) : 50,000+ English-Myanmar Dictionary : 1,000,000+ Golden Dictionary (EN-AR) : 1,000,000+ All Language Translator Free : 1,000,000+ Azpen eReader : 500,000+ URBANO V 02 instruction manual : 100,000+ Bible : 100,000,000+ C Programs and Reference : 50,000+ C Offline Tutorial : 1,000+ C Programs Handbook : 50,000+ Amazon Kindle : 100,000,000+ Aab e Hayat Full Novel : 100,000+ Aldiko Book Reader : 10,000,000+ Google I/O 2018 : 500,000+ R Language Reference Guide : 10,000+ Learn R Programming Full : 5,000+ R Programing Offline Tutorial : 1,000+ Guide for R Programming : 5+ Learn R Programming : 10+ R Quick Reference Big Data : 1,000+ V Made : 100,000+ Wattpad 📖 Free Books : 100,000,000+ Dictionary - WordWeb : 5,000,000+ Guide (for X-MEN) : 100,000+ AC Air condition Troubleshoot,Repair,Maintenance : 5,000+ AE Bulletins : 1,000+ Ae Allah na Dai (Rasa) : 10,000+ 50000 Free eBooks & Free AudioBooks : 5,000,000+ Ag PhD Field Guide : 10,000+ Ag PhD Deficiencies : 10,000+ Ag PhD Planting Population Calculator : 1,000+ Ag PhD Soybean Diseases : 1,000+ Fertilizer Removal By Crop : 50,000+ A-J Media Vault : 50+ Al-Quran (Free) : 10,000,000+ Al Quran (Tafsir & by Word) : 500,000+ Al Quran Indonesia : 10,000,000+ Al'Quran Bahasa Indonesia : 10,000,000+ Al Quran Al karim : 1,000,000+ Al-Muhaffiz : 50,000+ Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+ Al-Quran 30 Juz free copies : 500,000+ Koran Read &MP3 30 Juz Offline : 1,000,000+ Hafizi Quran 15 lines per page : 1,000,000+ Quran for Android : 10,000,000+ Surah Al-Waqiah : 100,000+ Hisnul Al Muslim - Hisn Invocations & Adhkaar : 100,000+ Satellite AR : 1,000,000+ Audiobooks from Audible : 100,000,000+ Kinot & Eichah for Tisha B'Av : 10,000+ AW Tozer Devotionals - Daily : 5,000+ Tozer Devotional -Series 1 : 1,000+ The Pursuit of God : 1,000+ AY Sing : 5,000+ Ay Hasnain k Nana Milad Naat : 10,000+ Ay Mohabbat Teri Khatir Novel : 10,000+ Arizona Statutes, ARS (AZ Law) : 1,000+ Oxford A-Z of English Usage : 1,000,000+ BD Fishpedia : 1,000+ BD All Sim Offer : 10,000+ Youboox - Livres, BD et magazines : 500,000+ B&H Kids AR : 10,000+ B y H Niños ES : 5,000+ Dictionary.com: Find Definitions for English Words : 10,000,000+ English Dictionary - Offline : 10,000,000+ Bible KJV : 5,000,000+ Borneo Bible, BM Bible : 10,000+ MOD Black for BM : 100+ BM Box : 1,000+ Anime Mod for BM : 100+ NOOK: Read eBooks & Magazines : 10,000,000+ NOOK Audiobooks : 500,000+ NOOK App for NOOK Devices : 500,000+ Browsery by Barnes & Noble : 5,000+ bp e-store : 1,000+ Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+ BR Ambedkar Biography & Quotes : 10,000+ BU Alsace : 100+ Catholic La Bu Zo Kam : 500+ Khrifa Hla Bu (Solfa) : 10+ Kristian Hla Bu : 10,000+ SA HLA BU : 1,000+ Learn SAP BW : 500+ Learn SAP BW on HANA : 500+ CA Laws 2018 (California Laws and Codes) : 5,000+ Bootable Methods(USB-CD-DVD) : 10,000+ cloudLibrary : 100,000+ SDA Collegiate Quarterly : 500+ Sabbath School : 100,000+ Cypress College Library : 100+ Stats Royale for Clash Royale : 1,000,000+ GATE 21 years CS Papers(2011-2018 Solved) : 50+ Learn CT Scan Of Head : 5,000+ Easy Cv maker 2018 : 10,000+ How to Write CV : 100,000+ CW Nuclear : 1,000+ CY Spray nozzle : 10+ BibleRead En Cy Zh Yue : 5+ CZ-Help : 5+ Modlitební knížka CZ : 500+ Guide for DB Xenoverse : 10,000+ Guide for DB Xenoverse 2 : 10,000+ Guide for IMS DB : 10+ DC HSEMA : 5,000+ DC Public Library : 1,000+ Painting Lulu DC Super Friends : 1,000+ Dictionary : 10,000,000+ Fix Error Google Playstore : 1,000+ D. H. Lawrence Poems FREE : 1,000+ Bilingual Dictionary Audio App : 5,000+ DM Screen : 10,000+ wikiHow: how to do anything : 1,000,000+ Dr. Doug's Tips : 1,000+ Bible du Semeur-BDS (French) : 50,000+ La citadelle du musulman : 50,000+ DV 2019 Entry Guide : 10,000+ DV 2019 - EDV Photo & Form : 50,000+ DV 2018 Winners Guide : 1,000+ EB Annual Meetings : 1,000+ EC - AP & Telangana : 5,000+ TN Patta Citta & EC : 10,000+ AP Stamps and Registration : 10,000+ CompactiMa EC pH Calibration : 100+ EGW Writings 2 : 100,000+ EGW Writings : 1,000,000+ Bible with EGW Comments : 100,000+ My Little Pony AR Guide : 1,000,000+ SDA Sabbath School Quarterly : 500,000+ Duaa Ek Ibaadat : 5,000+ Spanish English Translator : 10,000,000+ Dictionary - Merriam-Webster : 10,000,000+ JW Library : 10,000,000+ Oxford Dictionary of English : Free : 10,000,000+ English Hindi Dictionary : 10,000,000+ English to Hindi Dictionary : 5,000,000+ EP Research Service : 1,000+ Hymnes et Louanges : 100,000+ EU Charter : 1,000+ EU Data Protection : 1,000+ EU IP Codes : 100+ EW PDF : 5+ BakaReader EX : 100,000+ EZ Quran : 50,000+ FA Part 1 & 2 Past Papers Solved Free – Offline : 5,000+ La Fe de Jesus : 1,000+ La Fe de Jesús : 500+ Le Fe de Jesus : 500+ Florida - Pocket Brainbook : 1,000+ Florida Statutes (FL Code) : 1,000+ English To Shona Dictionary : 10,000+ Greek Bible FP (Audio) : 1,000+ Golden Dictionary (FR-AR) : 500,000+ Fanfic-FR : 5,000+ Bulgarian French Dictionary Fr : 10,000+ Chemin (fr) : 1,000+ The SCP Foundation DB fr nn5n : 1,000+
Even though the 'books_and_reference'
contains granular data (books, dictioanries and softwares for reading), but there seems to be some few apps that skewed the average. Let's find out.
for app in android_free:
if app[1] == 'BOOKS_AND_REFERENCE' and (app[5] == '1,000,000,000+'
or app[5] == '500,000,000+'
or app[5] == '100,000,000+'):
print(app[0], ':', app[5])
Google Play Books : 1,000,000,000+ Bible : 100,000,000+ Amazon Kindle : 100,000,000+ Wattpad 📖 Free Books : 100,000,000+ Audiobooks from Audible : 100,000,000+
There seems to be a few popular apps in this category, so the market shows potential.
Let's get some idea about the apps that are in between 1,000,000 and 100,000,000 downloads.
for app in android_free:
if app[1] == 'BOOKS_AND_REFERENCE' and (app[5] == '1,000,000+'
or app[5] == '5,000,000+'
or app[5] == '10,000,000+'
or app[5] == '10,000,000+'):
print(app[0], ':', app[5])
Wikipedia : 10,000,000+ Cool Reader : 10,000,000+ Book store : 1,000,000+ FBReader: Favorite Book Reader : 10,000,000+ Free Books - Spirit Fanfiction and Stories : 1,000,000+ AlReader -any text book reader : 5,000,000+ FamilySearch Tree : 1,000,000+ Cloud of Books : 1,000,000+ ReadEra – free ebook reader : 1,000,000+ Ebook Reader : 5,000,000+ Read books online : 5,000,000+ eBoox: book reader fb2 epub zip : 1,000,000+ All Maths Formulas : 1,000,000+ Ancestry : 5,000,000+ HTC Help : 10,000,000+ Moon+ Reader : 10,000,000+ English-Myanmar Dictionary : 1,000,000+ Golden Dictionary (EN-AR) : 1,000,000+ All Language Translator Free : 1,000,000+ Aldiko Book Reader : 10,000,000+ Dictionary - WordWeb : 5,000,000+ 50000 Free eBooks & Free AudioBooks : 5,000,000+ Al-Quran (Free) : 10,000,000+ Al Quran Indonesia : 10,000,000+ Al'Quran Bahasa Indonesia : 10,000,000+ Al Quran Al karim : 1,000,000+ Al Quran : EAlim - Translations & MP3 Offline : 5,000,000+ Koran Read &MP3 30 Juz Offline : 1,000,000+ Hafizi Quran 15 lines per page : 1,000,000+ Quran for Android : 10,000,000+ Satellite AR : 1,000,000+ Oxford A-Z of English Usage : 1,000,000+ Dictionary.com: Find Definitions for English Words : 10,000,000+ English Dictionary - Offline : 10,000,000+ Bible KJV : 5,000,000+ NOOK: Read eBooks & Magazines : 10,000,000+ Brilliant Quotes: Life, Love, Family & Motivation : 1,000,000+ Stats Royale for Clash Royale : 1,000,000+ Dictionary : 10,000,000+ wikiHow: how to do anything : 1,000,000+ EGW Writings : 1,000,000+ My Little Pony AR Guide : 1,000,000+ Spanish English Translator : 10,000,000+ Dictionary - Merriam-Webster : 10,000,000+ JW Library : 10,000,000+ Oxford Dictionary of English : Free : 10,000,000+ English Hindi Dictionary : 10,000,000+ English to Hindi Dictionary : 5,000,000+
This niche seems to be dominated by software for processing and reading ebooks, as well as various collections of libraries and dictionaries, so it's probably not a good idea to build similar apps since there'll be some significant competition.
We also notice there are quite a few apps built around the book Quran, which suggests that building an app around a popular book can be profitable. It seems that taking a popular book (perhaps a more recent book) and turning it into an app could be profitable for both the Google Play and the App Store markets.
However, it looks like the market is already full of libraries, so we need to add some special features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes on the book, a forum where people can discuss the book, etc.
In this project, we analyzed data about the App Store and Google Play mobile apps with the goal of recommending an app profile that can be profitable for both markets.
We concluded that taking a popular book (perhaps a more recent book) and turning it into an app could be profitable for both the Google Play and the App Store markets. The markets are already full of libraries, so we need to add some special features besides the raw version of the book. This might include daily quotes from the book, an audio version of the book, quizzes on the book, a forum where people can discuss the book, etc.