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Descriptive statistics.
Describe(
data,
all.as.numeric = TRUE,
digits = 2,
nsmall = digits,
file = NULL,
plot = FALSE,
upper.triangle = FALSE,
upper.smooth = "none",
plot.file = NULL,
plot.width = 8,
plot.height = 6,
plot.dpi = 500
)
Data frame or numeric vector.
TRUE
(default) or FALSE
.
Transform all variables into numeric (continuous).
Number of decimal places of output. Default is 2
.
File name of MS Word (.doc
).
TRUE
or FALSE
(default).
Visualize the descriptive statistics using GGally::ggpairs()
.
TRUE
or FALSE
(default).
Add (scatter) plots to upper triangle (time consuming when sample size is large).
"none"
(default), "lm"
, or "loess"
.
Add fitting lines to scatter plots (if any).
NULL
(default, plot in RStudio) or a file name ("xxx.png"
).
Width (in "inch") of the saved plot. Default is 8
.
Height (in "inch") of the saved plot. Default is 6
.
DPI (dots per inch) of the saved plot. Default is 500
.
Invisibly return a list consisting of
(1) a data frame of descriptive statistics and
(2) a ggplot2
object if users set plot=TRUE
.
# NOT RUN {
set.seed(1)
Describe(rnorm(1000000), plot=TRUE)
Describe(airquality)
Describe(airquality, plot=TRUE, upper.triangle=TRUE, upper.smooth="lm")
# ?psych::bfi
Describe(psych::bfi[c("age", "gender", "education")])
d=as.data.table(psych::bfi)
d[, `:=`(
gender=as.factor(gender),
education=as.factor(education),
E=MEAN(d, "E", 1:5, rev=c(1,2), likert=1:6),
A=MEAN(d, "A", 1:5, rev=1, likert=1:6),
C=MEAN(d, "C", 1:5, rev=c(4,5), likert=1:6),
N=MEAN(d, "N", 1:5, likert=1:6),
O=MEAN(d, "O", 1:5, rev=c(2,5), likert=1:6)
)]
Describe(d[, .(age, gender, education)], plot=TRUE, all.as.numeric=FALSE)
Describe(d[, .(age, gender, education, E, A, C, N, O)], plot=TRUE)
# }
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