r - 拆分和删除分组变量

Question

我正在尝试将数据框拆分为列表。 This question很有帮助，但我也想删除用于分组的列，因为它会弄乱以后的步骤。 drop split 的论据仅适用于未使用的级别。数据框如下:

structure(list(Var1 = c(-1L, -1L, -1L, -1L, -1L, -1L, -1L, -1L, 1L,
                         1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
                         1L, 1L, 1L, 1L, 1L, 1L, 1L, -1L, -1L, -1L, 
                         -1L, -1L, -1L, -1L, -1L), 
               Var2 = c(-1L, -1L, -1L, -1L, 0L, -1L, -1L, -1L, 0L, 
                        0L, 0L, -1L, -1L, -1L, -1L, -1L, -1L, -1L, 
                        -1L, -1L, -1L, -1L, -1L, -1L, -1L, -1L, -1L,
                        -1L, -1L, -1L, -1L, -1L, -1L, -1L, -1L),
               Var3 = c(1L, -1L, -1L, -1L, -1L, -1L, -1L, -1L, 0L, 0L, 
                        0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 
                        1L, 1L, 1L, 1L, 1L, 1L, -1L, -1L, -1L, -1L, 
                        -1L, -1L, -1L, -1L), 
               Var4 = c(1L, -1L, -1L, 2L, -1L, -1L, -1L, 1L, 1L, 1L, 
                        1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
                        0L, 0L, 0L, 0L, 0L, 1L, -1L, -1L, -1L, -1L, 
                        -1L, -1L, -1L, -1L), 
               Var5 = c(1L, -1L, -1L, 2L, -1L, -1L, -1L, 2L, 1L, 1L, 
                        1L, 1L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 1L, 
                        0L, 0L, 1L, 1L, 1L, 1L, -1L, -1L, -1L, -1L, 
                        -1L, -1L, -1L, -1L), 
               Bin = c(1L, 1L, 2L, 2L, 3L, 3L, 4L, 4L, 5L, 6L, 6L, 
                       7L, 7L, 8L, 8L, 9L, 9L, 10L, 10L, 11L, 11L, 
                       12L, 12L, 13L, 13L, 14L, 14L, 15L, 15L, 16L, 
                       16L, 17L, 17L, 18L, 18L)), 
           .Names = c("Var1", "Var2", "Var3", "Var4", "Var5", "Bin"), 
            class = "data.frame", row.names = c(NA, -35L))

如何在删除“Bin”的同时通过“Bin”拆分它？

Answer 1

根据您关于此列的信息，您可以使用

split(df[, -ncol(df)], df$Bin)

如果你知道这是最后一个，并且

split(df[, !names(df) == "Bin"], df$Bin)

如果你只知道它的名字。还

split(df[, -which(names(df) == "Bin")], df$Bin)

和

split(df[, -match("Bin", names(df))], df$Bin)