I have spatial weather data of UK in Ascii text format for 7 years (each file/dataframe have monthly data of one year - 12 columns and 52201 rows as each row represents one location). I want to merge data frames with alternative rows - 1st row of data frame 1 then 1st row of data frame 2 till 1st row of data frame 7 then 2nd row of data frame 1 till 2nd row of data frame 7 and continue ....
V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12
-1199 -1199 -1199 -1199 -1199 -1199 -1199 -1199 -1199 -1199 -1199 -1199
-1299 -1299 -1299 -1299 -1299 -1299 -1299 -1299 -1299 -1299 -1299 -1299
-1399 -1399 -1399 -1399 -1399 -1399 -1399 -1399 -1399 -1399 -1399 -1399
-9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999
-9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999
Here is my code:
n1<-read.table("data/y1call.txt", sep="")
n2<-read.table("data/y2call.txt", sep="")
n3<-read.table("data/y3call.txt", sep="")
c<-rbind(n1,n2,n3)
merge(n1,n2,n3)
I have tried merge, rbind, cbind but all failed.
You can create a new column representing the rownames in each data frame, and sort on that variable after you rbind, i.e.
ddf_all <- do.call(rbind, lapply(list(df1, df2, df3), function(i)transform(i, new = rownames(i))))
ddf_all[order(ddf_all$new),]
which gives,
v1 v2 new 1 1 6 1 6 11 16 1 11 21 26 1 2 2 7 2 7 12 17 2 12 22 27 2 3 3 8 3 8 13 18 3 13 23 28 3 4 4 9 4 9 14 19 4 14 24 29 4 5 5 10 5 10 15 20 5 15 25 30 5
DATA:
df1 <- data.frame(v1 = c(1, 2, 3, 4, 5), V2 = c(6, 7, 8, 9, 10))
df2 <- data.frame(v1 = c(11, 12, 13, 14, 15), v2 = c(16, 17, 18, 19, 20))
df3 <- data.frame(v1 = c(21, 22, 23, 24, 25), v2 = c(26, 27, 28, 29, 30))