Determine the Pearson correlation coefficient between two variables in a data frame using pipeable and formula-friendly syntax
get_correlation(data, formula, na.rm = FALSE, ...)a data frame object
a formula with the response variable name on the left and the explanatory variable name on the right
a logical value indicating whether NA values should be stripped before the computation proceeds.
further arguments passed to stats::cor()
A 1x1 data frame storing the correlation value
library(moderndive)
# Compute correlation between mpg and cyl:
mtcars %>%
get_correlation(formula = mpg ~ cyl)
#> cor
#> 1 -0.852162
# Group by one variable:
library(dplyr)
mtcars %>%
group_by(am) %>%
get_correlation(formula = mpg ~ cyl)
#> # A tibble: 2 × 2
#> am cor
#> <dbl> <dbl>
#> 1 0 -0.796
#> 2 1 -0.826
# Group by two variables:
mtcars %>%
group_by(am, gear) %>%
get_correlation(formula = mpg ~ cyl)
#> # A tibble: 4 × 3
#> # Groups: am [2]
#> am gear cor
#> <dbl> <dbl> <dbl>
#> 1 0 3 -0.645
#> 2 0 4 -0.959
#> 3 1 4 -0.601
#> 4 1 5 -0.961