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videogameinsightsR

R package for the Video Game Insights API. Retrieve player counts, revenue, units sold, wishlists, reviews, and more for Steam games – all returned as tidy tibbles with snake_case column names.

Installation

devtools::install_github("econosopher/videogameinsightsR")

Quick Start

library(videogameinsightsR)

# Store your API token (once per session, or add to .Renviron)
Sys.setenv(VGI_AUTH_TOKEN = "your_token_here")

# Search and inspect a game
vgi_search_games("Valheim")
vgi_game_metadata(892970)

Core Workflow

The typical workflow is search -> inspect -> pull time series -> analyse. Every function returns a tibble so results pipe naturally.

library(dplyr)

# 1. Find a game
games <- vgi_search_games("Elden Ring")
app_id <- games$steam_app_id[1]

# 2. Pull metadata
meta <- vgi_game_metadata(app_id)
meta$name
#> "ELDEN RING"

# 3. Get daily time-series data
ccu   <- vgi_concurrent_players_by_date("2025-06-01", steam_app_ids = app_id)
dau   <- vgi_active_players_by_date("2025-06-01", steam_app_ids = app_id)
rev   <- vgi_revenue_by_date("2025-06-01", steam_app_ids = app_id)
units <- vgi_units_sold_by_date("2025-06-01", steam_app_ids = app_id)

# 4. Or grab everything at once with the historical data endpoint
hist <- vgi_historical_data(app_id)
names(hist)
#> "steam_app_id" "revenue" "units_sold" "concurrent_players"
#> "active_players" "reviews" "wishlists" "followers" "price_history"

Function Families

Game Discovery

Function	Description
`vgi_search_games()`	Search by title (uses local cache + API fallback)
`vgi_game_list()`	Full game catalogue
`vgi_top_games()`	Top games by various ranking metrics
`vgi_game_metadata()`	Detailed metadata for a single game

Time Series (by date)

All accept date and optional steam_app_ids to filter.

Function	Columns
`vgi_concurrent_players_by_date()`	`peak_concurrent`, `avg_concurrent`
`vgi_active_players_by_date()`	`dau`, `mau`, `dau_mau_ratio`
`vgi_revenue_by_date()`	`revenue`, `daily_revenue`
`vgi_units_sold_by_date()`	`units_sold`, `daily_units`
`vgi_reviews_by_date()`	`positive_reviews`, `negative_reviews`, `positive_ratio`
`vgi_followers_by_date()`	`follower_count`
`vgi_wishlists_by_date()`	`wishlist_count`

Comprehensive Historical Data

hist <- vgi_historical_data(892970)
hist$revenue        # tibble: date, revenue, daily_revenue
hist$active_players # tibble: date, dau, mau
hist$price_history  # tibble: date, price_initial, price_final

Insights (per-game summaries)

Function	Returns
`vgi_insights_ccu()`	CCU history
`vgi_insights_dau_mau()`	Active player history
`vgi_insights_revenue()`	Revenue time series
`vgi_insights_units()`	Units sold time series
`vgi_insights_playtime()`	Average/median playtime + ranges
`vgi_insights_player_regions()`	Player geographic distribution
`vgi_insights_price_history()`	Price change periods by currency

Convenience Functions

# Everything in one call
summary <- vgi_game_summary(
  steam_app_ids = c(892970, 1245620),
  start_date = "2025-01-01",
  end_date   = "2025-01-31"
)
summary$summary_table
summary$time_series$concurrent

# Year-over-year comparison
yoy <- vgi_game_summary_yoy(
  steam_app_ids = 892970,
  years = c(2024, 2025),
  start_month = "Jan",
  end_month = "Mar"
)
yoy$comparison_table

Publishers and Developers

vgi_publishers_overview()   # All publishers with key metrics
vgi_developers_overview()   # All developers with key metrics
vgi_publisher_list()        # Publisher names and IDs
vgi_developer_list()        # Developer names and IDs

Configuration

# Base URL (default: v4)
options(vgi.base_url = "https://vginsights.com/api/v4")

# Timeouts and retries
options(vgi.timeout = 30)
options(vgi.retry_max_tries = 4)

# Request caching (seconds, GET only)
options(vgi.request_cache_ttl = 3600)

# Rate limiting
options(vgi.auto_rate_limit = TRUE)
options(vgi.calls_per_batch = 10)
options(vgi.batch_delay = 1)

# Verbose logging
options(vgi.verbose = TRUE)

Important Notes

Steam App IDs required: Pass explicit IDs to time-series functions. Without them the API returns demo/aggregate data only.
DAU/MAU availability: DAU from 2024-03-18, MAU from 2024-03-23.
Column names: All output uses snake_case (e.g. steam_app_id, peak_concurrent, daily_revenue). This is a breaking change from v0.0.x.
Return types: All data-returning functions produce tibbles.

Development

devtools::load_all()
devtools::test()
devtools::check(cran = TRUE)

Tests use httptest2 fixtures under tests/testthat/vginsights.com/.

License

MIT

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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