complete_cases: Statistics/Summaries with (Only) Missing Data Removed

In roperators: Additional Operators to Help you Write Cleaner R Code

Statistics/Summaries with (Only) Missing Data Removed

Description

Univariate and bivariate summaries and statistics with the least missing data removed (such as complete-cases correlations). These are typically default arguments to standard statistics functions.

Usage

length_cc(x, ...)

n_unique_cc(x, ...)

min_cc(x, ...)

max_cc(x, ...)

range_cc(x, ...)

all_cc(x, ...)

any_cc(x, ...)

sum_cc(x, ...)

prod_cc(x, ...)

mean_cc(x, ...)

median_cc(x, ...)

var_cc(x, y = NULL, ...)

cov_cc(x, y = NULL, ...)

cor_cc(x, y = NULL, ...)

sd_cc(x, ...)

weighted.mean_cc(x, w, ...)

quantile_cc(x, ...)

IQR_cc(x, ...)

mad_cc(x, ...)

rowSums_cc(x, ...)

colSums_cc(x, ...)

rowMeans_cc(x, ..., rescale = FALSE)

colMeans_cc(x, ..., rescale = FALSE)

Arguments

x	An R object. Currently there are methods for numeric/logical vectors and date, date-time and time interval objects. Complex vectors are allowed for trim = 0, only.
...	arguments to pass to wrapped functions
y	NULL (default) or a vector, matrix or data frame with compatible dimensions to x. The default is equivalent to y = x (but more efficient).
w	a numerical vector of weights the same length as x giving the weights to use for elements of x.
rescale	whether to rescale the matrix/df/vector before calculating summaries

Examples

n_o <- 20
n_m <- round(n_o / 3)
x   <- rnorm(n_o)
y   <- rnorm(n_o)

x[sample(n_o, n_m)] <- NA
y[sample(n_o, n_m)] <- NA

mean_cc(x)   # mean of complete cases
mean_cc(y)
var_cc(x)    # variance of complete cases
var_cc(y)
cor_cc(x, y) # correlation between available cases

roperators documentation built on July 26, 2023, 5:27 p.m.