Second this. There is also the findInterval function, which omits the factor
attributes and just returns integers that can be used in lookup tables.
On January 19, 2021 10:33:59 AM PST, Bert Gunter <bgunter.4...@gmail.com> wrote:
>If you are willing to entertain another approach, have a look at ?cut.
>By
>defining the 'breaks' argument appropriately, you can easily create a
>factor that tells you which values should be looked up and which
>accepted
>as is. If I understand correctly, this seems to be what you want. If I
>have
>not, just ignore and wait for a more useful reply.
>
>Cheers,
>Bert
>
>Bert Gunter
>
>"The trouble with having an open mind is that people keep coming along
>and
>sticking things into it."
>-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
>On Tue, Jan 19, 2021 at 10:24 AM Steven Rigatti <sjriga...@gmail.com>
>wrote:
>
>> I am having some problems with what seems like a pretty simple issue.
>I
>> have some data where I want to convert numbers. Specifically, this is
>> cancer data and the size of tumors is encoded using millimeter
>> measurements. However, if the actual measurement is not available the
>> coding may imply a less specific range of sizes. For instance numbers
>0-89
>> may indicate size in mm, but 90 indicates "greater than 90 mm" , 91
>> indicates "1 to 2 cm", etc. So, I want to translate 91 to 90, 92 to
>15,
>> etc.
>>
>> I have many such tables so I would like to be able to write a
>function
>> which takes as input a threshold over which new values need to be
>looked
>> up, and the new lookup table, returning the new values.
>>
>> I successfully wrote the function:
>>
>> translate_seer_numeric <- function(var, upper, lookup) {
>> names(lookup) <- c('old','new')
>> names(var) <- 'old'
>> var <- as.data.frame(var)
>> lookup2 <- data.frame(old = c(1:upper),
>> new = c(1:upper))
>> lookup3 <- rbind(lookup, lookup2)
>> print(var)
>> res <- left_join(var, lookup3, by = 'old') %>%
>> select(new)
>>
>> res
>>
>> }
>>
>> test1 <- data.frame(old = c(99,95,93, 8))lup <- data.frame(bif =
>c(93, 95,
>> 99),
>> new = c(3, 5, NA))
>> translate_seer_numeric(test1, 90, lup)
>>
>> The above test generates the desired output:
>>
>> old1 992 953 934 8
>> new1 NA2 53 34 8
>>
>> My problem comes when I try to put this in line with pipes and the
>mutate
>> function:
>>
>> test1 %>%
>> mutate(varb = translate_seer_numeric(var = old, 90, lup))####
>> Error: Problem with `mutate()` input `varb`.
>> x Join columns must be present in data.
>> x Problem with `old`.
>> i Input `varb` is `translate_seer_numeric(var = test1$old, 90, lup)`.
>>
>> Thoughts??
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@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.
>>
>
> [[alternative HTML version deleted]]
>
>______________________________________________
>R-help@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.
______________________________________________
R-help@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.
