R: losing column names when adding rows to an empty data frame

Question

I am just starting with R and encountered a strange behaviour: when inserting the first row in an empty data frame, the original column names get lost.

example:

a<-data.frame(one = numeric(0), two = numeric(0)) a #[1] one two #<0 rows> (or 0-length row.names) names(a) #[1] "one" "two" a<-rbind(a, c(5,6)) a #  X5 X6 #1  5  6 names(a) #[1] "X5" "X6" 

As you can see, the column names one and two were replaced by X5 and X6.

Could somebody please tell me why this happens and is there a right way to do this without losing column names?

A shotgun solution would be to save the names in an auxiliary vector and then add them back when finished working on the data frame.

Thanks

Context:

I created a function which gathers some data and adds them as a new row to a data frame received as a parameter. I create the data frame, iterate through my data sources, passing the data.frame to each function call to be filled up with its results.

Answer 1

The rbind help pages specifies that :

For ‘cbind’ (‘rbind’), vectors of zero length (including ‘NULL’) are ignored unless the result would have zero rows (columns), for S compatibility. (Zero-extent matrices do not occur in S3 and are not ignored in R.)

So, in fact, a is ignored in your rbind instruction. Not totally ignored, it seems, because as it is a data frame the rbind function is called as rbind.data.frame :

rbind.data.frame(c(5,6)) #  X5 X6 #1  5  6 

Maybe one way to insert the row could be :

a[nrow(a)+1,] <- c(5,6) a #  one two #1   5   6 

But there may be a better way to do it depending on your code.

Answer 2

was almost surrendering to this issue.

1) create data frame with stringsAsFactor set to FALSE or you run straight into the next issue

2) don't use rbind - no idea why on earth it is messing up the column names. simply do it this way:

df[nrow(df)+1,] <- c("d","gsgsgd",4)

df <- data.frame(a = character(0), b=character(0), c=numeric(0))  df[nrow(df)+1,] <- c("d","gsgsgd",4)  #Warnmeldungen: #1: In `[<-.factor`(`*tmp*`, iseq, value = "d") : #  invalid factor level, NAs generated #2: In `[<-.factor`(`*tmp*`, iseq, value = "gsgsgd") : #  invalid factor level, NAs generated  df <- data.frame(a = character(0), b=character(0), c=numeric(0), stringsAsFactors=F)  df[nrow(df)+1,] <- c("d","gsgsgd",4)  df #  a      b c #1 d gsgsgd 4