Thanks Eric,
That's very neat! Sort of fits my belief about base R and telegrams (that's
not knocking it, I really do respect it, my wetware is just not good at it).
For many reasons, particularly the convenience for formatting and passing on
results from the real function I'm applying, I am really keen to find
tidyverse/dplyr answers/options. Any offers?!
TIA (all),
Chris
----- Original Message -----
> From: "Eric Berger" <ericjber...@gmail.com>
> To: "Chris Evans" <chrish...@psyctc.org>
> Cc: "r-help" <r-help@r-project.org>
> Sent: Monday, 21 September, 2020 15:03:44
> Subject: Re: [R] Is there a simple way to analyse all the data using dplyr?
> Hi,
> I am not sure if the request is about a 'simple way' or requires
> dplyr. Here's an approach without using dplyr that is just 2 lines
> (not counting creating the data or outputting the result).
>
> n <- 500
> myDf <- data.frame( gender=sample(c("Man","Woman","Other"), n, replace =
> TRUE),
> GPC_score=rnorm(n), scaleMeasures=runif(n))
> aL <- list(Man="Man",Woman="Woman",All=c("Man","Woman","Other"))
> z <- sapply( 1:length(aL), function(i) { x=myDf[ myDf$gender %in%
> aL[[i]], ]; cor(x[,2],x[,3]) } )
> names(z) <- names(aL)
> z
>
> HTH,
> Eric
>
>
> On Mon, Sep 21, 2020 at 3:13 PM Chris Evans <chrish...@psyctc.org> wrote:
>>
>> I am sure the answer is "yes" and I'm also sure the question may sound mad.
>> Here's a reprex that I think captures what I'm doing
>>
>> n <- 500
>> gender <- sample(c("Man","Woman","Other"), n, replace = TRUE)
>> GPC_score <- rnorm(n)
>> scaleMeasures <- runif(n)
>> bind_cols(gender = gender,
>> GPC_score = GPC_score,
>> scaleMeasures = scaleMeasures) -> tibUse
>>
>> ### let's have the correlation between the two variables broken down by
>> gender
>> tibUse %>%
>> filter(gender != "Other") %>%
>> select(gender, GPC_score, scaleMeasures) %>%
>> na.omit() %>%
>> group_by(gender) %>%
>> summarise(cor = cor(cur_data())[1,2]) -> tmp1
>>
>> ### but I'd also like the correlation for the whole dataset, not by gender
>> ### this is a kludge to achieve that which I am using partly because I cant'
>> ### find the equivalent of cur_data() for an ungrouped tibble/df
>> tibUse %>%
>> mutate(gender = "All") %>% # nasty kludge to get all the data!
>> select(gender, GPC_score, scaleMeasures) %>%
>> na.omit() %>%
>> group_by(gender) %>% # ditto!
>> summarise(cor = cor(cur_data())[1,2]) -> tmp2
>>
>> bind_rows(tmp1,
>> tmp2)
>>
>> ### gets me what I want:
>> # A tibble: 3 x 2
>> gender cor
>> <chr> <dbl>
>> 1 Man 0.0225
>> 2 Woman 0.0685
>> 3 All 0.0444
>>
>> In reality I have some functions that are more complex than cor()[2,1] (sorry
>> about that particular kludge) that digest dataframes and I'd love to have a
>> simpler way of doing this.
>>
>> So two questions:
>> 1) I am sure there a term/function that works on an ungrouped tibble in
>> dplyr as
>> cur_data() does for a grouped tibble ... but I can't find it.
>> 2) I suspect someone has automated a way to get the analysis of the complete
>> data after the analyses of the groups within a single dplyr run ... it seems
>> an
>> obvious and common use case, but I can't find that either.
>>
>> Sorry, I'm over 99% sure I'm being stupid and missing the obvious here ...
>> but
>> that's the recurrent problem I have with my wetware and searchware doesn't
>> seem
>> to being fixing this!
>>
>> TIA,
>>
>> Chris
>>
>> --
>> Small contribution in our coronavirus rigours:
>> https://www.coresystemtrust.org.uk/home/free-options-to-replace-paper-core-forms-during-the-coronavirus-pandemic/
>>
>> Chris Evans <ch...@psyctc.org> Visiting Professor, University of Sheffield
>> <chris.ev...@sheffield.ac.uk>
>> I do some consultation work for the University of Roehampton
>> <chris.ev...@roehampton.ac.uk> and other places
>> but <ch...@psyctc.org> remains my main Email address. I have a work web site
>> at:
>> https://www.psyctc.org/psyctc/
>> and a site I manage for CORE and CORE system trust at:
>> http://www.coresystemtrust.org.uk/
>> I have "semigrated" to France, see:
>> https://www.psyctc.org/pelerinage2016/semigrating-to-france/
>>
>> https://www.psyctc.org/pelerinage2016/register-to-get-updates-from-pelerinage2016/
>>
>> If you want an Emeeting, I am trying to keep them to Thursdays and my diary
>> is
>> at:
>> https://www.psyctc.org/pelerinage2016/ceworkdiary/
>> Beware: French time, generally an hour ahead of UK.
>>
>> ______________________________________________
>> 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.
--
Small contribution in our coronavirus rigours:
https://www.coresystemtrust.org.uk/home/free-options-to-replace-paper-core-forms-during-the-coronavirus-pandemic/
Chris Evans <ch...@psyctc.org> Visiting Professor, University of Sheffield
<chris.ev...@sheffield.ac.uk>
I do some consultation work for the University of Roehampton
<chris.ev...@roehampton.ac.uk> and other places
but <ch...@psyctc.org> remains my main Email address. I have a work web site
at:
https://www.psyctc.org/psyctc/
and a site I manage for CORE and CORE system trust at:
http://www.coresystemtrust.org.uk/
I have "semigrated" to France, see:
https://www.psyctc.org/pelerinage2016/semigrating-to-france/
https://www.psyctc.org/pelerinage2016/register-to-get-updates-from-pelerinage2016/
If you want an Emeeting, I am trying to keep them to Thursdays and my diary is
at:
https://www.psyctc.org/pelerinage2016/ceworkdiary/
Beware: French time, generally an hour ahead of UK.
______________________________________________
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.
