Sorry, My bad.
A vector must be of a single class. When you declare c("in", "V>N",
round(runif(1, 7000, 16000), 0)) R will calculate the random number, but then
convert it to a character class to conform with the other two elements in that
vector. R then binds this to your original df and finds that it must add a
character to a numeric vector. To keep the vector of all the same class it
converts everything to character.
Better?
Tim
From: [email protected] <[email protected]>
Sent: Monday, September 19, 2022 8:07 AM
To: Ebert,Timothy Aaron <[email protected]>
Cc: [email protected]
Subject: Re: [R] Question concerning side effects of treating invalid factor
levels
[External Email]
Hi,
this is a misunderstanding of my question. I wasn't worried about invalid
factor levels that produce NA. My question was why a column changes its class,
which I thought was a side effect. If you add a vector containing one character
string, the class of the whole vector becomes _chr_. And after this element has
been added to a column, we have two NAs for the column which are factors, and a
character string, which is responsible for the change of a numerical vector
into a character string vector (see ?c, where you find: "The output type is
determined from the highest type of the components in the hierarchy NULL < raw
< logical < integer < double < complex < character < list < expression.").
Best
Tibor
Am 19.09.2022 um 13:59 schrieb Ebert,Timothy Aaron
<[email protected]<mailto:[email protected]>>:
In your example code, the variable remains a class factor, and all entries are
valid. The variables will behave as expected given the factor levels in the
original dataframe.
(At least on my system R 4.2, in RStudio, in Windows) R returns a couple of
error messages warning me that I was bad.
What you get is NA for "not available", or "not appropriate" or a missing
value. You gave the system an invalid factor level so it was entered as
missing. If you get data that has a new factor level, you need to tell R to
expect a new factor level first.
levels(f1) <- c(levels(f1),"New Level")
levels(f1) <- c(levels(f1),c("NL1","NL2"))
Tim
-----Original Message-----
From: R-help
<[email protected]<mailto:[email protected]>> On Behalf
Of Tibor Kiss via R-help
Sent: Monday, September 19, 2022 6:11 AM
To: [email protected]<mailto:[email protected]>
Subject: [R] Question concerning side effects of treating invalid factor levels
[External Email]
Dear List members,
I have tried now for several times to find out about a side effect of treating
invalid factor levels, but did not find an answer. Various answers on
stackexchange etc. produce the stuff that irritates me without even mentioning
it.
So I am asking the list (apologies if this has been treated in the past).
If you add an invalid factor level to a column in a data frame, this has the
side effect of turning a numerical column into a column with character strings.
Here is a simple example:
df <- data.frame(
P = factor(c("mittels", "mit", "mittels", "ueber", "mit", "mit")),
ANSWER = factor(c(rep("PP>OBJ", 4), rep("OBJ>PP", 2))),
RT = round(runif(6, 7000, 16000), 0))
str(df)
'data.frame': 6 obs. of 3 variables:
$ P : Factor w/ 3 levels "mit","mittels",..: 2 1 2 3 1 1
$ ANSWER: Factor w/ 2 levels "OBJ>PP","PP>OBJ": 2 2 2 2 1 1
$ RT : num 11157 13719 14388 14527 14686 ..
df <- rbind(df, c("in", "V>N", round(runif(1, 7000, 16000), 0)))
str(df)
'data.frame': 7 obs. of 3 variables:
$ P : Factor w/ 3 levels "mit","mittels",..: 2 1 2 3 1 1 NA
$ ANSWER: Factor w/ 2 levels "OBJ>PP","PP>OBJ": 2 2 2 2 1 1 NA
$ RT : chr "11478" "15819" "8305" "8852" ...
You see that RT has changed from _num_ to _chr_ as a side effect of adding the
invalid factor level as NA. I would appreciate understanding what the purpose
of the type coercion is.
Thanks in advance
Tibor
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