Thank you for the suggestion. I tried it, but could not get it to work.
When I added a second ggplot statement, I hit an error saying that one
cannot add a ggplot to a ggplot object. So I added a second geom_tile
statement instead. That worked, except that it warned that since a scale
for fill was already present, the new fill would replace the old one. In
other words, the colour scale was changed not just for the target, B,
but also for the other two variables. So I am still searching for a
solution.
Philip
On 2024-12-09 23:33, Ebert,Timothy Aaron wrote:
What happens if you switch the colors in this line:
scale_fill_gradient2(low = "#E94A26", mid = "white", high =
"#A1D385", midpoint = 0.5) +
to be the following
scale_fill_gradient2(low = "# A1D385", mid = "white", high = "#
E94A26", midpoint = 0.5) +
That said, a red-green heat map may be unhelpful to color blind people.
So then you need two ggplot statements, one with each
scale_fill_gradient2 and then specify which version to plot for each
variable.
Tim
-----Original Message-----
From: R-help <r-help-boun...@r-project.org> On Behalf Of
p...@philipsmith.ca
Sent: Monday, December 9, 2024 7:56 PM
To: R-help@r-project.org
Subject: [R] Heat maps containing two types of variables
[External Email]
I am working with a heat map, as in the REPREX below. The code works
fine as long as "bigger numbers imply greener and smaller numbers imply
redder". These are time series where bigger numbers are "better", like
total employment for example. But I also have cases within the heat map
where "bigger numbers imply redder and smaller numbers imply greener".
These are time series where bigger numbers are "worse", like total
unemployment for example. So suppose column B in dat is of the second
type, i.e. "bigger numbers imply redder and smaller numbers imply
greener". I would like the colour coding to be the reverse of what it
is for columns A and C. How can I modify the code to accomplish this? I
have tried different approaches with no success. Thanks for your help.
Philip
# REPREX
library(ggplot2)
library(tidyr)
library(dplyr)
dat <- data.frame(
date=seq.Date(as.Date("2024-01-01"),as.Date("2024-06-01"),by="month"),
A=c(1,3,3,4,2,6),
B=c(3,5,6,4,8,9),
C=c(10,8,17,19,26,22)
)
dat_long <- pivot_longer(dat,2:4,names_to="variable",values_to="value")
normalize <- function(x) { y <- (x-min(x))/(max(x)-min(x)) } dat_norm
<- mutate(dat,across(2:4,normalize)) dat_long_norm <-
pivot_longer(dat_norm,2:4,names_to="variable",values_to="norm_value")
dat_long <- inner_join(dat_long,dat_long_norm,by=c("date","variable"))
heatmap <- ggplot(dat_long, aes(x = date, y =
variable,fill=norm_value))
+
geom_tile() +
geom_text(aes(label = as.character(value)),
color = "black", size = 2.5) +
labs(title="REPREX",x="",y="")+
scale_fill_gradient2(low = "#E94A26", mid = "white", high =
"#A1D385", midpoint = 0.5) +
scale_x_continuous(breaks=seq.Date(as.Date("2024-01-01"),
as.Date("2024-06-01"),by="month"),
labels=function(x) format(x,"%b\n%Y"),position="top")+
theme(legend.position="none")
heatmap
ggsave("REPREXHeatmap.png",heatmap,height=3.5,width=4.9,dpi=200)
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______________________________________________
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PLEASE do read the posting guide https://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
