Message-ID: <5e822ed0-2285-306e-7ee5-c90e444812ef@sapo.pt>
Date: 2020-07-05T11:16:19Z
From: Rui Barradas
Subject: Can I pass the grouped portions of a dataframe/tibble to a function in dplyr
In-Reply-To: <95eb1446-5dd4-eeec-f992-4d6ca922992b@sapo.pt>
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
?s 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
>
> ?s 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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