首先,让我感谢所有为Stackoverflow和R做出贡献的人!我是那些不太擅长编程的R用户之一,但是勇敢地尝试将它用于工作,所以下面的问题可能是微不足道的......
这是问题所在。我需要将JSON格式的文件导入R:
# library(plyr)
# library(RJSONIO)
# lstJson <- fromJSON("JSON_test.json") #This is the file I read
# dput(lstJson) #What I did to get the txtJson below, for the benefit of testing.
txtJson <- structure(list(version = "1.1", result = structure(list(warnings = structure(list(), class = "AsIs"), fields = list(structure(list(info = "", rpl = 15, name = "time", type = "timeperiod"), .Names = c("info", "rpl", "name", "type")), structure(list(info = "", name = "object", type = "string"), .Names = c("info", "name", "type")), structure(list(info = "Counter1", name = "Counter1", type = "int"), .Names = c("info", "name", "type")), structure(list( info = "Counter2", name = "Counter2", type = "int"), .Names = c("info", "name", "type"))), timeout = 180, name = NULL, data = list( list(list("2011-05-01 17:00", NULL), list("Total", NULL), list(8051, NULL), list(44, NULL)), list(list("2011-05-01 17:15", NULL), list("Total", NULL), list(8362, NULL), list( 66, NULL))), type = "AbcDataSet"), .Names = c("warnings", "fields", "timeout", "name", "data", "type"))), .Names = c("version", "result"))
dfJson <- ldply(txtJson, data.frame)
我需要的是与此类似的数据框:
time object Counter1 Counter2
2011-05-01 17:00 Total 8051 44
2011-05-01 17:15 Total 8362 66
但我得到了
"Error in data.frame("2011-05-01 17:00", NULL, check.names = FALSE, stringsAsFactors = TRUE) :
arguments imply differing number of rows: 1, 0"
如果我使用lstJson,我会得到同样的错误。
我不确定RJSONIO
是否应该“足够智能”来解析这样的文件,或者我是否必须手动读取文件的第一行,设置列类型等等。我不使用CSV是因为我想“自动”以日期格式等方式获取日期。
谢谢, /克里斯
答案 0 :(得分:6)
查看txtJson的结构,你会发现所有有用的位都在txtJson $ result $ data中:
> sapply( txtJson$result$data, unlist )
[,1] [,2]
[1,] "2011-05-01 17:00" "2011-05-01 17:15"
[2,] "Total" "Total"
[3,] "8051" "8362"
[4,] "44" "66"
> t(sapply( txtJson$result$data, unlist ))
[,1] [,2] [,3] [,4]
[1,] "2011-05-01 17:00" "Total" "8051" "44"
[2,] "2011-05-01 17:15" "Total" "8362" "66"
> as.data.frame(t(sapply( txtJson$result$data, unlist )) )
V1 V2 V3 V4
1 2011-05-01 17:00 Total 8051 44
2 2011-05-01 17:15 Total 8362 66
在将这些作为未列出的向量获取然后传递给'as.data.frame'的过程中,它们现在都是类'因子',因此可能需要额外的努力来重新分类()这些值。您可以改为使用:
data.frame(t(sapply( txtJson$result$data, unlist )) ,stringsAsFactors=FALSE)
他们都是'性格'
就导入CSV文件而言,read.table()的colClasses参数将接受“POSIXlt”或“POSIXct”作为已知类型。我相信规则是必须有。 _ 方法。这是一个最小的例子:
> read.table(textConnection("2011-05-01 17:00"), sep=",", colClasses="POSIXct")
V1
1 2011-05-01 17:00:00