[R] Can I pass the grouped portions of a dataframe/tibble to a function in dplyr

[Rui Barradas]

Hello,

I forgot to say I redid the data set setting the RNG seed first.



set.seed(2020)
n <- 50
x <- 1:n
y <- sample(1:3, n, replace = TRUE)
z <- rnorm(n)
tib <- tibble(x,y,z)


Also, don't do

as_tibble(cbind(...))
as.data.frame(cbind(...))


If one of the variables is of a different class (example, "character") 
all variables are coerced to the least common denominator. It's much 
better to call tibble() or data.frame() directly.

Hope this helps,

Rui Barradas


Às 12:04 de 05/07/2020, Rui Barradas escreveu:
> Hello,
> 
> You can pass a grouped tibble to a function with grouped_modify but the 
> function must return a data.frame (or similar).
> 
> ## this will also do it
> #sillyFun <- function(tib){
> #  tibble(nrow = nrow(tib), ncol = ncol(tib))
> #}
> 
> 
> sillyFun <- function(tib){
>    data.frame(nrow = nrow(tib), ncol = ncol(tib)))
> }
> 
> tib %>%
>    group_by(y) %>%
>    group_modify(~ sillyFun(.))
> ## A tibble: 3 x 3
> ## Groups:   y [3]
> #      y  nrow  ncol
> #  <dbl> <int> <int>
> #1     1    17     2
> #2     2    21     2
> #3     3    12     2
> 
> 
> Hope this helps,
> 
> Rui Barradas
> 
> Às 09:43 de 05/07/2020, Chris Evans escreveu:
>> Apologies if this is a stupid question but searching keeps getting 
>> things I know and don't need.
>>
>> What I want to do is to use the group-by() power of dplyr to run 
>> functions that expect a dataframe/tibble per group but I can't see how 
>> do it. Here is a reproducible example.
>>
>> ### create trivial tibble
>> n <- 50
>> x <- 1:n
>> y <- sample(1:3, n, replace = TRUE)
>> z <- rnorm(n)
>> tib <- as_tibble(cbind(x,y,z))
>>
>> ### create trivial function that expects a tibble/data frame
>> sillyFun <- function(tib){
>> return(list(nrow = nrow(tib),
>> ncol = ncol(tib)))
>> }
>>
>> ### works fine on the whole tibble
>> tib %>%
>> summarise(dim = list(sillyFun(.))) %>%
>> unnest_wider(dim)
>>
>> That gives me:
>> # A tibble: 1 x 2
>>     nrow  ncol
>>    <int> <int>
>> 1    50     3
>>
>>
>> ### So I try the following hoping to apply the function to the grouped 
>> tibble
>> tib %>%
>> group_by(y) %>%
>> summarise(dim = list(sillyFun(.))) %>%
>> unnest_wider(dim)
>>
>> ### But that gives me:
>> # A tibble: 3 x 3
>>        y  nrow  ncol
>>    <dbl> <int> <int>
>> 1     1    50     3
>> 2     2    50     3
>> 3     3    50     3
>>
>> Clearly "." is still passing the whole tibble, not the grouped 
>> subsets.  What I can't find is whether there is an alternative to "." 
>> that would pass just the grouped subset of the tibble.
>>
>> I have bodged my way around this by writing a function that takes 
>> individual columns and reassembles them into a data frame that the 
>> actual functions I need to use require but that takes me back to a lot 
>> of clumsiness both selecting the variables to pass in the dplyr call 
>> to the function and putting the reassemble-to-data-frame bit in the 
>> function I call.  (The functions I really need are reliability 
>> explorations and can called on whole dataframes.)
>>
>> I know I can do this using base R split and lapply but I feel sure it 
>> must be possible to do this within dplyr/tidyverse.  I'm slowly 
>> transferring most of my code to the tidyverse and hitting frustrations 
>> but also finding that it does really help me program more sensibly, 
>> handle relational data structures more easily, and write code that I 
>> seem better at reading when I come back to it after months on other 
>> things so I am slowly trying to move all my coding to tidyverse.  If I 
>> could see how to do this, it would help.
>>
>> Very sorry if the answer should be blindingly obvious to me.  I'd also 
>> love to have pointers to guidance to the tidyverse written for people 
>> who aren't professional coders or statisticians and that go a bit 
>> beyond the obvious basics of tidyverse into issues like this.
>>
>> TIA,
>>
>> Chris
>>
> 

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