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移动应用商店(7200个应用程序),移动应用分析数据

移动应用商店(7200个应用程序),移动应用分析数据

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Business,Mobile and Wireless Classification

Mobile App Statistics (Apple iOS app store)The ever-changing mobile landscape is a challenging space to navigate. . The......

数据结构 ? 13.16M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Mobile App Statistics (Apple iOS app store)

    The ever-changing mobile landscape is a challenging space to navigate.  . The percentage of mobile over desktop is only increasing.   Android holds about 53.2% of the smartphone market, while iOS is 43%.   To get more people to download your app, you need to make sure they can easily find your app.  Mobile app analytics is a great way to understand the existing strategy to drive growth and retention of future user.

    With million of apps around nowadays,  the following data set  has become very key to getting top trending apps in iOS app store.  This data set contains more than 7000 Apple iOS mobile application details. The data was extracted from the iTunes Search API at the Apple Inc website.  R and  linux web scraping tools were used for this study.

    Interactive full Shiny app can be seen here(
    https://multiscal.shinyapps.io/appStore/)

    Data collection date (from API);
    July 2017

    Dimension of the data set;
    7197 rows and 16 columns

    Content:

    appleStore.csv

    1. "id" : App ID

    2. "track_name": App Name

    3. "size_bytes": Size (in Bytes)

    4. "currency": Currency Type

    5. "price": Price amount

    6. "ratingcounttot": User Rating counts (for all version)

    7. "ratingcountver": User Rating counts (for current version)

    8. "user_rating" : Average User Rating value (for all version)

    9. "userratingver": Average User Rating value (for current version)

    10. "ver" : Latest version code

    11. "cont_rating": Content Rating

    12. "prime_genre": Primary Genre

    13. "sup_devices.num": Number of supporting devices

    14. "ipadSc_urls.num": Number of screenshots showed for display

    15. "lang.num": Number of supported languages

    16. "vpp_lic": Vpp Device based Licensing Enabled

    appleStore_description.csv

    1. id : App ID

    2. track_name: Application name

    3. size_bytes: Memory size (in Bytes)

    4. app_desc: Application description

    Acknowledgements

    The data was extracted from the iTunes Search API at the Apple Inc website.  R and  linux web scraping tools were used for this study.

    Inspiration

    1. How does the App details contribute the user ratings?

    2. Try to compare app statistics for different groups?

    Reference: R package
    From github, with
    devtools::install_github("ramamet/applestoreR")

    Licence

    Copyright (c) 2018 Ramanathan Perumal



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