googleAnalyticsR (version 1.2.0)

google_analytics_3: Get Google Analytics v3 data (formerly google_analytics())

Description

Legacy v3 API, for more modern API use google_analytics.

Usage

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")
)

Value

For one id a data.frame of data, with meta-data in attributes.

Arguments

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

Level of precision of the API requests

max_results

Default 100. If greater than 10,000 then will batch GA calls.

type

ga = Google Analytics v3; mcf = Multi-Channel Funels.

See Also

https://developers.google.com/analytics/devguides/reporting/core/v3/

Examples

if (FALSE) {

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")


}