Converting data to a 2 column format? - r

Question

If I have a dataset like the following:
LA NY MA
1 2 3
4 5 6
3 5
4
(In other words, each row has a different structure. LA has 3 values, NY has 4 values, etc.)
I am trying to use lm to perform an ANOVA test (to decide whether the mean number is the same in each state), and it keeps showing "an error occurred" because rows do not match. One idea I got was to convert data to a 2-column format. Which command/package should I use to perform that task?
Edit: the data is from the txt file.

Answer 1

Another option after you read the file to convert to a 2-column format would be
df <- read.table("Betty.txt", header=TRUE, fill=TRUE, sep="\t")
## (as #Richard Scriven mentioned in the comment)
na.omit(stack(df))
# values ind
#1 1 LA
#2 4 LA
#3 3 LA
#5 2 NY
#6 5 NY
#7 5 NY
#8 4 NY
#9 3 MA
#10 6 MA
Update
The above I got by transforming the data to have \t delimiter. But, if the file is copy/pasted directly from the OP's post without any change (making sure that there are spaces for the 3rd and 4th row after the 2nd column)
lines <- readLines('Betty1.txt')
lines2 <- gsub("(?<=[^ ]) +|^[ ]+(?<=[ ])(?=[^ ])", ",", lines, perl=TRUE)
lines2
#[1] "LA,NY,MA" "1,2,3" "4,5,6" "3,5," ",4,"
df1 <- read.table(text=lines2, sep=',', header=TRUE)
df1
# LA NY MA
#1 1 2 3
#2 4 5 6
#3 3 5 NA
#4 NA 4 NA
and then do
na.omit(stack(df1))
Update2
Another option if you have fixed width columns is to use read.fwf
df <- read.fwf('Betty1.txt', widths=c(3,3,3), skip=1)
colnames(df) <- scan('Betty1.txt', nlines=1, what="", quiet=TRUE)
df
# LA NY MA
#1 1 2 3
#2 4 5 6
#3 3 5 NA
#4 NA 4 NA
library(tidyr)
gather(df, Var, Val, LA:MA, na.rm=TRUE)
# Var Val
#1 LA 1
#2 LA 4
#3 LA 3
#4 NY 2
#5 NY 5
#6 NY 5
#7 NY 4
#8 MA 3
#9 MA 6

Answer 2

Just add an 'NA' to the 4th line of your text and try:
> ddf = read.table(text="
+ LA NY MA
+ 1 2 3
+ 4 5 6
+ 3 5
+ NA 4
+ ", header=T, fill=T)
>
> ddf
LA NY MA
1 1 2 3
2 4 5 6
3 3 5 NA
4 NA 4 NA
>
> dput(ddf)
structure(list(LA = c(1L, 4L, 3L, NA), NY = c(2L, 5L, 5L, 4L),
MA = c(3L, 6L, NA, NA)), .Names = c("LA", "NY", "MA"), class = "data.frame", row.names = c(NA,
-4L))
>
> mm = melt(ddf)
No id variables; using all as measure variables
>
> mm
variable value
1 LA 1
2 LA 4
3 LA 3
4 LA NA
5 NY 2
6 NY 5
7 NY 5
8 NY 4
9 MA 3
10 MA 6
11 MA NA
12 MA NA
>
> with(mm, aov(value~variable))
Call:
aov(formula = value ~ variable)
Terms:
variable Residuals
Sum of Squares 4.833333 15.166667
Deg. of Freedom 2 6
Residual standard error: 1.589899
Estimated effects may be unbalanced
3 observations deleted due to missingness