Convert the upper or lower triangle of a correlation data frame (cor_df) to missing values.
Arguments
- x
cor_df. See
correlate.- upper
Boolean. If TRUE, set upper triangle to NA; lower triangle if FALSE.
Value
cor_df. See correlate.
Examples
x <- correlate(mtcars)
#> Correlation computed with
#> • Method: 'pearson'
#> • Missing treated using: 'pairwise.complete.obs'
shave(x) # Default; shave upper triangle
#> # A tibble: 11 × 12
#> term mpg cyl disp hp drat wt qsec vs am
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 mpg NA NA NA NA NA NA NA NA NA
#> 2 cyl -0.852 NA NA NA NA NA NA NA NA
#> 3 disp -0.848 0.902 NA NA NA NA NA NA NA
#> 4 hp -0.776 0.832 0.791 NA NA NA NA NA NA
#> 5 drat 0.681 -0.700 -0.710 -0.449 NA NA NA NA NA
#> 6 wt -0.868 0.782 0.888 0.659 -0.712 NA NA NA NA
#> 7 qsec 0.419 -0.591 -0.434 -0.708 0.0912 -0.175 NA NA NA
#> 8 vs 0.664 -0.811 -0.710 -0.723 0.440 -0.555 0.745 NA NA
#> 9 am 0.600 -0.523 -0.591 -0.243 0.713 -0.692 -0.230 0.168 NA
#> 10 gear 0.480 -0.493 -0.556 -0.126 0.700 -0.583 -0.213 0.206 0.794
#> 11 carb -0.551 0.527 0.395 0.750 -0.0908 0.428 -0.656 -0.570 0.0575
#> # … with 2 more variables: gear <dbl>, carb <dbl>
#> # ℹ Use `colnames()` to see all variable names
shave(x, upper = FALSE) # shave lower triangle
#> # A tibble: 11 × 12
#> term mpg cyl disp hp drat wt qsec vs am
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 mpg NA -0.852 -0.848 -0.776 0.681 -0.868 0.419 0.664 0.600
#> 2 cyl NA NA 0.902 0.832 -0.700 0.782 -0.591 -0.811 -0.523
#> 3 disp NA NA NA 0.791 -0.710 0.888 -0.434 -0.710 -0.591
#> 4 hp NA NA NA NA -0.449 0.659 -0.708 -0.723 -0.243
#> 5 drat NA NA NA NA NA -0.712 0.0912 0.440 0.713
#> 6 wt NA NA NA NA NA NA -0.175 -0.555 -0.692
#> 7 qsec NA NA NA NA NA NA NA 0.745 -0.230
#> 8 vs NA NA NA NA NA NA NA NA 0.168
#> 9 am NA NA NA NA NA NA NA NA NA
#> 10 gear NA NA NA NA NA NA NA NA NA
#> 11 carb NA NA NA NA NA NA NA NA NA
#> # … with 2 more variables: gear <dbl>, carb <dbl>
#> # ℹ Use `colnames()` to see all variable names