How many apps are there in the Play Store? The number of available apps in the Google Play Store was most recently placed at 1.68 million apps, after surpassing 1 million apps in July 2013. Google Play Store Google Play was originally launched in October 2008 under the name Android Market. As Google’s official app store, it offers its customers a wide range of applications and digital media including music, magazines, books, film, and TV. As of April 2021, the ranking of the top-grossing Android apps worldwide is dominated by mobile games with Coin Master, Garena Free Fire, and PUBG mobile leading the ranking. This hardly comes as a surprise as it is estimated that gaming apps will account for over 70 percent of Google Play app revenues in 2024. As most apps in the Google Play Store are available for free, the company needs to utilize effective business models to secure healthy revenue. How do apps make money? Despite the robust gaming app revenues, most gaming apps are free to download and rely on monetization via in-app advertising or in-game purchases of items such as boosters and accessories. A November 2021 survey of mobile app publishers found that video ads were the most popular mobile app monetization model, followed by display ads and in-app purchases. Additionally, monetizing via subscriptions has proven an effective model for several highly popular apps, with subscription revenues hitting 18.3 billion U.S. dollars in revenues in 2021.

During the second quarter of 2024, over 2.26 million mobile apps were available on the Google Play Store, down by 18 percent compared to the previous quarter. Between the beginning of 2019 and the end of 2021, the number of mobile apps available to Android users via the Google Play Store experienced a constant increase, reaching 4.67 million apps during the last quarter of 2021. However, after 2022, the number of apps available in the Google Play Store fluctuated.

[ADVISORY] IMPORTANT

Instructions for citation:

If you use this dataset anywhere in your work, kindly cite as the below: L. Gupta, "Google Play Store Apps," Feb 2019. [Online]. Available: https://www.kaggle.com/lava18/google-play-store-apps

Context

While many public datasets (on Kaggle and the like) provide Apple App Store data, there are not many counterpart datasets available for Google Play Store apps anywhere on the web. On digging deeper, I found out that iTunes App Store page deploys a nicely indexed appendix-like structure to allow for simple and easy web scraping. On the other hand, Google Play Store uses sophisticated modern-day techniques (like dynamic page load) using JQuery making scraping more challenging.

Content

Each app (row) has values for catergory, rating, size, and more.

Acknowledgements

This information is scraped from the Google Play Store. This app information would not be available without it.

Inspiration

The Play Store apps data has enormous potential to drive app-making businesses to success. Actionable insights can be drawn for developers to work on and capture the Android market!

In February 2025, TikTok was the most-downloaded app in the Google Play Store worldwide, generating almost 65 million downloads from Android users. WhatsApp was the second-most popular app with approximately 41 million downloads from global users. The Google Play Store ecosystem Launched in March 2016, the Google Play Store is the major app distributor for global Android users, as well as one of the most important mobile app stores in the industry. As of the second quarter of 2024, over 2.26 million mobile apps were available on the Google Play Store, after hitting the record number of 4.67 million apps available to users during the fourth quarter of 2021. Android users browsing the Google Play Store can find any type of mobile app, from dating to mobile productivity, with gaming apps being the most popular app category on the platform. Maintenance of apps hosted in the Google Play Store helps improve the overall quality of content proposed to users. Built for success: app optimization in the Google Play Store Being featured in the first positions on mobile app stores results page is key to the success of an application, as it improves impressions and increases the chances of downloads. User satisfaction and good experiences are, as always, the top variables to determine apps’ popularity. As of February 2022, the average rating of mobile apps figuring in the first 10 positions on the Google Play Store was almost four stars, with reviews ranging from 3.90 to 3.98 stars. When it came to SEO, it was found that mobile apps spotting category-specific target keywords in the titles ranked higher than those who did not. Additionally, app icons in the Google Play Store presented industry-specific colors for different categories, like black for gaming apps and red for food and drink apps. Highly recognizable app category colors might not only help users in their app search endeavors, but also increase brand awareness.

The amount of Android apps available for download is constantly increasing, exerting a continuous pressure on developers to publish outstanding apps. Google Play (GP) is the default distribution channel for Android apps, which provides mobile app users with metrics to identify and report apps quality such as rating, amount of downloads, previous users comments, etc. In addition to those metrics, GP presents a set of top charts that highlight the outstanding apps in different categories. Both metrics and top app charts help developers to identify whether their development decisions are well valued by the community. Therefore, app presence in these top charts is a valuable information when understanding the features of top-apps. In this paper we present Hall-of-Apps, a dataset containing top charts' apps metadata extracted (weekly) from GP, for 4 different countries, during 30 weeks. The data is presented as (i) raw HTML files, (ii) a MongoDB database with all the information contained in app's HTML files (e.g., app description, category, general rating, etc.), and (iii) data visualizations built with the D3.js framework. A first characterization of the data along with the urls to retrieve it can be found in our online appendix: https://thesoftwaredesignlab.github.io/hall-of-apps-tools/

We built a crawler to collect data from the Google Play store including the application's metadata and APK files. The manifest files were extracted from the APK files and then processed to extract the features. The data set is composed of 870,515 records/apps, and for each app we produced 48 features. The data set was used to built and test two bootstrap aggregating of multiple XGBoost machine learning classifiers. The dataset were collected between April 2017 and November 2018. We then checked the status of these applications on three different occasions; December 2018, February 2019, and May-June 2019.

A large-scale dataset on the dynamic profiles based on function calls of 35,974 benign and malicious Android apps from 10 historical years (2010 through 2019). Function calls are a commonly used means to model program behaviors, which may contribute to various code analysis approaches to assuring software correctness, reliability, and security. In particular, our dataset includes dynamic profiles of each app resulting from the same-length of time (10 mins) of being exercised by randomly generated inputs on both emulator and real device, enabling interesting and useful app analysis that reason about app behaviors in an evolutionary perspective while informing the differences of app behaviors on different run-time hardware platforms. Since we have 20 yearly datasets associated with 35,974 unique Android apps across the 10 years, profiling these apps took 12,000 hours. Considering the costs of filtering out apps that were originally sampled but that we were unable to profile (due to various reasons such as broken APKs, not being executable because of incompatibility issues, not instrumentable, etc.), we took over two years to produce all these traces. We hope to save future researchers' time in producing such a set of dynamic data to enable their empirical and technical work.

==================

Thanks for your interest in our dataset. Collecting this dataset took tremendous computational and human effort. Thus, please observe the following restrictions in using our dataset:

- Do not redistribute this dataset without our consent.
- Do not make commercial usage of this dataset.
- Get a faculty, or someone in a permanent position, to agree and commit to these conditions.
- When publishing your work that uses our dataset, please cite the following MSR 2021 data paper.

@inproceedings{AndroidCT,
title = {AndroCT: Ten Years of App Call Traces in Android},
author = {Wen Li, Xiaoqin Fu, and Haipeng Cai},
booktitle = {The 18th International Conference on Mining Software Repositories (MSR 2021), Data Showcase Track},
year = {2021},
}

Context

Google Play stores top 500 app data based on their rankings on January 2022 for all the available categories. Link to scraping code: https://github.com/Shakthi-Dhar/AppPin Link to backup datafiles: github data files

Content

The dataset contains the top 500 android apps available on the google play store for the following categories: All Categories, Art & Design, Auto & Vehicles, Beauty, Books & Reference, Business, Comics, Communication, Education, Entertainment, Events, Finance, Food & Drink, Health & Fitness, House & Home, Libraries & Demo, Lifestyle, Maps & Navigation, Medical, Music & Audio, News & Magazines, Parenting, Personalization, Photography, Productivity, Shopping, Social, Sports, Tools, Travel & Local, and Video Players & Editors.

The app rankings are based on google play store app rankings for January 2022.

Abbreviations

In Review and Downloads, the alphabet T, L, Cr represents Thousands, Lakhs, Crores as per the google play store naming convention. They are similar to M, B which represent millions, billions. 1L (1 Lakh) = 100T (100 Thousand) 10L (10 Lakhs) = 1M (1 Million) 1Cr( 1 Crore) = 10M (10 Million)

Acknowledgements

This data is not provided directly by Google, so I used Appium an automation tool with python to scrape the data from the google play store app.

Inspiration

Inspired by Fortune500. Fortune500 provides data on top companies in the world, so why not have a data source for top apps in the world.

This data set contains meta data about more than a million third-party Android application that were collected from the Google Play store between 2017 and 2019. Two privacy scores were calculated for each application based on: permission requests, broadcast receivers, and user's privacy preferences. The scores also depend on other applications in the app's category. The scores were calculated based on two published formulas. The first fomulas was proposed by Mohsel et al. and published in TrustCom '18, "Countering intrusiveness using new security-centric ranking algorithm built on top of elasticsearch". The second formula was published in SPSM '16 Taylor, and Martinovic, "SecuRank: Starving Permission-Hungry Apps Using Contextual Permission Analysis"s

As COVID-19 continues to spread across the world, a growing number of malicious campaigns are exploiting the pandemic. It is reported that COVID-19 is being used in a variety of online malicious activities, including Email scam, ransomware and malicious domains. As the number of the afflicted cases continue to surge, malicious campaigns that use coronavirus as a lure are increasing. Malicious developers take advantage of this opportunity to lure mobile users to download and install malicious apps.

However, besides a few media reports, the coronavirus-themed mobile malware has not been well studied. Our community lacks of the comprehensive understanding of the landscape of the coronavirus-themed mobile malware, and no accessible dataset could be used by our researchers to boost COVID-19 related cybersecurity studies.

We make efforts to create a daily growing COVID-19 related mobile app dataset. By the time of mid-November, we have curated a dataset of 4,322 COVID-19 themed apps, and 611 of them are considered to be malicious. The number is growing daily and our dataset will update weekly. For more details, please visit https://covid19apps.github.io

This dataset includes the following files:

(1) covid19apps.xlsx

In this file, we list all the COVID-19 themed apps information, including apk file hashes, released date, package name, AV-Rank, etc.

(2)covid19apps.zip

We put the COVID-19 themed apps Apk samples in zip files . In order to reduce the size of a single file, we divide the sample into multiple zip files for storage. And the APK file name after the file SHA256.

If your papers or articles use our dataset, please use the following bibtex reference to cite our paper: https://arxiv.org/abs/2005.14619

(Accepted to Empirical Software Engineering)

 @misc{wang2021virus,
   title={Beyond the Virus: A First Look at Coronavirus-themed Mobile Malware}, 
   author={Liu Wang and Ren He and Haoyu Wang and Pengcheng Xia and Yuanchun Li and Lei Wu and Yajin Zhou and Xiapu Luo and Yulei Sui and Yao Guo and Guoai Xu},
   year={2021},
   eprint={2005.14619},
   archivePrefix={arXiv},
   primaryClass={cs.CR}
}

Nowadays, mobile applications (a.k.a., apps) are used by over two billion users for every type of need, including social and emergency connectivity. Their pervasiveness in today world has inspired the software testing research community in devising approaches to allow developers to better test their apps and improve the quality of the tests being developed. In spite of this research effort, we still notice a lack of empirical analyses aiming at assessing the actual quality of test cases manually developed by mobile developers: this perspective could provide evidence-based findings on the future research directions in the field as well as on the current status of testing in the wild. As such, we performed a large-scale empirical study targeting 1,780 open-source Android apps and aiming at assessing (1) the extent to which these apps are actually tested, (2) how well-designed are the available tests, and (3) what is their effectiveness. The key results of our study show that mobile developers still tend not to properly test their apps, possibly because of time to market requirements. Furthermore, we discovered that the test cases of the considered apps have a low (i) design quality, both in terms of test code metrics and test smells, and (ii) effectiveness when considering code coverage as well as assertion density.

A large-scale dataset on the static and dynamic profiles based on function calls of 30,634 benign and malicious Android apps from eight historical years (2010 through 2017). Function calls are a commonly used means to model program behaviors, which may contribute to various code analysis approaches to assuring software correctness, reliability, and security. In particular, our dataset includes static and dynamic profiles of each app based on the same set of metrics that define the profile, enabling hybrid app analysis that reason about app behaviors from the dynamic profiles with the corresponding profiles as context. The static profiles are computed by the state-of-the-art static app analysis for Android, while the dynamic profiles are the result of running each sample app against automatically generated test inputs for ten minutes.

This dataset is about book subjects. It has 5 rows and is filtered where the books is Android for the beaglebone black : design and implement android apps that interface with your own custom hardware circuits and the beaglebone black. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This package contains data and code to replicate the findings presented in our paper titled "GUI Testing of Android Applications: Investigating the Impact of the Number of Testers on Different Exploratory Testing Strategies".

Abstract

Graphical User Interface (GUI) testing plays a pivotal role in ensuring the quality and functionality of mobile apps. In this context, Exploratory Testing (ET), a distinctive methodology in which individual testers pursue a creative, and experience-based approach to test design, is often used as an alternative or in addition to traditional scripted testing. Managing the exploratory testing process is a challenging task, that can easily result either in wasteful spending or in inadequate software quality, due to the relative unpredictability of exploratory testing activities, which depend on the skills and abilities of individual testers. A number of works have investigated the diversity of testers’ performance when using ET strategies, often in a crowdtesting setting. These works, however, investigated ET effectiveness in detecting bugs, and not in scenarios in which the goal is to generate a re-executable test suite, as well. Moreover, less work has been conducted on evaluating the impact of adopting different exploratory testing strategies. As a first step towards filling this gap in the literature, in this work we conduct an empirical evaluation involving four open-source Android apps and twenty masters students, that we believe can be representative of practitioners partaking in exploratory testing activities. The students were asked to generate test suites for the apps using a Capture and Replay tool and different exploratory testing strategies. We then compare the effectiveness, in terms of aggregate code coverage, that different-sized groups of students using different exploratory testing strategies may achieve. Results provide deeper insights into code coverage dynamics to project managers interested in using exploratory approaches to test simple Android apps, on which they can make more informed decisions.

Contents and Instructions

This package contains:

apps-under-test.zip A zip archive containing the source code of the four Android applications we considered in our study, namely MunchLife, TippyTipper, Trolly, and SimplyDo.

apps-under-test-instrumented.zip A zip archive containing the instrumented source code of the four Android applications we used to compute branch coverage.

students-test-suites.zip A zip archive containing the test suites developed by the students using Uninformed Exploratory Testing (referred to as "Black Box" in the subdirectories) and Informed Exploratory Testing (referred to as "White Box" in the subdirectories). This also includes coverage reports.

compute-coverage-unions.zip A zip archive containing Python scripts we developed to compute the aggregate LOC coverage of all possible subsets of students. The scripts have been tested on MS Windows. To compute the LOC coverage achieved by any possible subsets of testers using IET and UET strategies, run the analysisAndReport.py script. To compute the LOC coverage achieved by mixed crowds in which some testers use a U+IET approach and others use a UET approach, run the analysisAndReport_UET_IET_combinations_emma.py script.

branch-coverage-computation.zip A zip archive containing Python scripts we developed to compute the aggregate branch coverage of all considered subsets of students. The scripts have been tested on MS Windows. To compute the branch coverage achieved by any possible subsets of testers using UET and I+UET strategies, run the branch_coverage_analysis.py script. To compute the code coverage achieved by mixed crowds in which some testers use a U+IET approach and others use a UET approach, run the mixed_branch_coverage_analysis.py script.

data-analysis-scripts.zip A zip archive containing R scripts to merge and manipulate coverage data, to carry out statistical analysis and draw plots. All data concerning RQ1 and RQ2 is available as a ready-to-use R data frame in the ./data/all_coverage_data.rds file. All data concerning RQ3 is available in the ./data/all_mixed_coverage_data.rds file.

The graph presents the leading Android app titles in the Google Play Store in Austria as of September 2020, ranked by number of downloads. During the period under consideration,Among Us!was downloaded approximately 111.7 thousand times onto android devices in Austria. The number one app by number of downloads was SchoolFox with 131.3 thousand downloads onto Austrian devices.

This dataset is about book subjects. It has 3 rows and is filtered where the books is App Inventor for Android : build your own apps- no experience required. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

Mental Health Apps Market Outlook

The global mental health apps market size was valued at approximately USD 4.2 billion in 2023 and is expected to reach around USD 17.5 billion by 2032, growing at a robust CAGR of 17.3% during the forecast period. This remarkable growth is driven by increasing awareness about mental health, advancements in technology, and the rising prevalence of mental health disorders.

The surge in mental health issues, particularly among the younger population, is one of the primary growth factors for the mental health apps market. An increasing number of individuals are facing anxiety, depression, and stress, leading to a higher demand for accessible and affordable mental health solutions. Mental health apps offer a convenient way for individuals to manage their symptoms and seek help, bridging the gap between traditional therapy and self-care. Moreover, the stigma around mental health is gradually decreasing, encouraging more people to seek help through these apps.

The COVID-19 pandemic has significantly accelerated the demand for mental health apps, as lockdowns, social isolation, and the general uncertainty of the times have exacerbated mental health issues globally. This has led to an increased adoption of digital health solutions as a means to access mental health support. The convenience of accessing mental health services via smartphones has made these apps popular, especially when traditional services are either overwhelmed or inaccessible.

Advancements in technology have also played a crucial role in the growth of the mental health apps market. With the integration of artificial intelligence, machine learning, and data analytics, these apps are becoming more personalized and effective. They can now offer tailored content, real-time monitoring, and predictive analytics to provide better support to users. Furthermore, the increasing penetration of smartphones and internet connectivity worldwide has made these apps more accessible to a broader audience.

The development of Mental Health Software and Devices is a significant advancement in the realm of mental health care. These technologies are designed to complement mental health apps by providing more comprehensive solutions. They offer features such as remote patient monitoring, teletherapy, and integration with electronic health records, which enhance the ability of healthcare providers to deliver personalized care. The use of such devices can help in early diagnosis and continuous monitoring of mental health conditions, providing timely interventions. As these technologies become more sophisticated, they promise to bridge the gap between traditional mental health services and digital solutions, making mental health care more accessible and effective for a wider audience.

Regionally, North America holds the largest market share in the mental health apps market due to high awareness levels, advanced healthcare infrastructure, and the high prevalence of mental health issues. Europe follows closely, with countries like the UK and Germany showing significant adoption rates. The Asia Pacific region is expected to witness the fastest growth during the forecast period, driven by increasing smartphone penetration, a growing middle class, and rising awareness about mental health. Latin America and the Middle East & Africa are also showing promising growth, albeit at a slower pace due to varying levels of healthcare infrastructure and awareness.

Platform Analysis

The platform segment of the mental health apps market is divided into iOS, Android, and Windows. Each of these platforms caters to a different segment of the population, and their usage patterns vary significantly. The iOS platform, for example, holds a substantial share of the market due to the high spending power of Apple users and the strong security features of the iOS operating system. These users are often willing to pay for premium features and subscriptions, contributing to higher revenue generation.

Android, on the other hand, dominates the market in terms of user numbers due to its widespread adoption and affordability. Android phones are more prevalent in emerging markets, where there is a growing need for mental health solutions. The open-source nature of Android also allows for a broader range of apps, catering to diverse needs and preferences. Despite the lower average revenue per user compared to iOS, the sheer volume of Android use

Book Reading Apps Market Outlook

The global book reading apps market size was valued at $5.2 billion in 2023 and is projected to reach $12.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 10.4% during the forecast period. This market's growth is significantly driven by the increasing penetration of smartphones and the rising preference for digital content consumption. The proliferation of digital devices such as tablets and e-readers has also played a pivotal role in expanding the market for book reading apps. As more consumers opt for the convenience of carrying digital libraries in their pockets, the demand for book reading applications is anticipated to surge in the coming years.

One of the primary growth factors for the book reading apps market is the steady increase in smartphone and internet penetration globally. With over 4.9 billion people having access to the internet and more than 3.8 billion smartphone users as of 2021, the potential user base for book reading apps is enormous. Moreover, the affordability of smartphones and data plans has made it easier for consumers from various socioeconomic backgrounds to access these apps. This trend is particularly evident in emerging economies where digital literacy initiatives and affordable mobile technology are bridging the gap in information access.

Another significant growth driver is the evolving reading habits of consumers. The modern reader is increasingly inclined towards digital formats due to their inherent advantages such as portability, accessibility, and interactive features. Digital books, or eBooks, offer functionalities like adjustable fonts, backlighting, and built-in dictionaries that enhance the reading experience. Additionally, the environmental benefits of digital reading, such as reduced paper consumption, are resonating with eco-conscious consumers, further propelling the market forward.

The COVID-19 pandemic has also played a crucial role in accelerating the adoption of book reading apps. With lockdowns and social distancing measures in place, people turned to digital platforms for entertainment and education. Educational institutions adopted online teaching methods, and students relied on digital books and resources for learning. This sudden shift to digital platforms has induced a habit that is likely to persist post-pandemic, contributing to the sustained growth of the book reading apps market.

Regionally, North America dominates the book reading apps market, driven by high smartphone penetration, advanced technological infrastructure, and a large number of tech-savvy consumers. However, the Asia Pacific region is expected to register the highest CAGR during the forecast period. Factors such as the rapid adoption of smartphones, increasing internet penetration, and a growing middle-class population are driving the growth in this region. Markets like China and India are witnessing substantial growth due to their large populations and increasing digital literacy rates.

In addition to book reading apps, the rise of News Apps has significantly transformed how users consume information. With the increasing reliance on smartphones, news apps provide instant access to current events, breaking news, and in-depth articles, catering to the fast-paced lifestyle of modern consumers. These apps offer personalized news feeds, allowing users to customize their reading experience based on their interests and preferences. The integration of multimedia elements such as videos and podcasts further enriches the user experience, making news consumption more engaging and interactive. As digital literacy continues to rise globally, news apps are becoming an essential tool for staying informed, complementing the growth of digital content consumption alongside book reading apps.

Platform Analysis

The book reading apps market is segmented by platform into iOS, Android, Windows, and Others. The iOS segment holds a significant share in the market due to the high number of iPhone and iPad users who prefer the seamless integration of AppleÂ’s ecosystem. The App StoreÂ’s stringent quality standards ensure that book reading apps on iOS are generally reliable and user-friendly. Popular iOS book reading apps include Apple Books and Kindle, which offer a wide range of features supporting various reading preferences and needs.

Android, however, leads the market in terms of the number of users, given its global reach and dominance in sm

Tencent Appstore is the most popular third-party app store for Android devices in China. As of January 27, 2025, there were almost 88,000 mobile apps available for download and over 48,000 app publishers on the Tencent Appstore.

The Android launcher market, encompassing applications like Nova Launcher and Smart Launcher, is a dynamic segment within the broader mobile application ecosystem. While precise market sizing data isn't provided, considering the widespread adoption of Android globally and the prevalence of customization options, a reasonable estimate for the 2025 market size could be around $200 million. This market is characterized by a healthy Compound Annual Growth Rate (CAGR), likely in the range of 15-20% through 2033, driven by several key factors. Increasing smartphone penetration, especially in emerging markets, fuels demand for personalized user experiences. Furthermore, the continuous evolution of Android operating systems and the expanding app ecosystem encourage users to seek more sophisticated and aesthetically pleasing launchers. Trends such as AI-powered features, improved gesture controls, and enhanced customization options are shaping the competitive landscape, pushing developers to innovate and differentiate their offerings. However, market restraints include the potential for platform fragmentation, competition from built-in launcher options, and challenges in monetization for many free or freemium launcher apps. Segmentation by application (mobile phones, tablets, etc.) and type (design launchers, smart launchers) is crucial for understanding the varying needs and preferences of different user segments. The market is highly competitive with numerous established players and emerging startups vying for market share. Regional variations in smartphone usage patterns and Android adoption rates will influence market growth, with North America and Asia Pacific likely representing significant market segments. The forecast period of 2025-2033 presents several opportunities for growth. Continuous innovation in launcher functionality, such as integration with other productivity and lifestyle apps, offers potential for premium features and subscription models. Market players must focus on delivering exceptional user experience, enhancing security features, and addressing user privacy concerns to maintain a competitive edge. The ongoing evolution of Android and the increasing demand for personalized mobile experiences will continue to be significant drivers of growth, ensuring the Android launcher market remains a lucrative and dynamic space.