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List: r-help
Subject: Re: [R] Is there a simple way to analyse all the data using dplyr?
From: Chris Evans <chrishold () psyctc ! org>
Date: 2020-09-21 16:05:14
Message-ID: 2053406566.5018001.1600704314331.JavaMail.zimbra () psyctc ! org
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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" <ericjberger@gmail.com>
> To: "Chris Evans" <chrishold@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 <chrishold@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 <chris@psyctc.org> Visiting Professor, University of Sheffield
> > <chris.evans@sheffield.ac.uk>
> > I do some consultation work for the University of Roehampton
> > <chris.evans@roehampton.ac.uk> and other places
> > but <chris@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 <chris@psyctc.org> Visiting Professor, University of Sheffield \
<chris.evans@sheffield.ac.uk> I do some consultation work for the University of \
Roehampton <chris.evans@roehampton.ac.uk> and other places but <chris@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.
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