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

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.

Solution 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.

Solution 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

Solution 3:

Workaround would be:

a <- rbind(a, data.frame(one = 5, two = 6))

?rbind states that merging objects demands matching names:

It then takes the classes of the columns from the first data frame, and matches columns by name (rather than by position)