R help - Jan 2001 - R 1.2.1 - read.table - factors problem or is it a data.frame problem

Patrick Connolly refers to the read.table help manual page to show how to
coerce input columns to character or to numeric. Indeed coercion with a logical
vector will set the mode regardless of the column content. He also notes one
can set factors with factor(). 

However, the problem encountered is not one of setting factors but of unsetting
them. The manual states that variables of mode or type character will become
factors. My data input efforts showed no relationship between type and factor.
With no evident reason, most character variables did not become factors while
many real variables did. It is a bit disconcerting to get an output with
thousands of floating point factor levels or error messages that one''s
data are
of the wrong mode for any analysis whatsoever.

How does one unset mode assignment of factor and how does one avoid the problem
of automatic misassignment with other datasets?

Gordon

   
> |> 
> |> R-1.2.1 Suse 7.0 binary
> |> 
> |> > fooframe <- read.table("foo", header=FALSE,
as.is=c(1:22,398),
> |> col.names=foo.colheads)
> |> 
> |> cols 1-9 are alphabetic, 10-22 and 398 are numbers but unordered
> categorical |>      23-375 are numeric with and without decimal points
> |> 
> |> As I read the description the "as.is" index numbers should
force those
> columns |> to be "character" and "factor". However
only the 1-9 alpha
> become "character" |> but they did not become
"factor". Everything else
> shows mode "numeric" but 
> 
> Here is your explanation:
> 
>    as.is: the default behavior of `read.table'' is to convert
>           non-numeric variables to factors.  The variable `as.is''
>           controls this conversion.  Its value is either a vector of
>           logicals (values are recycled if necessary), or a vector of
>           numeric indices which specify which columns should be left as
>           character strings.
> 
> Since your column 10, etc are not character, as.is will not have an
> effect on them.  I think it is simple enough to convert numeric
> columns into factors (as distinct from continuous variables) with
> factor().
> 
> 
> |> "is.factor" distributes TRUE to various variables in no
pattern
> discernible to |> me either in distribution or in the data content of
the
> columns. (I tried |> giving as.is a type vector but that just made
> everything "numeric" with no |> pattern to factors.) No
"as.is" parameter
> still leaves the odd distribution of |> factors.
> |> 
> |> The main effects are that for some statistical functions on data
> subsets, one |> is warned one cannot perform the operations on
categorical
> data while others |> stop for NA''s. There are no NA''s
in the dataset!
> Running "unique" on each |> variate and collecting outside the
frame shows
> adequate dispersion for analysis |> with no zero variances.
"cor" will only
> run "pairwise" though "complete.cases" |> finds no
NA''s.
> |> 
> |> What am I missing?
> 
> My guess is that something unplanned is happening when you try as.is
> on numeric columns.

Gordon M. Harrington		Mail:	3720 Village Place, #6308
Professor Emeritus			Waterloo, IA 50702-5848
University of Northern Iowa 	Phone:	319-291-8535
gordon.harrington at uni.edu	Fax:	319-291-8491
dryfly at aya.yale.edu			319-291-8324

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On Wed, 31 Jan 2001 gordon.harrington at uni.edu wrote:
> However, the problem encountered is not one of setting factors but of
unsetting
> them. The manual states that variables of mode or type character will
become
> factors. My data input efforts showed no relationship between type and
factor.
> With no evident reason, most character variables did not become factors
while
> many real variables did. It is a bit disconcerting to get an output with
> thousands of floating point factor levels or error messages that
one''s data are
> of the wrong mode for any analysis whatsoever.
> 
> How does one unset mode assignment of factor and how does one avoid the
problem
> of automatic misassignment with other datasets?
You can convert a factor to the correct numeric values with
   as.numeric(as.character(the.factor))

We don''t have enough information to tell what happened in your case but
in
my experience the most common reason for a numeric variable to read as a
factor has been misspecifying the missing value codes in the na.strings
argument. This argument lists the strings that should be converted to NAs;
any other strings will trigger a conversion to factor.

	-thomas

Thomas Lumley			Asst. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle

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I have some problems with read.table and floats turning up as 
factors. In my case it was not a blank in the file but an unary minus!!
so 3.24,-57.23,... the 3.24 is numeric but -57.23 is a factor.
Yes I turned it into a numeric with as.numeric(as.character(.. but I 
think it will be better to modify somehow the read.table/read.csv 
code.
Thanks anyway.

R. Heberto Ghezzo  Ph.D.
Meakins-Christie Labs
McGill University
Montreal - Canada
heberto at meakins.lan.mcgill.ca
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