将我的数据熔化/铸造成形状

时间:2011-05-28 03:36:03

标签: r reshape

我有一个看起来像这样的表:

enter image description here

我需要它看起来像这样,net =毛重:

enter image description here

我该怎么做?


我首先将数据融化,然后作为列进行转换,然后为净读数创建新列。

  df_m <- melt(df, id = 1:3)
  df_c <- cast(df_m, ... ~ variable + type)

  df_c$wr_net  <- df_c$wr_gross  - df_c$wr_tare
  df_c$wc_net  <- df_c$wc_gross  - df_c$wc_tare
  df_c$tsa_net <- df_c$tsa_gross - df_c$tsa_tare

哪个给出了

enter image description here

但是现在我无法弄清楚如何融合这个表格以使数据框看起来像我需要的方式,其中'type'列的值为'gross'和'tare'和'net'。

有更简单的方法吗?我是用熔化/铸造吠叫错误的树吗?


您可以使用此功能重现我的数据的一小部分......

  df <- structure(list(train = structure(c(1L, 1L, 1L, 1L, 1L, 1L), .Label = "AC0485n", class = "factor"), 
    position = c(1L, 1L, 2L, 2L, 3L, 3L), type = structure(c(2L, 
    1L, 2L, 1L, 2L, 1L), .Label = c("gross", "tare"), class = "factor"), 
    wids_raw = c(24.85, 146.2, 26.16, 135, 24.7, 135.1), wids_corr = c(26.15, 
    145.43, 27.44, 134.43, 26, 134.52), tsa = c(24.1, 139.2, 
    25, 133.6, 24, 131.1)), .Names = c("train", "position", "type", 
    "wr", "wc", "tsa"), class = "data.frame", row.names = c(NA, 
    -6L))

2 个答案:

答案 0 :(得分:4)

如果你真的想用重塑来做,我就是这样做的:

library(reshape2)

df_m <- melt(df, id = 1:3)

df_c <- dcast(df_m, ... ~  type)
df_c$net <- df_c$gross  - df_c$tare

df_m2 <- melt(df_c, 1:3)
names(df_m2)[4] <- "type"

dcast(df_m2, ... ~ variable)

答案 1 :(得分:3)

我认为你需要的只是使用ddply:

ddply(df,.(position),.fun=function(x){
newrow <- x[1,]
newrow$type <- "net"
newrow[4:6] <- x[x$type=="gross",4:6] - x[x$type=="tare",4:6]
return(rbind(x,newrow))
})

返回,

   train   position  type     wr     wc   tsa
 1 AC0485n        1  tare  24.85  26.15  24.1
 2 AC0485n        1 gross 146.20 145.43 139.2
 3 AC0485n        1   net 121.35 119.28 115.1
 4 AC0485n        2  tare  26.16  27.44  25.0
 5 AC0485n        2 gross 135.00 134.43 133.6
 6 AC0485n        2   net 108.84 106.99 108.6
 7 AC0485n        3  tare  24.70  26.00  24.0
 8 AC0485n        3 gross 135.10 134.52 131.1
 9 AC0485n        3   net 110.40 108.52 107.1

编辑: 我认为如果你真的想使用熔化/铸造,这是有效的:

dd <-  melt.data.frame(df_c,id.vars=1:2)
dd$type <- factor(do.call("rbind",strsplit(as.character(dd$variable),"_"))[,2])
dd$variable <- factor(do.call("rbind",strsplit(as.character(dd$variable),"_"))[,1])