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#rlang — Public Fediverse posts

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  1. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  2. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  3. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  4. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  5. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  6. Here's a question for #rlang programmers: do y'all use the package `box` to handle namespaces?

    As someone who thinks R's handling of namespaces is hot garbage, this looks very good to me. However, I work with a lot of people who think standard "library/require" is a *good* pattern (i.e. the "namespace challenged") and I want to know if this package is used a lot?

    Or is your practice all `package::function()`?

    Or are there other solutions that I am missing?

    #r #rstats

    klmr.me/box/

  7. Here's a question for #rlang programmers: do y'all use the package `box` to handle namespaces?

    As someone who thinks R's handling of namespaces is hot garbage, this looks very good to me. However, I work with a lot of people who think standard "library/require" is a *good* pattern (i.e. the "namespace challenged") and I want to know if this package is used a lot?

    Or is your practice all `package::function()`?

    Or are there other solutions that I am missing?

    #r #rstats

    klmr.me/box/

  8. Here's a question for #rlang programmers: do y'all use the package `box` to handle namespaces?

    As someone who thinks R's handling of namespaces is hot garbage, this looks very good to me. However, I work with a lot of people who think standard "library/require" is a *good* pattern (i.e. the "namespace challenged") and I want to know if this package is used a lot?

    Or is your practice all `package::function()`?

    Or are there other solutions that I am missing?

    #r #rstats

    klmr.me/box/

  9. Here's a question for #rlang programmers: do y'all use the package `box` to handle namespaces?

    As someone who thinks R's handling of namespaces is hot garbage, this looks very good to me. However, I work with a lot of people who think standard "library/require" is a *good* pattern (i.e. the "namespace challenged") and I want to know if this package is used a lot?

    Or is your practice all `package::function()`?

    Or are there other solutions that I am missing?

    #r #rstats

    klmr.me/box/

  10. Here's a question for #rlang programmers: do y'all use the package `box` to handle namespaces?

    As someone who thinks R's handling of namespaces is hot garbage, this looks very good to me. However, I work with a lot of people who think standard "library/require" is a *good* pattern (i.e. the "namespace challenged") and I want to know if this package is used a lot?

    Or is your practice all `package::function()`?

    Or are there other solutions that I am missing?

    #r #rstats

    klmr.me/box/

  11. TIL (1) that R has a function called `dput()` that writes a text representation of an R object and (2) that a `c()` in an index will effectively flatten a mixture of indices. Hence:

    `dput(names(df)[c(1:4, 7)]`

    solves the problem of picking out a list of column names from a data frame and turning that into an object ready to insert into code. 🙃

    #rlang #r #rstats #datascience #dataanalysis

  12. TIL (1) that R has a function called `dput()` that writes a text representation of an R object and (2) that a `c()` in an index will effectively flatten a mixture of indices. Hence:

    `dput(names(df)[c(1:4, 7)]`

    solves the problem of picking out a list of column names from a data frame and turning that into an object ready to insert into code. 🙃

    #rlang #r #rstats #datascience #dataanalysis

  13. TIL (1) that R has a function called `dput()` that writes a text representation of an R object and (2) that a `c()` in an index will effectively flatten a mixture of indices. Hence:

    `dput(names(df)[c(1:4, 7)]`

    solves the problem of picking out a list of column names from a data frame and turning that into an object ready to insert into code. 🙃

    #rlang #r #rstats #datascience #dataanalysis

  14. TIL (1) that R has a function called `dput()` that writes a text representation of an R object and (2) that a `c()` in an index will effectively flatten a mixture of indices. Hence:

    `dput(names(df)[c(1:4, 7)]`

    solves the problem of picking out a list of column names from a data frame and turning that into an object ready to insert into code. 🙃

    #rlang #r #rstats #datascience #dataanalysis

  15. TIL (1) that R has a function called `dput()` that writes a text representation of an R object and (2) that a `c()` in an index will effectively flatten a mixture of indices. Hence:

    `dput(names(df)[c(1:4, 7)]`

    solves the problem of picking out a list of column names from a data frame and turning that into an object ready to insert into code. 🙃

    #rlang #r #rstats #datascience #dataanalysis

  16. "A little bit less than two years ago, building on work by Jim Hester and Kevin Ushey, Davis Vaughan completed a very impactful JavaScript file for the R community: an R grammar for the Tree-sitter parsing generator." by @rOpenSci

    ropensci.org/blog/2026/04/02/t

    #dataScience #rlang

  17. "A little bit less than two years ago, building on work by Jim Hester and Kevin Ushey, Davis Vaughan completed a very impactful JavaScript file for the R community: an R grammar for the Tree-sitter parsing generator." by @rOpenSci

    ropensci.org/blog/2026/04/02/t

    #dataScience #rlang

  18. "A little bit less than two years ago, building on work by Jim Hester and Kevin Ushey, Davis Vaughan completed a very impactful JavaScript file for the R community: an R grammar for the Tree-sitter parsing generator." by @rOpenSci

    ropensci.org/blog/2026/04/02/t

    #dataScience #rlang

  19. "A little bit less than two years ago, building on work by Jim Hester and Kevin Ushey, Davis Vaughan completed a very impactful JavaScript file for the R community: an R grammar for the Tree-sitter parsing generator." by @rOpenSci

    ropensci.org/blog/2026/04/02/t

    #dataScience #rlang

  20. "A little bit less than two years ago, building on work by Jim Hester and Kevin Ushey, Davis Vaughan completed a very impactful JavaScript file for the R community: an R grammar for the Tree-sitter parsing generator." by @rOpenSci

    ropensci.org/blog/2026/04/02/t

    #dataScience #rlang

  21. Wait! You can wrap pipelines in R in parentheses to directly use the last value?!?

    #rlang #tidyverse #R

  22. Wait! You can wrap pipelines in R in parentheses to directly use the last value?!?

    #rlang #tidyverse #R

  23. Wait! You can wrap pipelines in R in parentheses to directly use the last value?!?

    #rlang #tidyverse #R

  24. Wait! You can wrap pipelines in R in parentheses to directly use the last value?!?

    #rlang #tidyverse #R

  25. Wait! You can wrap pipelines in R in parentheses to directly use the last value?!?

    #rlang #tidyverse #R

  26. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  27. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  28. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  29. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  30. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  31. Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:

    |>, %>%, with(), lambdas, %$%, ...

    there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)

    Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!

    #rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!

  32. Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:

    |>, %>%, with(), lambdas, %$%, ...

    there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)

    Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!

    #rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!

  33. Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:

    |>, %>%, with(), lambdas, %$%, ...

    there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)

    Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!

    #rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!

  34. Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:

    |>, %>%, with(), lambdas, %$%, ...

    there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)

    Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!

    #rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!

  35. Having gotten my head fully around R pipes, I feel I need to write an article about it before I forget the fiddly details:

    |>, %>%, with(), lambdas, %$%, ...

    there are a lot of clever tricks for edge cases! (The with() hack I should have figured out for myself though!)

    Also, %$% -- the exposition pipe -- why didn't any of you tell me about this one!?!? You're slacking!

    #rlang #datascience #stats #statistics #rprogramming #tidyverse #tidydata #Rpipes #pipes!

  36. Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.

    Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.

    Hmm. How's Julia ecosystem for phylogenetic trees these days?

    #microbiology #bioinformatics

  37. Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.

    Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.

    Hmm. How's Julia ecosystem for phylogenetic trees these days?

    #microbiology #bioinformatics

  38. Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.

    Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.

    Hmm. How's Julia ecosystem for phylogenetic trees these days?

    #microbiology #bioinformatics

  39. Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.

    Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.

    Hmm. How's Julia ecosystem for phylogenetic trees these days?

    #microbiology #bioinformatics

  40. Fresh WIP piece of #Archaea #phylogenetics data for a collaborator.

    Those barplot margins are driving me crazy - it's actually throwing off the immediate impression of the data! (pink bars are essentially all 1/2 or less of the orange bars, which is pretty important in context) I really need to buckle down and get to hand-coding my trees from scratch using #rlang or #julialang soon.

    Hmm. How's Julia ecosystem for phylogenetic trees these days?

    #microbiology #bioinformatics

  41. Ok, why do people keep doing this:

    library(tidyverse)
    library(lubridate)

    when the first call automatically loads the package in the second call? Am I missing something here?

    I see this **everywhere**!

    #rlang #rlanguage #tidyverse #lubridate

  42. Ok, why do people keep doing this:

    library(tidyverse)
    library(lubridate)

    when the first call automatically loads the package in the second call? Am I missing something here?

    I see this **everywhere**!

    #rlang #rlanguage #tidyverse #lubridate

  43. Ok, why do people keep doing this:

    library(tidyverse)
    library(lubridate)

    when the first call automatically loads the package in the second call? Am I missing something here?

    I see this **everywhere**!

    #rlang #rlanguage #tidyverse #lubridate

  44. Ok, why do people keep doing this:

    library(tidyverse)
    library(lubridate)

    when the first call automatically loads the package in the second call? Am I missing something here?

    I see this **everywhere**!

    #rlang #rlanguage #tidyverse #lubridate

  45. Ok, why do people keep doing this:

    library(tidyverse)
    library(lubridate)

    when the first call automatically loads the package in the second call? Am I missing something here?

    I see this **everywhere**!

    #rlang #rlanguage #tidyverse #lubridate

  46. Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

    Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu :blobcat_hearthug: #rlang #dataviz

  47. Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

    Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu :blobcat_hearthug: #rlang #dataviz

  48. Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

    Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu :blobcat_hearthug: #rlang #dataviz

  49. Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

    Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu :blobcat_hearthug: #rlang #dataviz

  50. Finally sat down to try to get my head around `reshape()` after being told somewhere that `melt`/`cast` are old hat, `reshape` is the new hotness...the result?

    Friendship ended with `reshape`, now me and #tidyr are besties, `pivot_longer`/`pivot_wider` ilu :blobcat_hearthug: #rlang #dataviz

  51. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  52. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  53. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  54. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  55. Want to use {pak} as backend for {renv} actions? Set the variable RENV_CONFIG_PAK_ENABLED = TRUE github.com/rstudio/renv/issues #renv #pak #reproducibility #RLang

  56. Hello again, R . . .

    R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.

    R is making a comeback:
    infoworld.com/article/4102696/

    #rlang

  57. Hello again, R . . .

    R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.

    R is making a comeback:
    infoworld.com/article/4102696/

    #rlang

  58. Hello again, R . . .

    R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.

    R is making a comeback:
    infoworld.com/article/4102696/

    #rlang

  59. Hello again, R . . .

    R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.

    R is making a comeback:
    infoworld.com/article/4102696/

    #rlang

  60. Hello again, R . . .

    R for sure has deficits (but so does python), but for exploratory data analysis, particularly ones heavy in statistics, R can sometimes shine. I still abhore passing variables into functions, but I get why for simple EDA one might want non-standard evaluation.

    R is making a comeback:
    infoworld.com/article/4102696/

    #rlang