[R] writing a function to work with dplyr::mutate()

[Steven Rigatti]

This works perfectly. Ah, just needed a vector as output instead of a
1-column df.
Thank you!!!

On Tue, Jan 19, 2021 at 2:18 PM Bill Dunlap <williamwdunlap using gmail.com>
wrote:

> Your translate... function seems unnecessarily complicated and reusing the
> name 'var' for both the input and the data.frame containing the input makes
> it confusing to me.  The following replacement, f, uses your algorithm but
> I think gets the answer you want.
>
> f <-
> function(var, upper, lookup) {
>     names(lookup) <- c('old','new')
>     var_df <- data.frame(old = var)
>     lookup2 <- data.frame(old = c(1:upper),
>                           new = c(1:upper))
>     lookup3 <- rbind(lookup, lookup2)
>     res <- left_join(var_df, lookup3, by = 'old')
>     res$new # return a vector, not a data.frame or tibble.
> }
> E.g.,
> > data.frame(XXX=c(95,93,10,20), YYY=c(55,66,93,98)) %>% mutate( YYY_mm =
> f(YYY, 90, lup))
>   XXX YYY YYY_mm
> 1  95  55     55
> 2  93  66     66
> 3  10  93      3
> 4  20  98     NA
>
> You can modify this so that it names the output column based on the name
> of the input column (by returning a data.frame/tibble instead of a numeric
> vector):
>
> f1 <-
> function(var, upper, lookup,  new_varname =
> paste0(deparse1(substitute(var)), "_mm")) {
>     names(lookup) <- c('old',new_varname)
>     var_df <- data.frame(old = var)
>     lookup2 <- data.frame(old = c(1:upper),
>                           new = c(1:upper))
>     names(lookup2)[2] <- new_varname
>     lookup3 <- rbind(lookup, lookup2)
>     res <- left_join(var_df, lookup3, by = 'old')[2]
>     res
> }
> E.g.,
> > data.frame(XXX=c(95,93,10,20), YYY=c(55,66,93,98)) %>% mutate( f1(YYY,
> 90, lup))
>   XXX YYY YYY_mm
> 1  95  55     55
> 2  93  66     66
> 3  10  93      3
> 4  20  98     NA
>
> -Bill
>
> On Tue, Jan 19, 2021 at 10:24 AM Steven Rigatti <sjrigatti using 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??
>>
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>>
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>>
>

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