Description Usage Arguments Details Value Author(s) References See Also Examples
This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 | 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,
...
)
|
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. |
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 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).
A list of dataframes with the requested values.
Gjalt-Jorn Peters
Maintainer: Gjalt-Jorn Peters gjalt-jorn@userfriendlyscience.com
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.
summary
, [psych::describe()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ### 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
)
);
|
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