App list

Get a list of applications in the Steam store, either a complete list or the top games by concurrent players, all-time players, or top releases.

get_app_list()

get_games_by_ccu(
  language = "english",
  elanguage = NULL,
  country_code = "US",
  steam_realm = 1L,
  include = NULL,
  apply_user_filters = FALSE
)

get_most_played_games()

get_top_releases()

get_apps_in_genre(genre, language = "english", country_code = "US")

get_apps_in_category(category, language = "english", country_code = "US")

Value

get_app_list

A dataframe containing the appID and name.

get_games_by_ccu

A dataframe containing the appID, the rank by CCU and the total number and all-time record of concurrent players.

get_most_played_game

A dataframe containing the appID, the rank by total all-time players and players last week as well as the all-time record of concurrent players.

get_top_releases

A dataframe with three rows containing the top releases of the last three months. Each row contains the start of the month, the url path for the top releases and a vector top release appIDs. The URL path can be appended to the following URL:

https://store.steampowered.com/charts/topnewreleases/

See also

steamspy for a similar approach by the SteamSpy API

Examples

get_app_list()
#> # A tibble: 225,267 × 2
#>    appid name                     
#>    <int> <chr>                    
#>  1     5 Dedicated Server         
#>  2     7 Steam Client             
#>  3     8 winui2                   
#>  4    10 Counter-Strike           
#>  5    20 Team Fortress Classic    
#>  6    30 Day of Defeat            
#>  7    40 Deathmatch Classic       
#>  8    50 Half-Life: Opposing Force
#>  9    60 Ricochet                 
#> 10    70 Half-Life                
#> # ℹ 225,257 more rows

# get most played games
get_games_by_ccu()
#> # A tibble: 100 × 4
#>     rank   appid concurrent_in_game peak_in_game
#>    <int>   <int>              <int>        <int>
#>  1     1     730             585699      1527145
#>  2     2 2767030             374868       441152
#>  3     3 2694490             350770       464713
#>  4     4     570             280866       594495
#>  5     5 1938090              99866       116690
#>  6     6 2923300              99526       105848
#>  7     7  578080              92149       770160
#>  8     8  252490              83276       133112
#>  9     9  271590              69321       169678
#> 10    10 2507950              65776        91698
#> # ℹ 90 more rows

# get most popular games of all time
get_most_played_games()
#> # A tibble: 100 × 4
#>     rank   appid last_week_rank peak_in_game
#>    <int>   <int>          <int>        <int>
#>  1     1     730              1      1460550
#>  2     2 2767030             -1       460883
#>  3     3     570              2       600334
#>  4     4  578080              3       747601
#>  5     5  431960              4       121241
#>  6     6 2694490             -1       480368
#>  7     7 1203220              5       293356
#>  8     8  271590              7       178332
#>  9     9 1938090              6       122668
#> 10    10 1172470              8       144501
#> # ℹ 90 more rows

# get the best releases
get_top_releases()
#> # A tibble: 3 × 4
#>   name                           start_of_month      url_path           item_ids
#>   <chr>                          <dttm>              <chr>              <list>  
#> 1 Top Releases of October 2024   2024-10-01 07:00:00 top_october_2024   <int>   
#> 2 Top Releases of September 2024 2024-09-01 07:00:00 top_september_2024 <int>   
#> 3 Top Releases of August 2024    2024-08-01 07:00:00 top_august_2024    <int>