Hi
It would be better if you provided either str(yourdata) or dput(yourdata)
(or a part illustrating those 2 kinds of missing values)
Anyway I would use NA for missing and some other identifier for empty.
temp
a b c
1 1 empty
2 NA filled xx
3 2 filled xx
is.na(temp)
a b c
[1,] FALSE FALSE FALSE
[2,] TRUE FALSE FALSE
[3,] FALSE FALSE FALSE
dput(temp)
structure(list(a = c(1L, NA, 2L), b = structure(c(1L, 2L, 2L), .Label =
c("empty",
"filled"), class = "factor"), c = structure(c(1L, 2L, 2L), .Label = c("",
"xx"), class = "factor")), .Names = c("a", "b", "c"), class = "data.frame",
row.names = c(NA,
-3L))
str(temp)
'data.frame': 3 obs. of 3 variables:
$ a: int 1 NA 2
$ b: Factor w/ 2 levels "empty","filled": 1 2 2
$ c: Factor w/ 2 levels "","xx": 1 2 2
The only real NA value which can be used for imputation is in first column.
Regards
Petr
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
> project.org] On Behalf Of Ma Teresa Martinez Soriano
> Sent: Friday, July 19, 2013 11:28 AM
> To: r-help@R-project.org
> Subject: [R] R Help
>
> Hi
> everyone,
>
> I have
> a dataset which I am handling with
> R . Unfortunately I have two kinds of empty cells, one corresponds to
> missing values and the other one is empty because it has to.
>
> I 'm going
> to put an example (just a part of my dataset ) to try to clarify my
> question:
>
> missing
> values are represented withNAs
>
>
> Enterprise
> Data of Stablishment Earnings
> 2005 earning
> 2006 earnings 2007 earning 2008
>
> Enterprise
> 1
> 05/06/2007
> It has to be empty It has to be
> empty
> 2,3
> NA
>
> Enterprise
> 2
> 09/08/2005
> 2.3
> 3,6
> NA
> 1.6
>
>
>
> My intention is to find this missing values using imputation (library
> VIM) . How could I differenciate this NA with Cells that have to be
> empty?? I have tried putting Na for missing values and Nan for the
> others but it doesn't work because R imputes everythitng.
> Could you answer me
> to this e-mail
>
> Thanks in
> advance
>
>
> [[alternative HTML version deleted]]
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