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
mpg | cyl | disp | hp | drat | wt | qsec | vs | am | gear | carb | |
mpg | |||||||||||
cyl | |||||||||||
disp | |||||||||||
hp | |||||||||||
drat | |||||||||||
wt | |||||||||||
qsec | |||||||||||
vs | |||||||||||
am | |||||||||||
gear | |||||||||||
carb |