从表结果中提取因子标签以用作数据框列

时间:2013-02-06 12:02:15

标签: r dataframe syntax r-factor

我正在使用原始行输入格式UID = character,Win / Lose = Boolean执行clickstream日志文件摘要。我想要创建的输出摘要的形式为行UID,sumWin,sumLose。我已经使用表来获取我想要的部分内容,但是我无法找到正确的语法来从表结果中提取因子标签以便在摘要df中使用。下面的示例构建了一个很小的测试用例,并显示了我遇到的问题:我无法从表结果中获取因子标签。 (当然,你认为有更好的方式来处理整个事情 - 这显然也非常有用!)

我仍然无法在编辑器中进行格式化 - 显然这是我接下来要问的问题......!

foo <- data.frame(Uid=character(4), Win=logical(4), stringsAsFactors=FALSE)  
  foo$Uid <- c("UidA", "UidB", "UidA", "UidC")  
  foo$Win <- c(FALSE, TRUE, TRUE, FALSE)  
  #display foo  
  foo  
   Uid   Win  
1 UidA FALSE  
2 UidB  TRUE  
3 UidA  TRUE  
4 UidC FALSE  

  # my desired summary df is, for each UID: NWin (foo$Win=TRUE), NRunUp (foo$Win=FALSE)   
  # here I initialise a holder for it  
  fooNUniques <- length(unique(foo$Uid))  
  fooSummary <- data.frame(Uids=character(fooNUniques),NWins=numeric(fooNUniques),NRunUps=numeric(fooNUniques))   
  fooSummary

  Uids NWins NRunUps

1          0       0  
2          0       0  
3          0       0  
  #I can reference in to the result of applying table to get part of what I want  
  #First I get the table, this gets me a table by win/lose value  
  fooTable <- table(foo$Uid, foo$Win)  
  fooTable  

         FALSE TRUE  
  UidA     1    1  
  UidB     0    1  
  UidC     1    0  

  # I can get at the actual results via unname which gives me a matrix  
  fooTableAsMat <- unname(fooTable)  
  fooTableAsMat  
     [,1] [,2]  
[1,]    1    1  
[2,]    0    1  
[3,]    1    0  

  #but the UID vec is hidden in the table structure *somewhere* and   
  # I can't work out how to reference it out  

  #coercing the result to a dataFrame doesn't work

  as.data.frame(fooTable)  
    Var1  Var2 Freq  
  1 UidA FALSE    1  
  2 UidB FALSE    0  
  3 UidC FALSE    1  
  4 UidA  TRUE    1  
  5 UidB  TRUE    1  
  6 UidC  TRUE    0  

  #I have also tried 'aggregate' but have not made friends with it

1 个答案:

答案 0 :(得分:1)

这有帮助吗?

使用plyr

> ddply(foo, .(Uid), summarise, NWin = sum(Win), NRunUp = sum(!Win))
#    Uid NWin NRunUp
# 1 UidA    1      1
# 2 UidB    1      0
# 3 UidC    0      1