descr (or descriptives)

This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.

descr(
  x,
  digits = 4,
  errorOnFactor = FALSE,
  include = c("central tendency", "spread", "range", "distribution shape", "sample size"),
  maxModes = 1,
  t = FALSE,
  conf.level = 0.95,
  quantileType = 2
)

# S3 method for default
descr(
  x,
  digits = 4,
  errorOnFactor = FALSE,
  include = c("central tendency", "spread", "range", "distribution shape", "sample size"),
  maxModes = 1,
  t = FALSE,
  conf.level = 0.95,
  quantileType = 2
)

# S3 method for descr
print(
  x,
  digits = attr(x, "digits"),
  t = attr(x, "transpose"),
  row.names = FALSE,
  ...
)

# S3 method for descr
pander(x, headerPrefix = "", headerStyle = "**", ...)

# S3 method for descr
as.data.frame(x, row.names = NULL, optional = FALSE, ...)

# S3 method for data.frame
descr(x, ...)

Arguments

x

The vector for which to return descriptives.

digits

The number of digits to round the results to when showing them.

errorOnFactor

Whether to show an error when the vector is a factor, or just show the frequencies instead.

include

Which elements to include when showing the results.

maxModes

Maximum number of modes to display: displays "multi" if more than this number of modes if found.

t

Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers).

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 quantile for more information.

row.names

Whether to show row names (TRUE) or not (FALSE).

...

Additional arguments are passed to the default print and pander methods.

headerPrefix

The prefix for the heading; can be used to insert hashes (#) to create Markdown headings.

headerStyle

A string to insert before and after the heading (to make stuff bold or italic in Markdown).

optional

Provided for compatibility with the default as.data.frame() method - see that help page for details.

Value

A list of dataframes with the requested values.

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. multidimensionality, computed by diptest::dip.test() from the dip.test package. 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 diptest::dip.test(); also see Table 1 of Hartigan & Hartigan (1985) for an indication as to critical values).

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()

Author

Gjalt-Jorn Peters

Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com

Examples

descr(mtcars$mpg);
#> ###### Descriptives for mtcars$mpg 
#> 
#> Describing the central tendency:
#>   mean median    mode    95% CI mean
#>  20.09   19.2 (multi) [17.92; 22.26]
#> 
#> Describing the spread:
#>    var    sd  iqr    se
#>  36.32 6.027 7.45 1.065
#> 
#> Describing the range:
#>   min   q1   q3  max
#>  10.4 15.2 22.8 33.9
#> 
#> Describing the distribution shape:
#>  skewness kurtosis    dip
#>    0.6724 -0.02201 0.0569
#> 
#> Describing the sample size:
#>  total NA. valid
#>     32   0    32
#>