loops - Google Analytics(分析)自然搜索循环问题

Question

循环的功能完全不同，我不确定是否是因为使用了Google Analytics（分析）软件包，因为代码之间的差异很小。

打印语句输出中的WORK差异不会显示结果未正确输出。

library(googleAnalyticsR)
library(tidyverse)

#settings
start_dat <- as.character(Sys.Date()-31)
end_dat <- as.character(Sys.Date()-1)


#Authorize Google Analytics R- this will open a webpage
#You must be logged into your Google Analytics account on your web browser
ga_auth()

account_sum <- ga_account_list()



#Add the start and end date to the date frame, as well as some columns to use to populate the metrics
account_sum$start_dat <- start_dat
account_sum$end_dat <- end_dat

## choose the v3 segment
segment_for_call <- "gaid::-5"

## make the v3 segment object in the v4 segment object:
seg_ob <- segment_ga4("OrganicTraffic", segment_id = segment_for_call)


# cycle through the list of views, pull the data, and add it to the
#account_summary

for (i in 1:5){

  view_id <- (Book1CSV[[1]][i])
  views=view_id




  ga_dat <- google_analytics_4(views, 
                            date_range = c(start_dat, end_dat),
                            segments = seg_ob,
                            metrics = c("sessions", "pageviews"),
                            dimensions = c("year","segment"))

  ga_dat <- summarise(ga_dat,
                       sessions = sum(sessions),
                       pageviews = sum(pageviews))

  account_sum$sessions[i] <- ga_data$sessions
  account_sum$pageviews[i] <- ga_data$pageviews
  print(account_summary)
}

clean_sum <- select(account_sum,
                        ID = webPropertyId ,
                        Account = accountName,
                        Views = views,
                        Type = type,
                        Level = level,
                        'Start Date' = start_dat,
                        'End Date' = end_dat,
                        Sessions = sessions,
                        Pageviews = pageviews)



write.csv (ga_dat, "doesntwork.csv", row.names = TRUE)

这项工作!!!!!!!!!!!!!!!打印语句打印代码

library(googleAnalyticsR)
library(tidyverse)

#settings
start_date <- as.character(Sys.Date()-31)
end_date <- as.character(Sys.Date()-1)
metrics <- c("sessions", "pageviews")
dimensions <- "year"

#Authorize Google Analytics R- this will open a webpage
#You must be logged into your Google Analytics account on your web browser
ga_auth()

account_summary <- ga_account_list()



#Add the start and end date to the date frame, as well as some columns to use to populate the metrics
account_summary$start_date <- start_date
account_summary$end_date <- end_date


# cycle through the list of views, pull the data, and add it to the
#account_summary

for (i in 1:6){

  view_id <- (Book1CSV[[1]][i])

  ga_data <- google_analytics_4(viewId = view_id,
                                date_range = c(start_date,end_date),
                                metrics = metrics,
                                dimensions = dimensions)

  # This query might return multiple rows (if it spans a year boundary), so
  #collapse and clean up

  ga_data <- summarise(ga_data,
                       sessions = sum(sessions),
                       pageviews = sum(pageviews))

  #add the totals to the account summary

  account_summary$sessions[i] <- ga_data$sessions
  account_summary$pageviews[i] <- ga_data$pageviews
  print(account_summary)
}

# Make a more compact set of data

clean_summary <- select(account_summary,
                        Account = accountName,
                        View = viewId,
                        Type = type,
                        Level = level,
                        'Start Date' = start_date,
                        'End Date' = end_date,
                        Sessions = sessions,
                        Pageviews = pageviews,
                        ID = webPropertyId)
select

write.csv (clean_summary, "worksfine.csv", row.names = FALSE)

无法真正理解这里出了什么问题。想要一些详细的帮助。我上载了一个名为 Book1CSV的文件，因为我无法获得可以捕获错误的try-catch语句。 Google商家商店的Beta版帐户导致了崩溃。

Answer 1

这是一种反R模式，可在循环中修改对象。最好返回data.frames列表，然后合并，最后创建摘要。

所以像这样：

my_view_ids <- c(12345,233445,232434)

## fetch data, create a list of 
all_data <- lapply(my_view_ids, function(id){
  one_data <- tryCatch(google_analytics_4(viewId = id,
                 date_range = c(start_date,end_date),
                 metrics = metrics,
                 dimensions = dimensions),
               error = function(ex){message(ex); NULL})
  one_data$viewId <- id
  one_data
})

## Reduce the list of data.frames to one data.frame
all_dataframe <- Reduce(rbind, all_data)

### make your summary etc.