#1

Hello -

Currently working on building an R shiny application as an R package which for now is available for install via github and thus can be installed using devtools (devtools::install_github). However, my question is when a new user installs devtools, tibble version 3.0.4 gets installed, yet this version of tibble gives an error with my application and my application requires tibble version 2.1.3.

I see when making my description file and I use
usethis::use_package("tibble", min_version="2.1.3)
The output from the above command in the Description file is so:
tibble (>= 2.1.3), which reads that the application can use a version of tibble that is not acceptable.

I am curious about the best way to deal with this within my package.
One potential work around is to tell new users after downloading to use this command
devtools::install_version("tibble", version = "2.1.3")
but I would like an way to not have to request a new user who downloads the application to do this.

Any thoughts -

#2

If I put myself in the shoes of an r user that wanted to run your app, I would think its best if you made your program compatible with versions of tibble after 2.1.3.

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#3

Yes, I agree with your statement @ nirgrahamuk but the error I get when using the two different versions is:

Warning: Error in : Assigned data values must be compatible with existing data.
i Error occurred for column 2013C-3134_fastx5.
x Can't convert double to character.

and I have been unsuccessful at dealing with this error.
So I guess a secondary/alternative questions would be - Any thoughts on dealing with this error.

#4

Id be happy to investigate and see what can be done, others on the forum may also.

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

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#5

Okay - here is a minimal reprex

#honestly this seems a bit bananas to me that I need to do lines 5-14de to get a matrix that matches to what I would read in
testing_genetic <- matrix(c(1, "-", 0.2, 0.5, 0.1, 0, "-", 0.3, 0.9, 0.8, 0.2, 0.2, "-", 0.5, "-", 0.7), nrow = 4, dimnames = list(c("A","B","C","D"), c("A","B","C","D")))
testing_genetic <- as.data.frame(testing_genetic)
testing_genetic <- droplevels(testing_genetic)
testing_genetic <- data.frame(lapply(testing_genetic, as.character), stringsAsFactors=FALSE)
testing_genetic <- tibble::rownames_to_column(testing_genetic, var=".")  
#rename this column to make a matrix with both 
testing_genetic[1,1] <- "A"
testing_genetic[2,1] <- "B"
testing_genetic[3,1] <- "C"
testing_genetic[4,1] <- "D"

#additional manipulation of genetic distance matrix for ultimately getting the mean number of SNPs 
testing_genetic  <- testing_genetic %>%
  dplyr::rename( label = 1) %>% #rename columnn 1 to label for joining of data sets later
  stats::na.omit()%>% #remove na
  tidyr::pivot_longer(-label)%>%  #convert to a three column data frame 
  .[which(.$label != .$name),]  #remove self comparisons for this table - necessary for snp mean/median calculation.

testing_genetic <-  testing_genetic%>%
     replace(., .=="-", 0) #replace - with zero in the file; if zeros already infile, still works

When the above code is run I get the error -
"Error: Assigned data values must be compatible with existing data.
i Error occurred for column value.
x Can't convert double to character."

Let me know if this is not an acceptable minimum reprex

#6

you can use


testing_genetic <-  testing_genetic%>%
  mutate(value=ifelse(value=="-", 0,value)) #replace - with zero in the file
#7

Very cool! Thank you :grinning:

1 Like
#8

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