Related
This is my script for the plot,
data = data.frame(Kingdom = c("Bacteria", "Archaea"),
Total = c(273523, 2616))
sizeRange <- c(0,30)
library(ggplot2)
ggplot(data, aes(x=0,y=Kingdom,color=Kingdom)) +
geom_point(aes(size = Total,alpha=10),colour="blue",stroke=2) +
scale_size(range = sizeRange)+
theme_bw() +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "white"))
somebody, please tell me how can I get a connecting line between my y-axis label and the plot
My plot looks like this
I want something like this
A clean alternative would be to label the points directly, and remove the y-axis if wanted. e.g.:
ggplot(data, aes(x=0,y=Kingdom,color=Kingdom)) +
ggrepel::geom_text_repel(aes(label = Kingdom), vjust = -1,colour="black") +
geom_point(aes(size = Total),colour="blue",stroke=2) +
scale_size(range = sizeRange)+
theme_bw() +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "white"),
axis.text.y=element_blank(),
axis.title.y = element_blank(),
axis.ticks.y=element_blank())
you can manually add segments, but then the alpha of your points will kind of show them.
Here is a try, altought it's not perfect if the x axis expend.
ggplot(data, aes(x=0,y=Kingdom,color=Kingdom)) +
# Added the segments here before the points.
# I tried to alpha it but I can't figure out how to limit the
# segment to the point border.
geom_segment(x = rep(-100,2), xend = rep(0,2),
y = c(1, 2), yend = c(1,2),colour="blue", alpha = 10) +
geom_point(aes(size = Total,alpha=10),colour="blue",stroke=2) +
scale_size(range = sizeRange)+
theme_bw() + guides(alpha = "none") + # remove alpha from legend.
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "white"))
How can I implement histogram with such complex x-axis?
First x-axis row is the week start, second - week end.
Data for tests in csv: https://gofile.io/d/FrhLZh.
What I managed to
hist_data %>%
ggplot(aes(x = week, y = count)) +
geom_col(fill = "#5B879E", width = 0.9, size = 0.7) +
labs(title = "", x = "", y = "") +
theme_bw() + theme_minimal() + theme(legend.position="none")+
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_text(vjust = 0.5, size = 8, family = "Inter", colour = "#ffffff"),
axis.line.x = element_blank(),
axis.title.x = element_blank(),
plot.background = element_rect(fill = "#3A464F"),
plot.margin=unit(c(0,0.25,0.5,0), "cm"))+
scale_x_discrete(expand=c(0,0), labels = format(as.Date(hist_data$week_start), "%d-%m"), position = "bottom") +
scale_y_continuous()
Thanks to teunbrand and his ggh4x package, solution:
hist_data %>%
ggplot(aes(x = week, y = count)) +
geom_col(fill = "#5B879E", width = 0.8, size = 0.7)+
labs(title = "", x = "", y = "") +
theme_bw() + theme_minimal() + theme(legend.position="none")+
theme(
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
axis.text.y = element_blank(),
axis.text.x = element_text(vjust = 0.5, size = 8, lineheight = 0.8, family = "Inter", colour = "#ffffff"),
axis.line.x = element_blank(),
axis.title.x = element_blank(),
ggh4x.axis.nestline.x = element_line(size = 0.5, colour = "#5B879E", lineend = "square"),
plot.background = element_rect(fill = "#3A464F"),
plot.margin=unit(c(1,0.5,1,0.5), "cm"))+
scale_x_discrete(expand=c(0,0),
labels = paste0(format(as.Date(sort(hist_data$week_start)), "%d.%m"),
"\n", "nonsense", "\n",
format(as.Date(sort(hist_data$week_end)), "%d.%m")), position = "bottom") +
scale_y_continuous() +
guides(x = guide_axis_nested(delim = "nonsense"))
You can add multiple layers of geom_text and geom_segment. Adjust the relative y positions of these layers using a scaling factor.
plotscale <- max(hist_data$count)/50
library(ggplot2)
ggplot(data = hist_data,
aes(x = week_start + floor(week_end-week_start)/2, y = count)) +
geom_col(fill = "#5B879E", width = 4) +
geom_text(aes(y = -6 * plotscale ,
label = format(week_start, "%m-%d")),
color = "#ffffff")+
geom_segment(aes(x = week_start, xend = week_end,
y = -10 * plotscale, yend = -10 * plotscale),
color = "#5B879E", size = 1.5)+
geom_text(aes(y = -14 * plotscale,
label = format(week_end, "%m-%d")),
color = "#ffffff")+
theme_minimal() +
theme(
panel.grid = element_blank(),
axis.text = element_blank(),
axis.title = element_blank(),
plot.background = element_rect(fill = "#3A464F"))+
scale_x_date(expand=c(0,0), date_breaks = "1 week",
labels = NULL)
Consider using ggh4x package for more complex nested x axes.
Raw Data
hist_data <- read.table(text='"","week","count","week_start","week_end"
"1","1",21.5823972708382,2021-01-04,2021-01-10
"2","2",36.122556304552,2021-01-11,2021-01-17
"3","3",34.2809483156697,2021-01-18,2021-01-24
"4","4",25.8546925450454,2021-01-25,2021-01-31
"5","5",29.0309819292706,2021-02-01,2021-02-07
"6","6",33.1503608888827,2021-02-08,2021-02-14
"7","7",27.0490347440184,2021-02-15,2021-02-21
"8","8",30.3031289757874,2021-02-22,2021-02-28
"9","50",32.2876434072602,2020-12-07,2020-12-13
"10","51",33.1939593686481,2020-12-14,2020-12-20
"11","52",26.6853246329896,2020-12-21,2020-12-27
"12","53",23.0715199391151,2020-12-28,2021-01-03', header = TRUE, sep = ",")
hist_data$week_start <- as.Date(hist_data$week_start)
hist_data$week_end <- as.Date(hist_data$week_end)
I am developing a custom theme based on the 538 theme in ggthemes. I have a particular use case where I would like to conditionally change the legend text if I am preparing graphs about organisms. I want to make the legend text italics if I am reporting Genus species results.
Here is my theme so far:
theme_EPI <- function() {
theme_fivethirtyeight(base_size = 14) %+replace%
theme(
panel.background = element_blank(),
plot.background = element_rect(fill = 'white', colour = NA),
plot.title = element_text(size = 18),
strip.text = element_text(size=14),
legend.text = element_text(size = 12, face = 'italic'),
legend.background = element_rect(fill="transparent", colour=NA),
legend.key = element_rect(fill="transparent", colour=NA),
panel.grid.major.y = element_line(colour = 'grey90'),
panel.grid.major.x = element_blank(),
strip.background = element_blank()
)
}
If have tried passing the parameter organism=TRUE to the the function call and then an ifelse(organism==TRUE, face='italic', 'face='plain') in the element_text.
Is this even possible in a custom theme?
Yes, this is definitely possible, you just have to slightly rethink how the ifelse() will work:
theme_EPI = function(organism = TRUE) {
theme_dark() %+replace%
# axis.title: labels for x and y axes
theme(axis.title = element_text(
face = ifelse(organism, 'italic', 'plain')
))
}
ggplot(iris, aes(Petal.Width, Petal.Length)) +
geom_point() +
theme_EPI() # Default: organism = TRUE
ggplot(iris, aes(Petal.Width, Petal.Length)) +
geom_point() +
theme_EPI(organism = FALSE)
I want to place ticks on all four sides of my graph. The way suggested for this is mirror_ticks.
library(ggplot2)
library(ggplotTicks)
sp6<-ggplot(Anna_Smooth, aes(y=log10(Prob2), x=log10(AvSize)))+
geom_point( data=Anna_Smooth, aes(y=log10(Prob2), x=log10(AvSize), color=PART) )+
guides( color=FALSE)
sp8<-sp6+ labs(x=expression(paste(log(s))))+
labs(y=expression(paste(log(P(s)))) )+
theme(axis.text.y = element_text(size=14),
axis.text.x = element_text(size=14),
axis.title.y = element_text(size=15),
axis.title.x = element_text(size=15),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
panel.border = element_rect(colour = "black", fill=NA, size=2)
)
sp10<-mirror_ticks(sp10, allPanels=TRUE)
My output sp10 has no ticks on opposite panels, same result if I put allPanels=TRUE
Is there a fix? I am open to learn how one does this with theme settings?
As of ggplot2 version 2.2.0 (2016-11-11), the scale_x_continuous() and scale_y_continuous() can display a secondary axis which is positioned opposite to the primary axis and which can be controlled with the sec.axis argument.
This can be used to mirror the tick marks.
The OP hasn't provided reproducible data so we use the mpg dataset which comes with the ggplot2 package:
Chart without mirrored tick marks
library(ggplot2)
g1 <- ggplot(mpg, aes(log10(displ), log10(hwy))) +
geom_point() +
theme(
axis.text.y = element_text(size = 14),
axis.text.x = element_text(size = 14),
axis.title.y = element_text(size = 15),
axis.title.x = element_text(size = 15),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
panel.border = element_rect(
colour = "black",
fill = NA,
size = 2
)
)
g1
Chart with secondary axes
g1 +
scale_x_continuous(sec.axis = dup_axis()) +
scale_y_continuous(sec.axis = dup_axis())
g1 +
scale_x_continuous(sec.axis = dup_axis(name = NULL)) +
scale_y_continuous(sec.axis = dup_axis(name = NULL))
g1 +
scale_x_continuous(sec.axis = dup_axis(name = NULL, labels = NULL)) +
scale_y_continuous(sec.axis = dup_axis(name = NULL, labels = NULL))
Mirrored tick marks with log10 scales
The secondary axes are also available with the scale_x_log10() and scale_x_log10() functions.
So, it can be avoided to use the log() function within the call to aes() but by specifying an appropriate log scale:
ggplot(mpg, aes(displ, hwy)) +
geom_point() +
theme(
axis.text.y = element_text(size = 14),
axis.text.x = element_text(size = 14),
axis.title.y = element_text(size = 15),
axis.title.x = element_text(size = 15),
panel.background = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "black"),
panel.border = element_rect(
colour = "black",
fill = NA,
size = 2
)
) +
scale_x_log10(sec.axis = dup_axis(name = NULL, labels = NULL)) +
scale_y_log10(sec.axis = dup_axis(name = NULL, labels = NULL))
I'd like to make a forest plot for my project. Since it is not a typical forest plot built-in any R package, I found the first figure of this page is helpful to my goal, a side table accompanied with the forest plot:
https://mcfromnz.wordpress.com/2012/11/06/forest-plots-in-r-ggplot-with-side-table/
The code which produces that particular figure is pasted below (the original link:https://github.com/nzcoops/blog_code/blob/master/forest_plot.Rmd)
The problem that I ran into is in the "data_table" step. An error pop up when I type the following in R:
data_table
Error: Aesthetics must be either length 1 or the same as the data (28): yintercept
I guess the issue came from geom_hlinein data_table.
After some online search and some try-and-error, I still cannot get rid of that error message and wonder if I can get some help here. Thanks in advance for your help.
--Code that particular produce the first figure:
library(ggplot2)
library(gridExtra)
dat <- data.frame(group = factor(c("A","B","C","D","E","F","G"), levels=c("F","E","D","C","B","A","G")),
cen = c(3.1,2.0,1.6,3.2,3.6,7.6,NA),
low = c(2,0.9,0.8,1.5,2,4.2,NA),
high = c(6,4,2,6,5,14.5,NA))
theme_set(theme_bw())
theme_update(
axis.line = element_line(colour = "black"),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
plot.margin = unit(c(0,0,0,0), "lines"))
p <- ggplot(dat,aes(cen,group)) +
geom_point(size=5, shape=18) +
geom_errorbarh(aes(xmax = high, xmin = low), height = 0.15) +
geom_vline(xintercept = 1, linetype = "longdash") +
scale_x_continuous(breaks = seq(0,14,1), labels = seq(0,14,1)) +
labs(x="Adjusted Odds Ratio", y="")
data_table <- ggplot(lab, aes(x = V05, y = V0, label = format(V1, nsmall = 1))) +
geom_text(size = 4, hjust=0, vjust=0.5) + theme_bw() +
geom_hline(aes(yintercept=c(6.5,7.5))) +
theme(panel.grid.major = element_blank(),
legend.position = "none",
panel.border = element_blank(),
axis.text.x = element_text(colour="white"),#element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_line(colour="white"),#element_blank(),
plot.margin = unit(c(0,0,0,0), "lines")) +
labs(x="",y="") +
coord_cartesian(xlim=c(1,4.5))
lab <- data.frame(V0 = factor(c("A","B","C","D","E","F","G","A","B","C","D","E","F","G","A","B","C","D","E","F","G","A","B","C","D","E","F","G"),, levels=c("G","F","E","D","C","B","A")),
V05 = rep(c(1,2,3,4),each=7),
V1 = c("Occuption","Active","","Inactive","","Inactive","","Recreation","Inactive","","Active","","Inactive","","Gender","Men","Women","Men","Women","Men","Women","OR",3.1,2.0,1.6,3.2,3.6,7.6))
data_table <- ggplot(lab, aes(x = V05, y = V0, label = format(V1, nsmall = 1))) +
geom_text(size = 4, hjust=0, vjust=0.5) + theme_bw() +
geom_hline(aes(yintercept=c(6.5,7.5))) +
theme(panel.grid.major = element_blank(),
legend.position = "none",
panel.border = element_blank(),
axis.text.x = element_text(colour="white"),#element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_line(colour="white"),#element_blank(),
plot.margin = unit(c(0,0,0,0), "lines")) +
labs(x="",y="") +
coord_cartesian(xlim=c(1,4.5))
The easiest fix would be separating geom_hline into 2 different calls
data_table <- ggplot(lab, aes(x = V05, y = V0, label = format(V1, nsmall = 1))) +
geom_text(size = 4, hjust=0, vjust=0.5) + theme_bw() +
geom_hline(aes(yintercept=c(6.5))) +
geom_hline(aes(yintercept=c(7.5))) +
theme(panel.grid.major = element_blank(),
legend.position = "none",
panel.border = element_blank(),
axis.text.x = element_text(colour="white"),#element_blank(),
axis.text.y = element_blank(),
axis.ticks = element_line(colour="white"),#element_blank(),
plot.margin = unit(c(0,0,0,0), "lines")) +
labs(x="",y="") +
coord_cartesian(xlim=c(1,4.5))
data_table
Created on 2018-03-31 by the reprex package (v0.2.0).
You don't need to use aes() with geom_hline (only use aes() if you want a horizontal line for every row of your data.) You can just do:
geom_hline(yintercept = c(6.5, 7.5))
This is explained in the help, see ?geom_hline for more details.