This has nothing to do with data frames and everything to do with how factors
behave.
The levels of a factor are not necessarily linked with the content of the
factor. For example, a factor representing "Male" and "Female" has both of
those levels even if all the data in a subset represents "Male".
If you want traces of those eliminated values removed, consider using character
data rather than factors. In particular, using the as.is=TRUE or the
stringsAsFactors= FALSE argument to read.table and similar functions will
prevent automatic generation of factors. You can then choose when to convert to
factor after you have manipulated your data.
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Sent from my phone. Please excuse my brevity.
Raoni Rodrigues <caciquesamu...@gmail.com> wrote:
>Hello all,
>
>I don't understand a strange behavior in data frame manipulation.
>
>data_frame1 = data.frame(Site = c("S1", "S2", "S3", "S4", "L1", "L2",
>"L3", "L4"),
> Number = c(1, 3, 5, 2, 1, 1, 2, 1))
>
>data_frame2 = data_frame1 [data_frame1$Site != "S1", ]
>
>dput (data_frame2)
>
>structure(list(Site = structure(c(6L, 7L, 8L, 1L, 2L, 3L, 4L), .Label =
>c("L1",
>"L2", "L3", "L4", "S1", "S2", "S3", "S4"), class = "factor"),
> Number = structure(c(3L, 4L, 2L, 1L, 1L, 2L, 1L), .Label = c("1",
> "2", "3", "5"), class = "factor")), .Names = c("Site", "Number"
>), row.names = 2:8, class = "data.frame")
>
>Why site "S1" do not disappeared from data_frame2's structure?
>
>And what I have to do to eliminate it definitively from my new data
>frame (data_frame2)?
>
>Sorry for this basic question, but I really did not understand...
>
>Thanks in advanced,
>
>Raoni
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