ga_data
Google Analytics Data for GA4 (App+Web)
Description
![[Experimental]](../help/figures/lifecycle-experimental.svg)
Fetches Google Analytics from the Data API for Google Analytics 4 (Previously App+Web)
Usage
ga_data( propertyId, metrics, date_range = NULL, dimensions = NULL, dim_filters = NULL, dimensionDelimiter = "/", met_filters = NULL, orderBys = NULL, limit = 100, page_size = 100000L, realtime = FALSE, raw_json = NULL )
Arguments
propertyId |
A GA4 property Id |
metrics |
The metrics to request - see ga_meta - set to NULL to only see dimensions |
date_range |
A vector with start and end dates in YYYY-MM-DD format - can send in up to four date ranges at once |
dimensions |
The dimensions to request - see ga_meta |
dim_filters |
Filter on the dimensions of the request - a filter object created by ga_data_filter |
dimensionDelimiter |
If combining dimensions in one column, the delimiter for the value field |
met_filters |
Filter on the metrics of the request - a filter object created by ga_data_filter |
orderBys |
How to order the response - an order object created by ga_data_order |
limit |
The number of rows to return - use -1 to return all rows |
page_size |
The size of API pages - default is 100000L rows |
realtime |
If TRUE then will call the real-time reports, that have a more limited set of dimensions/metrics - see valid real-time dimensions |
raw_json |
You can send in the raw JSON string for a Data API request which will skip all checks |
Details
This is the main function to call the Google Analytics 4 Data API.
Value
A data.frame tibble, including attributes metadata, metricAggregations and rowCount. Use ga_data_aggregations to extract the data.frames of metricAggregations
See Also
Other GA4 functions:
ga_data_filter(),
ga_data_order()
Examples
## Not run:
# send up to 4 date ranges
multi_date <- ga_data(
206670707,
metrics = c("activeUsers","sessions"),
dimensions = c("date","city","dayOfWeek"),
date_range = c("2020-03-31", "2020-04-27", "2020-04-30", "2020-05-27"),
dim_filters = ga_data_filter("city"=="Copenhagen"),
limit = 100
)
# metric and dimension expressions
# create your own named metrics
met_expression <- ga_data(
206670707,
metrics = c("activeUsers","sessions",sessionsPerUser = "sessions/activeUsers"),
dimensions = c("date","city","dayOfWeek"),
date_range = c("2020-03-31", "2020-04-27"),
limit = 100
)
# create your own aggregation dimensions
dim_expression <- ga_data(
206670707,
metrics = c("activeUsers","sessions"),
dimensions = c("date","city","dayOfWeek", cdow = "city/dayOfWeek"),
date_range = c("2020-03-31", "2020-04-27"),
limit = 100
)
# run a real-time report (no date dimension allowed)
realtime <- ga_data(
206670707,
metrics = "activeUsers",
dimensions = c("city","unifiedScreenName"),
limit = 100,
realtime = TRUE)
# extract meta data from the table
ga_data_aggregations(realtime)
# add ordering
a <- ga_data_order(-sessions)
b <- ga_data_order(-dayOfWeek, type = "NUMERIC")
ga_data(
206670707,
metrics = c("activeUsers","sessions"),
dimensions = c("date","city","dayOfWeek"),
date_range = c("2020-03-31", "2020-04-27"),
orderBys = c(a, b)
)
## End(Not run)