Hi Rui,
Thank you very much!
Yes, I verified using real data, it worked correctly as expected after adding
tidyr:: to the pivot_longer function and dplyr:: to the group_by and summarize
Function.
I did not know how to assign the tidyr and dplyr to the three functions because
I do not really understand well the three functions and just got the code from
a google search.
I also tried your simplified code, but got the following error
Error in `dplyr::summarize()`:
! Can't supply both `.by` and `.groups`.
Run `rlang::last_trace()` to see where the error occurred.
Ding
From: Rui Barradas <ruipbarra...@sapo.pt>
Sent: Wednesday, June 12, 2024 11:29 AM
To: Yuan Chun Ding <ycd...@coh.org>; CALUM POLWART <polc1...@gmail.com>
Cc: r-help@r-project.org
Subject: Re: [R] my R code worked well when running the first 1000 lines of R
code
Hello, Inline. Às 19: 03 de 12/06/2024, Yuan Chun Ding via R-help escreveu: > I am sorry
that I know I should provide a dataset that allows to replicate my problem. > > It is
a research dataset and quite large, so I can not share. >
Hello,
Inline.
Às 19:03 de 12/06/2024, Yuan Chun Ding via R-help escreveu:
I am sorry that I know I should provide a dataset that allows to replicate my
problem.
It is a research dataset and quite large, so I can not share.
Both Bert and Tim guessed my problem correctly. I also thought about the
conflicting issue between different packages and function masking.
I just hope to that someone has similar experience, so providing me suggestion.
For conflicting issue,
What I tried was to add dplyr::pivot_longer or tidyr:: pivot_longer,
Do that to all functions comming from contributed packages. At least to
those.
summary_anno1148ft <- anno1148ft %>%
tidyr::pivot_longer(c(t_depth, t_alt_count, t_alt_ratio), names_to =
"measure") %>%
dplyr::group_by(dat, measure) %>%
dplyr::summarize(minimum = min(value,na.rm=T),
q25 = quantile(value, probs = 0.25,na.rm=T),
med = median(value,na.rm=T),
q75 = quantile(value, probs = 0.75,na.rm=T),
maximum = max(value,na.rm=T),
average = mean(value,na.rm=T),
#standard_deviation = sd(value),
.groups = "drop"
)
Or, simpler, no need to group_by anymore. It can be done in summarise.
summary_anno1148ft <- anno1148ft %>%
tidyr::pivot_longer(c(t_depth, t_alt_count, t_alt_ratio), names_to =
"measure") %>%
dplyr::summarize(minimum = min(value,na.rm=T),
q25 = quantile(value, probs = 0.25,na.rm=T),
med = median(value,na.rm=T),
q75 = quantile(value, probs = 0.75,na.rm=T),
maximum = max(value,na.rm=T),
average = mean(value,na.rm=T),
#standard_deviation = sd(value),
.by = c(dat, measure),
.groups = "drop"
)
This is only a guess, the question cannot really be answered.
Hope this helps,
Rui Barradas
but still not resolved the problem.
I will restart from the first line my code, it will work again and then I will
track down.
Thank you,
Ding
From: CALUM POLWART <polc1...@gmail.com<mailto:polc1...@gmail.com>>
Sent: Wednesday, June 12, 2024 10:52 AM
To: Yuan Chun Ding <ycd...@coh.org<mailto:ycd...@coh.org>>
Cc: r-help@r-project.org<mailto:r-help@r-project.org>
Subject: Re: [R] my R code worked well when running the first 1000 lines of R
code
I sometimes think people on this list are quite rude to posters. I'm afraid I'm likely to
join in with some rudeness? 1. "Here is some code that works but also doesn't"
is probably not going to get you an answer 2. I provide
I sometimes think people on this list are quite rude to posters.
I'm afraid I'm likely to join in with some rudeness?
1. "Here is some code that works but also doesn't" is probably not going to get
you an answer
2. I provide no information about the data it works on or doesn't
3. I tell you I'm using a load of dependencies, but don't tell you what
4. I refer to 2000 lines of code but probably means 2000 lines of data?
So. Please post a question someone can actually answer.
If the question is "why might code fail on a 2000 line dataset when it works on 1000
line dataset" then here are some thoughts:
* Is the 1000 lines being run as dataset[1:1000,] or is it dataset1 and
dataset2 ?
* Is there a structural difference in the datasets - i.e. numbers, characters
or factors as columns. Often import functions guess a column type by reading
the first 500/1000 lines. If the data has numbers in column 1 for 1-1000 but on
line 1999 has a letter... The data type may vary.
On Wed, 12 Jun 2024, 17:28 Yuan Chun Ding via R-help,
<r-help@r-project.org<mailto:r-help@r-project.org<mailto:r-help@r-project.org%3cmailto:r-help@r-project.org>>>
wrote:
Hi R users,
The following code worked well to summarize four data groups in a dataframe for
three variables (t_depth, t_alt_count, t_alt_ratio), 12 columns of summary, see
attached.
However, after running another 2000 lines of R codes using functions from more
than 10 other R libraries, then it only generated one column of summary.
Do you know why?
Thank you,
Yuan Chun Ding
summary_anno1148ft <- anno1148ft %>%
pivot_longer(c(t_depth, t_alt_count, t_alt_ratio), names_to = "measure") %>%
group_by(dat, measure) %>%
summarize(minimum = min(value,na.rm=T),
q25 = quantile(value, probs = 0.25,na.rm=T),
med = median(value,na.rm=T),
q75 = quantile(value, probs = 0.75,na.rm=T),
maximum = max(value,na.rm=T),
average = mean(value,na.rm=T),
#standard_deviation = sd(value),
.groups = "drop"
)
summary_anno1148ft <-t(summary_anno1148ft)
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