在r中解开列表中的列表中的列表，

Question

我遇到了一些困难，可以解开Goog​​le页面速​​度API响应中列表中的列表。

理想情况下，我只想将审核结果导出为CSV文件。因此，我可以比较客户网站的网站加载时间和性能。

''

library(httr)
library(tidyverse)
library(tidyr)

#URL to submit GET request to
url <- "https://www.googleapis.com/pagespeedonline/v5/runPagespeedurl=https://www.google.com/"


# GET request returned as list
raw_list <- url %>% 
httr::GET() %>% 
httr::content()


#turning the list into a dataframe 
df_pagespeed <- as.data.frame(do.call(rbind, raw_list))

#attempted unpack list in audit results with no luck
df_pagespeed <- tidyr::unnest(df_pagespeed, cols = audits)

# select only the audit results. 
df_pagespeed_final <- df_pagespeed[c(audits)]

#export to csv file
write.csv(df_pagespeed_final,"test-pagespeed.csv", row.names = FALSE)

''

理想情况下，我希望第二个数据帧（DF_PAGESPEED_FINAL）包含与PagesPeed审计结果相关的信息。有意义的见解，例如我的第一个智商，

希望能够清楚地了解某人。如果没有，请告诉我，我将修改这个问题。

感谢您的帮助。

Answer 1

我设法弄清楚了。可能不是最好的解决方案或最清洁的解决方案，但它起作用。

希望这对与Google PageSpeed API和R一起工作的其他人有帮助。

library(httr)
library(tidyverse)
library(tidyr)
library(purrr)
library(magrittr)
library(ggplot2)
library(reshape)

#URL to submit GET request to
url <- "https://www.googleapis.com/pagespeedonline/v5/runPagespeed?url=https://www.google.com/"


# GET request returned as list
raw_list <- url %>% 
  httr::GET() %>% 
  httr::content()



#turning the list into a dataframe 
df_pagespeed <- as.data.frame(do.call(rbind, raw_list))

df_all_audit <- df_pagespeed["lighthouseResult", "audits"]

df_all_audit <- as.data.frame(do.call(rbind, df_all_audit))


#df for meaningful paint 
df_first_meaningful_paint <- df_all_audit["lighthouseResult", "first-meaningful-paint"]

df_first_meaningful_paint <- as.data.frame(do.call(rbind, df_first_meaningful_paint))

df_first_meaningful_paint <- df_first_meaningful_paint$numericValue[1]



#df for largest content paint
df_largest_content_paint <- df_all_audit["lighthouseResult", "largest-contentful-paint"]

df_largest_content_paint <- as.data.frame(do.call(rbind, df_largest_content_paint))

df_largest_content_paint <- df_largest_content_paint$numericValue[1]



#df for total-blocking time
df_total_blocking_time <- df_all_audit["lighthouseResult", "total-blocking-time"]

df_total_blocking_time <- as.data.frame(do.call(rbind, df_total_blocking_time))

df_total_blocking_time <- df_total_blocking_time$numericValue[1]


#df for total-blocking time
df_speed_index <- df_all_audit["lighthouseResult", "speed-index"]

df_speed_index <- as.data.frame(do.call(rbind, df_speed_index ))

df_speed_index  <- df_speed_index$numericValue[1]



#df for content paint 
df_first_content_paint <- df_all_audit["lighthouseResult", "first-contentful-paint"]

df_first_content_paint <- as.data.frame(do.call(rbind, df_first_content_paint))

df_first_content_paint <- df_first_content_paint$numericValue[1]


#df for cumulative layout shift 
df_cumulative_shift <- df_all_audit["lighthouseResult", "cumulative-layout-shift"]

df_cumulative_shift <- as.data.frame(do.call(rbind, df_cumulative_shift))

df_cumulative_shift <- df_cumulative_shift$numericValue[1]



#df for server response time
df_server_response_time <- df_all_audit["lighthouseResult", "server-response-time"]

df_server_response_time<- as.data.frame(do.call(rbind, df_server_response_time))

df_server_response_time <- df_server_response_time$numericValue[1]



now <- Sys.time()
time <- data.frame(now)


#put all data frames into list
df_list <- bind_cols(time, df_first_content_paint, df_first_meaningful_paint, df_largest_content_paint, df_total_blocking_time, df_speed_index, df_cumulative_shift, df_server_response_time)

# renaming columns in dataframe
names(df_list)[1] <- "time"
names(df_list)[2] <- "first_content_paint"
names(df_list)[3] <- "first_meaningful_paint"
names(df_list)[4] <- "largest_content_paint"
names(df_list)[5] <- "total_blocking_time"
names(df_list)[6] <- "speed_index"
names(df_list)[7] <- "cumulative_shift"
names(df_list)[8] <- "server_response_time"

#assigning data to df_pagespeed_new
df_pagespeed_new <- df_list

# loading in old pagespeed file
df_pagespeed_old <- read_csv("pagespeed.csv")

#adding additional row to df page speed 
total <- rbind(df_pagespeed_old, df_pagespeed_new)

#writing the new new dataframe (larger more rows to dataframe)
write.csv(total,"pagespeed.csv", row.names = FALSE)


#plotting the graph
p <- ggplot()+
  geom_line(data=total,aes(y=first_content_paint,x= time,colour="first_content_paint"),size=1 )+
  geom_line(data=total,aes(y=largest_content_paint,x= time,colour="largest_content_paint"),size=1 )+
  geom_line(data=total,aes(y=total_blocking_time,x= time,colour="total_blocking_time"),size=1 )+
  geom_line(data=total,aes(y=speed_index,x= time,colour="speed_index"),size=1 )+
  geom_line(data=total,aes(y=cumulative_shift,x= time,colour="cumulative_shift"),size=1 )+
  geom_line(data=total,aes(y=server_response_time,x= time,colour="server_response_time"),size=1) +
  scale_color_manual(name = "Speed Metrics", values = c("first_content_paint" = "#008080", "largest_content_paint" = "#58508d", "total_blocking_time" = "#bc5090", "speed_index" = "#ff6361", "cumulative_shift" = "#ffa600", "server_response_time" = "#003f5c")) +
  xlab("Time & Date") +
  scale_y_continuous("Loadtime (milliseconds)") + 
  labs(title="www.google.com Page Speed Metrics")+ 
  theme(plot.title=element_text(hjust=0.5))

p + theme_classic() # Classic theme