[R] missing values error in if statement

Avi Gross @v|gro@@ @end|ng |rom ver|zon@net
Sat May 21 04:54:38 CEST 2022 

Neha,

This forum tends to be focused on General R help and your initial question might have qualified. 

As you helped us understand better, it became obvious the proximal source of your problem was deep in a package that created a special plot driver called if the argument to the generic plot() function was of class fairness_object

I have no experience using that package and probably few others here do either. Your traceback shows an error happening several functions deeper. Your bug can be in "fc" as a variable before plotting it or something not anticipated or coded for in the custom plot function.

Yes, an "if" statement is the proximal point of failure but I suggest it did exactly what it should do given the arguments. Some people writecode protectively like checking for is.na() before calling anything that might break badly or surrounding an area of code with a try() of some kind to catch and handle errors.

You have used various packages in your code so you need to monitor if any of the functions you used to change your data introduced an NA. If not, the package maintainer or some forum that focuses on it may be your best bet. 

Failing that, are there other packages you might use to do your analysis, perhaps including parts you write for yourself by hand?


-----Original Message-----
From: Neha gupta <neha.bologna90 using gmail.com>
To: PIKAL Petr <petr.pikal using precheza.cz>
Cc: r-help mailing list <r-help using r-project.org>
Sent: Fri, May 20, 2022 9:22 am
Subject: Re: [R] missing values error in if statement

What do you mean by "fraction" ?

traceback()
4: readable_number(max_value - min_value, FALSE)
3: get_nice_ticks(lower_bound, upper_bound)
2: plot.fairness_object(fc)
1: plot(fc)

On Fri, May 20, 2022 at 3:18 PM PIKAL Petr <petr.pikal using precheza.cz> wrote:

> Hallo
>
> From what you say the error comes from
>
> > fraction <- NA
> > if(fraction <= 1) print(5)
> Error in if (fraction <= 1) print(5) :
>  missing value where TRUE/FALSE needed
> >
> so somewhere fraction is set to NA during your code.
>
> I would consult traceback, you could try debug used functions but maybe you
> should start with explainer, prot and privileged, if they are as expected
> by
> fairness_check
>
> > > fc= fairness_check(explainer,
> > >                          protected = prot,
> > >                    privileged = privileged)
>
> Cheers
> Petr
>
> > -----Original Message-----
> > From: R-help <r-help-bounces using r-project.org> On Behalf Of Neha gupta
> > Sent: Friday, May 20, 2022 3:03 PM
> > To: Jeff Newmiller <jdnewmil using dcn.davis.ca.us>
> > Cc: r-help mailing list <r-help using r-project.org>
> > Subject: Re: [R] missing values error in if statement
> >
> > Actually I am not very sure where exactly the error raised but when I run
> the
> > plot(fc) , it shows the error.
> >
> > I checked it online and people suggested that it may come with missing
> > values in 'if' or 'while; statements etc.
> >
> > I do not know how your code works and mine not.
> >
> > Best regards
> >
> > On Fri, May 20, 2022 at 10:16 AM Neha gupta
> > <neha.bologna90 using gmail.com>
> > wrote:
> >
> > > I am sorry.. The code is here and data is provided at the end of this
> > > email.
> > >
> > > data = readARFF("aho.arff")
> > >
> > > index= sample(1:nrow(data), 0.7*nrow(data)) train= data[index,] test=
> > > data[-index,]
> > >
> > > task = TaskClassif$new("data", backend = train, target = "isKilled")
> > > learner= lrn("classif.randomForest", predict_type = "prob") model=
> > > learner$train(task )
> > >
> > > ///explainer is created to identify a bias in a particular feature
> > > i.e. CE feature in this case
> > >
> > > explainer = explain_mlr3(model,
> > >                          data = test[,-15],
> > >                          y = as.numeric(test$isKilled)-1,
> > >                          label="RF")
> > > prot <- ifelse(test$CE == '2', 1, 0)      /// Error comes here
> > > privileged <- '1'
> > >
> > >
> > > fc= fairness_check(explainer,
> > >                          protected = prot,
> > >                    privileged = privileged)
> > > plot(fc)
> > >
> > >
> > > ////////////////////////////////////////// my data is
> > >
> > > dput(test)
> > > structure(list(DepthTree = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1), NumSubclass = c(0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 2), McCabe = c(1, 1, 1, 3, 3, 3, 3, 1, 2, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 2, 2, 2, 1, 2, 2, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,
> > > 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 2, 2, 2, 2, 5, 5, 5, 5, 5,
> > > 5, 5, 5, 5, 5, 5, 5, 5, 5, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2,
> > > 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 4, 4, 1, 1, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1), LOC = c(3,
> > > 3, 4, 10, 10, 10, 10, 4, 5, 22, 22, 22, 22, 22, 22, 22, 22, 3, 3, 3,
> > > 3, 8, 8, 4, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23,
> > > 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 8, 8, 8, 16, 16, 16, 16, 16,
> > > 16, 16, 16, 16, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 7, 7,
> > > 7, 7, 18, 18, 18, 18, 18, 18, 15, 15, 15, 15, 15, 15, 15, 15, 6, 6, 6,
> > > 15, 15, 15, 15, 15, 15, 9, 9, 9, 9, 9, 9, 9, 4, 4, 3, 3, 3, 3, 4, 4,
> > > 4, 5, 8, 8, 3, 3, 3, 7, 7, 3, 3, 15, 15, 15, 15, 15, 15, 15, 15, 3, 3,
> > > 3, 4, 4, 4, 4, 8, 8, 8, 8, 4, 3), DepthNested = c(1, 1, 1, 2, 2, 2, 2,
> > > 1, 2, 4, 4, 4, 4, 4, 4, 4, 4, 1, 1, 1, 1, 2, 2, 1, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2,
> > > 2, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1,
> > > 1), CA = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
> > > 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1,
> > > 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1), CE = c(2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
> > > 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 2, 2),
> > > Instability = c(0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.667, 0.667, 0.667,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0.667, 0, 0, 0, 0, 0.667,
> > > 0.667), numCovered = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 123,
> > > 54, 54, 54, 123, 54, 54, 39, 84, 54, 54, 15, 138, 189, 189, 189, 27,
> > > 51, 33, 6, 27, 27, 150, 150, 150, 54, 150, 54, 54, 150, 117, 51, 66,
> > > 60, 15, 15, 72, 12, 45, 255, 255, 129, 129, 129, 0, 129, 0, 0, 6, 6,
> > > 6, 303, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 15, 12, 12, 12, 18, 12,
> > > 12, 48, 12, 1557, 48, 12, 171, 0, 0, 0, 141, 141, 45, 141, 18, 39),
> > > operator = structure(c(4L, 13L, 13L, 1L, 4L, 9L, 12L, 4L, 11L, 4L, 7L,
> > > 8L, 8L, 8L, 8L, 8L, 9L, 7L, 8L, 8L, 6L, 7L, 8L, 4L, 1L, 2L, 3L, 4L,
> > > 7L, 8L, 8L, 8L, 8L, 8L, 9L, 11L, 12L, 12L, 4L, 6L, 7L, 7L, 7L, 8L, 8L,
> > > 8L, 8L, 8L, 6L, 9L, 9L, 4L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 10L, 1L, 1L,
> > > 1L, 7L, 7L, 8L, 8L, 8L, 8L, 8L, 13L, 13L, 7L, 8L, 8L, 9L, 8L, 8L, 8L,
> > > 8L, 9L, 10L, 1L, 4L, 4L, 6L, 7L, 8L, 8L, 8L, 9L, 10L, 10L, 7L, 8L, 8L,
> > > 10L, 11L, 11L, 7L, 8L, 4L, 8L, 9L, 10L, 10L, 4L, 10L, 7L, 7L, 10L, 6L,
> > > 8L, 8L, 10L, 8L, 8L, 10L, 9L, 8L, 10L, 7L, 7L, 13L, 2L, 2L, 2L, 8L,
> > > 8L, 8L, 8L, 8L, 11L, 10L, 10L, 13L, 13L, 8L, 8L, 8L, 6L, 7L, 8L, 10L,
> > > 13L, 13L), .Label = c("T0", "T1", "T2", "T3", "T4", "T5", "T6", "T7",
> > > "T8", "T9", "T10", "T11", "T12", "T13", "T14", "T15"), class =
> > > "factor"), methodReturn = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> > > 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> > > 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> > > 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 4L, 4L, 4L,
> > > 4L, 4L, 4L, 4L, 4L, 4L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 3L, 3L,
> > > 3L, 1L, 4L, 4L, 4L, 2L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 4L, 4L,
> > > 4L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 2L, 2L, 4L, 4L, 4L, 1L, 1L, 1L, 1L,
> > > 2L, 2L), .Label = c("I", "V", "Z", "method", "D", "[D", "[[D", "J",
> > > "[I", "C", "[J", "[C", "[S", "F", "[F", "[B", "S", "B", "[Z", "[[S",
> > > "[[B", "[[Z"), class = "factor"), numTestsCover = c(16, 16, 16, 15,
> > > 15, 16, 15, 4, 16, 16, 15, 16, 15, 15, 15, 15, 15, 3, 3, 3, 2, 16, 11,
> > > 4, 16, 3, 16, 16, 16, 16, 16, 4, 16, 16, 16, 4, 16, 16, 3, 3, 3, 2, 4,
> > > 3, 2, 1, 4, 1, 15, 16, 15, 2, 3, 2, 3, 3, 2, 2, 2, 3, 4, 5, 5, 5, 4,
> > > 5, 5, 4, 4, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4, 5, 4, 5,
> > > 5, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 6, 6, 6, 0, 6, 0, 0, 2, 2, 2,
> > > 7, 0, 0, 0, 15, 16, 16, 16, 15, 17, 17, 17, 15, 5, 4, 4, 4, 3, 4, 4,
> > > 3, 4, 16, 16, 4, 17, 0, 0, 0, 5, 5, 3, 5, 2, 3), mutantAssert = c(55,
> > > 55, 55, 55, 55, 55, 55, 13, 55, 55, 55, 55, 55, 55, 55, 55, 55, 9, 9,
> > > 9, 9, 55, 41, 13, 55, 5, 55, 55, 55, 55, 55, 13, 55, 55, 55, 13, 55,
> > > 55, 13, 13, 13, 8, 13, 13, 8, 4, 13, 4, 55, 55, 55, 9, 9, 9, 9, 9, 9,
> > > 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 5,
> > > 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 6, 9, 9, 9, 14, 14,
> > > 14, 0, 14, 0, 0, 2, 2, 2, 15, 0, 0, 0, 55, 58, 58, 55, 55, 58, 58, 58,
> > > 55, 9, 6, 6, 6, 6, 6, 6, 6, 6, 55, 55, 13, 57, 0, 0, 0, 11, 11, 7, 11,
> > > 9, 9), classAssert = c(3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
> > > 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 10, 10, 10, 10, 10, 10,
> > > 10, 10, 10, 10, 10, 10, 10, 10, 10, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
> > > 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 1, 1, 1, 1, 3, 3, 3, 3, 0, 0), isKilled
> > > = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
> > > 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> > > 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L,
> > > 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
> > > 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L,
> > > 1L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L), .Label = c("yes",
> > > "no"), class = "factor")), row.names = c(3L, 4L, 5L, 7L, 9L, 17L, 20L,
> > > 21L, 26L, 28L, 32L, 33L, 40L, 43L, 45L, 49L, 54L, 62L, 64L, 65L, 70L,
> > > 75L, 77L, 81L, 84L, 86L, 88L, 89L, 93L, 95L, 97L, 99L, 101L, 102L,
> > > 106L, 111L, 112L, 113L, 118L, 122L, 125L, 128L, 129L, 134L, 141L,
> > > 142L, 143L, 146L, 156L, 168L, 169L, 174L, 178L, 179L, 182L, 184L,
> > > 185L, 192L, 193L, 195L, 197L, 198L, 199L, 203L, 205L, 209L, 211L,
> > > 215L, 216L, 218L, 220L, 224L, 227L, 228L, 230L, 233L, 243L, 244L,
> > > 246L, 247L, 251L, 252L, 259L, 262L, 263L, 265L, 270L, 273L, 274L,
> > > 275L, 284L, 285L, 286L, 291L, 296L, 297L, 300L, 301L, 306L, 314L,
> > > 316L, 322L, 328L, 331L, 332L, 333L, 336L, 341L, 346L, 347L, 348L,
> > > 360L, 363L, 366L, 367L, 383L, 392L, 395L, 398L, 404L, 408L, 409L,
> > > 410L, 420L, 421L, 426L, 428L, 434L, 437L, 438L, 440L, 441L, 447L,
> > > 449L, 450L, 452L, 454L, 457L, 458L, 459L, 463L, 465L, 469L, 471L,
> > > 472L, 483L), class = "data.frame")
> > >
> > > On Fri, May 20, 2022 at 12:20 AM Jeff Newmiller
> > > <jdnewmil using dcn.davis.ca.us>
> > > wrote:
> > >
> > >> Not reproducible. Posted HTML.
> > >>
> > >> On May 19, 2022 2:30:58 PM PDT, Neha gupta
> > <neha.bologna90 using gmail.com>
> > >> wrote:
> > >> >Why do I get the following error when my variable in the 'if
> statement'
> > >> has
> > >> >no missing values.
> > >> >
> > >> >I check with is.na(my variable) and it has no missing values
> > >> >
> > >> >Error in if (fraction <= 1) { : missing value where TRUE/FALSE
> > >> >needed
> > >> >
> > >> >Best regards
> > >> >
> > >> >      [[alternative HTML version deleted]]
> > >> >
> > >> >______________________________________________
> > >> >R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > >> >https://stat.ethz.ch/mailman/listinfo/r-help
> > >> >PLEASE do read the posting guide
> > >> http://www.R-project.org/posting-guide.html
> > >> >and provide commented, minimal, self-contained, reproducible code.
> > >>
> > >> --
> > >> Sent from my phone. Please excuse my brevity.
> > >>
> > >
> >
> >      [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>

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______________________________________________
R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

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