| descr {rosetta} | R Documentation | 
descr (or descriptives)
Description
This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.
Usage
descr(
  x,
  items = names(x),
  varLabels = NULL,
  mean = TRUE,
  meanCI = TRUE,
  median = TRUE,
  mode = TRUE,
  var = TRUE,
  sd = TRUE,
  se = FALSE,
  min = TRUE,
  max = TRUE,
  q1 = FALSE,
  q3 = FALSE,
  IQR = FALSE,
  skewness = TRUE,
  kurtosis = TRUE,
  dip = TRUE,
  totalN = TRUE,
  missingN = TRUE,
  validN = TRUE,
  histogram = FALSE,
  boxplot = FALSE,
  digits = 2,
  errorOnFactor = FALSE,
  convertFactor = FALSE,
  maxModes = 1,
  maxPlotCols = 4,
  t = FALSE,
  headingLevel = 3,
  conf.level = 0.95,
  quantileType = 2
)
rosettaDescr_partial(
  x,
  digits = attr(x, "digits"),
  show = attr(x, "show"),
  headingLevel = attr(x, "headingLevel"),
  maxPlotCols = attr(x, "maxPlotCols"),
  echoPartial = FALSE,
  partialFile = NULL,
  quiet = TRUE,
  ...
)
## S3 method for class 'rosettaDescr'
knit_print(
  x,
  digits = attr(x, "digits"),
  show = attr(x, "show"),
  headingLevel = attr(x, "headingLevel"),
  maxPlotCols = attr(x, "maxPlotCols"),
  echoPartial = FALSE,
  partialFile = NULL,
  quiet = TRUE,
  ...
)
## S3 method for class 'rosettaDescr'
print(
  x,
  digits = attr(x, "digits"),
  show = attr(x, "show"),
  maxPlotCols = attr(x, "maxPlotCols"),
  headingLevel = attr(x, "headingLevel"),
  forceKnitrOutput = FALSE,
  ...
)
Arguments
x | 
 The object to print (i.e. as produced by   | 
items | 
 Optionally, if   | 
varLabels | 
 Optionally, a named vector with 'pretty labels' to show
for the variables. This has to be a vector of the same length as   | 
mean, meanCI, median, mode | 
 Whether to compute the mean, its
confidence interval, the median, and/or the mode (all logical, so   | 
var, sd, se | 
 Whether to compute the variance, standard deviation, and
standard error (all logical, so   | 
min, max, q1, q3, IQR | 
 Whether to compute the minimum, maximum, first and
third quartile, and inter-quartile range (all logical, so   | 
skewness, kurtosis, dip | 
 Whether to compute the skewness, kurtosis and
dip test (all logical, so   | 
totalN, missingN, validN | 
 Whether to show the total sample size, the
number of missing values, and the number of valid (i.e. non-missing) values
(all logical, so   | 
histogram, boxplot | 
 Whether to show a histogram and/or boxplot  | 
digits | 
 The number of digits to round the results to when showing them.  | 
errorOnFactor, convertFactor | 
 If   | 
maxModes | 
 Maximum number of modes to display: displays "multi" if more than this number of modes if found.  | 
maxPlotCols | 
 The maximum number of columns when plotting multiple histograms and/or boxplots.  | 
t | 
 Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers). Note: this functionality has not yet been implemented!  | 
headingLevel | 
 The number of hashes to print in front of the headings when printing while knitting  | 
conf.level | 
 Confidence of confidence interval around the mean in the central tendency measures.  | 
quantileType | 
 The type of quantiles to be used to compute the
interquartile range (IQR). See   | 
show | 
 A vector of elements to show in the results, based on the
arguments that activate/deactivate the descriptives (from   | 
echoPartial | 
 Whether to show the executed code in the R Markdown
partial (  | 
partialFile | 
 This can be used to specify a custom partial file. The
file will have object   | 
quiet | 
 Passed on to   | 
... | 
 Any additional arguments are passed to the default print method
by the print method, and to   | 
forceKnitrOutput | 
 Force knitr output.  | 
Details
Note that R (of course) has many similar functions, such as
summary, psych::describe() in the excellent
psych::psych package.
The Hartigans' Dip Test may be unfamiliar to users; it is a measure of uni-
vs. multimodality, computed by the dip.test() function from the
{diptest} package from the. Depending on the sample size, values over
.025 can be seen as mildly indicative of multimodality, while values over
.05 probably warrant closer inspection (the p-value can be obtained using
that dip.test() function from {diptest}; also see Table 1 of
Hartigan & Hartigan (1985) for an indication as to critical values).
Value
A list of dataframes with the requested values.
Author(s)
Gjalt-Jorn Peters
Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com
References
Hartigan, J. A.; Hartigan, P. M. The Dip Test of Unimodality. Ann. Statist. 13 (1985), no. 1, 70–84. doi:10.1214/aos/1176346577. https://projecteuclid.org/euclid.aos/1176346577.
See Also
summary, [psych::describe()
Examples
### Simplest example with default settings
descr(mtcars$mpg);
### Also requesting a histogram and boxplot
descr(mtcars$mpg, histogram=TRUE, boxplot=TRUE);
### To show the output as Rmd Partial in the viewer
rosetta::rosettaDescr_partial(
  rosetta::descr(
    mtcars$mpg
  )
);
### Multiple variables, including one factor
rosetta::rosettaDescr_partial(
  rosetta::descr(
    iris
  )
);