You will need to add code to tell R which variables to plot in reverse color
order. In this code, I chose variable B to plot in reverse order.
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)
)
normalize <- function(x) {
(x - min(x)) / (max(x) - min(x))
}
dat_long <- dat %>%
mutate(across(2:4, normalize)) %>%
pivot_longer(cols = A:C, names_to = "variable", values_to = "norm_value") %>%
left_join(
dat %>%
pivot_longer(cols = A:C, names_to = "variable", values_to = "value"),
by = c("date", "variable")
)
dat_long <- dat_long %>%
mutate(adjusted_norm_value = ifelse(variable == "B", 1 - norm_value,
norm_value))
heatmap <- ggplot(dat_long, aes(x = date, y = variable, fill =
adjusted_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
-----Original Message-----
From: [email protected] <[email protected]>
Sent: Tuesday, December 10, 2024 7:59 AM
To: Ebert,Timothy Aaron <[email protected]>
Cc: [email protected]
Subject: Re: [R] Heat maps containing two types of variables
[External Email]
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 <[email protected]> On Behalf Of
> [email protected]
> Sent: Monday, December 9, 2024 7:56 PM
> To: [email protected]
> 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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