Conditionally focus correlation data frame

Apply a predicate function to each column of correlations. Columns that evaluate to TRUE will be included in a call to focus.

Usage

focus_if(x, .predicate, ..., mirror = FALSE)

Arguments

x: Correlation data frame or object to be coerced to one via as_cordf.
.predicate: A predicate function to be applied to the columns. The columns for which .predicate returns TRUE will be included as variables in focus.
...: Additional arguments to pass to the predicate function if not anonymous.
mirror: Boolean. Whether to mirror the selected columns in the rows or not.

Value

A tibble or, if mirror = TRUE, a correlation data frame.

Examples

library(dplyr)
any_greater_than <- function(x, val) {
  mean(abs(x), na.rm = TRUE) > val
}

x <- correlate(mtcars)
#> Correlation computed with
#> • Method: 'pearson'
#> • Missing treated using: 'pairwise.complete.obs'

x %>% focus_if(any_greater_than, .6)
#> # A tibble: 6 × 6
#>   term     mpg    cyl   disp     hp     wt
#>   <chr>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
#> 1 drat   0.681 -0.700 -0.710 -0.449 -0.712
#> 2 qsec   0.419 -0.591 -0.434 -0.708 -0.175
#> 3 vs     0.664 -0.811 -0.710 -0.723 -0.555
#> 4 am     0.600 -0.523 -0.591 -0.243 -0.692
#> 5 gear   0.480 -0.493 -0.556 -0.126 -0.583
#> 6 carb  -0.551  0.527  0.395  0.750  0.428
x %>% focus_if(any_greater_than, .6, mirror = TRUE) %>% network_plot()