tests/testthat/test_ga4.R
In MarkEdmondson1234/googleAnalyticsR_public: Google Analytics API into R
source("setup.R")
test_that("Vanilla test data fetch", {
skip_on_cran()
skip_on_travis()
options(googleAuthR.verbose = 2)
t11 <- google_analytics(ga_id,
date_range = c("2015-07-30","2015-10-01"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
})
test_that("With custom date ranges", {
skip_on_cran()
skip_on_travis()
t11 <- google_analytics(ga_id,
date_range = c("5DaysAgo","yesterday"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
t12 <- google_analytics(ga_id,
date_range = c("15DaysAgo","today"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
})
test_that("v3 Multi-channel funnels", {
skip_on_cran()
skip_on_travis()
v3 <- google_analytics_3(ga_id,
start = "2015-07-30", end = "2015-10-01",
dimensions=c('sourcePath'),
metrics = c('totalConversions'),
type = "mcf")
expect_s3_class(v3, "data.frame")
})
test_that("Cohorts work", {
skip_on_cran()
skip_on_travis()
## first make a cohort group
cohort4 <- make_cohort_group(list("Jan2016" = c("2016-01-01", "2016-01-31"),
"Feb2016" = c("2016-02-01","2016-02-28")))
## then call cohort report. No date_range and must include metrics and dimensions
## from the cohort list
cohort_example <- google_analytics(ga_id,
dimensions=c('cohort'),
cohorts = cohort4,
metrics = c('cohortTotalUsers'))
expect_s3_class(cohort_example, "data.frame")
})
test_that("Cohorts work with segments", {
skip_on_cran()
skip_on_travis()
## first make a cohort group
cohort4 <- make_cohort_group(list("Jan2016" = c("2016-01-01", "2016-01-31"),
"Feb2016" = c("2016-02-01","2016-02-28")))
## make two segment elements
se <- segment_element("sessions",
operator = "GREATER_THAN",
type = "METRIC",
comparisonValue = 1,
scope = "USER")
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
## choose between segment_vector_simple or segment_vector_sequence
## Elements can be combined into clauses, which can then be combined into OR filter clauses
sv_simple <- segment_vector_simple(list(list(se)))
sv_simple2 <- segment_vector_simple(list(list(se2)))
## Each segment vector can then be combined into a logical AND
seg_defined <- segment_define(list(sv_simple, sv_simple2))
## Each segement defintion can apply to users, sessions or both.
## You can pass a list of several segments
segment4 <- segment_ga4("simple", user_segment = seg_defined)
## then call cohort report. No date_range and must include metrics and dimensions
## from the cohort list
cohort_example <- google_analytics(ga_id,
dimensions=c('cohort'),
cohorts = cohort4,
segments = segment4,
metrics = c('cohortTotalUsers'))
expect_s3_class(cohort_example, "data.frame")
})
test_that("Pivots work", {
skip_on_cran()
skip_on_travis()
## filter pivot results to
pivot_dim_filter1 <- dim_filter("source",
"REGEXP",
"organic|social|email|cpc")
pivot_dim_clause <- filter_clause_ga4(list(pivot_dim_filter1))
pivme <- pivot_ga4("source",
metrics = c("sessions"),
maxGroupCount = 4,
dim_filter_clause = pivot_dim_clause)
pivtest1 <- google_analytics(ga_id,
c("2016-01-30","2016-10-01"),
dimensions=c('source'),
metrics = c('sessions'),
pivots = list(pivme))
expect_s3_class(pivtest1, "data.frame")
})
test_that("Fetch segment list", {
skip_on_cran()
skip_on_travis()
## get list of segments
my_segments <- ga_segment_list()
expect_s3_class(my_segments, "data.frame")
})
test_that("Segment v3 syntax work", {
skip_on_cran()
skip_on_travis()
## choose the v3 segment
segment_for_call <- "gaid::-4"
## make the v3 segment object in the v4 segment object:
seg_obj <- segment_ga4("PaidTraffic", segment_id = segment_for_call)
## make the segment call
segmented_ga1 <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium'),
segments = seg_obj,
metrics = c('sessions','bounces')
)
expect_s3_class(segmented_ga1, "data.frame")
## or pass the segment v3 defintion in directly:
segment_def_for_call <-
"sessions::condition::ga:medium=~^(cpc|ppc|cpa|cpm|cpv|cpp)$"
## make the v3 segment object in the v4 segment object:
seg_obj <- segment_ga4("PaidTraffic", segment_id = segment_def_for_call)
## make the segment call
segmented_ga1 <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium','segment'),
segments = seg_obj,
metrics = c('sessions','bounces')
)
expect_s3_class(segmented_ga1, "data.frame")
})
test_that("Segment v4 syntax works - simple", {
skip_on_cran()
skip_on_travis()
## make two segment elements
se <- segment_element("sessions",
operator = "GREATER_THAN",
type = "METRIC",
comparisonValue = 1,
scope = "USER")
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
## choose between segment_vector_simple or segment_vector_sequence
## Elements can be combined into clauses, which can then be combined into OR filter clauses
sv_simple <- segment_vector_simple(list(list(se)))
sv_simple2 <- segment_vector_simple(list(list(se2)))
## Each segment vector can then be combined into a logical AND
seg_defined <- segment_define(list(sv_simple, sv_simple2))
## Each segment definition can apply to users, sessions or both.
## You can pass a list of several segments
segment4 <- segment_ga4("simple", user_segment = seg_defined)
## Add the segments to the segments param
segment_example <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium','segment'),
segments = segment4,
metrics = c('sessions','bounces'))
expect_s3_class(segment_example, "data.frame")
})
test_that("Segment v4 Syntax - step sequence", {
skip_on_cran()
skip_on_travis()
## Sequence segment
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
se3 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
not = TRUE,
expressions = "organic")
## step sequence
## users who arrived via organic then via referral
sv_sequence <- segment_vector_sequence(list(list(se2),
list(se3)))
seq_defined2 <- segment_define(list(sv_sequence))
segment4_seq <- segment_ga4("sequence", user_segment = seq_defined2)
## Add the segments to the segments param
segment_seq_example <- google_analytics(ga_id,
c("2016-01-01","2016-03-01"),
dimensions=c('source','segment'),
segments = segment4_seq,
metrics = c('sessions','bounces'))
expect_s3_class(segment_seq_example, "data.frame")
})
# test_that("Can upload a data.frame ", {
# skip_on_cran()
# upload_me <- data.frame(medium = "shinyapps",
# source = "referral",
# adCost = 1,
# date = "20160801")
#
# rr <- ga_custom_upload_file(47480439, "UA-47480439-2", "_jDsJHSFSU-uw038Bh8fUg", upload_me)
# expect_equal(rr$kind, "analytics#upload")
#
# new_rr <- ga_custom_upload(upload_object = rr)
# expect_equal(rr$kind, "analytics#upload")
# })
# context("BigQuery")
#
# test_that("Can query from BigQuery using parser", {
# skip_on_cran()
#
# bq_result <- google_analytics_bq("mark-edmondson-gde",
# "98288890",
# start = "2015-08-10", end = "2016-03-01",
# metrics = c("sessions","users"),
# dimensions = c("date","medium"))
#
# expect_s3_class(bq_result, "data.frame")
#
# })
#
# test_that("Can query from BigQuery directly",{
# skip_on_cran()
#
# q <- "SELECT fullVisitorId, visitId, date, hits.hour as hour, hits.minute as minute FROM (TABLE_DATE_RANGE([98288890.ga_sessions_], TIMESTAMP('2016-08-10'), TIMESTAMP('2016-09-01'))) group by fullVisitorId, visitId, date, hour, minute LIMIT 10000"
#
# bq_result <- google_analytics_bq("mark-edmondson-gde",
# "98288890",
# query = q)
#
# expect_s3_class(bq_result, "data.frame")
#
#
# })
MarkEdmondson1234/googleAnalyticsR_public documentation built on Dec. 10, 2023, 2:43 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
source("setup.R")
test_that("Vanilla test data fetch", {
skip_on_cran()
skip_on_travis()
options(googleAuthR.verbose = 2)
t11 <- google_analytics(ga_id,
date_range = c("2015-07-30","2015-10-01"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
})
test_that("With custom date ranges", {
skip_on_cran()
skip_on_travis()
t11 <- google_analytics(ga_id,
date_range = c("5DaysAgo","yesterday"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
t12 <- google_analytics(ga_id,
date_range = c("15DaysAgo","today"),
dimensions=c('medium'),
metrics = c('sessions'),
order = order_type("sessions"))
expect_s3_class(t11, "data.frame")
})
test_that("v3 Multi-channel funnels", {
skip_on_cran()
skip_on_travis()
v3 <- google_analytics_3(ga_id,
start = "2015-07-30", end = "2015-10-01",
dimensions=c('sourcePath'),
metrics = c('totalConversions'),
type = "mcf")
expect_s3_class(v3, "data.frame")
})
test_that("Cohorts work", {
skip_on_cran()
skip_on_travis()
## first make a cohort group
cohort4 <- make_cohort_group(list("Jan2016" = c("2016-01-01", "2016-01-31"),
"Feb2016" = c("2016-02-01","2016-02-28")))
## then call cohort report. No date_range and must include metrics and dimensions
## from the cohort list
cohort_example <- google_analytics(ga_id,
dimensions=c('cohort'),
cohorts = cohort4,
metrics = c('cohortTotalUsers'))
expect_s3_class(cohort_example, "data.frame")
})
test_that("Cohorts work with segments", {
skip_on_cran()
skip_on_travis()
## first make a cohort group
cohort4 <- make_cohort_group(list("Jan2016" = c("2016-01-01", "2016-01-31"),
"Feb2016" = c("2016-02-01","2016-02-28")))
## make two segment elements
se <- segment_element("sessions",
operator = "GREATER_THAN",
type = "METRIC",
comparisonValue = 1,
scope = "USER")
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
## choose between segment_vector_simple or segment_vector_sequence
## Elements can be combined into clauses, which can then be combined into OR filter clauses
sv_simple <- segment_vector_simple(list(list(se)))
sv_simple2 <- segment_vector_simple(list(list(se2)))
## Each segment vector can then be combined into a logical AND
seg_defined <- segment_define(list(sv_simple, sv_simple2))
## Each segement defintion can apply to users, sessions or both.
## You can pass a list of several segments
segment4 <- segment_ga4("simple", user_segment = seg_defined)
## then call cohort report. No date_range and must include metrics and dimensions
## from the cohort list
cohort_example <- google_analytics(ga_id,
dimensions=c('cohort'),
cohorts = cohort4,
segments = segment4,
metrics = c('cohortTotalUsers'))
expect_s3_class(cohort_example, "data.frame")
})
test_that("Pivots work", {
skip_on_cran()
skip_on_travis()
## filter pivot results to
pivot_dim_filter1 <- dim_filter("source",
"REGEXP",
"organic|social|email|cpc")
pivot_dim_clause <- filter_clause_ga4(list(pivot_dim_filter1))
pivme <- pivot_ga4("source",
metrics = c("sessions"),
maxGroupCount = 4,
dim_filter_clause = pivot_dim_clause)
pivtest1 <- google_analytics(ga_id,
c("2016-01-30","2016-10-01"),
dimensions=c('source'),
metrics = c('sessions'),
pivots = list(pivme))
expect_s3_class(pivtest1, "data.frame")
})
test_that("Fetch segment list", {
skip_on_cran()
skip_on_travis()
## get list of segments
my_segments <- ga_segment_list()
expect_s3_class(my_segments, "data.frame")
})
test_that("Segment v3 syntax work", {
skip_on_cran()
skip_on_travis()
## choose the v3 segment
segment_for_call <- "gaid::-4"
## make the v3 segment object in the v4 segment object:
seg_obj <- segment_ga4("PaidTraffic", segment_id = segment_for_call)
## make the segment call
segmented_ga1 <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium'),
segments = seg_obj,
metrics = c('sessions','bounces')
)
expect_s3_class(segmented_ga1, "data.frame")
## or pass the segment v3 defintion in directly:
segment_def_for_call <-
"sessions::condition::ga:medium=~^(cpc|ppc|cpa|cpm|cpv|cpp)$"
## make the v3 segment object in the v4 segment object:
seg_obj <- segment_ga4("PaidTraffic", segment_id = segment_def_for_call)
## make the segment call
segmented_ga1 <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium','segment'),
segments = seg_obj,
metrics = c('sessions','bounces')
)
expect_s3_class(segmented_ga1, "data.frame")
})
test_that("Segment v4 syntax works - simple", {
skip_on_cran()
skip_on_travis()
## make two segment elements
se <- segment_element("sessions",
operator = "GREATER_THAN",
type = "METRIC",
comparisonValue = 1,
scope = "USER")
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
## choose between segment_vector_simple or segment_vector_sequence
## Elements can be combined into clauses, which can then be combined into OR filter clauses
sv_simple <- segment_vector_simple(list(list(se)))
sv_simple2 <- segment_vector_simple(list(list(se2)))
## Each segment vector can then be combined into a logical AND
seg_defined <- segment_define(list(sv_simple, sv_simple2))
## Each segment definition can apply to users, sessions or both.
## You can pass a list of several segments
segment4 <- segment_ga4("simple", user_segment = seg_defined)
## Add the segments to the segments param
segment_example <- google_analytics(ga_id,
c("2015-07-30","2015-10-01"),
dimensions=c('source','medium','segment'),
segments = segment4,
metrics = c('sessions','bounces'))
expect_s3_class(segment_example, "data.frame")
})
test_that("Segment v4 Syntax - step sequence", {
skip_on_cran()
skip_on_travis()
## Sequence segment
se2 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
expressions = "organic")
se3 <- segment_element("medium",
operator = "EXACT",
type = "DIMENSION",
not = TRUE,
expressions = "organic")
## step sequence
## users who arrived via organic then via referral
sv_sequence <- segment_vector_sequence(list(list(se2),
list(se3)))
seq_defined2 <- segment_define(list(sv_sequence))
segment4_seq <- segment_ga4("sequence", user_segment = seq_defined2)
## Add the segments to the segments param
segment_seq_example <- google_analytics(ga_id,
c("2016-01-01","2016-03-01"),
dimensions=c('source','segment'),
segments = segment4_seq,
metrics = c('sessions','bounces'))
expect_s3_class(segment_seq_example, "data.frame")
})
# test_that("Can upload a data.frame ", {
# skip_on_cran()
# upload_me <- data.frame(medium = "shinyapps",
# source = "referral",
# adCost = 1,
# date = "20160801")
#
# rr <- ga_custom_upload_file(47480439, "UA-47480439-2", "_jDsJHSFSU-uw038Bh8fUg", upload_me)
# expect_equal(rr$kind, "analytics#upload")
#
# new_rr <- ga_custom_upload(upload_object = rr)
# expect_equal(rr$kind, "analytics#upload")
# })
# context("BigQuery")
#
# test_that("Can query from BigQuery using parser", {
# skip_on_cran()
#
# bq_result <- google_analytics_bq("mark-edmondson-gde",
# "98288890",
# start = "2015-08-10", end = "2016-03-01",
# metrics = c("sessions","users"),
# dimensions = c("date","medium"))
#
# expect_s3_class(bq_result, "data.frame")
#
# })
#
# test_that("Can query from BigQuery directly",{
# skip_on_cran()
#
# q <- "SELECT fullVisitorId, visitId, date, hits.hour as hour, hits.minute as minute FROM (TABLE_DATE_RANGE([98288890.ga_sessions_], TIMESTAMP('2016-08-10'), TIMESTAMP('2016-09-01'))) group by fullVisitorId, visitId, date, hour, minute LIMIT 10000"
#
# bq_result <- google_analytics_bq("mark-edmondson-gde",
# "98288890",
# query = q)
#
# expect_s3_class(bq_result, "data.frame")
#
#
# })
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.