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July 26, 2021 14:17
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R Code Snippet for Extracting All Probable Voice Query Information from Google Search Console
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| # 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") |
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