R help - Sep 2021 - tidyverse: grouped summaries (with summarize) [RESOLVED]

As Eric has pointed out, perhaps Rich is not thinking pipelined. Summarize()
takes a first argument as:
	summarise(.data=whatever, ...)

But in a pipeline, you OMIT the first argument and let the pipeline supply an
argument silently.

What I think summarize saw was something like:

summarize(. , disc_by_month, vol = mean(cfs, na.rm = TRUE))

There is now a superfluous SECOND argument in a place it expected not a
data.frame type of variable but the name of a column in the hidden
data.frame-like object it was passed. You do not have a column called
disc_by_month and presumably some weird logic made it suggest it was replacing
that by the first column or something.

I hope this makes sense. You do not cobble a pipeline together from parts
without carefully making sure all first arguments otherwise used are NOT used.

And, just FYI, the subject line should not use a word that some see as the
opposite companion of "winterize" ...

-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of Rich Shepard
Sent: Monday, September 13, 2021 5:51 PM
To: r-help at r-project.org
Subject: Re: [R] tidyverse: grouped summaries (with summerize)

On Mon, 13 Sep 2021, Rich Shepard wrote:
> That's what I thought I did. I'll rewrite the script and work
toward
> the output I need.
Still not the correct syntax. Command is now:
disc_by_month %>%
     group_by(year, month) %>%
     summarize(disc_by_month, vol = mean(cfs, na.rm = TRUE))

and results are:
> source('disc.R')
`summarise()` has grouped output by 'year', 'month'. You can
override using the `.groups` argument.
> disc_by_month
# A tibble: 590,940 ? 6
# Groups:   year, month [66]
     year month   day  hour   min    cfs
    <int> <int> <int> <int> <int>  <dbl>
  1  2016     3     3    12     0 149000
  2  2016     3     3    12    10 150000
  3  2016     3     3    12    20 151000
  4  2016     3     3    12    30 156000
  5  2016     3     3    12    40 154000
  6  2016     3     3    12    50 150000
  7  2016     3     3    13     0 153000
  8  2016     3     3    13    10 156000
  9  2016     3     3    13    20 154000
10  2016     3     3    13    30 155000
# ? with 590,930 more rows

The grouping is still not right. I expected to see a mean value for each month
of each year in the data set, not for each minute.

Rich

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On Mon, 13 Sep 2021, Avi Gross via R-help wrote:
> As Eric has pointed out, perhaps Rich is not thinking pipelined.
Summarize() takes a first argument as:
> 	summarise(.data=whatever, ...)
>
> But in a pipeline, you OMIT the first argument and let the pipeline supply
an argument silently.
Avi,

Thank you. I read your message carefully and re-read the example on the
bottom of page 60 and top of page 61. Then changed the command to:
disc_by_month = disc %>%
     group_by(year, month) %>%
     summarize(vol = mean(cfs, na.rm = TRUE))

And, the script now returns what I need:
> disc_by_month
# A tibble: 66 ? 3
# Groups:   year [7]
     year month     vol
    <int> <int>   <dbl>
  1  2016     3 221840.
  2  2016     4 288589.
  3  2016     5 255164.
  4  2016     6 205371.
  5  2016     7 167252.
  6  2016     8 140465.
  7  2016     9  97779.
  8  2016    10 135482.
  9  2016    11 166808.
10  2016    12 165787.

I missed the beginning of the command where the resulting dataframe needs to
be named first.

This clarifies my understanding and I appreciate your and Eric's help.

Regards,

Rich