Get Google Analytics v3 data (formerly google_analytics())
Legacy v3 API, for more modern API use google_analytics.
google_analytics_3( id, start, end, metrics = c("sessions", "bounceRate"), dimensions = NULL, sort = NULL, filters = NULL, segment = NULL, samplingLevel = c("DEFAULT", "FASTER", "HIGHER_PRECISION"), max_results = 100, type = c("ga", "mcf") )
id |
A character vector of View Ids to fetch from. |
start |
Start date in YYY-MM-DD format. |
end |
End date in YYY-MM-DD format. |
metrics |
A character vector of metrics. With or without ga: prefix. |
dimensions |
A character vector of dimensions. With or without ga: prefix. |
sort |
How to sort the results, in form 'ga:sessions,-ga:bounceRate' |
filters |
Filters for the result, in form 'ga:sessions>0;ga:pagePath=~blah' |
segment |
How to segment. |
samplingLevel |
Choose "WALK" to mitigate against sampling. |
max_results |
Default 100. If greater than 10,000 then will batch GA calls. |
type |
ga = Google Analytics v3; mcf = Multi-Channel Funels. |
For one id a data.frame of data, with meta-data in attributes.
https://developers.google.com/analytics/devguides/reporting/core/v3/
## Not run: library(googleAnalyticsR) ## Authenticate in Google OAuth2 ## this also sets options ga_auth() ## if you need to re-authenticate use ga_auth(new_user=TRUE) ## if you have your own Google Dev console project keys, ## then don't run ga_auth() as that will set to the defaults. ## instead put your options here, and run googleAuthR::gar_auth() ## get account info, including View Ids account_list <- ga_account_list() ga_id <- account_list$viewId[1] ## get a list of what metrics and dimensions you can use meta <- ga_meta() head(meta) ## pick the account_list$viewId you want to see data for. ## metrics and dimensions can have or have not "ga:" prefix gadata <- google_analytics_3(id = ga_id, start="2015-08-01", end="2015-08-02", metrics = c("sessions", "bounceRate"), dimensions = c("source", "medium")) ## if more than 10000 rows in results, auto batching ## example is setting lots of dimensions to try and create big sampled data batch_gadata <- google_analytics_3(id = ga_id, start="2014-08-01", end="2015-08-02", metrics = c("sessions", "bounceRate"), dimensions = c("source", "medium", "landingPagePath", "hour","minute"), max=99999999) ## mitigate sampling by setting samplingLevel="WALK" ## this will send lots and lots of calls to the Google API limits, beware walk_gadata <- google_analytics_3(id = ga_id, start="2014-08-01", end="2015-08-02", metrics = c("sessions", "bounceRate"), dimensions = c("source", "medium", "landingPagePath"), max=99999999, samplingLevel="WALK") ## multi-channel funnels set type="mcf" mcf_gadata <- google_analytics_3(id = ga_id, start="2015-08-01", end="2015-08-02", metrics = c("totalConversions"), dimensions = c("sourcePath"), type="mcf") ## reach meta-data via attr() attr(gadata, "profileInfo") attr(gadata, "dateRange") ## End(Not run)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.