On 10/22/2008 12:09 PM, Ivan Alves wrote:
Dear all,
Thanks for all the replies.
I get something with Duncan's code (slightly more compact than the
other two), but of class "integer", whereas the two inputs are class
"factor". Clearly the name information is lost. I did not see
anything on this in the help page for ifelse.
It is there, in this warning:
The mode of the result may depend on the value of 'test', and the
class attribute of the result is taken from 'test' and may be
inappropriate for the values selected from 'yes' and 'no'.
You'd want the result to be a factor, but those attributes are lost. I
think this is a result of two design flaws: ifelse() shouldn't base the
class on the test, it should base it on the values. And factors in S
and R have all sorts of problems.
You can work around this by converting to character vectors:
Name <- ifelse(is.na(Name.x), as.character(Name.y), as.character(Name.x))
If you really want factors, you can convert back at the end, but why
would you want to?
Duncan Murdoch
On this experience I also tried
df$Name <- df$NAME.x
df[is.na(df$NAME.x),"Name"] <- df[is.na(df $NAME.x),"NAME.y"]
but then again the "factor" issue was a problem (clearly the levels
are not the same and then there is a conflict)
Any further guidance?
Kind regards,
Ivan
On 22 Oct 2008, at 17:26, Duncan Murdoch wrote:
On 10/22/2008 11:21 AM, Ivan Alves wrote:
Dear all,
I searched the mail archives and the R site and found no guidance
(tried "merge", "cbind" and terms like "coalesce" with no
success). There surely is a way to coalesce (like in SQL) columns
in a dataframe, right? For example, I would like to go from a
dataframe with two columns to one with only one as follows:
From
Name.x Name.y
nx1 ny1
nx2 NA
NA ny3
NA NA
...
To
Name
nx1
nx2
ny3
NA
...
where column Name.x is taken if there is a value, and if not then
column Name.y
Any help would be appreciated
I don't know of any special function to do that, but ifelse() can
handle it easily:
Name <- ifelse(is.na(Name.x), Name.y, Name.x)
(If those are columns of a dataframe named df, you'd prefix each
column name by df$, or do
within(df, Name <- ifelse(is.na(Name.x), Name.y, Name.x))
Duncan Murdoch
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