Created
July 26, 2021 14:17
-
-
Save zldoty/ee9cb2c9fca81fa0398073897c500d62 to your computer and use it in GitHub Desktop.
R Code Snippet for Extracting All Probable Voice Query Information from Google Search Console
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
# Load packages # | |
library(searchConsoleR) | |
library(dplyr) | |
library(ggplot2) | |
library(writexl) | |
library(stringr) | |
# Authorize & choose Google profile # | |
scr_auth() | |
# Specify website --- Client Code or Line of Business Code Here # | |
client <- "CLCODE" | |
website <- "https://www.twosigma.com" | |
############ SPECIFYING THE MONTHS ############ | |
start1 <- "2020-04-01" | |
end1 <- "2020-04-30" | |
start2 <- "2020-05-01" | |
end2 <- "2020-05-31" | |
start3 <- "2020-06-01" | |
end3 <- "2020-06-30" | |
start4 <- "2020-07-01" | |
end4 <- "2020-07-31" | |
start5 <- "2020-08-01" | |
end5 <- "2020-08-31" | |
start6 <- "2020-09-01" | |
end6 <- "2020-09-30" | |
start7 <- "2020-10-01" | |
end7 <- "2020-10-31" | |
start8 <- "2020-11-01" | |
end8 <- "2020-11-30" | |
start9 <- "2020-12-01" | |
end9 <- "2020-12-31" | |
start10 <- "2021-01-01" | |
end10 <- "2021-01-31" | |
start12 <- "2021-02-01" | |
end12 <- "2021-02-28" | |
start13 <- "2021-03-01" | |
end13 <- "2021-03-31" | |
start14 <- "2021-04-01" | |
end14 <- "2021-04-30" | |
start15 <- "2021-05-01" | |
end15 <- "2021-05-31" | |
start16 <- "2021-06-01" | |
end16 <- "2021-06-30" | |
# Specify the voice cue variables for dataframe functionality # | |
who <- "who" # 1 | |
what <- "what" # 1 | |
when <- "when" # 1 | |
where <- "where" # 1 | |
why <- "why" # 1 | |
how <- "how" # 1 | |
does <- "does" # 1 | |
have <- "have" # 1 | |
has <- "has" # 1 | |
are <- "are" # 1 | |
which <- "which" # 1 | |
will <- "will" # 1 | |
was <- "was" # 1 | |
should <- "should" # 1 | |
would <- "would" # 1 | |
could <- "could" # 1 | |
near <- "near" # 1 | |
google <- "google" # 1 | |
alexa <- "alexa" # 1 | |
do <- "do" # 1 | |
is <- "is" # 1 | |
can <- "can" # 1 | |
# # | |
# # _____ | |
# # |\ /| | | 1 | |
# # | \ / | | | | |
# # | \/ | | | | |
# # | | | | | |
# # | | | | | |
# # | | | | | |
# # | | |_____| | |
# # | |
# # | |
# # # Start who 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
who_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~who"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(who_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(who,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
who_queries_merged_1 <- data.frame(clientName,date,primaryCue,who_queries) | |
# Testing df creation | |
# pivotData | |
# head(who_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(who_queries_merged, "who_queries_1.xlsx") | |
# # # END who 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start what 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
what_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~what"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(what_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(what,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
what_queries_merged_1 <- data.frame(clientName,date,primaryCue,what_queries) | |
# Testing df creation | |
# pivotData | |
# head(what_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(what_queries_merged, "what_queries_1.xlsx") | |
# # # END what 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start when 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
when_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~when"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(when_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(when,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
when_queries_merged_1 <- data.frame(clientName,date,primaryCue,when_queries) | |
# Testing df creation | |
# pivotData | |
# head(when_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(when_queries_merged, "when_queries_1.xlsx") | |
# # # END when 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start where 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
where_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~where"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(where_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(where,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
where_queries_merged_1 <- data.frame(clientName,date,primaryCue,where_queries) | |
# Testing df creation | |
# pivotData | |
# head(where_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(where_queries_merged, "where_queries_1.xlsx") | |
# # # END where 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start why 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
why_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~why"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(why_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(why,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
why_queries_merged_1 <- data.frame(clientName,date,primaryCue,why_queries) | |
# Testing df creation | |
# pivotData | |
# head(why_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(why_queries_merged, "why_queries_1.xlsx") | |
# # # END why 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start how 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
how_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~how"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(how_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(how,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
how_queries_merged_1 <- data.frame(clientName,date,primaryCue,how_queries) | |
# Testing df creation | |
# pivotData | |
# head(how_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(how_queries_merged, "how_queries_1.xlsx") | |
# # # END how 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start Does 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
does_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~does"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(does_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(does,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
does_queries_merged_1 <- data.frame(clientName,date,primaryCue,does_queries) | |
# Testing df creation | |
# pivotData | |
# head(does_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
# write_xlsx(does_queries_merged, "does_queries_1.xlsx") | |
# # # END DOES 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start Have 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
have_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~have"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(have_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(have,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
have_queries_merged_1 <- data.frame(clientName,date,primaryCue,have_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(have_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(have_queries_merged_1, "have_queries_1.xlsx") | |
# # # END HAVE 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start has 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
has_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~has"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(has_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(has,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
has_queries_merged_1 <- data.frame(clientName,date,primaryCue,has_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(has_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(has_queries_merged_1, "has_queries_1.xlsx") | |
# # # END has 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start Are 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
are_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~are"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(are_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(are,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
are_queries_merged_1 <- data.frame(clientName,date,primaryCue,are_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(are_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(are_queries_merged_1, "are_queries_1.xlsx") | |
# # # END ARE 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start Which 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
which_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~which"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(which_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(which,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
which_queries_merged_1 <- data.frame(clientName,date,primaryCue,which_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(which_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(which_queries_merged_1, "which_queries_1.xlsx") | |
# # # END WHICH 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start Will 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
will_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~will"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(will_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(will,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
will_queries_merged_1 <- data.frame(clientName,date,primaryCue,will_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(will_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(will_queries_merged_1, "will_queries_1.xlsx") | |
# # # END will 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start was 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
was_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~was"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(was_queries) | |
# Testing purposes - making sure rows vector was properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(was,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
was_queries_merged_1 <- data.frame(clientName,date,primaryCue,was_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(was_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(was_queries_merged_1, "was_queries_1.xlsx") | |
# # # END was 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start should 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
should_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~should"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(should_queries) | |
# Testing purposes - making sure rows vector should properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(should,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
should_queries_merged_1 <- data.frame(clientName,date,primaryCue,should_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(should_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(should_queries_merged_1, "should_queries_1.xlsx") | |
# # # END should 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start would 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
would_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~would"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(would_queries) | |
# Testing purposes - making sure rows vector would properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(would,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
would_queries_merged_1 <- data.frame(clientName,date,primaryCue,would_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(would_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(would_queries_merged_1, "would_queries_1.xlsx") | |
# # # END would 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start could 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
could_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~could"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(could_queries) | |
# Testing purposes - making sure rows vector could properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(could,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
could_queries_merged_1 <- data.frame(clientName,date,primaryCue,could_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(could_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(could_queries_merged_1, "could_queries_1.xlsx") | |
# # # END could 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start near 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
near_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~near"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(near_queries) | |
# Testing purposes - making sure rows vector near properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(near,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
near_queries_merged_1 <- data.frame(clientName,date,primaryCue,near_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(near_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(near_queries_merged_1, "near_queries_1.xlsx") | |
# # # END near 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start google 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
google_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~google"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(google_queries) | |
# Testing purposes - making sure rows vector google properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(google,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
google_queries_merged_1 <- data.frame(clientName,date,primaryCue,google_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(google_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(google_queries_merged_1, "google_queries_1.xlsx") | |
# # # END google 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start alexa 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
alexa_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~alexa"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(alexa_queries) | |
# Testing purposes - making sure rows vector alexa properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(alexa,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
alexa_queries_merged_1 <- data.frame(clientName,date,primaryCue,alexa_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(alexa_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(alexa_queries_merged_1, "alexa_queries_1.xlsx") | |
# # # END alexa 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start do 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
do_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~do"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(do_queries) | |
# Testing purposes - making sure rows vector do properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(do,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
do_queries_merged_1 <- data.frame(clientName,date,primaryCue,do_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(do_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(do_queries_merged_1, "do_queries_1.xlsx") | |
# # # END do 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start is 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
is_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~is"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(is_queries) | |
# Testing purposes - making sure rows vector is properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(is,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
is_queries_merged_1 <- data.frame(clientName,date,primaryCue,is_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(is_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(is_queries_merged_1, "is_queries_1.xlsx") | |
# # # END is 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
# # # Start can 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
############ REPLACE QUERY ############ | |
can_queries <- search_analytics( | |
siteURL = website, | |
startDate = start1, | |
endDate = end1, | |
dimensions = c("query", "page"), | |
##### REPLACE QUERY ##### | |
dimensionFilterExp = c("query~~can"), | |
searchType="web", | |
rowLimit = 1000000 | |
) | |
# Dynamically get the number of rows from the GSC export so the created vectors match number of rows | |
############ REPLACE QUERY ############ | |
rows <- nrow(can_queries) | |
# Testing purposes - making sure rows vector can properly formed | |
# rows | |
# Make a vector that populates the client code | |
clientName <- rep(client,rows) | |
# Testing vector creation | |
# clientName | |
# Make a vector that populates the start date for Month filtering, segmenting, pivoting | |
######## ######## | |
############ REPLACE DATE ############ | |
date <- rep(start1,rows) | |
# Testing vector creation | |
# date | |
############ REPLACE QUERY ############ | |
primaryCue <- rep(can,rows) | |
# primaryCue | |
# Make a data frame from the created vectors | |
############ REPLACE QUERY ############ | |
can_queries_merged_1 <- data.frame(clientName,date,primaryCue,can_queries) | |
# Testing df creation | |
# pivotData | |
############ REPLACE QUERY ############ | |
# head(can_queries_merged_1,5) | |
############### QA CHECKPOINT ###################### | |
# Write the data frame to an XLSX file | |
############ REPLACE QUERY ############ | |
# write_xlsx(can_queries_merged_1, "can_queries_1.xlsx") | |
# # # END can 1 | |
# # # | |
# # # | |
# # # | |
# # # | |
month_1_queries <- rbind(who_queries_merged_1,what_queries_merged_1,when_queries_merged_1,where_queries_merged_1,why_queries_merged_1,how_queries_merged_1,does_queries_merged_1,have_queries_merged_1,has_queries_merged_1,are_queries_merged_1,which_queries_merged_1,will_queries_merged_1,was_queries_merged_1,should_queries_merged_1,would_queries_merged_1,could_queries_merged_1,near_queries_merged_1,google_queries_merged_1,alexa_queries_merged_1, | |
do_queries_merged_1,is_queries_merged_1,can_queries_merged_1) | |
write_xlsx(month_1_queries, "month_1_queries.xlsx") | |
# Write the data frame to an XLSX file | |
# write_xlsx(does_queries, "does_queries.xlsx") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment