Full pairwise correlation table

Every numeric pair's correlation in long form – one row per pair, which is easier to sort, filter and join than a matrix. The counterpart of corrr::correlate().

Usage

correlation_table(data, method = c("spearman", "pearson"), min_pairs = 3L)

Arguments

data

A data frame; non-numeric columns are ignored.

method

"spearman" (default) or "pearson". See top_correlations() for why the rank correlation is the default.

min_pairs

Minimum complete pairs required before a correlation is computed (default 3). Below it the pair is NA rather than a number computed from almost nothing.

Value

A data frame of class bricklayer_cortable with x, y, correlation and n_pairs.

See also

top_correlations() for just the strongest, core_cov() for the matrix form.

Examples

set.seed(1)
df <- data.frame(a = stats::rnorm(100), b = stats::rnorm(100))
df$c <- df$a + stats::rnorm(100, sd = 0.2)

correlation_table(df)
#> ── Correlations (spearman) ─────────────────────────────────────── 
#>  x y correlation n_pairs
#>  a b       0.039     100
#>  a c       0.967     100
#>  b c       0.015     100
#> ────────────────────────────────────────────────────────────────── 

# n_pairs shows how much data each figure rests on.
gappy <- df
gappy$a[1:80] <- NA
correlation_table(gappy)
#> ── Correlations (spearman) ─────────────────────────────────────── 
#>  x y correlation n_pairs
#>  a b       0.165      20
#>  a c       0.959      20
#>  b c       0.015     100
#> ────────────────────────────────────────────────────────────────── 

# A pair with too little overlap is NA, not a number from nothing.
thin <- df
thin$a[1:99] <- NA
correlation_table(thin)$correlation
#> [1]         NA         NA 0.01508551