define_keywords: Modify Keywords Used In Outputs

View source: R/define_keywords.R

define_keywordsR Documentation

Modify Keywords Used In Outputs

Description

As an alternative to use_custom_lang, this function allows temporarily modifying the pre-defined terms in the outputs.

Usage

define_keywords(..., ask = FALSE, file = NA)

Arguments

...

One or more pairs of keywords and their new values see Details for the complete list of existing keywords.

ask

Logical. When 'TRUE' (default), a dialog box comes up to ask whether to save the edited values in a csv file for later use.

file

Character. Path and name of custom language file to be saved. This comma delimited file can be reused by calling use_custom_lang.

Details

On systems with GUI capabilities, a window will pop-up when calling define_keywords() without any parameters, allowing the modification of the custom column. The changes will be active as long as the package is loaded. When the edit window is closed, a dialog will pop up, prompting the user to save the modified set of keywords in a custom csv language file that can later be used with use_custom_lang.

Here is the full list of modifiable keywords.

title.freq

main heading for freq()

title.freq.weighted

main heading for freq() (weighted)

title.ctable

main heading for ctable()

title.ctable.weighted

main heading ctable() (weighted)

title.ctable.row

indicates what proportions are displayed

title.ctable.col

indicates what proportions are displayed

title.ctable.tot

indicates what proportions are displayed

title.descr

main heading for descr()

title.descr.weighted

main heading for descr() (weighted)

title.dfSummary

main heading for dfSummary()

n

heading item used in descr()

dimensions

heading item used in dfSummary()

duplicates

heading item used in dfSummary()

data.frame

heading item (all functions)

label

heading item (all functions) & column name in dfSummary()

variable

heading item (all functions) & column name in dfSummary()

group

heading item (all functions when used with stby()

by

heading item for descr() when used with stby()

weights

heading item - descr() & freq()

type

heading item for freq()

logical

heading item - type in freq()

character

heading item - type in freq()

numeric

heading item - type in freq()

factor

heading item - type in freq()

factor.ordered

heading item - type in freq()

date

heading item - type in freq()

datetime

heading item - type in freq()

freq

column name in freq()

pct

column name in freq() when report.nas=FALSE

pct.valid.f

column name in freq()

pct.valid.cum

column name in freq()

pct.total

column name in freq()

pct.total.cum

column name in freq()

pct.cum

column name in freq()

valid

column name in freq() and dfSummary() & column content in dfSummary()

invalid

column content in dfSummary() (emails)

total

column grouping in freq(), html version

mean

row name in descr()

sd.long

row name in descr()

sd

cell content (dfSummary)

min

row name in descr()

q1

row name in descr() - 1st quartile

med

row name in descr()

q3

row name in descr() - 3rd quartile

max

row name in descr()

mad

row name in descr() - Median Absolute Deviation

iqr

row name in descr() - Inter-Quartile Range

cv

row name in descr() - Coefficient of Variation

skewness

row name in descr()

se.skewness

row name in descr() - Std. Error for Skewness

kurtosis

row name in descr()

n.valid

row name in descr() - Count of non-missing values

pct.valid

row name in descr() - pct. of non-missing values

no

column name in dfSummary() - position of column in the data frame

stats.values

column name in dfSummary()

freqs.pct.valid

column name in dfSummary()

graph

column name in dfSummary()

missing

column name in dfSummary()

distinct.value

cell content in dfSummary() - singular form

distinct.values

cell content in dfSummary() - plural form

all.nas

cell content in dfSummary() - column has only NAs

all.empty.str

cell content in dfSummary() - column has only empty strings

all.empty.str.nas

cell content in dfSummary() - col. has only NAs and empty strings

no.levels.defined

cell content in dfSummary() - factor has no levels defined

int.sequence

cell content in dfSummary()

rounded

cell content in dfSummary() - note appearing in Stats/Values

others

cell content in dfSummary() - nbr of values not displayed

codes

cell content in dfSummary() - When UPC codes are detected

mode

cell content in dfSummary() - mode = most frequent value

med.short

cell content in dfSummary() - median (shortened term)

start

cell content in dfSummary() - earliest date for date-type cols

end

cell content in dfSummary() - latest date for data-type cols

emails

cell content in dfSummary()

generated.by

footnote content

version

footnote content

date.fmt

footnote - date format (see strptime)

Note

Setting a keyword starting with “title.” to NA or to empty string causes the main title to disappear altogether, which might be desired in some circumstances (when generating a table of contents, for instance).

Examples

## Not run: 
define_keywords(n = "Nb. Obs.")

## End(Not run) 


summarytools documentation built on May 20, 2022, 9:06 a.m.