Reading in Complicated CSV to R - r

Question

I am trying to read in the following .csv file into R. As you can see from the imagine below, Row 2 has the unique variable names, while Row 3 has the values for the above variables. So Rows 2/3 together represent one observation. This process continues, so that Row 4 is a line of variable names and Row 5 corresponds to those variable values. This process continues so that each two-row pair (2/3, 4/5, 6/7....999/1000) represent one observation. There are 1,000 observations total in the data set.
What I am having trouble with is reading this into R so that I have a more usable dataset. My goal is to have a standard set of variable names across the top row, and each subsequent line representing one observation.
Any expert R coders have suggestions?
Thank you,

Answer 1

Here is a solution that worked on a simple test case I made. You'd need to import your data into a data.frame, x = read.csv(file="your-file.csv")
To test this though, I used the test data.frame, x:
x=structure(list(V1 = structure(c(2L, 1L, 4L, 3L), .Label = c("1",
"a", "ab", "h"), class = "factor"), V2 = structure(c(2L, 1L,
4L, 3L), .Label = c("2", "b", "cd", "i"), class = "factor"),
V3 = structure(c(3L, 1L, 2L, 4L), .Label = c("3", "a", "c",
"ef"), class = "factor"), V4 = structure(c(3L, 1L, 2L, 4L
), .Label = c("4", "b", "d", "gh"), class = "factor"), V5 = structure(c(3L,
1L, 2L, 4L), .Label = c("5", "c", "e", "ij"), class = "factor"),
V6 = structure(c(3L, 1L, 2L, 4L), .Label = c("6", "d", "f",
"kl"), class = "factor"), V7 = structure(c(3L, 1L, 2L, 4L
), .Label = c("7", "e", "g", "mno"), class = "factor")), .Names = c("V1",
"V2", "V3", "V4", "V5", "V6", "V7"), class = "data.frame", row.names = c(NA,
-4L))
Which turns this table (rows 1 and 3 are your labels):
V1 V2 V3 V4 V5 V6 V7
1 a b c d e f g
2 1 2 3 4 5 6 7
3 h i a b c d e
4 ab cd ef gh ij kl mno
Using this script to generate a final data.frame dat:
library(plyr)
variables = x[seq(1,nrow(x),2),] #df of all variable rows
values = x[seq(2,nrow(x),2),] #df of all value rows
dat=data.frame() #generate blank data.frame
for(i in 1:nrow(variables)) {
dat.temp=data.frame(values[i,])#make temporary df for the row i of your values
colnames(dat.temp)=as.matrix(variables[i,]) # name the temporary df from row i of your variables
print(dat.temp) #check that they are coming out right (comment this out as necessary)
dat=rbind.fill(dat,dat.temp) #create the final data.frame
rm(dat.temp) #remove the temporary df
}
Into this final table (variables are the column names now):
a b c d e f g h i
1 1 2 3 4 5 6 7 <NA> <NA>
2 ef gh ij kl mno <NA> <NA> ab cd
Hope it works.