Re: [R] Can I pass the grouped portions of a dataframe/tibble to a function in dplyr
Ouch. I should have know all those points Rui: my bad. Casual behaviour while
just rushing up a little example. Good to be reminded.
group_modify() is clearly exactly what I wanted and I will experiment with it
and make sure I understand it properly. I see from the help that it evolves
from, or supercedes aspects of do() which I think must have been the function I
had forgotten. Even more interestingly I see that it seems to lead me into
interesting options and experimental developments in tidyverse that I didn't
know.
Excellent. Perfect help ... many thanks!
Chris
- Original Message -
> From: "Rui Barradas"
> To: "Chris Evans" , "R-help"
> Sent: Sunday, 5 July, 2020 13:16:19
> Subject: Re: [R] Can I pass the grouped portions of a dataframe/tibble to a
> function in dplyr
> 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
>> #
>> #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
>>>
>>> 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
>>>
>>> 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
>>>
>>
>
> --
> Este e-mail foi verificado em termos de vírus pelo software antivírus Avast.
> https://www.avast.com/antivirus
--
Small contribution in our coronavirus rigours:
Re: [R] Can I pass the grouped portions of a dataframe/tibble to a function in dplyr
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
#
#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
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
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
--
Este e-mail foi verificado em termos de vírus pelo software antivírus Avast.
https://www.avast.com/antivirus
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] Can I pass the grouped portions of a dataframe/tibble to a function in dplyr
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
#
#1 117 2
#2 221 2
#3 312 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
150 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
1 150 3
2 250 3
3 350 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
--
Este e-mail foi verificado em termos de vírus pelo software antivírus Avast.
https://www.avast.com/antivirus
__
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.
