Correlation matrix

David Gohel

These examples is using a correlation matrix as data source.

# correlations ----
correlations <- cor(mtcars)
correlations <- data.frame(
  rowname = row.names(correlations), 
  stringsAsFactors = FALSE) %>%
  cbind(correlations)
correlations
##      rowname        mpg        cyl       disp         hp        drat         wt
## mpg      mpg  1.0000000 -0.8521620 -0.8475514 -0.7761684  0.68117191 -0.8676594
## cyl      cyl -0.8521620  1.0000000  0.9020329  0.8324475 -0.69993811  0.7824958
## disp    disp -0.8475514  0.9020329  1.0000000  0.7909486 -0.71021393  0.8879799
## hp        hp -0.7761684  0.8324475  0.7909486  1.0000000 -0.44875912  0.6587479
## drat    drat  0.6811719 -0.6999381 -0.7102139 -0.4487591  1.00000000 -0.7124406
## wt        wt -0.8676594  0.7824958  0.8879799  0.6587479 -0.71244065  1.0000000
## qsec    qsec  0.4186840 -0.5912421 -0.4336979 -0.7082234  0.09120476 -0.1747159
## vs        vs  0.6640389 -0.8108118 -0.7104159 -0.7230967  0.44027846 -0.5549157
## am        am  0.5998324 -0.5226070 -0.5912270 -0.2432043  0.71271113 -0.6924953
## gear    gear  0.4802848 -0.4926866 -0.5555692 -0.1257043  0.69961013 -0.5832870
## carb    carb -0.5509251  0.5269883  0.3949769  0.7498125 -0.09078980  0.4276059
##             qsec         vs          am       gear        carb
## mpg   0.41868403  0.6640389  0.59983243  0.4802848 -0.55092507
## cyl  -0.59124207 -0.8108118 -0.52260705 -0.4926866  0.52698829
## disp -0.43369788 -0.7104159 -0.59122704 -0.5555692  0.39497686
## hp   -0.70822339 -0.7230967 -0.24320426 -0.1257043  0.74981247
## drat  0.09120476  0.4402785  0.71271113  0.6996101 -0.09078980
## wt   -0.17471588 -0.5549157 -0.69249526 -0.5832870  0.42760594
## qsec  1.00000000  0.7445354 -0.22986086 -0.2126822 -0.65624923
## vs    0.74453544  1.0000000  0.16834512  0.2060233 -0.56960714
## am   -0.22986086  0.1683451  1.00000000  0.7940588  0.05753435
## gear -0.21268223  0.2060233  0.79405876  1.0000000  0.27407284
## carb -0.65624923 -0.5696071  0.05753435  0.2740728  1.00000000
cor_color <- function(x){
  col_palette <- c("#D73027", "#F46D43", "#FDAE61", "#FEE08B", 
                   "#D9EF8B", "#A6D96A", "#66BD63", "#1A9850")
  mycut <- cut(x, 
    breaks = c(-1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1), 
    include.lowest = TRUE, label = FALSE)
  col_palette[mycut]
}

std_border <- fp_border_default(color = "white")

flextable

ft <- flextable(correlations) %>%
  border_outer(part = "all", border = std_border) %>%
  border_inner(border = std_border, part = "all") %>%
  compose(i = 1, j = 1, value = as_paragraph(""), part = "header") %>%
  compose(j = ~ . - rowname, value = as_paragraph(""), part = "body") %>%
  bg(j = ~ . - rowname, bg = cor_color) %>%
  height(height = .5) %>%
  hrule(rule = "exact", part = "body") %>%
  width(width = .5)

ft