examples/github-issues/qwraps2-issue-0077_reprex.md
In dewittpe/qwraps2: Quick Wraps 2
Simple answers to both questions, yes, and yes.
Some examples. First we set up a simple summary table
library(qwraps2)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
options(qwraps2_markup = "markdown")
my_mtcars <- dplyr::select(mtcars, mpg, cyl, hp)
stats_summary <- list("MPG" =
list("min" = ~ qwraps2::frmt(min(.data[["mpg"]])),
"max" = ~ qwraps2::frmt(max(.data[["mpg"]]))))
st <- summary_table(dplyr::group_by(my_mtcars, cyl), stats_summary)
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
The default table is
st
#>
#>
#> | |4 (N = 11) |6 (N = 7) |8 (N = 14) |
#> |:----------------|:------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
First question, is it possible to rename the columns, yes. One way is to
define the column names via the cname argument of the print method for
the summary table.
print(st, cname = c("Four Cylinders", "Six", "Eight"))
#>
#>
#> | |Four Cylinders |Six |Eight |
#> |:----------------|:--------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Another way to rename the columns, and one that might be safer in a dynamic
program is to change the column names of the object.
Look at the structure of the st object. It is a character matrix and the
column names used by the print method when the cname argument is not
provided.
str(st)
#> 'qwraps2_summary_table' chr [1:2, 1:3] "Inf" "-Inf" "Inf" "-Inf" "Inf" ...
#> - attr(*, "dimnames")=List of 2
#> ..$ : chr [1:2] "min" "max"
#> ..$ : chr [1:3] "4 (N = 11)" "6 (N = 7)" "8 (N = 14)"
#> - attr(*, "rgroups")= Named int 2
#> ..- attr(*, "names")= chr "MPG"
colnames(st)
#> [1] "4 (N = 11)" "6 (N = 7)" "8 (N = 14)"
colnames(st) <- gsub("cyl", "Cylinders", colnames(st))
colnames(st) <- gsub("\\(.*\\)", "", colnames(st))
st
#>
#>
#> | |4 |6 |8 |
#> |:----------------|:------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Reordering the columns is a little less intuitive right now. Perhaps I
should extend the package features. For now, I would suggest building an
factor in your data frame with the levels set in the order you want the
columns to appear in.
my_mtcars$my_cyl <- factor(my_mtcars$cyl, levels = c(6, 4, 8), labels = c("Six", "Four", "Eight"))
summary_table(dplyr::group_by(my_mtcars, my_cyl), stats_summary)
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#>
#>
#> | |Six (N = 7) |Four (N = 11) |Eight (N = 14) |
#> |:----------------|:------------|:-------------|:--------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Created on 2020-08-27 by the reprex package (v0.3.0)
Session info
devtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.0.2 (2020-06-22)
#> os macOS Catalina 10.15.6
#> system x86_64, darwin17.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/Denver
#> date 2020-08-27
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0)
#> backports 1.1.9 2020-08-24 [1] CRAN (R 4.0.2)
#> callr 3.4.3 2020-03-28 [1] CRAN (R 4.0.0)
#> cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.0)
#> crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.0)
#> desc 1.2.0 2018-05-01 [1] CRAN (R 4.0.0)
#> devtools 2.3.1 2020-07-21 [1] CRAN (R 4.0.2)
#> digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.0)
#> dplyr * 1.0.2 2020-08-18 [1] CRAN (R 4.0.2)
#> ellipsis 0.3.1 2020-05-15 [1] CRAN (R 4.0.0)
#> evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.0)
#> fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.0)
#> fs 1.5.0 2020-07-31 [1] CRAN (R 4.0.2)
#> generics 0.0.2 2018-11-29 [1] CRAN (R 4.0.0)
#> glue 1.4.1 2020-05-13 [1] CRAN (R 4.0.0)
#> highr 0.8 2019-03-20 [1] CRAN (R 4.0.0)
#> htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.0)
#> knitr 1.29 2020-06-23 [1] CRAN (R 4.0.0)
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#> ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2)
#> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.0)
#> qwraps2 * 0.4.2.9006 2020-08-26 [1] local
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#> tibble 3.0.3 2020-07-10 [1] CRAN (R 4.0.2)
#> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.0)
#> usethis 1.6.1 2020-04-29 [1] CRAN (R 4.0.0)
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#> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library
dewittpe/qwraps2 documentation built on Jan. 4, 2024, 1:59 p.m.
R Package Documentation
Browse R Packages
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Simple answers to both questions, yes, and yes.
Some examples. First we set up a simple summary table
library(qwraps2)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
options(qwraps2_markup = "markdown")
my_mtcars <- dplyr::select(mtcars, mpg, cyl, hp)
stats_summary <- list("MPG" =
list("min" = ~ qwraps2::frmt(min(.data[["mpg"]])),
"max" = ~ qwraps2::frmt(max(.data[["mpg"]]))))
st <- summary_table(dplyr::group_by(my_mtcars, cyl), stats_summary)
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
The default table is
st
#>
#>
#> | |4 (N = 11) |6 (N = 7) |8 (N = 14) |
#> |:----------------|:------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
First question, is it possible to rename the columns, yes. One way is to
define the column names via the cname argument of the print method for
the summary table.
print(st, cname = c("Four Cylinders", "Six", "Eight"))
#>
#>
#> | |Four Cylinders |Six |Eight |
#> |:----------------|:--------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Another way to rename the columns, and one that might be safer in a dynamic
program is to change the column names of the object.
Look at the structure of the st object. It is a character matrix and the
column names used by the print method when the cname argument is not
provided.
str(st)
#> 'qwraps2_summary_table' chr [1:2, 1:3] "Inf" "-Inf" "Inf" "-Inf" "Inf" ...
#> - attr(*, "dimnames")=List of 2
#> ..$ : chr [1:2] "min" "max"
#> ..$ : chr [1:3] "4 (N = 11)" "6 (N = 7)" "8 (N = 14)"
#> - attr(*, "rgroups")= Named int 2
#> ..- attr(*, "names")= chr "MPG"
colnames(st)
#> [1] "4 (N = 11)" "6 (N = 7)" "8 (N = 14)"
colnames(st) <- gsub("cyl", "Cylinders", colnames(st))
colnames(st) <- gsub("\\(.*\\)", "", colnames(st))
st
#>
#>
#> | |4 |6 |8 |
#> |:----------------|:------------|:------------|:------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Reordering the columns is a little less intuitive right now. Perhaps I should extend the package features. For now, I would suggest building an factor in your data frame with the levels set in the order you want the columns to appear in.
my_mtcars$my_cyl <- factor(my_mtcars$cyl, levels = c(6, 4, 8), labels = c("Six", "Four", "Eight"))
summary_table(dplyr::group_by(my_mtcars, my_cyl), stats_summary)
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#> Warning in min(.data[["mpg"]]): no non-missing arguments to min; returning Inf
#> Warning in max(.data[["mpg"]]): no non-missing arguments to max; returning -Inf
#>
#>
#> | |Six (N = 7) |Four (N = 11) |Eight (N = 14) |
#> |:----------------|:------------|:-------------|:--------------|
#> |**MPG** | | | |
#> | min |Inf |Inf |Inf |
#> | max |-Inf |-Inf |-Inf |
Created on 2020-08-27 by the reprex package (v0.3.0)
Session infodevtools::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.0.2 (2020-06-22)
#> os macOS Catalina 10.15.6
#> system x86_64, darwin17.0
#> ui X11
#> language (EN)
#> collate en_US.UTF-8
#> ctype en_US.UTF-8
#> tz America/Denver
#> date 2020-08-27
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date lib source
#> assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0)
#> backports 1.1.9 2020-08-24 [1] CRAN (R 4.0.2)
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#> ps 1.3.4 2020-08-11 [1] CRAN (R 4.0.2)
#> purrr 0.3.4 2020-04-17 [1] CRAN (R 4.0.0)
#> qwraps2 * 0.4.2.9006 2020-08-26 [1] local
#> R6 2.4.1 2019-11-12 [1] CRAN (R 4.0.0)
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#> sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.0)
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#> stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.0)
#> testthat 2.3.2 2020-03-02 [1] CRAN (R 4.0.0)
#> tibble 3.0.3 2020-07-10 [1] CRAN (R 4.0.2)
#> tidyselect 1.1.0 2020-05-11 [1] CRAN (R 4.0.0)
#> usethis 1.6.1 2020-04-29 [1] CRAN (R 4.0.0)
#> vctrs 0.3.2 2020-07-15 [1] CRAN (R 4.0.2)
#> withr 2.2.0 2020-04-20 [1] CRAN (R 4.0.0)
#> xfun 0.16 2020-07-24 [1] CRAN (R 4.0.2)
#> yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)
#>
#> [1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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