View source: R/freeform_report.R
Get a report analogous to a Freeform Table visualization in Analysis Workspace. The function uses the arguments to construct and execute a JSON-based query to the Adobe Analytics API and then returns the results as a data frame.
aw_freeform_table( company_id = Sys.getenv("AW_COMPANY_ID"), rsid = Sys.getenv("AW_REPORTSUITE_ID"), date_range = c(Sys.Date() - 30, Sys.Date() - 1), dimensions = c("page", "lasttouchchannel", "mobiledevicetype"), metrics = c("visits", "visitors"), top = c(5), page = 0, filterType = "breakdown", segmentId = NA, metricSort = "desc", include_unspecified = TRUE, search = NA, prettynames = FALSE, debug = FALSE, check_components = TRUE )
Company ID. If an environment variable called
Adobe report suite ID (RSID). If an environment variable called
A length-2 vector with a start date and an end date.
A character vector of dimensions. There is currently a limit of 20 dimension
breakdowns. Each dimension value that gets broken down by another dimension requires an additional API
call, so the more dimensions that are included, the longer the function will take to return results.
This is how the Adobe Analytics API works. Use
A character vector of metrics. Use
The number of values to be pulled for each dimension. The default is 5 and the "top" is based on
Used in combination with
This is a placeholder argument for use as additional functionality is added to the package.
Currently, it defaults to
A single segment ID or a vector of multiple segment IDs to apply to the overall report.
Pre-sorts the table by metrics. Values are either
Whether or not to include Unspecified values in the results. This is the equivalent
of the Include Unspecified (None) checkbox in freeform tables in Analysis Workspace. This defaults to
Criteria to filter the results by one or more dimensions. Searches are case-insenstive. Refer to the Details for more information on constructing values for this argument.
A logical that determines whether the column names in the results use the API field name
(e.g., "mobiledevicetype", "pageviews") or the "pretty name" for the field (e.g., "Mobile Device Type",
"Page Views"). This applies to both dimensions and metrics. The default value is
Specifies whether to check the validity of metrics and
dimensions before running the query. This defaults to
This function is based on the Freeform Table visualization in Analysis Workspace. It is accessing the same API call type that is used to generate those visualizations.
Adobe Analytics only queries one dimension at a time, even though the results get returned in a single data frame (or table in the case of Analysis Workspace). The more dimensions are included in the report–the more breakdowns of the data–the more queries are required. As a result, the order of the dimensions can have a dramatic impact on the total query time, even if the resulting data is essentially identical.
One way to understand this is to consider how much dragging and dropping would be required to return the data in Analysis Workspace if you were not able to <Shift>-<click> to highlight multiple values before dragging a new dimension to break down existing values.
Consider a scenario where you are pulling metrics for the last 30 days (
daterangeday) for Mobile Device Type
mobiledevicetype), which has 7 unique values. Setting
dimensions = c("daterangeday", "mobiledevicetype")
would make one query to get the values of the 30 days included. The query would then run a separate query
for each of those 30 days to get the
mobiledevicetype results for each day. So, this would be 31 API calls.
If, instead, the function was called with the
dimension values reversed (
dimensions = c("mobiledevicetype", "daterangeday")), then
the first query would return the 7
mobiledevicetype values, and then would run an additional query for each of
those 7 mobile device type values to return the results for the 30 days within each device type. This would be only 7 API calls.
Strategically ordering dimensions–and then wrangling the resulting data set as needed–is one of the best ways to improve query performance.
Date handling has several special characteristics that are worth getting familiar with:
The API names for day, week, month, etc. are prepended with
daterange, so daily data uses
daterangeday, weekly data uses
daterangeweek, monthly data uses
When setting the argument for
top, if the first (or only)
dimension value is a
then, if this argument is not explicitly specified or if it uses only a single value (e.g.,
top = 10),
the function will still return all of the values that fall in that date range. For instance, if the
date_range was set for a 30-day period and the first
dimension value was
daterangeday, and no value
is specified for
top, rather than simply returning the first 5 dates in the range, all 30 days will be
returned. In the same scenario, if
top = 10 was set, then all 30 days would still be returned, and the
10 would simply be applied to the additional dimensions.
If you want to return all of the date/time values but then have specific control over the number of
values returned for each of the drilldown dimensions, then set
0 as the first value in the
argument and then specify different numbers for each breakdown (e.g.,
top = c(0, 3, 10) would return
all of the date/time values for the specified
date_range, the top 3 values for the second specified
dimension, and then the top 10 values for each of the next dimension's results).
If you are using a
daterange... value not as the first dimension, then simply using
0 at the
same level in the
top argument specification will return all of the values for that date/time value.
There are powerful filtering abilities within the function. However, to support that power requires a syntax that can feel a bit cumbersome for simple queries. Note: search filters are case-insensitive. This is Adobe Analytics API functionality and can not be specified otherwise in queries.
search argument takes a vector of search strings, with each value in the vector corresponding to
dimension value that is at the same position. These search strings support a range of operators,
The default for any search string is to use
CONTAINS. Consider a query where
dimensions = c("mobiledevicetype", "lasttouchchannel"):
search = "CONTAINS 'mobile'" will return results where
mobiledevicetype contains "mobile", so would return all rows for Mobile Phone.
This could be shortened to
search = "'mobile'" and would behave exactly the same, since
CONTAINS is the default operator
search = c("CONTAINS 'mobile'", "CONTAINS 'search'") will return results where
mobiledevicetype contains "mobile" and, within those results, results where
lasttouchchannel contains "search".
search = c("(CONTAINS 'mobile') OR (CONTAINS 'tablet')", "(MATCH 'paid search')") will return results where
mobiledevicetype contains "mobile" or "tablet" and, within those results, will only include results where
lasttouchchannel exactly matches "paid search" (but is case-insensitive, so would return "Paid Search" values).
A data frame with the specified dimensions and metrics.
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