I have the following data frame:
df <- structure(list(Setno = structure(c(1L, 1L, 1L), .Label = "set4", class = "factor"),
Organ = structure(c(1L, 1L, 1L), .Label = "LN", class = "factor"),
Adjn = structure(c(1L, 1L, 1L), .Label = "FOO", class = "factor"),
Module_number = 1:3, Up_Count = c(2L, 0L, 0L), Down_count = c(1L,
8L, 6L)), .Names = c("Setno", "Organ", "Adjn", "Module_number",
"Up_Count", "Down_count"), row.names = c(NA, 3L), class = "data.frame")
That looks like this
Setno Organ Adjn Module_number Up_Count Down_count
1 set4 LN FOO 1 2 1
2 set4 LN FOO 2 0 8
3 set4 LN FOO 3 0 6
What I want do to is to melt or collapse the data based on Up_Count and Down_count yielding this:
Setno Organ Adjn Category Module_number Count
set4 LN FOO Up_count 1 2
set4 LN FOO Up_count 2 0
set4 LN FOO Up_count 3 0
set4 LN FOO Down_count 1 2
set4 LN FOO Down_count 2 8
set4 LN FOO Down_count 3 6
I tried this but didn't give what I want:
> library(reshape)
> melt(df)
Using Setno, Organ, Adjn as id variables
Setno Organ Adjn variable value
1 set4 LN FOO Module_number 1
2 set4 LN FOO Module_number 2
3 set4 LN FOO Module_number 3
4 set4 LN FOO Up_Count 2
5 set4 LN FOO Up_Count 0
6 set4 LN FOO Up_Count 0
7 set4 LN FOO Down_count 1
8 set4 LN FOO Down_count 8
9 set4 LN FOO Down_count 6
What's the right way to do it?