Heatmaps

 Quick and easy solutions

library(gplots)
library("RColorBrewer")
## scale the dataset
df = scale(mtcars)

knitr::kable(head(df, 5)) ## first five rows

	mpg	cyl	disp	hp	drat	wt	qsec	vs	am	gear	carb
Mazda RX4	0.1508848	-0.1049878	-0.5706198	-0.5350928	0.5675137	-0.6103996	-0.7771651	-0.8680278	1.1899014	0.4235542	0.7352031
Mazda RX4 Wag	0.1508848	-0.1049878	-0.5706198	-0.5350928	0.5675137	-0.3497853	-0.4637808	-0.8680278	1.1899014	0.4235542	0.7352031
Datsun 710	0.4495434	-1.2248578	-0.9901821	-0.7830405	0.4739996	-0.9170046	0.4260068	1.1160357	1.1899014	0.4235542	-1.1221521
Hornet 4 Drive	0.2172534	-0.1049878	0.2200937	-0.5350928	-0.9661175	-0.0022995	0.8904872	1.1160357	-0.8141431	-0.9318192	-1.1221521
Hornet Sportabout	-0.2307345	1.0148821	1.0430812	0.4129422	-0.8351978	0.2276543	-0.4637808	-0.8680278	-0.8141431	-0.9318192	-0.5030337

heatmap(df, scale = "none", 
        col= colorRampPalette(brewer.pal(10, "Blues"))(256))

## or eventually with color key

heatmap.2(df, scale = "none", col = greenred(100),
          trace = "none", density.info = "none")

## With another package
library("pheatmap") 
pheatmap(df, cutree_rows = 4, colorRampPalette(brewer.pal(10, "OrRd"))(256))

## An Interactive way
library("d3heatmap")
d3heatmap(scale(mtcars), colors = "Spectral",
          k_row = 4, # Number of groups in rows 
          k_col = 2) # Number of groups in columns 

library(dendextend)
# order for rows
Rowv <- mtcars %>% scale %>% dist %>% hclust %>% as.dendrogram %>%
  set("branches_k_color", k = 3) %>% set("branches_lwd", 1.2) %>%
  ladderize
# Order for columns: We must transpose the data
Colv <- mtcars %>% scale %>% t %>% dist %>% hclust %>% as.dendrogram %>% set("branches_k_color", k = 2, value = c("orange", "blue")) %>% set("branches_lwd", 1.2) %>%
  ladderize

heatmap(scale(mtcars), Rowv = Rowv, Colv = Colv, scale = "none")

## with gqplot package
heatmap.2(scale(mtcars), scale = "none", col = greenred(100),
          Rowv = Rowv, Colv = Colv,
          trace = "none", density.info = "none")

## with d3heatmap

d3heatmap(scale(mtcars), colors = "Spectral",
                               Rowv = Rowv, Colv = Colv)

Code suggestions come from Alboukadel Kassambara, Practical Guide To Cluster Analysis in R