Heatmap in ggplot2 issue with fill - r

Question

I'm trying to make a heatmap using ggplot2. What I want to be plotted is in the form of a matrix which is the result of a function.
Here is the data:
Image A B C D E F
1 3 23 45 23 45 90
2 4 34 34 34 34 89
3 34 33 24 89 23 67
4 3 45 234 90 12 78
5 78 89 34 23 12 56
6 56 90 56 67 34 45
Here is the function:
vector_a <- names(master)[2:4]
vector_b <- names(master)[5:6]
heatmap_prep <- function(dataframe, vector_a,vector_b){
dummy <- as.data.frame(matrix(0, nrow=length(vector_a), ncol=length(vector_b)))
for (i in 1:length(vector_a)){
first_value <- dataframe[[ vector_a[i] ]]
# print(first_value)
for(j in 1:length(vector_b)){
second_value <- dataframe[[ vector_b[j] ]]
result <- cor(first_value, second_value, method = "spearman")
dummy [i,j] <- result
}
}
rownames(dummy) <- vector_a
return(as.matrix(dummy))
heatmap_data_matrix1 <- heatmap_prep(master,vector_a, vector_b)
Using the data in heatmap_data_matrix1, I want to create a heatmap using the following code:
library(ggplot2)
if (length(grep("ggplot2", (.packages() ))) == 0){
library(ggplot2)
}
p <- ggplot(data = heatmap_data_matrix1, aes(x = vector_a, y = vector_b)
+ geom_tile(aes(fill = ))
However, this does not work. How should I reformat my data/code so this heatmap can be created? What should I put under "fill="?
Thanks!

Answer 1

Due to many of R functions being vectorized and that, for the most part, you don't need to pre-allocate or define a vector the for loop is unnecessary. You can simply run corr(x,y, method = "spearman") without the complications of the loop.
Regarding your question of what to put in for fill, you'll need to reshape your data to the configuration that ggplot2 uses (long format).
The gather function from tidyr does this, placing the rows/columns of the correlation into separate columns, and then using the r value for fill.
library(tidyverse) # for tidyr, tibble, ggplot2, and magrittr
heatmap_function <- function(df, a, b) {
cor_data <- cor(df[a], df[b], method = "spearman") %>%
as.data.frame(rownames = a) %>%
rownames_to_column("x") %>%
gather(y, fill, -x)
ggplot(cor_data, aes(x = x, y = y, fill = fill)) +
geom_tile()
}
This results in:
heatmap_function(master, c("A","B","C"), c("D","E"))