在 R 中解析正则表达式

Question

我对正则表达式非常陌生，并且在 payload.hours 中有一些 JSON 数据：

这些代表不同地点一周中每一天的营业时间。将这些数据提取到同一数据框的新列中的最干净的方法是什么？我希望将每天的营业时间提取到单独的列中。

在此处附加数据 - ：

structure(list(payload.name = c("Windsor Castle", "Penrhyn Castle", 
"Barcaldine Castle", "University of Birmingham", "Kensington Gardens", 
"Bristol Zoo Gardens", "Alton Towers Resort", "The Royal Shakespeare Company", 
"University of Surrey", "Hampton Court Palace", "BFI Imax", "Usher Gallery", 
"The Cambridge Chop House", "The Balmoral Hotel", "Scottish National Portrait Gallery", 
"Old Trafford Stadium", "Exeter Cathedral", "Excel London", "Cavern Club"
), payload.hours_display = c("Mon-Sat 11:30 AM-11:00 PM; Sun 12:00 PM-11:00 PM", 
"Open Daily 11:00 AM-5:00 PM", "Open Daily 9:00 AM-10:00 PM", 
"Mon-Fri 8:00 AM-7:00 PM; Sat-Sun 10:00 AM-3:00 PM", "Open Daily 5:00 AM-11:59 PM", 
"Open Daily 9:00 AM-5:00 PM", "Open Daily 10:30 AM-5:00 PM", 
"Mon-Sat 11:30 AM-11:00 PM; Sun 11:30 AM-4:30 PM", "Mon-Fri 8:30 AM-11:00 PM; Sat-Sun 10:00 AM-11:00 PM", 
"Mon-Sat 12:00 PM-11:00 PM; Sun 12:00 PM-10:30 PM", "Mon 1:30 PM-11:00 PM; Tue 10:30 AM-11:00 PM; Wed-Fri 1:30 PM-11:00 PM; Sat-Sun 11:00 AM-11:00 PM", 
"Open Daily 10:00 AM-4:00 PM", "Mon-Thu 12:00 PM-10:30 PM; Fri-Sat 12:00 PM-11:00 PM; Sun 12:00 PM-9:30 PM", 
"Open Daily 12:00 AM-12:00 AM", "Mon-Wed 10:00 AM-5:00 PM; Thu 10:00 AM-7:00 PM; Fri-Sun 10:00 AM-5:00 PM", 
"Open Daily 9:30 AM-5:00 PM", "Mon-Sat 9:30 AM-4:45 PM; Sun 11:30 AM-3:30 PM", 
"Open Daily 5:30 AM-10:00 PM", "Mon 12:00 AM-12:30 AM, 11:00 AM-8:00 PM; Tue-Wed 11:00 AM-8:00 PM; Thu 11:00 AM-11:59 PM; Fri 12:00 AM-2:00 AM, 11:00 AM-11:59 PM; Sat-Sun 12:00 AM-2:30 AM, 11:00 AM-11:59 PM"
), payload.hours = c("{\"monday\":[[\"11:30\",\"23:00\"]],\"tuesday\":[[\"11:30\",\"23:00\"]],\"wednesday\":[[\"11:30\",\"23:00\"]],\"thursday\":[[\"11:30\",\"23:00\"]],\"friday\":[[\"11:30\",\"23:00\"]],\"saturday\":[[\"11:30\",\"23:00\"]],\"sunday\":[[\"12:00\",\"23:00\"]]}", 
"{\"monday\":[[\"11:00\",\"17:00\"]],\"tuesday\":[[\"11:00\",\"17:00\"]],\"wednesday\":[[\"11:00\",\"17:00\"]],\"thursday\":[[\"11:00\",\"17:00\"]],\"friday\":[[\"11:00\",\"17:00\"]],\"saturday\":[[\"11:00\",\"17:00\"]],\"sunday\":[[\"11:00\",\"17:00\"]]}", 
"{\"monday\":[[\"9:00\",\"22:00\"]],\"tuesday\":[[\"9:00\",\"22:00\"]],\"wednesday\":[[\"9:00\",\"22:00\"]],\"thursday\":[[\"9:00\",\"22:00\"]],\"friday\":[[\"9:00\",\"22:00\"]],\"saturday\":[[\"9:00\",\"22:00\"]],\"sunday\":[[\"9:00\",\"22:00\"]]}", 
"{\"monday\":[[\"8:00\",\"19:00\"]],\"tuesday\":[[\"8:00\",\"19:00\"]],\"wednesday\":[[\"8:00\",\"19:00\"]],\"thursday\":[[\"8:00\",\"19:00\"]],\"friday\":[[\"8:00\",\"19:00\"]],\"saturday\":[[\"10:00\",\"15:00\"]],\"sunday\":[[\"10:00\",\"15:00\"]]}", 
"{\"monday\":[[\"5:00\",\"23:59\"]],\"tuesday\":[[\"5:00\",\"23:59\"]],\"wednesday\":[[\"5:00\",\"23:59\"]],\"thursday\":[[\"5:00\",\"23:59\"]],\"friday\":[[\"5:00\",\"23:59\"]],\"saturday\":[[\"5:00\",\"23:59\"]],\"sunday\":[[\"5:00\",\"23:59\"]]}", 
"{\"monday\":[[\"9:00\",\"17:00\"]],\"tuesday\":[[\"9:00\",\"17:00\"]],\"wednesday\":[[\"9:00\",\"17:00\"]],\"thursday\":[[\"9:00\",\"17:00\"]],\"friday\":[[\"9:00\",\"17:00\"]],\"saturday\":[[\"9:00\",\"17:00\"]],\"sunday\":[[\"9:00\",\"17:00\"]]}", 
"{\"monday\":[[\"10:30\",\"17:00\"]],\"tuesday\":[[\"10:30\",\"17:00\"]],\"wednesday\":[[\"10:30\",\"17:00\"]],\"thursday\":[[\"10:30\",\"17:00\"]],\"friday\":[[\"10:30\",\"17:00\"]],\"saturday\":[[\"10:30\",\"17:00\"]],\"sunday\":[[\"10:30\",\"17:00\"]]}", 
"{\"monday\":[[\"11:30\",\"23:00\"]],\"tuesday\":[[\"11:30\",\"23:00\"]],\"wednesday\":[[\"11:30\",\"23:00\"]],\"thursday\":[[\"11:30\",\"23:00\"]],\"friday\":[[\"11:30\",\"23:00\"]],\"saturday\":[[\"11:30\",\"23:00\"]],\"sunday\":[[\"11:30\",\"16:30\"]]}", 
"{\"monday\":[[\"8:30\",\"23:00\"]],\"tuesday\":[[\"8:30\",\"23:00\"]],\"wednesday\":[[\"8:30\",\"23:00\"]],\"thursday\":[[\"8:30\",\"23:00\"]],\"friday\":[[\"8:30\",\"23:00\"]],\"saturday\":[[\"10:00\",\"23:00\"]],\"sunday\":[[\"10:00\",\"23:00\"]]}", 
"{\"monday\":[[\"12:00\",\"23:00\"]],\"tuesday\":[[\"12:00\",\"23:00\"]],\"wednesday\":[[\"12:00\",\"23:00\"]],\"thursday\":[[\"12:00\",\"23:00\"]],\"friday\":[[\"12:00\",\"23:00\"]],\"saturday\":[[\"12:00\",\"23:00\"]],\"sunday\":[[\"12:00\",\"22:30\"]]}", 
"{\"monday\":[[\"13:30\",\"23:00\"]],\"tuesday\":[[\"10:30\",\"23:00\"]],\"wednesday\":[[\"13:30\",\"23:00\"]],\"thursday\":[[\"13:30\",\"23:00\"]],\"friday\":[[\"13:30\",\"23:00\"]],\"saturday\":[[\"11:00\",\"23:00\"]],\"sunday\":[[\"11:00\",\"23:00\"]]}", 
"{\"monday\":[[\"10:00\",\"16:00\"]],\"tuesday\":[[\"10:00\",\"16:00\"]],\"wednesday\":[[\"10:00\",\"16:00\"]],\"thursday\":[[\"10:00\",\"16:00\"]],\"friday\":[[\"10:00\",\"16:00\"]],\"saturday\":[[\"10:00\",\"16:00\"]],\"sunday\":[[\"10:00\",\"16:00\"]]}", 
"{\"monday\":[[\"12:00\",\"22:30\"]],\"tuesday\":[[\"12:00\",\"22:30\"]],\"wednesday\":[[\"12:00\",\"22:30\"]],\"thursday\":[[\"12:00\",\"22:30\"]],\"friday\":[[\"12:00\",\"23:00\"]],\"saturday\":[[\"12:00\",\"23:00\"]],\"sunday\":[[\"12:00\",\"21:30\"]]}", 
"{\"monday\":[[\"00:00\",\"24:00\"]],\"tuesday\":[[\"00:00\",\"24:00\"]],\"wednesday\":[[\"00:00\",\"24:00\"]],\"thursday\":[[\"00:00\",\"24:00\"]],\"friday\":[[\"00:00\",\"24:00\"]],\"saturday\":[[\"00:00\",\"24:00\"]],\"sunday\":[[\"00:00\",\"24:00\"]]}", 
"{\"monday\":[[\"10:00\",\"17:00\"]],\"tuesday\":[[\"10:00\",\"17:00\"]],\"wednesday\":[[\"10:00\",\"17:00\"]],\"thursday\":[[\"10:00\",\"19:00\"]],\"friday\":[[\"10:00\",\"17:00\"]],\"saturday\":[[\"10:00\",\"17:00\"]],\"sunday\":[[\"10:00\",\"17:00\"]]}", 
"{\"monday\":[[\"9:30\",\"17:00\"]],\"tuesday\":[[\"9:30\",\"17:00\"]],\"wednesday\":[[\"9:30\",\"17:00\"]],\"thursday\":[[\"9:30\",\"17:00\"]],\"friday\":[[\"9:30\",\"17:00\"]],\"saturday\":[[\"9:30\",\"17:00\"]],\"sunday\":[[\"9:30\",\"17:00\"]]}", 
"{\"monday\":[[\"9:30\",\"16:45\"]],\"tuesday\":[[\"9:30\",\"16:45\"]],\"wednesday\":[[\"9:30\",\"16:45\"]],\"thursday\":[[\"9:30\",\"16:45\"]],\"friday\":[[\"9:30\",\"16:45\"]],\"saturday\":[[\"9:30\",\"16:45\"]],\"sunday\":[[\"11:30\",\"15:30\"]]}", 
"{\"monday\":[[\"5:30\",\"22:00\"]],\"tuesday\":[[\"5:30\",\"22:00\"]],\"wednesday\":[[\"5:30\",\"22:00\"]],\"thursday\":[[\"5:30\",\"22:00\"]],\"friday\":[[\"5:30\",\"22:00\"]],\"saturday\":[[\"5:30\",\"22:00\"]],\"sunday\":[[\"5:30\",\"22:00\"]]}", 
"{\"monday\":[[\"00:00\",\"00:30\"],[\"11:00\",\"20:00\"]],\"tuesday\":[[\"11:00\",\"20:00\"]],\"wednesday\":[[\"11:00\",\"20:00\"]],\"thursday\":[[\"11:00\",\"23:59\"]],\"friday\":[[\"00:00\",\"2:00\"],[\"11:00\",\"23:59\"]],\"saturday\":[[\"00:00\",\"2:30\"],[\"11:00\",\"23:59\"]],\"sunday\":[[\"00:00\",\"2:30\"],[\"11:00\",\"23:59\"]]}"
)), .Names = c("payload.name", "payload.hours_display", "payload.hours"
), row.names = c(3L, 5L, 10L, 14L, 18L, 19L, 24L, 32L, 33L, 35L, 
36L, 37L, 38L, 42L, 43L, 44L, 45L, 47L, 54L), class = "data.frame")

我尝试使用 plyr::ldply() 函数根据此处的答案 - How to convert a list consisting of vector of different lengths to a usable data frame in R? 将这个 JSON 展平，并且非常接近，但时间没有按正确的顺序排列（有些日子有多个营业时间）

最后，我想通过提取周日下午 12 点之前营业的企业来操作数据框。

Answer 1

我的感觉是，如果您可以使用上面引用的 JSON 库，那将是可行的方法。我也是，不熟悉 JSON 数据。假设您选择在紧要关头做我想做的事情，并且只使用您所拥有的，这里有几个想法：

因此，使用您的示例数据（例如，df1）：

library(splitstackshape)
library(reshape2)
# form your payload.hours column into columns:
df2 <- cbind(df,cSplit(df,splitCols='payload.hours',sep='],"',direction='wide'))
# your example actually comes out neatly to 7 columns.  I'd put it into a long format for easier logical operations:
df3 <- melt(df2,id.vars=c('payload.name','payload.hours_display','payload.hours'))
# Now, you can do your regexp if desired more easily:
df3$start <- gsub(x=df3$value,pattern='^.*y.*"(.*)","(.*)"]$',replacement='\\1')
df3$end <- gsub(x=df3$value,pattern='^.*y.*"(.*)","(.*)"]$',replacement='\\2')

此时您可以使用标准 POSIXct、strftime 或 strptime 函数将字符串转换为时间并根据需要操作格式。

上面的代码似乎基本上适用于您的示例数据，但星期日除外，但我现在必须运行。如果这对您有帮助并且您有任何问题，我很乐意稍后进行编辑。

Answer 2

更新

按照以下步骤，我已设法将我需要的内容提取到单独的列中。

mydf = cbind(mydf, do.call(plyr::rbind.fill, lapply(paste0("
[",mydf$payload.hours,"]"), function(x) jsonlite::fromJSON(x))))

这通过将每天的值提取为字符串列表来创建新列。

接下来我取消列出值并展平数据框

x = stri_list2matrix(mydf$sunday, byrow=TRUE).
colnames(x) = c("From.1", "To.1", "From.2", "To.2")

最后我将它绑定到原始数​​据框以获得结果。

mydf = data.frame(mydf,x)

清理后，它看起来像这样（显示特定日期）：