Reshape specific rows into columns in R - r

Question

My sample data frame would look like the following:
1 Number Type Code Reason
2 0123 06 09 010
3 Date Amount Damage Act
4 08/31/16 10,000 Y N
5 State City Zip Phone
6 WI GB 1234 Y
I want to make rows 1, 3, and 5 column names and have the data below each fall into each column, respectively. I was looking into the reshape function, but I only saw examples where an entire column of values needed to be individual columns. So I wasn't sure what to do in this scenario--apologies if it's obvious.
Here is the desired output:
1 Number Type Code Reason Date Amount Damage Act State City Zip Phone
2 0123 06 09 010 08/31/16 10,000 Y N WI GB 1234 Y
Thanks

Answer 1

As some people have commented, you could build a data frame out of the rows of your starting data frame, but I think it's a little easier to work on the lines of text.
If your starting file looks something like this
Number , Type , Code ,Reason
0123 , 06 , 09 , 010
Date , Amount , Damage , Act
08/31/16 , 10000 , Y , N
State , City , Zip , Phone
WI , GB , 1234, Y
we can read it in with each line as an element of a character vector:
lines <- readLines("start.csv")
make all the odd lines into a single line:
oddind <- seq(from=1, to= length(lines), by=2)
namelines <- paste(lines[oddind], collapse=",")
make all the even lines into a single line:
datlines <- paste(lines[oddind+1], collapse=",")
make those lines into a new CSV to read:
writeLines(text= c(namelines, datlines), con= "nice.csv")
print(read.csv("nice.csv"))
This gives
Number Type Code Reason Date Amount Damage Act State
1 123 6 9 10 08/31/16 10000 Y N WI
City Zip Phone
1 GB 1234 Y
So, it's all in one row of the data frame and all the variable names show up correctly in the data frame.
The benefits of this strategy are:
It will work for starting CSV files where the number of variables isn't a multiple of 4.
It will work for starting CSV files with any number of rows
There is no chance of weird dynamic casting happening with unlist() or as.character().

Answer 2

Creating a dataframe roughly appearing like that (although it necessarily has column names). Those are probably factor columns if you just used one of the standard read.* functions without using stringsAsFactors=FALSE, hence the need to convert with as.character.
dat=read.table(text="1 Number Type Code Reason
2 0123 06 09 010
3 Date Amount Damage Act
4 08/31/16 10,000 Y N
5 State City Zip Phone
6 WI GB 1234 Y")
Then you can set odd number rows as names of the values-vector of the even number rows with:
setNames( unlist( lapply( dat[!c(TRUE,FALSE), ] ,as.character)),
unlist( lapply( dat[c(TRUE,FALSE), ] ,as.character)) )
1 3 5 Number Date State Type
"2" "4" "6" "0123" "08/31/16" "WI" "06"
Amount City Code Damage Zip Reason Act
"10,000" "GB" "09" "Y" "1234" "010" "N"
Phone
"Y"
The !c(TRUE,FALSE) and its logical complement in the next extract operation get magically recycled along all the possible rows. Obviously there would be better ways of doing this if you posted a version of a text file rather than saying that the starting point was a dataframe. You would need to remove what were probably rownames. If you want a "clean solution then post either dput(.) from your dataframe or the raw text file.