desc_stat {metan} | R Documentation |
Descriptive statistics
Description
-
desc_stat()
Computes the most used measures of central tendency, position, and dispersion. -
desc_wider()
is useful to put the variables in columns and grouping variables in rows. The table is filled with a statistic chosen with the argumentstat
.
Usage
desc_stat(
.data = NULL,
...,
by = NULL,
stats = "main",
hist = FALSE,
level = 0.95,
digits = 4,
na.rm = FALSE,
verbose = TRUE,
plot_theme = theme_metan()
)
desc_wider(.data, which)
Arguments
.data |
The data to be analyzed. It can be a data frame (possible with
grouped data passed from |
... |
A single variable name or a comma-separated list of unquoted
variables names. If no variable is informed, all the numeric variables from
|
by |
One variable (factor) to compute the function by. It is a shortcut
to |
stats |
The descriptive statistics to show. This is used to filter the
output after computation. Defaults to
Use a names to select the statistics. For example, |
hist |
Logical argument defaults to |
level |
The confidence level to compute the confidence interval of mean. Defaults to 0.95. |
digits |
The number of significant digits. |
na.rm |
Logical. Should missing values be removed? Defaults to |
verbose |
Logical argument. If |
plot_theme |
The graphical theme of the plot. Default is
|
which |
A statistic to fill the table. |
Value
-
desc_stats()
returns a tibble with the statistics in the columns and variables (with possible grouping factors) in rows. -
desc_wider()
returns a tibble with variables in columns and grouping factors in rows.
Author(s)
Tiago Olivoto tiagoolivoto@gmail.com
Examples
library(metan)
#===============================================================#
# Example 1: main statistics (coefficient of variation, maximum,#
# mean, median, minimum, sample standard deviation, standard #
# error and confidence interval of the mean) for all numeric #
# variables in data #
#===============================================================#
desc_stat(data_ge2)
#===============================================================#
#Example 2: robust statistics using a numeric vector as input #
# data
#===============================================================#
vect <- data_ge2$TKW
desc_stat(vect, stats = "robust")
#===============================================================#
# Example 3: Select specific statistics. In this example, NAs #
# are removed before analysis with a warning message #
#===============================================================#
desc_stat(c(12, 13, 19, 21, 8, NA, 23, NA),
stats = c('mean, se, cv, n, n.valid'),
na.rm = TRUE)
#===============================================================#
# Example 4: Select specific variables and compute statistics by#
# levels of a factor variable (GEN) #
#===============================================================#
stats <-
desc_stat(data_ge2,
EP, EL, EH, ED, PH, CD,
by = GEN)
stats
# To get a 'wide' format with the maximum values for all variables
desc_wider(stats, max)
#===============================================================#
# Example 5: Compute all statistics for all numeric variables #
# by two or more factors. Note that group_by() was used to pass #
# grouped data to the function desc_stat() #
#===============================================================#
data_ge2 %>%
group_by(ENV, GEN) %>%
desc_stat()