Help for package saros

Type:

Package

Title:

Semi-Automatic Reporting of Ordinary Surveys

Version:

1.5.4

Maintainer:

Stephan Daus <stephus.daus@gmail.com>

Description:

Offers a systematic way for conditional reporting of figures and tables for many (and bivariate combinations of) variables, typically from survey data. Contains interactive 'ggiraph'-based (https://CRAN.R-project.org/package=ggiraph) plotting functions and data frame-based summary tables (bivariate significance tests, frequencies/proportions, unique open ended responses, etc) with many arguments for customization, and extensions possible. Uses a global options() system for neatly reducing redundant code. Also contains tools for immediate saving of objects and returning a hashed link to the object, useful for creating download links to high resolution images upon rendering in 'Quarto'. Suitable for highly customized reports, primarily intended for survey research.

Note:

Free to use for non-Norwegian institutions, otherwise see LICENSE.

License:

MIT + file LICENSE

URL:

https://nifu-no.github.io/saros/, https://github.com/NIFU-NO/saros

BugReports:

https://github.com/NIFU-NO/saros/issues

Depends:

R (≥ 4.2.0)

Imports:

cli, dplyr, forcats, fs, ggiraph, ggplot2, glue, grDevices, lifecycle, mschart, officer, rlang, stringi, tidyr, tidyselect, utils, vctrs

Suggests:

covr, haven, labelled, quarto, knitr, readr, scales, spelling, srvyr, testthat (≥ 3.0.0), tibble, vdiffr, withr, writexl

Config/testthat/edition:

Encoding:

UTF-8

RoxygenNote:

7.3.2

Language:

en-US

VignetteBuilder:

quarto

Config/Needs/website:

rmarkdown

Config/testthat/parallel:

true

LazyData:

true

NeedsCompilation:

Packaged:

2025-06-02 21:01:51 UTC; py128

Author:

Stephan Daus

[aut, cre, cph], Julia Silge [ctb] (Author of internal scale_x_reordered), David Robinson [ctb] (Author of internal scale_x_reordered), Nordic Institute for The Studies of Innovation, Research and Education (NIFU) [fnd], Kristiania University College [fnd]

Repository:

CRAN

Date/Publication:

2025-06-04 12:10:06 UTC

saros: Semi-Automatic Reporting of Ordinary Surveys

Description

Author(s)

Maintainer: Stephan Daus stephus.daus@gmail.com (ORCID) [copyright holder]

Other contributors:

Julia Silge (Author of internal scale_x_reordered) [contributor]
David Robinson (Author of internal scale_x_reordered) [contributor]
Nordic Institute for The Studies of Innovation, Research and Education (NIFU) [funder]
Kristiania University College [funder]

Embed Interactive Categorical Plot (DEPRECATED!)

Description

This function has been deprecated. Use instead makeme()

Usage

embed_cat_prop_plot(
  data,
  ...,
  dep = tidyselect::everything(),
  indep = NULL,
  colour_palette = NULL,
  mesos_group = NULL,
  html_interactive = TRUE,
  inverse = FALSE
)

Arguments

data

data.frame, tibble or potentially a srvyr-object.

...

Dynamic dots, arguments forwarded to underlying function(s).

dep

tidyselect-syntax for dependent variable(s).

indep

tidyselect-syntax for an optional independent variable.

colour_palette

Character vector. Avoid using this.

mesos_group

String

html_interactive

Flag, whether to include interactivity.

inverse

Flag, whether to flip plot or table.

Embed Reactable Table (DEPRECATED!)

Description

This function has been deprecated. Use instead makeme()

Usage

embed_cat_table(
  data,
  ...,
  dep = tidyselect::everything(),
  indep = NULL,
  mesos_group = NULL
)

Arguments

data

data.frame, tibble or potentially a srvyr-object.

...

Dynamic dots, arguments forwarded to underlying function(s).

dep

tidyselect-syntax for dependent variable(s).

indep

tidyselect-syntax for an optional independent variable.

mesos_group

String

Interactive table of text data (DEPRECATED)

Description

This function has been deprecated. Use instead makeme()

Usage

embed_chr_table_html(data, dep, ..., mesos_group = NULL)

Arguments

data

data.frame, tibble or potentially a srvyr-object.

dep

tidyselect-syntax for dependent variable(s).

...

Dynamic dots, arguments forwarded to underlying function(s).

mesos_group

String

ex_survey: Mockup dataset of a survey.

Description

A dataset containing fake respondents' answers to survey questions. The first two, x_sex and x_human, are intended to be independent variables, whereas the remaining are dependent. The underscore _ in variable names separates item groups (prefix) from items (suffix) (i.e. a_1-a_9 => a + 1-9), whereas ' - ' separates the same for labels. The latter corresponds with the default in SurveyXact.

Usage

ex_survey

Format

A data frame with 100 rows and 29 variables:

x1_sex: Gender
x2_human: Is respondent human?
x3_nationality: Where is the respondent born?
a_1: Do you consent to the following? - Agreement #1
a_2: Do you consent to the following? - Agreement #2
a_3: Do you consent to the following? - Agreement #3
a_4: Do you consent to the following? - Agreement #4
a_5: Do you consent to the following? - Agreement #5
a_6: Do you consent to the following? - Agreement #6
a_7: Do you consent to the following? - Agreement #7
a_8: Do you consent to the following? - Agreement #8
a_9: Do you consent to the following? - Agreement #9
b_1: How much do you like living in - Beijing
b_2: How much do you like living in - Brussels
b_3: How much do you like living in - Budapest
c_1: How many years of experience do you have in - Company A
c_2: How many years of experience do you have in - Company B
d_1: Rate your degree of confidence doing the following - Driving
d_2: Rate your degree of confidence doing the following - Drinking
d_3: Rate your degree of confidence doing the following - Driving
d_4: Rate your degree of confidence doing the following - Dancing
e_1: How often do you do the following? - Eat
e_2: How often do you do the following? - Eavesdrop
e_3: How often do you do the following? - Exercise
e_4: How often do you do the following? - Encourage someone whom you have only recently met and who struggles with simple tasks that they cannot achieve by themselves
p_1: To what extent do you agree or disagree to the following policies - Red Party
p_2: To what extent do you agree or disagree to the following policies - Green Party
p_3: To what extent do you agree or disagree to the following policies - Yellow Party
p_4: To what extent do you agree or disagree to the following policies - Blue Party
f_uni: Which of the following universities would you prefer to study at?
open_comments: Do you have any comments to the survey?
resp_status: Response status

Estimate figure height for a horizontal bar chart

Description

This function estimates the height of a figure for a horizontal bar chart based on several parameters including the number of dependent and independent variables, number of categories, maximum characters in the labels, and legend properties.

Usage

fig_height_h_barchart(
  n_y,
  n_cats_y,
  max_chars_labels_y = 20,
  max_chars_cats_y = 20,
  n_x = NULL,
  n_cats_x = NULL,
  max_chars_labels_x = NULL,
  max_chars_cats_x = NULL,
  freq = FALSE,
  x_axis_label_width = 20,
  strip_width = 20,
  strip_angle = 0,
  main_font_size = 7,
  legend_location = c("plot", "panel"),
  n_legend_lines = NULL,
  legend_key_chars_equivalence = 5,
  multiplier_per_horizontal_line = 1,
  multiplier_per_vertical_letter = 1,
  multiplier_per_facet = 1,
  multiplier_per_bar = 1,
  multiplier_per_legend_line = 1,
  multiplier_per_plot = 1,
  fixed_constant = 0,
  margin_in_cm = 0,
  figure_width_in_cm = 14,
  max = 12,
  min = 2,
  hide_axis_text_if_single_variable = FALSE,
  add_n_to_dep_label = FALSE,
  add_n_to_indep_label = FALSE,
  showNA = c("ifany", "never", "always")
)

Arguments

n_y, n_x

Integer. Number of dependent/independent variables.

n_cats_y

Integer. Number of categories across the dependent variables.

max_chars_labels_y

Integer. Maximum number of characters across the dependent variables' labels.

max_chars_cats_y

Integer. Maximum number of characters across the dependent variables' response categories (levels).

n_cats_x

Integer or NULL. Number of categories across the independent variables.

max_chars_labels_x

Integer or NULL. Maximum number of characters across the independent variables' labels.

max_chars_cats_x

Integer or NULL. Maximum number of characters across the independent variables' response categories (levels).

freq

Logical. If TRUE, frequency plot with categories next to each other. If FALSE (default), proportion plot with stacked categories.

x_axis_label_width, strip_width

Numeric. Width allocated for x-axis labels and strip labels respectively.

strip_angle

Integer. Angle of the strip text.

main_font_size

Numeric. Font size for the main text.

legend_location

Character. Location of the legend. "plot" (default) or "panel".

n_legend_lines

Integer. Number of lines in the legend.

legend_key_chars_equivalence

Integer. Approximate number of characters the legend key equals.

multiplier_per_horizontal_line

Numeric. Multiplier per horizontal line.

multiplier_per_vertical_letter

Numeric. Multiplier per vertical letter.

multiplier_per_facet

Numeric. Multiplier per facet height.

multiplier_per_bar

Numeric. Multiplier per bar height (thickness).

multiplier_per_legend_line

Numeric. Multiplier per legend line.

multiplier_per_plot

Numeric. Multiplier for entire plot estimates.

fixed_constant

Numeric. Fixed constant to be added to the height.

margin_in_cm

Numeric. Margin in centimeters.

figure_width_in_cm

Numeric. Width of the figure in centimeters.

max

Numeric. Maximum height.

min

Numeric. Minimum height.

hide_axis_text_if_single_variable

Boolean. Whether the label is hidden for single dependent variable plots.

add_n_to_dep_label, add_n_to_indep_label

Boolean. If TRUE, will add 10 characters to the max label lengths. This is primarily useful when obtaining these settings from the global environment, avoiding the need to compute this for each figure chunk.

showNA

String, one of "ifany", "always" or "never". Not yet in use.

Value

Numeric value representing the estimated height of the figure.

Examples

fig_height_h_barchart(
  n_y = 5,
  n_cats_y = 3,
  max_chars_labels_y = 20,
  max_chars_cats_y = 8,
  n_x = 1,
  n_cats_x = 4,
  max_chars_labels_x = 12,
  freq = FALSE,
  x_axis_label_width = 20,
  strip_angle = 0,
  main_font_size = 8,
  legend_location = "panel",
  n_legend_lines = 2,
  legend_key_chars_equivalence = 5,
  multiplier_per_horizontal_line = 1,
  multiplier_per_vertical_letter = .15,
  multiplier_per_facet = .95,
  multiplier_per_legend_line = 1.5,
  figure_width_in_cm = 16
)

Estimate figure height for a horizontal bar chart

Description

Taking an object from makeme(), this function estimates the height of a figure for a horizontal bar chart.

Usage

fig_height_h_barchart2(
  ggobj,
  main_font_size = 7,
  strip_angle = 0,
  freq = FALSE,
  x_axis_label_width = 20,
  strip_width = 20,
  legend_location = c("plot", "panel"),
  n_legend_lines = NULL,
  showNA = c("ifany", "never", "always"),
  legend_key_chars_equivalence = 5,
  multiplier_per_horizontal_line = NULL,
  multiplier_per_vertical_letter = 1,
  multiplier_per_facet = 1,
  multiplier_per_legend_line = 1,
  fixed_constant = 0,
  figure_width_in_cm = 14,
  margin_in_cm = 0,
  max = 8,
  min = 1
)

Arguments

ggobj

ggplot2-object

main_font_size

Numeric. Font size for the main text.

strip_angle

Integer. Angle of the strip text.

freq

Logical. If TRUE, frequency plot with categories next to each other. If FALSE (default), proportion plot with stacked categories.

x_axis_label_width, strip_width

Numeric. Width allocated for x-axis labels and strip labels respectively.

legend_location

Character. Location of the legend. "plot" (default) or "panel".

n_legend_lines

Integer. Number of lines in the legend.

showNA

String, one of "ifany", "always" or "never". Not yet in use.

legend_key_chars_equivalence

Integer. Approximate number of characters the legend key equals.

multiplier_per_horizontal_line

Numeric. Multiplier per horizontal line.

multiplier_per_vertical_letter

Numeric. Multiplier per vertical letter.

multiplier_per_facet

Numeric. Multiplier per facet height.

multiplier_per_legend_line

Numeric. Multiplier per legend line.

fixed_constant

Numeric. Fixed constant to be added to the height.

figure_width_in_cm

Numeric. Width of the figure in centimeters.

margin_in_cm

Numeric. Margin in centimeters.

max

Numeric. Maximum height.

min

Numeric. Minimum height.

Value

Numeric value representing the estimated height of the figure.

Examples

fig_height_h_barchart2(makeme(data = ex_survey, dep = b_1:b_3, indep = x1_sex))

Provide A Colour Set for A Number of Requested Colours

Description

Possibly using colour_palette_nominal if available. If not sufficient, uses a set palette from RColorBrewer.

Usage

get_colour_palette(
  data,
  col_pos,
  colour_palette_nominal = NULL,
  colour_palette_ordinal = NULL,
  colour_na = NULL,
  categories_treated_as_na = NULL,
  call = rlang::caller_env()
)

Arguments

data

Your data.frame/tibble or srvyr-object (experimental)

data.frame // required

The data to be used for plotting.

col_pos

Character vector of column names for which colours will be found.

colour_palette_nominal, colour_palette_ordinal

User specified colour set

⁠vector<character>⁠ // default: NULL (optional)

User-supplied default palette, excluding colour_na.

colour_na

Colour for NA category

⁠scalar<character>⁠ // default: NULL (optional)

Colour as a single string for NA values, if showNA is "ifany" or "always".

categories_treated_as_na

NA categories

⁠vector<character>⁠ // default: NULL (optional)

Categories that should be treated as NA.

call

Internal call

⁠obj:<call>⁠ // Default: rlang::caller_env() (optional)

Both the absolute and relative folderpaths are required, as strings.

Value

A colour set as character vector, where NA has the colour_na, and the rest are taken from colour_palette_nominal if available.

Provide A Colour Set for A Number of Requested Colours

Description

Possibly using colour_palette_nominal if available. If not sufficient, uses a set palette from RColorBrewer.

Usage

get_colour_set(
  x,
  common_data_type = "factor",
  colour_palette_nominal = NULL,
  colour_palette_ordinal = NULL,
  colour_na = NULL,
  colour_2nd_binary_cat = NULL,
  ordinal = FALSE,
  categories_treated_as_na = NULL,
  call = rlang::caller_env()
)

Arguments

x

Vector for which colours will be found.

common_data_type

factor or ordered data type

⁠scalar<character>⁠ // default: factor (optional)

Currently only supports factor and ordered.

colour_palette_nominal, colour_palette_ordinal

User specified colour set

⁠vector<character>⁠ // default: NULL (optional)

User-supplied default palette, excluding colour_na.

colour_na

Colour for NA category

⁠scalar<character>⁠ // default: NULL (optional)

Colour as a single string for NA values, if showNA is "ifany" or "always".

colour_2nd_binary_cat

Colour for second binary category

⁠scalar<character>⁠ // default: "#ffffff" (optional)

Colour for the second category in binary variables. Often useful to hide this.

ordinal

⁠scalar<logical>⁠ // default: FALSE (optional)

Is palette ordinal?

categories_treated_as_na

NA categories

⁠vector<character>⁠ // default: NULL (optional)

Categories that should be treated as NA.

call

Internal call

⁠obj:<call>⁠ // Default: rlang::caller_env() (optional)

Both the absolute and relative folderpaths are required, as strings.

Value

A colour set as character vector, where NA has the colour_na, and the rest are taken from colour_palette_nominal if available.

Get Valid Data Labels for Figures and Tables

Description

Get Valid Data Labels for Figures and Tables

Usage

get_data_label_opts()

Value

Character vector

Get all registered options for the type-argument in the `makeme`-function

Description

The makeme()-function take for the argument type one of several strings to indicate content type and output type. This function collects all registered alternatives. Extensions are possible, see further below.

Built-in types:

Whereas the names of the types can be arbitrary, a pattern is pursued in the built-in types. Prefix indicates what dependent data type it is intended for

"cat": Categorical (ordinal and nominal) data.
"chr": Open ended responses and other character data.
"int": Integer and numeric data.

Suffix indicates output

"html": Interactive html, usually what you want for Quarto, as Quarto can usually convert to other formats when needed
"docx": However, Quarto's and Pandoc's docx-support is currently still limited, for instance as vector graphics are converted to raster graphics for docx output. Hence, saros offers some types that outputs into MS Chart vector graphics. Note that this is experimental and not actively developed.
"pdf": This is basically just a shortcut for "html" with interactive=FALSE

Usage

get_makeme_types()

Value

Character vector

Further details about some of the built-in types:

"cat_plot_": A Likert style plot for groups of categorical variables sharing the same categories.
"cat_table_": A Likert style table.
"chr_table_": A single-column table listing unique open ended responses.
"sigtest_table_": See below

sigtest_table_\*: Make Table with All Combinations of Univariate/Bivariate Significance Tests Based on Variable Types

Although there are hundreds of significance tests for associations between two variables, depending upon the distributions, variables types and assumptions, most fall into a smaller set of popular tests. This function runs for all combinations of dependent and independent variables in data, with a suitable test (but not the only possible) for the combination. Also supports univariate tests, where the assumptions are that of a mean of zero for continuous variables or all equal proportions for binary/categorical.

This function does not allow any adjustments - use the original underlying functions for that (chisq.test, t.test, etc.)

Expanding with custom types

makeme() calls the generic make_content(), which uses the S3-method system to dispatch to the relevant method (i.e., paste0("make_content.", type)). makeme forwards all its arguments to make_content, with the following exceptions:

dep and indep are converted from dplyr::dplyr_tidy_select()-syntax to simple character vectors, for simplifying building your own functions.
data_summary is attached, which contains many useful pieces of info for many (categorical) displays.

Examples

get_makeme_types()

Helper function to extract raw variable labels from the data

Description

Helper function to extract raw variable labels from the data

Usage

get_raw_labels(data, col_pos = NULL, return_as_list = FALSE)

Arguments

data

Dataset

col_pos

Optional, character vector of column names or integer vector of positions

return_as_list

Flag, whether to return as list or character vector

Value

List or character vector

Wrapper Function for `ggplot2::ggsave()`

Description

This only exists to make it easy to use it in make_link()

Usage

ggsaver(plot, filename, ...)

Arguments

plot

Plot

filename

Note

...

Arguments forwarded to ggplot2::ggsave()

Value

No return value, called for side effects

Examples

library(ggplot2)
my_plot <- ggplot(data=mtcars, aes(x=hp, y=mpg)) + geom_point()
make_link(my_plot, folder=tempdir(), file_suffix = ".png",
          save_fn = ggsaver, width = 16, height = 16, units = "cm")

Pull global plotting settings before displaying plot

Description

This function extends ggiraph::girafe by allowing colour palettes to be globally specified.

Usage

girafe(
  ggobj,
  ...,
  char_limit = 200,
  label_wrap_width = 80,
  interactive = TRUE,
  palette_codes = NULL,
  priority_palette_codes = NULL,
  ncol = NULL,
  byrow = TRUE,
  checked = NULL,
  not_checked = NULL,
  width_svg = NULL,
  height_svg = NULL,
  pointsize = 12
)

Arguments

ggobj

ggplot2-object.

...

Dots forwarded to ggiraph::girafe()

char_limit

Integer. Number of characters to fit on a line of plot (legend-space). Will be replaced in the future with a function that guesses this.

label_wrap_width

Integer. Number of characters fit on the axis text space before wrapping.

interactive

Boolean. Whether to produce a ggiraph-plot with interactivity (defaults to TRUE) or a static ggplot2-plot.

palette_codes

Optional list of named character vectors with names being categories and values being colours. The final character vector of the list is taken as a final resort. Defaults to NULL.

priority_palette_codes

Optional named character of categories (as names) with corresponding colours (as values) which are used first, whereupon the remaining unspecified categories are pulled from the last vector of palette_codes. Defaults to NULL.

ncol

Optional integer or NULL.

byrow

Whether to display legend keys by row or by column.

checked, not_checked

Optional string. If specified and the fill categories of the plot matches these, a special plot is returned where not_checked is hidden. Its usefulness comes in plots which are intended for checkbox responses where unchecked is not always a conscious choice.

pointsize, height_svg, width_svg

See ggiraph::girafe().

Value

If interactive, only side-effect of generating ggiraph-plot. If interactive=FALSE, returns modified ggobj.

Examples

plot <- makeme(data = ex_survey, dep = b_1)
girafe(plot)

Get Global Options for saros-functions

Description

Get Global Options for saros-functions

Usage

global_settings_get(fn_name = "makeme")

Arguments

fn_name

String, one of "make_link", "fig_height_h_barchart" and "makeme".

Value

List with options in R

Examples

global_settings_get()

Reset Global Options for saros-functions

Description

Reset Global Options for saros-functions

Usage

global_settings_reset(fn_name = "makeme")

Arguments

fn_name

String, one of "make_link", "fig_height_h_barchart" and "makeme".

Value

Invisibly returned list of old and new values.

Examples

global_settings_reset()

Get Global Options for saros-functions

Description

Get Global Options for saros-functions

Usage

global_settings_set(
  new,
  fn_name = "makeme",
  quiet = FALSE,
  null_deletes = FALSE
)

Arguments

new

List of arguments (see ?make_link(), ?makeme(), fig_height_h_barchart())

fn_name

String, one of "make_link", "fig_height_h_barchart" and "makeme".

quiet

Flag. If FALSE (default), informs about what has been set.

null_deletes

Flag. If FALSE (default), NULL elements in new become NULL elements in the option. Otherwise, the corresponding element, if present, is deleted from the option.

Value

Invisibly returned list of old and new values.

Examples

global_settings_set(new=list(digits=2))

Identify Suitable Font Given Background Hex Colour

Description

Code is taken from XXX.

Usage

hex_bw(hex_code)

Arguments

hex_code

Colour in hex-format.

Value

Colours in hex-format, either black or white.

Are All Colours in Vector Valid Colours

Description

As title says. From: (https://stackoverflow.com/a/13290832/3315962)

Usage

is_colour(x)

Arguments

x

Character vector of colours in hex-format.

Value

Logical, or error.

Is x A String?

Description

Returns TRUE if object is a character of length 1.

Usage

is_string(x)

Arguments

x

Object

Value

Logical value.

Method for Creating Saros Contents

Description

Takes the same arguments as makeme, except that dep and indep in make_content are character vectors, for ease of user-customized function programming.

Usage

make_content(type, ...)

Arguments

type

Method name

⁠scalar<character>⁠ with a class named by itself.

Optional string indicating the specific method. Occasionally useful for error messages, etc.

...

Dots

Arguments provided by makeme

Value

The returned object class depends on the type. type="*_table_html" always returns a tibble. type="*_plot_html" always returns a ggplot. type="*_docx" always returns a rdocx object if path=NULL, or has side-effect of writing docx file to disk if path is set.

Save data to a file and return a Markdown link

Description

The file is automatically named by a hash of the object, removing the need to come up with unique file names inside a Quarto report. This has the added benefit of reducing storage needs if the objects needing linking to are identical, and all are stored in the same folder. It also allows the user to download multiple files without worrying about accidentally overwriting them.

Usage

make_link(
  data,
  folder = NULL,
  file_prefix = NULL,
  file_suffix = ".csv",
  save_fn = utils::write.csv,
  link_prefix = "[download figure data](",
  link_suffix = ")",
  ...
)

Arguments

data

Data or object

⁠<data.frame|tbl|obj>⁠

Data frame if using a tabular data save_fn, or possibly any R object, if a serializing save_fn is provided (e.g. saveRDS()).

folder

Where to store file

⁠scalar<character>⁠ // default: "." (optional)

Defaults to same folder.

file_prefix, file_suffix

File prefix/suffix

⁠scalar<character>⁠ // default: "" and ".csv" (optional)

file_suffix should include the dot before the extension.

save_fn

Saving function

function // default: utils::write.csv

Can be any saving/writing function. However, first argument must be the object to be saved, and the second must be the path. Hence, ggplot2::ggsave() must be wrapped in another function with filename and object swapped. See ggsaver() for an example of such a wrapper function.

link_prefix, link_suffix

Link prefix/suffix

⁠scalar<character>⁠ // default: "[download data](" and ")"

The stuff that is returned.

...

Dynamic dots

<dynamic-dots>

Arguments forwarded to the corresponding functions that create the elements.

Value

String.

Examples

make_link(mtcars, folder = tempdir())

Save data to a file and return a Markdown link

Description

Usage

## Default S3 method:
make_link(
  data,
  ...,
  folder = NULL,
  file_prefix = NULL,
  file_suffix = ".csv",
  save_fn = utils::write.csv,
  link_prefix = "[download figure data](",
  link_suffix = ")"
)

Arguments

data

Data or object

⁠<data.frame|tbl|obj>⁠

Data frame if using a tabular data save_fn, or possibly any R object, if a serializing save_fn is provided (e.g. saveRDS()).

...

Dynamic dots

<dynamic-dots>

Arguments forwarded to the corresponding functions that create the elements.

folder

Where to store file

⁠scalar<character>⁠ // default: "." (optional)

Defaults to same folder.

file_prefix, file_suffix

File prefix/suffix

⁠scalar<character>⁠ // default: "" and ".csv" (optional)

file_suffix should include the dot before the extension.

save_fn

Saving function

function // default: utils::write.csv

link_prefix, link_suffix

Link prefix/suffix

⁠scalar<character>⁠ // default: "[download data](" and ")"

The stuff that is returned.

Value

String.

Examples

make_link(mtcars, folder = tempdir())

Save data to a file and return a Markdown link

Description

Usage

## S3 method for class 'list'
make_link(
  data,
  ...,
  folder = NULL,
  file_prefix = NULL,
  file_suffix = ".csv",
  save_fn = utils::write.csv,
  link_prefix = "[download figure data](",
  link_suffix = ")",
  separator_list_items = ". "
)

Arguments

data

Data or object

⁠<data.frame|tbl|obj>⁠

Data frame if using a tabular data save_fn, or possibly any R object, if a serializing save_fn is provided (e.g. saveRDS()).

...

Dynamic dots

<dynamic-dots>

Arguments forwarded to the corresponding functions that create the elements.

folder

Where to store file

⁠scalar<character>⁠ // default: "." (optional)

Defaults to same folder.

file_prefix, file_suffix

File prefix/suffix

⁠scalar<character>⁠ // default: "" and ".csv" (optional)

file_suffix should include the dot before the extension.

save_fn

Saving function

function // default: utils::write.csv

link_prefix, link_suffix

Link prefix/suffix

⁠scalar<character>⁠ // default: "[download data](" and ")"

The stuff that is returned.

separator_list_items

Separator string between multiple list items

⁠scalar<character>⁠ // default: ". " (optional)

Embed Interactive Plot of Various Kinds Using Tidyselect Syntax

Description

This function allows embedding of interactive or static plots based on various types of data using tidyselect syntax for variable selection.

Usage

makeme(
  data,
  dep = tidyselect::everything(),
  indep = NULL,
  type = c("cat_plot_html", "int_plot_html", "cat_table_html", "int_table_html",
    "sigtest_table_html", "cat_prop_plot_docx", "cat_freq_plot_docx", "int_plot_docx"),
  ...,
  require_common_categories = TRUE,
  crowd = c("all"),
  mesos_var = NULL,
  mesos_group = NULL,
  simplify_output = TRUE,
  hide_for_crowd_if_all_na = TRUE,
  hide_for_crowd_if_valid_n_below = 0,
  hide_for_crowd_if_category_k_below = 2,
  hide_for_crowd_if_category_n_below = 0,
  hide_for_crowd_if_cell_n_below = 0,
  hide_for_all_crowds_if_hidden_for_crowd = NULL,
  hide_indep_cat_for_all_crowds_if_hidden_for_crowd = FALSE,
  add_n_to_dep_label = FALSE,
  add_n_to_indep_label = FALSE,
  add_n_to_label = FALSE,
  add_n_to_category = FALSE,
  totals = FALSE,
  categories_treated_as_na = NULL,
  label_separator = " - ",
  error_on_duplicates = TRUE,
  showNA = c("ifany", "always", "never"),
  data_label = c("percentage_bare", "percentage", "proportion", "count"),
  html_interactive = TRUE,
  hide_axis_text_if_single_variable = TRUE,
  hide_label_if_prop_below = 0.01,
  inverse = FALSE,
  vertical = FALSE,
  digits = 0,
  data_label_decimal_symbol = ".",
  x_axis_label_width = 25,
  strip_width = 25,
  sort_by = ".upper",
  descend = TRUE,
  labels_always_at_top = NULL,
  labels_always_at_bottom = NULL,
  table_wide = TRUE,
  table_main_question_as_header = FALSE,
  n_categories_limit = 12,
  translations = list(last_sep = " and ", table_heading_N = "Total (N)",
    table_heading_data_label = "%", add_n_to_dep_label_prefix = " (N = ",
    add_n_to_dep_label_suffix = ")", add_n_to_indep_label_prefix = " (N = ",
    add_n_to_indep_label_suffix = ")", add_n_to_label_prefix = " (N = ",
    add_n_to_label_suffix = ")", add_n_to_category_prefix = " (N = [",
    add_n_to_category_infix = ",", add_n_to_category_suffix = "])", by_total =
    "Everyone", sigtest_variable_header_1 = "Var 1", sigtest_variable_header_2 = "Var 2",
    crowd_all = "All", 
     crowd_target = "Target", crowd_others = "Others"),
  plot_height = 15,
  colour_palette = NULL,
  colour_2nd_binary_cat = "#ffffff",
  colour_na = "grey",
  label_font_size = 6,
  main_font_size = 6,
  strip_font_size = 6,
  legend_font_size = 6,
  font_family = "sans",
  path = NULL,
  docx_template = NULL
)

Arguments

data

Your data.frame/tibble or srvyr-object (experimental)

data.frame // required

The data to be used for plotting.

dep, indep

Variable selections

<tidyselect> // Default: NULL, meaning everything for dep, nothing for indep.

Columns in data. dep is compulsory.

type

Kind of output

⁠scalar<character>⁠ // default: "cat_plot_html" (optional)

For a list of registered types in your session, use get_makeme_types().

...

Dynamic dots

<dynamic-dots>

Arguments forwarded to the corresponding functions that create the elements.

require_common_categories

Check common categories

⁠scalar<logical>⁠ // default: TRUE (optional)

Whether to check if all items share common categories.

crowd

Which group(s) to display results for

⁠vector<character>⁠ // default: c("target", "others", "all") (optional)

Choose whether to produce results for target (mesos) group, others, all, or combinations of these.

mesos_var

Variable in data indicating groups to tailor reports for

⁠scalar<character>⁠ // default: NULL (optional)

Column name in data indicating the groups for which mesos reports will be produced.

mesos_group

⁠scalar<character>⁠ // default: NULL (optional)

String, target group.

simplify_output

⁠scalar<logical>⁠ // default: TRUE

If TRUE, a list output with a single output element will return the element itself, whereas list with multiple elements will return the list.

hide_for_crowd_if_all_na

Hide variable from output if containing all NA

⁠scalar<boolean>⁠ // default: TRUE

Whether to remove all variables (in particular useful for mesos) if all values are NA

hide_for_crowd_if_valid_n_below

Hide variable if variable has < n observations

⁠scalar<integer>⁠ // default: 0

Whether to hide a variable for a crowd if variable contains fewer than n observations (always ignoring NA).

hide_for_crowd_if_category_k_below

Hide variable if < k categories

⁠scalar<integer>⁠ // default: 2

Whether to hide a variable for a crowd if variable contains fewer than k used categories (always ignoring NA). Defaults to 2 because a unitary plot/table is rarely informative.

hide_for_crowd_if_category_n_below

Hide variable if having a category with < n observations

⁠scalar<integer>⁠ // default: 0

Whether to hide a variable for a crowd if variable contains a category with less than n observations (ignoring NA) Cells with a 0 count is not considered as these are usually not a problem for anonymity.

hide_for_crowd_if_cell_n_below

Hide variable if having a cell with < n

⁠scalar<integer>⁠ // default: 0

Whether to hide a variable for a crowd if the combination of dep-indep results in a cell with less than n observations (ignoring NA). Cells with a 0 count is not considered as these are usually not a problem for anonymity.

hide_for_all_crowds_if_hidden_for_crowd

Conditional hiding

⁠scalar<character>⁠ // default: NULL (optional)

Select one of the crowd output groups. If selected, will hide a variable across all crowd-outputs if it for some reason is not displayed for hide_for_all_if_hidden_for_crowd. For instance, say:

⁠crowd = c("target", "others"), hide_variable_if_all_na = TRUE,⁠ hide_for_all_if_hidden_for_crowd = "target"

will hide variables from both target and others-outputs if all are NA in the target-group.

hide_indep_cat_for_all_crowds_if_hidden_for_crowd

Conditionally hide independent categories

⁠scalar<logical>⁠ // default: FALSE

If hide_for_all_crowds_if_hidden_for_crowd is specified, should categories of the indep variable(s) be hidden for a crowd if it does not exist for the crowds specified in hide_for_all_crowds_if_hidden_for_crowd? This is useful when e.g. indep is academic disciplines, mesos_var is institutions, and a specific institution is not interested in seeing academic disciplines they do not offer themselves.

add_n_to_dep_label, add_n_to_indep_label

Add N= to the variable label

⁠scalar<logical>⁠ // default: FALSE (optional)

For some plots and tables it is useful to attach the "N=" to the end of the label of the dependent and/or independent variable. Whether it is N or N_valid depends on your showNA-setting. See also translations$add_n_to_dep_label_prefix, translations$add_n_to_dep_label_suffix, translations$add_n_to_indep_label_prefix, translations$add_n_to_indep_label_suffix.

add_n_to_label

Add N= to the variable label of both dep and indep

⁠scalar<logical>⁠ // default: FALSE (optional)

For some plots and tables it is useful to attach the "N=" to the end of the label. Whether it is N or N_valid depends on your showNA-setting. See also translations$add_n_to_label_prefix and translations$add_n_to_label_suffix.

add_n_to_category

Add N= to the category

⁠scalar<logical>⁠ // default: FALSE (optional)

For some plots and tables it is useful to attach the "N=" to the end of the category. This will likely produce a range across the variables, hence an infix (comma) between the minimum and maximum can be specified. Whether it is N or N_valid depends on your showNA-setting. See also translations$add_n_to_category_prefix, translations$add_n_to_category_infix, and translations$add_n_to_category_suffix.

totals

Include totals

⁠scalar<logical>⁠ // default: FALSE (optional)

Whether to include totals in the output.

categories_treated_as_na

NA categories

⁠vector<character>⁠ // default: NULL (optional)

Categories that should be treated as NA.

label_separator

How to separate main question from sub-question

⁠scalar<character>⁠ // default: NULL (optional)

Separator for main question from sub-question.

error_on_duplicates

Error or warn on duplicate labels

⁠scalar<logical>⁠ // default: TRUE (optional)

Whether to abort (TRUE) or warn (FALSE) if the same label (suffix) is used across multiple variables.

showNA

Show NA categories

⁠vector<character>⁠ // default: c("ifany", "always", "never") (optional)

Choose whether to show NA categories in the results.

data_label

Data label

⁠scalar<character>⁠ // default: "proportion" (optional)

One of "proportion", "percentage", "percentage_bare", "count", "mean", or "median".

html_interactive

Toggle interactive plot

⁠scalar<logical>⁠ // default: TRUE (optional)

Whether the plot is to be interactive (ggiraph) or static (ggplot2).

hide_axis_text_if_single_variable

Hide y-axis text if just a single variable

⁠scalar<boolean>⁠ // default: FALSE (optional)

Whether to hide text on the y-axis label if just a single variable.

hide_label_if_prop_below

Hide label threshold

⁠scalar<numeric>⁠ // default: NULL (optional)

Whether to hide label if below this value.

inverse

Flag to swap x-axis and faceting

⁠scalar<logical>⁠ // default: FALSE (optional)

If TRUE, swaps x-axis and faceting.

vertical

Display plot vertically

⁠scalar<logical>⁠ // default: FALSE (optional)

If TRUE, display plot vertically.

digits

Decimal places

⁠scalar<integer>⁠ // default: 0L (optional)

Number of decimal places.

data_label_decimal_symbol

Decimal symbol

⁠scalar<character>⁠ // default: "." (optional)

Decimal marker, some might prefer a comma ',' or something else entirely.

x_axis_label_width, strip_width

Label width of x-axis and strip texts in plots

⁠scalar<integer>⁠ // default: 20 (optional)

Width of the labels used for the categorical column names in x-axis texts and strip texts.

sort_by

What to sort output by

⁠vector<character>⁠ // default: NULL (optional)

Sort output (and collapse if requested). When using indep-argument, sorting differs between ordered factors and unordered factors: Ordering of ordered factors is always respected in output. Unordered factors will be reordered by sort_by. Currently, this works best for a single dep.

NULL: No sorting.
".top": The proportion for the highest category available in the variable.
".upper": The sum of the proportions for the categories above the middle category.
".mid_upper": The sum of the proportions for the categories including and above the middle category.
".mid_lower": The sum of the proportions for the categories including and below the middle category.
".lower": The sum of the proportions for the categories below the middle category.
".bottom": The proportions for the lowest category available in the variable.
".variable_label": Sort by the variable labels.
".variable_name": Sort by the variable names.
".variable_position": Sort by the variable position in the supplied data frame.
".by_group": The groups of the by argument.
character(): Character vector of category labels to sum together.

descend

Sorting order

⁠scalar<logical>⁠ // default: FALSE (optional)

Reverse sorting of sort_by in figures and tables. See arrange_section_by for sorting of report sections.

labels_always_at_top, labels_always_at_bottom

Top/bottom variables

⁠vector<character>⁠ // default: NULL (optional)

Column names in data that should always be placed at the top or bottom of figures/tables.

table_wide

Pivot table wider

⁠scalar<logical>⁠ // default: FALSE (optional)

Whether to pivot table wider.

table_main_question_as_header

Table main question as header

⁠scalar<logical>⁠ // default: FALSE (optional)

Whether to include the main question as a header in the table.

n_categories_limit

Limit for cat_table_ wide format

⁠scalar<integer>⁠ // default: 12 (optional)

If there are more than this number of categories in the categorical variable, cat_table_* will have a long format instead of wide format.

translations

Localize your output

⁠list<character>⁠

A list of translations where the name is the code and the value is the translation. See the examples.

plot_height

DOCX-setting

⁠scalar<numeric>⁠ // default: 12 (optional)

DOCX plots need a height, which currently cannot be set easily with a Quarto chunk option.

colour_palette

Colour palette

⁠vector<character>⁠ // default: NULL (optional)

Must contain at least the number of unique values (including missing) in the data set.

colour_2nd_binary_cat

Colour for second binary category

⁠scalar<character>⁠ // default: "#ffffff" (optional)

Colour for the second category in binary variables. Often useful to hide this.

colour_na

Colour for NA category

⁠scalar<character>⁠ // default: NULL (optional)

Colour as a single string for NA values, if showNA is "ifany" or "always".

main_font_size, label_font_size, strip_font_size, legend_font_size

Font sizes

⁠scalar<integer>⁠ // default: 6 (optional)

ONLY FOR DOCX-OUTPUT. Other output is adjusted using e.g. ggplot2::theme() or set with a global theme (ggplot2::theme_set()). Font sizes for general text (6), data label text (3), strip text (6) and legend text (6).

font_family

Font family

⁠scalar<character>⁠ // default: "sans" (optional)

Word font family. See officer::fp_text.

path

Output path for DOCX

⁠scalar<character>⁠ // default: NULL (optional)

Path to save docx-output.

docx_template

Filename or rdocx object

⁠scalar<character>|<rdocx>-object⁠ // default: NULL (optional)

Can be either a valid character path to a reference Word file, or an existing rdocx-object in memory.

Value

ggplot-object, optionally an extended ggplot object with ggiraph features.

Examples

makeme(
  data = ex_survey,
  dep = b_1:b_3
)
makeme(
  data = ex_survey,
  dep = b_1, indep = x1_sex
)
makeme(
  data = ex_survey,
  dep = b_1:b_3, indep = c(x1_sex, x2_human),
  type = "sigtest_table_html"
)
makeme(
  data = ex_survey,
  dep = b_1, indep = x1_sex,
  type = "cat_prop_plot_docx"
)
makeme(
  data = ex_survey,
  dep = p_1:p_4, indep = x2_human,
  type = "cat_table_html"
)
makeme(
  data = ex_survey,
  dep = b_1:b_3,
  crowd = c("target", "others", "all"),
  mesos_var = "f_uni",
  mesos_group = "Uni of A"
)

Provides a range (or single value) for N in data, given dep and indep

Description

Provides a range (or single value) for N in data, given dep and indep

Usage

n_range(
  data,
  dep,
  indep = NULL,
  mesos_var = NULL,
  mesos_group = NULL,
  glue_template_1 = "{n}",
  glue_template_2 = "[{n[1]}-{n[2]}]"
)

Arguments

data

Dataset

dep, indep

Tidyselect syntax

mesos_var

Optional, NULL or string specifying name of variable used to split dataset.

mesos_group

Optional, NULL or string specifying value in mesos_var indicating the target group.

glue_template_1, glue_template_2

String, for the case of a single value (1) or a range with minimum-maximum of values (2).

Value

String.

Examples

n_range(data = ex_survey, dep = b_1:b_3, indep = x1_sex)

Provides a range (or single value) for N in a `ggplot2`-object from `makeme()`

Description

Provides a range (or single value) for N in a ggplot2-object from makeme()

Usage

n_range2(ggobj, glue_template_1 = "{n}", glue_template_2 = "[{n[1]}-{n[2]}]")

Arguments

ggobj

A ggplot2-object.

glue_template_1, glue_template_2

String, for the case of a single value (1) or a range with minimum-maximum of values (2).

Value

String.

Examples

n_range2(makeme(data = ex_survey, dep = b_1:b_3))

Obtain range of N for a given data set and other settings.

Description

Obtain range of N for a given data set and other settings.

Usage

n_rng(
  data,
  dep,
  indep = NULL,
  crowd = "all",
  mesos_var = NULL,
  mesos_group = NULL,
  glue_template_1 = "{n}",
  glue_template_2 = "[{n[1]}-{n[2]}]"
)

Arguments

data

Dataset

dep, indep

Character vector, names of (in)dependent variables

crowd

String, one of "all", "target" or "others".

mesos_var

Optional, NULL or string specifying name of variable used to split dataset.

mesos_group

Optional, NULL or string specifying value in mesos_var indicating the target group.

glue_template_1, glue_template_2

String, for the case of a single value (1) or a range with minimum-maximum of values (2).

Value

Always a string.

Obtain range of N for a given `ggobj`.

Description

Obtain range of N for a given ggobj.

Usage

n_rng2(ggobj, glue_template_1 = "{n}", glue_template_2 = "[{n[1]}-{n[2]}]")

Arguments

ggobj

A ggplot2-object.

glue_template_1, glue_template_2

String, for the case of a single value (1) or a range with minimum-maximum of values (2).

Value

Always a string.

Code-snippets copied and modified from tidytext-package https://github.com/juliasilge/tidytext/blob/main/R/reorder_within.R

Description

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

Usage

reorder_within(x, by, within, fun = mean, sep = "___", ...)

Arguments

x

Vector

by

Vector

within

Vector (factor)

fun

Function, defaults to the mean

sep

String, separator

...

Dots

Details

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Source

"Original: Ordering categories within ggplot2 Facets" by Tyler Rinker: https://trinkerrstuff.wordpress.com/2016/12/23/ordering-categories-within-ggplot2-facets/ Based on https://opensource.org/licenses/MIT Copyright (c) 2017, Julia Silge and David Robinson

Given Ordered Integer Vector, Return Requested Set.

Description

Useful for identifying which categories are to be collected.

Usage

subset_vector(
  vec,
  set = c(".top", ".upper", ".mid_upper", ".lower", ".mid_lower", ".bottom", ".spread"),
  spread_n = NULL,
  sort = FALSE
)

Arguments

vec

A vector of any type.

set

A character string, one of c(".top", ".upper", ".mid_upper", ".lower", ".mid_lower", ".bottom")

spread_n

The number of values to extract when set is "spread".

sort

Whether to sort the output, defaults to FALSE.

Value

Selected set of vector.

Summarize a survey dataset for use in tables and graphs

Description

Summarize a survey dataset for use in tables and graphs

Usage

summarize_cat_cat_data(
  data,
  dep = colnames(data),
  indep = NULL,
  ...,
  showNA = c("ifany", "always", "never"),
  totals = FALSE,
  sort_by = ".upper",
  data_label = c("percentage_bare", "percentage", "proportion", "count"),
  digits = 0,
  add_n_to_dep_label = FALSE,
  add_n_to_indep_label = FALSE,
  add_n_to_label = FALSE,
  add_n_to_category = FALSE,
  hide_label_if_prop_below = 0.01,
  data_label_decimal_symbol = ".",
  categories_treated_as_na = NULL,
  label_separator = NULL,
  descend = FALSE,
  labels_always_at_bottom = NULL,
  labels_always_at_top = NULL,
  translations = list(),
  call = rlang::caller_env()
)

Arguments

data

Your data.frame/tibble or srvyr-object (experimental)

data.frame // required

The data to be used for plotting.

dep, indep

Variable selections

<tidyselect> // Default: NULL, meaning everything for dep, nothing for indep.

Columns in data. dep is compulsory.

...

Dynamic dots

<dynamic-dots>

Arguments forwarded to the corresponding functions that create the elements.

showNA

Show NA categories

⁠vector<character>⁠ // default: c("ifany", "always", "never") (optional)

Choose whether to show NA categories in the results.

totals

Include totals

⁠scalar<logical>⁠ // default: FALSE (optional)

Whether to include totals in the output.

sort_by

What to sort output by

⁠vector<character>⁠ // default: NULL (optional)

NULL: No sorting.
".top": The proportion for the highest category available in the variable.
".upper": The sum of the proportions for the categories above the middle category.
".mid_upper": The sum of the proportions for the categories including and above the middle category.
".mid_lower": The sum of the proportions for the categories including and below the middle category.
".lower": The sum of the proportions for the categories below the middle category.
".bottom": The proportions for the lowest category available in the variable.
".variable_label": Sort by the variable labels.
".variable_name": Sort by the variable names.
".variable_position": Sort by the variable position in the supplied data frame.
".by_group": The groups of the by argument.
character(): Character vector of category labels to sum together.

data_label

Data label

⁠scalar<character>⁠ // default: "proportion" (optional)

One of "proportion", "percentage", "percentage_bare", "count", "mean", or "median".

digits

Decimal places

⁠scalar<integer>⁠ // default: 0L (optional)

Number of decimal places.

add_n_to_dep_label, add_n_to_indep_label

Add N= to the variable label

⁠scalar<logical>⁠ // default: FALSE (optional)

add_n_to_label

Add N= to the variable label of both dep and indep

⁠scalar<logical>⁠ // default: FALSE (optional)

add_n_to_category

Add N= to the category

⁠scalar<logical>⁠ // default: FALSE (optional)

hide_label_if_prop_below

Hide label threshold

⁠scalar<numeric>⁠ // default: NULL (optional)

Whether to hide label if below this value.

data_label_decimal_symbol

Decimal symbol

⁠scalar<character>⁠ // default: "." (optional)

Decimal marker, some might prefer a comma ',' or something else entirely.

categories_treated_as_na

NA categories

⁠vector<character>⁠ // default: NULL (optional)

Categories that should be treated as NA.

label_separator

How to separate main question from sub-question

⁠scalar<character>⁠ // default: NULL (optional)

Separator for main question from sub-question.

descend

Sorting order

⁠scalar<logical>⁠ // default: FALSE (optional)

Reverse sorting of sort_by in figures and tables. See arrange_section_by for sorting of report sections.

labels_always_at_top, labels_always_at_bottom

Top/bottom variables

⁠vector<character>⁠ // default: NULL (optional)

Column names in data that should always be placed at the top or bottom of figures/tables.

translations

Localize your output

⁠list<character>⁠

A list of translations where the name is the code and the value is the translation. See the examples.

call

Internal call

⁠obj:<call>⁠ // Default: rlang::caller_env() (optional)

Both the absolute and relative folderpaths are required, as strings.

Value

Dataset with the columns: .variable_name, .variable_label, .category, .count, .count_se, .count_per_dep, .count_per_indep_group, .proportion, .proportion_se, .mean, .mean_se, indep-variable(s), .data_label, .comb_categories, .sum_value, .variable_label_prefix

saros: Semi-Automatic Reporting of Ordinary Surveys

Description

Author(s)

See Also

Embed Interactive Categorical Plot (DEPRECATED!)

Description

Usage

Arguments

Embed Reactable Table (DEPRECATED!)

Description

Usage

Arguments

Interactive table of text data (DEPRECATED)

Description

Usage

Arguments

ex_survey: Mockup dataset of a survey.

Description

Usage

Format

Estimate figure height for a horizontal bar chart

Description

Usage

Arguments

Value

Examples

Estimate figure height for a horizontal bar chart

Description

Usage

Arguments

Value

Examples

Provide A Colour Set for A Number of Requested Colours

Description

Usage

Arguments

Value

Provide A Colour Set for A Number of Requested Colours

Description

Usage

Arguments

Value

Get Valid Data Labels for Figures and Tables

Description

Usage

Value

Get all registered options for the type-argument in the makeme-function

Description

Usage

Value

Further details about some of the built-in types:

Expanding with custom types

Examples

Helper function to extract raw variable labels from the data

Description

Usage

Arguments

Value

Wrapper Function for ggplot2::ggsave()

Description

Usage

Arguments

Value

Examples

Pull global plotting settings before displaying plot

Description

Usage

Arguments

Value

Examples

Get Global Options for saros-functions

Description

Usage

Arguments

Value

Examples

Reset Global Options for saros-functions

Description

Usage

Arguments

Get all registered options for the type-argument in the `makeme`-function

Wrapper Function for `ggplot2::ggsave()`

Provides a range (or single value) for N in a `ggplot2`-object from `makeme()`

Obtain range of N for a given `ggobj`.