Dear Antonello,
How about this? Obviously, you can change the background colours for the
confidence levels (deprespal) and for the regression lines, etc.
Surely, many in the list can improve on my rough and ready solution.
deprespal=c("#CCCCCC","#999999")
p2 <- ggplot(data = df, aes(x =Levels_Depression, y = Social_impairment, group
= as.factor(Past_Admissions),fill = as.factor(Past_Admissions) )) +
geom_point(aes(size = Age)) + geom_smooth(method = "lm", col="black") +
xlab("Levels of depression") + ylab("Social impairment") +
scale_fill_manual(values=deprespal) +
scale_colour_discrete("History of \npast admissions\nto a psychiatric
service", labels = c("No", "Yes"))
p2
Regards,
José
Prof. José Iparraguirre
Chief Economist
Age UK
Age UK
Tavis House, 1- 6 Tavistock Square
London, WC1H 9NB
-----Original Message-----
From: R-help [mailto:[email protected]] On Behalf Of Antonello Preti
Sent: 20 February 2015 12:54
To: [email protected]
Subject: [R] colours in ggplot2
Hi, I'm using ggplot2 to make a plot of the regression of a variable x (let
say, levels of depression), on a variable y (let say, degree of social
impairment), by taking into account a binary factor (having had or not a past
admission to a psychiatric service), and age of partecipants.
After some search in Internet I produced a code which is satisfying to me.
This site was very helpful: http://editerna.free.fr/wp/?p=266
However, I have a problem: no matter what I try, the figures always include
bluette and pink flamingo colours.
The figure is for an academic article, and I cannot afford the price of having
the plot printed in colours.
I've extracted the structure of the figure, and I understand that the problem
is in the scale_name "hue", but I cannot figure out how to deal with it.
Any way to override the ggplot2 system of dealing with factors?
Here the codes and the sessionInfo
The code is a bit baroque, but this is the best I was able to do.
Thank you in advance,
Antonello Preti
######## code for exemplification
### the dataset
df <- structure(list(Social_impairment = c(2.83, 3.08, 2.75, 2.08, 2.92, 1.75,
3.5, 2.33, 2.91, 2.5, 3.25, 2.64, 3.25, 2.83, 2.08, 2.25, 2.17, 2.42, 2.58,
2.42, 2.58, 2.42, 3, 3, 2.83, 2.67, 3.58, 1.58, 2.83, 2.83, 2.67, 3.17, 2.42,
1.92, 2.92, 2.5, 2.42, 2.42, 2.58, 2.42, 3.33, 3, 3.17, 2.17, 2.58, 2.67, 2.58,
3.75, 2.5, 2.08, 2.25, 3.25, 3.17, 2.91, 2.08, 2.25, 3.08, 2.91, 3.08, 2.92,
1.83, 2.5, 2.5, 2.83, 2.67, 3.33, 2.83, 3.33, 2.92, 3), Levels_Depression =
c(1.3, 1.71, 3.08, 0.48, 0.51, 0.71, 1.37, 0.2, 1.21, 1.07, 2.8, 1.24, 0.46,
0.97, 0.81, 1.13, 1.58, 3.12, 1.8, 1.54, 1.02, 0.32, 2.63, 1.39, 1.34, 2.37,
2.6, 1.11, 1.59, 2.17, 1.99, 0.59, 0.76, 0.23, 2.22, 1.98, 0.41, 0.32, 0.37,
1.11, 2.29, 0.97, 1.61, 1.27, 1.22, 2.38, 1.28, 1.21, 0.93, 2.3, 0.8, 2.1,
2.86, 2.47, 2.34, 2.67, 0.31, 0.88, 1.84, 0.23, 2.41, 0.56, 2.03, 1.11, 0.12,
2.39, 0.34, 2.08, 1.01, 1.51), Age = c(66, 59, 49, 70, 42, 55, 28, 41, 69, 65,
40, 21, 18, 77, 28, 40, 47, 37, 47, 39, 32, 33, 42, 28, 59, 49, 29, 41, 22, 29,
53, 39, 55, 61, 30, 49, 43, 46, 18, 36, 34, 17, 42, 37, 37, 54, 48, 23, 71, 42,
52, 83, 19, 47, 23, 80, 43, 38, 47, 80, 36, 73, 74, 51, 76, 14, 65, 39, 17,
73), Past_Admissions = c(1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0,
1, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0,
0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1)),
.Names = c("Social_impairment", "Levels_Depression", "Age", "Past_Admissions"),
row.names = c(NA, 70L), class = "data.frame")
dim(df)
head(df)
str(df)
summary(df)
### call the library
library(ggplot2)
#### the plot
#### Levels_Depression on Social_impairment by Past_Admissions (yes/no) ####
linear model #### radius of the bubbles proportional to age
#### background elimination
p1 <- ggplot(data = df, aes(x =Levels_Depression, y = Social_impairment, group
= as.factor(Past_Admissions), col = as.factor(Past_Admissions))) +
geom_point(aes(size = Age)) + geom_smooth(method = "lm") + xlab("Levels of
depression") + ylab("Social impairment") +
scale_colour_discrete("History of \npast admissions\nto a psychiatric
service", labels = c("No", "Yes"))
p1 + theme(panel.grid.major = element_blank(), panel.grid.minor =
element_blank(),
panel.background = element_blank(), axis.line = element_line(colour =
"black"))
### change of then axes' ticks
p1 + theme(panel.grid.major = element_blank(), panel.grid.minor =
element_blank(),
panel.background = element_blank(), axis.line = element_line(colour =
"black"),
axis.text = element_text(color = "black", size = 12, face = "italic"))
### after saving, dev.off()
###
#### Age on Social_impairment by Past_Admissions (yes/no) #### linear model
#### radius of the bubbles proportional to Levels_Depression
#### background elimination
p2 <- ggplot(data = df, aes(x =Age , y = Social_impairment, group =
as.factor(Past_Admissions), col = as.factor(Past_Admissions))) +
geom_point(aes(size = Levels_Depression)) + geom_smooth(method = "lm")
+xlab("Age of participants") + ylab("Social impairment") +
scale_colour_discrete("History of \npast admissions\nto a psychiatric
service", labels = c("No", "Yes"))
p2 + theme(panel.grid.major = element_blank(), panel.grid.minor =
element_blank(),
panel.background = element_blank(), axis.line = element_line(colour =
"black"))
### change of then axes' ticks
p2 + theme(panel.grid.major = element_blank(), panel.grid.minor =
element_blank(),
panel.background = element_blank(), axis.line = element_line(colour =
"black"),
axis.text = element_text(color = "black", size = 12, face = "italic"))
### after saving, dev.off()
###
########################
#### paired plots
########################
library(gridExtra)
grid.arrange(p1, p2, ncol = 2)
########################
### sessionInfo()
########################
R version 3.0.2 (2013-09-25)
Platform: x86_64-w64-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=Italian_Italy.1252 LC_CTYPE=Italian_Italy.1252 [3]
LC_MONETARY=Italian_Italy.1252 LC_NUMERIC=C [5] LC_TIME=Italian_Italy.1252
attached base packages:
[1] grid stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] gridExtra_0.9.1 ggplot2_0.9.3.1
loaded via a namespace (and not attached):
[1] colorspace_1.2-4 dichromat_2.0-0 digest_0.6.4
gtable_0.1.2
[5] labeling_0.2 MASS_7.3-33 munsell_0.4.2
plyr_1.8
[9] proto_0.3-10 RColorBrewer_1.0-5 reshape2_1.2.2
scales_0.2.3
[13] stringr_0.6.2
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