This can be one approach.
df1 <- structure(list(UniqueID = structure(1:3, .Label = c("Tree001",
"Tree002", "Tree003"), class = "factor"), Site = structure(c(1L,
1L, 2L), .Label = c("FK", "NM"), class = "factor"), State = structure(c(1L,
1L, 1L), .Label = "OR", class = "factor"), Age = c(23L, 45L,
35L), Height = c(70L, 53L, 84L)), .Names = c("UniqueID", "Site",
"State", "Age", "Height"), class = "data.frame", row.names = c(NA,
-3L))
df2 <- structure(list(UniqueID = c(1996L, 1997L, 1998L, 1999L, 2010L,
2011L), Tree001A = c(4L, 7L, 3L, 11L, 8L, 10L), Tree001B = c(NA,
8L, 2L, 9L, 8L, 5L), Tree002A = c(2L, 7L, 9L, 2L, 4L, 6L), Tree002B = c(NA,
NA, 4L, 12L, 6L, 3L), Tree003A = c(NA, 3L, 7L, 3L, 11L, 8L),
Tree003B = c(NA, NA, NA, 13L, 4L, 9L)), .Names = c("UniqueID",
"Tree001A", "Tree001B", "Tree002A", "Tree002B", "Tree003A", "Tree003B"
), class = "data.frame", row.names = c(NA, -6L))
> df1
UniqueID Site State Age Height
1 Tree001 FK OR 23 70
2 Tree002 FK OR 45 53
3 Tree003 NM OR 35 84
> df2
UniqueID Tree001A Tree001B Tree002A Tree002B Tree003A Tree003B
1 1996 4 <NA> 2 <NA> <NA> <NA>
2 1997 7 8 7 <NA> 3 <NA>
3 1998 3 2 9 4 7 <NA>
4 1999 11 9 2 12 3 13
5 2010 8 8 4 6 11 4
6 2011 10 5 6 3 8 9
# Use transpose function to change df1
df3 <- as.data.frame(t(df1[,-1]))
colnames(df3) <- df1[,1]
# Change rownames to UniqueID
df3$UniqueID <- rownames(df3)
# ROwnames to numeric
rownames(df3) <- c(1:4)
# Modify dataframe so that you have two columns for each subject
df3 <- df3[,c(4,1,1,2,2,3,3)]
colnames(df3) <- c("UniqueID", "Tree001A", "Tree001B", "Tree002A",
"Tree002B", "Tree003A", "Tree003B")
# Change classes of columns of df2 to factor
df2 <- data.frame(sapply(df2,function(x) class(x)<- as.factor(x)))
# Now combine two data frames
new <- rbind(df3,df2)
> new
UniqueID Tree001A Tree001B Tree002A Tree002B Tree003A Tree003B
1 Site FK FK FK FK NM NM
2 State OR OR OR OR OR OR
3 Age 23 23 45 45 35 35
4 Height 70 70 53 53 84 84
5 1996 4 <NA> 2 <NA> <NA> <NA>
6 1997 7 8 7 <NA> 3 <NA>
7 1998 3 2 9 4 7 <NA>
8 1999 11 9 2 12 3 13
9 2010 8 8 4 6 11 4
10 2011 10 5 6 3 8 9