I have a dataset with 11 columns with over a 1000 rows each. The columns were labeled V1, V2, V11, etc.. I replaced the names with something more useful to me using the "c" command. I didn't realize that row 1 also contained labels for each column and my actual data starts on row 2.
Is there a way to delete row 1 and decrement?
Keep the labels from your original file like this:
df = read.table('data.txt', header = T)
If you have columns named x and y, you can address them like this:
df$x
df$y
If you'd like to actually delete the first row from a data.frame, you can use negative indices like this:
df = df[-1,]
If you'd like to delete a column from a data.frame, you can assign NULL to it:
df$x = NULL
Here are some simple examples of how to create and manipulate a data.frame in R:
# create a data.frame with 10 rows
> x = rnorm(10)
> y = runif(10)
> df = data.frame( x, y )
# write it to a file
> write.table( df, 'test.txt', row.names = F, quote = F )
# read a data.frame from a file:
> read.table( df, 'test.txt', header = T )
> df$x
[1] -0.95343778 -0.63098637 -1.30646529 1.38906143 0.51703237 -0.02246754
[7] 0.20583548 0.21530721 0.69087460 2.30610998
> df$y
[1] 0.66658148 0.15355851 0.60098886 0.14284576 0.20408723 0.58271061
[7] 0.05170994 0.83627336 0.76713317 0.95052671
> df$x = x
> df
y x
1 0.66658148 -0.95343778
2 0.15355851 -0.63098637
3 0.60098886 -1.30646529
4 0.14284576 1.38906143
5 0.20408723 0.51703237
6 0.58271061 -0.02246754
7 0.05170994 0.20583548
8 0.83627336 0.21530721
9 0.76713317 0.69087460
10 0.95052671 2.30610998
> df[-1,]
y x
2 0.15355851 -0.63098637
3 0.60098886 -1.30646529
4 0.14284576 1.38906143
5 0.20408723 0.51703237
6 0.58271061 -0.02246754
7 0.05170994 0.20583548
8 0.83627336 0.21530721
9 0.76713317 0.69087460
10 0.95052671 2.30610998
> df$x = NULL
> df
y
1 0.66658148
2 0.15355851
3 0.60098886
4 0.14284576
5 0.20408723
6 0.58271061
7 0.05170994
8 0.83627336
9 0.76713317
10 0.95052671
You can use negative indexing to remove rows, e.g.:
dat <- dat[-1, ]
Here is an example:
> dat <- data.frame(A = 1:3, B = 1:3)
> dat[-1, ]
A B
2 2 2
3 3 3
> dat2 <- dat[-1, ]
> dat2
A B
2 2 2
3 3 3
That said, you may have more problems than just removing the labels that ended up on row 1. It is more then likely that R has interpreted the data as text and thence converted to factors. Check what str(foo), where foo is your data object, says about the data types.
It sounds like you just need header = TRUE in your call to read in the data (assuming you read it in via read.table() or one of it's wrappers.)
While I agree with the most voted answer, here is another way to keep all rows except the first:
dat <- tail(dat, -1)
This can also be accomplished using Hadley Wickham's dplyr package.
dat <- dat %>% slice(-1)
No one probably really wants to remove row one. So if you are looking for something meaningful, that is conditional selection
#remove rows that have long length and "0" value for vector E
>> setNew<-set[!(set$length=="long" & set$E==0),]
I am not expert, but this may work as well,
dat <- dat[2:nrow(dat), ]
dat <- dat[-1, ] worked but it killed my dataframe, changing it into another type. Had to instead use
dat <- data.frame(dat[-1, ]) but this is possibly a special case as this dataframe initially had only one column.
