So, I am trying to build a circular barplot similiar as the one that follows:
library(tidyverse)
a <- c("Like", "Dislike", "Neutral")
b <- c("Price", "Functionality", "Functionality: missing pieces", "Durability")
n <- c(10, 0, 5, 6,5,4,19,28,4,6,9,1)
data <- data.frame(a,b,n)
ggplot(data, aes(x=b, y= n, fill = a))+geom_bar(stat="identity")+
ylim(-100, 120)+
coord_polar(start = 0)
But I would like to keep it clean and put the names of the bars in a legend box instead of above the bar. Substituting the names for numbers and then linking it to a legend would be ideal.
You could plot them as shapes:
data <- data.frame(a, b, n) %>%
mutate(b_fct = as.factor(b))
shapes <- data$b_fct %>%
levels() %>%
length() %>%
seq() %>%
as.character() %>%
map_int(utf8ToInt)
ggplot(data, aes(x = b_fct, shape = b, y = n, fill = a)) +
geom_bar(stat = "identity") +
geom_point(y = 120) +
ylim(-100, 120) +
coord_polar(start = 0) +
scale_x_discrete(labels = NULL) +
scale_shape_manual(values = shapes)
You could convert b to a factor and then abuse scale_color_manual a little:
a <- c("Like", "Dislike", "Neutral")
b <- factor(c("Price", "Functionality", "Functionality: missing pieces", "Durability"), c("Price", "Functionality", "Functionality: missing pieces", "Durability"), ordered = T)
n <- c(10, 0, 5, 6,5,4,19,28,4,6,9,1)
ggplot(data, aes(x=as.character(as.numeric(b)), y= n, fill = a, color = b))+geom_bar(stat="identity")+
ylim(-100, 120)+
coord_polar(start = 0) +
labs(x = NULL, y = NULL) +
scale_color_manual(
values = rep('#ffffff00', length(unique(b))),
labels = paste(as.numeric(b), as.character(b), sep = ': '),
guide = guide_legend(override.aes = list(fill = '#ffffff'), keywidth = 0))
Maybe something like this, using the caption feature:
a <- c("Like", "Dislike", "Neutral")
b <- as.character(seq_len(4))
n <- c(10, 0, 5, 6,5,4,19,28,4,6,9,1)
data <- data.frame(a,b,n)
ggplot(data, aes(x=b, y= n, fill = a))+geom_bar(stat="identity")+
ylim(-100, 120)+
coord_polar(start = 0) +
labs(caption=paste((paste(seq_len(4), c("Price", "Functionality", "Functionality: missing pieces", "Durability"), sep=": ")), collapse="\n")) +
theme (plot.caption=element_text(hjust=0))
Related
I have the following data:
library(ggplot2)
library(gganimate)
library(tidyverse)
createData<- function(vintage, id){#create data
# Generate a sequence of dates from 2010-01-01 to 2025-12-31 with a quarterly frequency
Dates <- seq(from = as.Date("2010-01-01"), to = as.Date("2025-12-31"), by = "quarter")
RLG<- cumsum(sample(c(-1, 1), 64, TRUE))
df<- data.frame( Dates,RLG, vintage,id)
return(df)
}
#createData
df<- createData("2018-01-01",1) %>%
rbind(createData("2019-01-01",2))%>%
rbind(createData("2020-01-01",3)) %>%
rbind(createData("2021-01-01",4))%>%
rbind(createData("2022-01-01",5))%>%
rbind(createData("2023-01-01",6))%>%
rbind(createData("2024-01-01",7))%>%
rbind(createData("2025-01-01",8))
Which I use to make the following chart:
options(gganimate.nframes = 8*length(unique(df$vintage)), gganimate.res = 30)
p<- ggplot(df) +
aes(x = Dates, y = RLG, group = as.Date(vintage), colour = "RLG") +
geom_line()+
scale_y_continuous(labels = \(x) paste0(x, "%"))+
theme(axis.title = element_blank(),legend.position="none")+
transition_time(id)+
exit_fade(alpha = 0.5)+
shadow_mark(alpha = 0.2)
animate(p, end_pause = 30)
I would like to add a geom_rect which goes from vintage to max(Dates). At each frame, vintage will increase, so the geom_rect will shrink slightly. How can I do this without interfering with the shadow_mark and exit_fades which I am applying to the lines?
If you mean something like a progress bar you could do it like so:
create an DF for the geom which is a subset of the original
df_geom <- df |>
mutate(vintage = as.Date(vintage)) |>
group_by(id) |>
slice(n())
Use geom_segment with the DF from above.
If you want to leave shadow_mark in you can do shadow_mark(exclude_layer = 2).
p <- ggplot(df) +
aes(x = Dates, y = RLG, group = as.Date(vintage), colour = RLG) +
geom_line()+
scale_y_continuous(labels = \(x) paste0(x, "%"))+
theme(axis.title = element_blank(),legend.position="none") +
geom_segment(
data = df_geom,
mapping = aes(x=vintage, xend=Dates,
y = 18, yend = 18),
size = 10, alpha =.4, color ='lightblue'
) +
transition_time(id)+
exit_fade(alpha = 0.5)
# shadow_mark(alpha = 0.2)
animate(p)
I plotted a matrix using geom_tile. Then, I would like to add the track colors below the x-axis. I ran the following code from the similar topic answer (ggplot Adding Tracking Colors Below X-Axis), but it shows the error "Discrete value supplied to continuous scale".
sp <- c("sp1","sp1","sp1","sp2","sp2","sp2","sp3","sp3","sp3","sp4","sp4","sp4","sp5","sp5","sp5")
category <- c("a","b","c","a","b","c","a","b","c","a","b","c","a","b","c")
count <- c(1,2,1,1,4,2,3,1,3,1,4,5,2,5,1)
habitat <- c("A","A","A","B","B","B","C","C","C","A","A","A","B","B","B")
d <- data.frame(cbind(sp, category, count, habitat))
dm <- d %>%
select(sp, category, count)%>%
tidyr::pivot_wider(names_from = "sp", values_from = "count")%>%
replace(is.na(.),0)
dm <- as.matrix(dm[, -1]) # -1 to omit categories from matrix
clust <- hclust(dist(t(dm)), method = "single")
dmc <- data.frame(x = factor(d$sp), colour = factor(d$habitat))
my_fill <- scale_fill_gradient(low="grey90", high="red",
breaks=c(0,5,10,15,20, 25, 30),
rescale=function(x, ...) scales::rescale(x, from=c(0, 30)),
limits=c(0,30))
ggplot(d, aes(category, sp))+
geom_tile(aes(fill = as.numeric(count)))+
my_fill +
scale_y_discrete(limits = colnames(dm)[clust$order])+
geom_tile(data=dmc, aes(x = x, y = 1, fill = colour))
Here is one potential solution:
library(tidyverse)
library(ggpubr)
sp <- c("sp1","sp1","sp1","sp2","sp2","sp2","sp3","sp3","sp3","sp4","sp4","sp4","sp5","sp5","sp5")
category <- c("a","b","c","a","b","c","a","b","c","a","b","c","a","b","c")
count <- c(1,2,1,1,4,2,3,1,3,1,4,5,2,5,1)
habitat <- c("A","A","A","B","B","B","C","C","C","D","D","D","E","E","E")
d <- data.frame(cbind(sp, category, count, habitat))
dm <- d %>%
select(sp, category, count)%>%
tidyr::pivot_wider(names_from = "sp", values_from = "count")%>% #clusterで並び替え
replace(is.na(.),0)
dm <- as.matrix(dm[, -1]) # -1 to omit categories from matrix
clust <- hclust(dist(t(dm)), method = "single")
dmc <- data.frame(x = factor(d$sp), colour = factor(d$sp))
my_fill <- scale_fill_gradient(low="grey90", high="red",
breaks=c(0,5,10,15,20, 25, 30),
rescale=function(x, ...) scales::rescale(x, from=c(0, 30)),
limits=c(0,30))
plot1 <- ggplot(d, aes(category, sp))+
geom_tile(aes(fill = as.numeric(count)))+
my_fill +
scale_y_discrete(limits = colnames(dm)[clust$order]) +
theme(legend.position = "right")
plot2 <- ggplot(dmc) +
geom_tile(aes(x = 1, y = x, fill = colour)) +
theme_void() +
scale_fill_manual(values = viridis::viridis(5)) +
theme(legend.position = "none")
ggarrange(plot2, plot1, nrow = 1, widths = c(0.25, 10), align = "hv")
I recently asked this question. However, I am asking a separate question now as the scope of my new question falls outside the range of the last question.
I am trying to create a heatmap in ggplot... however, outside of the axis I am trying to plot geom_tile. The issue is I cannot find a consistent way to get it to work. For example, the code I am using to plot is:
library(colorspace)
library(ggplot2)
library(ggnewscale)
library(tidyverse)
asd <- expand_grid(paste0("a", 1:9), paste0("b", 1:9))
df <- data.frame(
a = asd$`paste0("a", 1:9)`,
b = asd$`paste0("b", 1:9)`,
c = sample(20, 81, replace = T)
)
# From discrete to continuous
df$a <- match(df$a, sort(unique(df$a)))
df$b <- match(df$b, sort(unique(df$b)))
z <- sample(10, 18, T)
# set color palettes
pal <- rev(diverging_hcl(palette = "Blue-Red", n = 11))
palEdge <- rev(sequential_hcl(palette = "Plasma", n = 11))
# plot
ggplot(df, aes(a, b)) +
geom_tile(aes(fill = c)) +
scale_fill_gradientn(
colors = pal,
guide = guide_colorbar(
frame.colour = "black",
ticks.colour = "black"
),
name = "C"
) +
theme_classic() +
labs(x = "A axis", y = "B axis") +
new_scale_fill() +
geom_tile(data = tibble(a = 1:9,
z = z[1:9]),
aes(x = a, y = 0, fill = z, height = 0.3)) +
geom_tile(data = tibble(b = 1:9,
z = z[10:18]),
aes(x = 0, y = b, fill = z, width = 0.3)) +
scale_fill_gradientn(
colors = palEdge,
guide = guide_colorbar(
frame.colour = "black",
ticks.colour = "black"
),
name = "Z"
)+
coord_cartesian(clip = "off", xlim = c(0.5, NA), ylim = c(0.5, NA)) +
theme(aspect.ratio = 1,
plot.margin = margin(10, 15.5, 25, 25, "pt")
)
This produces something like this:
However, I am trying to find a consistent way to plot something more like this (which I quickly made in photoshop):
The main issue im having is being able to manipulate the coordinates of the new scale 'outside' of the plotting area. Is there a way to move the tiles that are outside so I can position them in an area that makes sense?
There are always the two classic options when plotting outside the plot area:
annotate/ plot with coord_...(clip = "off")
make different plots and combine them.
The latter option usually gives much more flexibility and way less headaches, in my humble opinion.
library(colorspace)
library(tidyverse)
library(patchwork)
asd <- expand_grid(paste0("a", 1:9), paste0("b", 1:9))
df <- data.frame(
a = asd$`paste0("a", 1:9)`,
b = asd$`paste0("b", 1:9)`,
c = sample(20, 81, replace = T)
)
# From discrete to continuous
df$a <- match(df$a, sort(unique(df$a)))
df$b <- match(df$b, sort(unique(df$b)))
z <- sample(10, 18, T)
# set color palettes
pal <- rev(diverging_hcl(palette = "Blue-Red", n = 11))
palEdge <- rev(sequential_hcl(palette = "Plasma", n = 11))
# plot
p_main <- ggplot(df, aes(a, b)) +
geom_tile(aes(fill = c)) +
scale_fill_gradientn("C",colors = pal,
guide = guide_colorbar(frame.colour = "black",
ticks.colour = "black")) +
theme_classic() +
labs(x = "A axis", y = "B axis")
p_bottom <- ggplot() +
geom_tile(data = tibble(a = 1:9, z = z[1:9]),
aes(x = a, y = 0, fill = z, height = 0.3)) +
theme_void() +
scale_fill_gradientn("Z",limits = c(0,10),
colors = palEdge,
guide = guide_colorbar(
frame.colour = "black", ticks.colour = "black"))
p_left <- ggplot() +
theme_void()+
geom_tile(data = tibble(b = 1:9, z = z[10:18]),
aes(x = 0, y = b, fill = z, width = 0.3)) +
scale_fill_gradientn("Z",limits = c(0,10),
colors = palEdge,
guide = guide_colorbar( frame.colour = "black", ticks.colour = "black"))
p_left + p_main +plot_spacer()+ p_bottom +
plot_layout(guides = "collect",
heights = c(1, .1),
widths = c(.1, 1))
Created on 2021-02-21 by the reprex package (v1.0.0)
I have some troubles with my code. I'm very very beginner in R, so I would like some help. I have a dataframe and I need to make an hist chart and then highlight some points. But I cannot understand how to find those points in my dataset. Here is and example of what I have.
x <- c("a","b","c","d","f","g","h","i","j","k")
y <- c(197421,77506,130474,18365,30470,22518,70183,15378,29747,11148)
z <- data.frame(x,y)
hist(z$y)
For example, how can I find in the hist where is the "a" and "h" value placed? and in a barplot? I tried the function points, but I cannot find the coordinates. Please let me know how could I make that . Thanks in advance.
Here is a way with dplyr and ggplot2. The approach is to cut the y variable into bins and then use summarise to create the counts and the labels.
library(dplyr)
library(ggplot2)
z %>%
mutate(bins = cut(y, seq(0, 200000, 50000))) %>%
group_by(bins) %>%
summarise(xes = paste0(x, collapse = ", "),
count = n()) %>%
ggplot() +
geom_bar(aes(x = bins, y = count), stat = "identity", color = "black", fill = "grey") +
geom_text(aes(x = bins, y = count + 0.5, label = xes)) +
xlab("y")
Here is a more complicated way that makes a plot that looks more like what hist() produces.
z2 <- z %>%
mutate(bins = cut(y, seq(0, 200000, 50000))) %>%
group_by(bins) %>%
summarise(xes = paste0(x, collapse = ", "),
count = n()) %>%
separate(bins, into = c("start", "end"), sep = ",") %>%
mutate(across(start:end, ~as.numeric(str_remove(., "\\(|\\]"))))
ggplot() +
geom_histogram(data = z, aes(x = y), breaks = seq(0, 200000, 50000),
color = "black", fill = "grey") +
geom_text(data = z2, aes(x = (start + end) / 2, y = count + 0.5, label = xes))
This is my df :
df <- data.frame(annee = rep(c(2003,2004), times = 1, each = 3), sps = c("a", "b", "c"), nb = 1:3)
I create a column containing my labels :
df$labels <- paste("nb", df$sps, "=", df$nb)
Then I do my plot :
ggplot(df, aes(nb)) +
geom_density(aes(fill = sps, colour = sps), alpha = 0.1) +
facet_wrap(~ annee) +
geom_text(data=df, aes(x=8, y=2.5, label= labels), colour="black", inherit.aes=FALSE, parse=FALSE)
But I have a problem with my text in each facet : I would like to have 3 lines (one for each sps).
I tried with the symbol "\n" but I failed in trying to obtain :
"nb a = 1 \n nb b = 2 \n nb c = 3" for each year
Thanks for help
You will have to concatenate what you want broken into several lines into one single string.
newdf <- aggregate(labels ~ annee, data = df, FUN = paste, collapse = "\n")
ggplot(df, aes(nb)) +
geom_density(aes(fill = sps, colour = sps), alpha = 0.1) +
facet_wrap(~ annee) +
geom_text(data = newdf, aes(x = 8, y = 2, label = labels), color = "black") +
scale_x_continuous(limits = c(0, 11)) +
scale_y_continuous(limits = c(0, 2.25))
You can achieve what you want by creating a separate data.frame for your labels:
library(tidyverse)
df <- data.frame(annee = rep(c(2003,2004),
times = 1, each = 3),
sps = c("a", "b", "c"),
nb = 1:3)
# create labels in separate data.frame
label_df <- df %>%
mutate(labels = paste("nb", sps, "=", nb)) %>%
group_by(annee) %>%
summarise(labels = paste(labels, collapse = "\n")) %>%
mutate(x = 6.5,
y = 2.2)
ggplot(df, aes(nb)) +
geom_density(aes(fill = sps, colour = sps), alpha = 0.1) +
facet_wrap(~annee) +
geom_text(data = label_df, aes(x = x, y = y, label = labels)) +
coord_cartesian(ylim = c(0, 2.4), xlim = c(1, 8))