I'm trying to draw map. Is there a way to write the name of the cities in bold within the map? ( i've found only the way to choose the size ). This is my script
right_join(prov2022, dataset, by = "COD_PROV") %>%
ggplot(aes(fill = `real wage`))+
geom_sf(data = ~ subset(., COD_REG == 7 | COD_REG >= 1 & COD_REG <= 3)) +
theme_void() +
theme(legend.title=element_blank())+
geom_sf_text(data = ~ subset(., COD_REG == 7 ), aes(label = city_name), size = 3) +
scale_fill_gradientn(colors = c( "#FFFFFF","#FFFF00", "#FF0000", "#000000")) +
geom_blank()
i'd like to have the city_name in bold, but in geom_sf_text(data = ~ subset(., COD_REG == 7 ), aes(label = city_name), size = 3) i cannot find the way to do it.... (increase the size is not a good option in my case bacause i've borders that not to be crossed)
You can simply use fontface = "bold" in geom_sf_text
library(ggplot2)
ggplot(df) +
geom_sf(fill = "white") +
geom_sf_text(aes(label = lab), size = 5, fontface = "bold")
Reproducible example
library(sf)
df <- st_polygon(list(cbind(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)))) |>
st_sfc(crs = "WGS84") |>
st_as_sf() |>
within(lab <- "Bold text")
Use plotmath expression "bold(<city_name>)" and parse = TRUE
right_join(prov2022, dataset, by = "COD_PROV") %>%
mutate(city_name = paste0("bold(\"", city_name, "\")")) %>%
ggplot(aes(fill = `real wage`))+
geom_sf(data = ~ subset(., COD_REG == 7 | COD_REG >= 1 & COD_REG <= 3)) +
theme_void() +
theme(legend.title=element_blank())+
geom_sf_text(data = ~ subset(., COD_REG == 7 ), aes(label = city_name), size = 3,
parse = TRUE) +
scale_fill_gradientn(colors = c( "#FFFFFF","#FFFF00", "#FF0000", "#000000")) +
geom_blank()
Note: cannot test because have not reproducible data.
Related
I'm trying to draw map. Is there a way to write the name of the cities outside their borders? Looking for an answer i've found the package ggrepel, but it seems that it has not been implemented also for geographical maps, indeed if I write
right_join(prov2022, dataset, by = "COD_PROV") %>%
ggplot(aes(fill = `real wage`))+
geom_sf(data = ~ subset(., COD_REG == 7 | COD_REG >= 1 & COD_REG <= 3)) +
theme_void() +
theme(legend.title=element_blank())+
geom_sf_text(data = ~ subset(., COD_REG == 7 ), aes(label = city_name), size = 3) +
scale_fill_gradientn(colors = c( "#FFFFFF","#FFFF00", "#FF0000", "#000000")) +
geom_blank()+
geom_sf_text_repel(aes(label = city_name))
R answers
Error in geom_sf_text_repel(aes(label = city_name)) :
could not find function "geom_sf_text_repel"
Do you know any other way shift the label city_name from within the borders to the outside ?
You can use nudge_x and nudge_y inside geom_sf_text to move the labels an arbitrary amount:
library(ggplot2)
ggplot(df) +
geom_sf(fill = "white") +
geom_sf_text(aes(label = lab), size = 5, nudge_x = 0.05, nudge_y = 0.05)
If you prefer to control the exact position of each label, these parameters take vectorized inputs:
ggplot(df) +
geom_sf(fill = "white") +
geom_sf_text(aes(label = lab), size = 5,
nudge_x = c(0, -0.05, 0.05),
nudge_y = c(0, -0.05, 0.05))
Data used
library(sf)
df <- st_polygon(list(cbind(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)))) |>
list(st_point(c(0.25, 0.25)), st_point(c(0.75, 0.75))) |>
st_sfc(crs = "WGS84") |>
st_as_sf() |>
within(lab <- c("", "City 1", "City 2"))
I am trying to recreate this image in R, however I am unable to work out how to have 3 layers to a donut chart - everything I find (for instance, webr::PieDonut) only allows 2. Using ggplot I am also unable to re-create it.
A MRE is:
library(ggplot2)
library(webr)
library(dplyr)
lexicon <- data.frame("Level1" = c(rep("Flavour", 11), rep("Appearance", 4)),
"Level2" = c(rep("Misc", 6), rep("Pungent", 5), rep("Colour", 4)),
"Level3" = c("Fresh", "Refreshing", "Soapy", "Minty", "Nutty", "Milky", "Peppery", "Sharp", "Horseradish", "Mustard hot", "Spicy", "Colourful"," Fresh Green", "Dark Green", "Bright Green")
)
PieDonut(lexicon, aes(Level1, Level2), title = "Salad Lexicon", showRatioDonut =FALSE, showRatioPie = FALSE)
ggplot(lexicon, aes(Level2, Level3, fill = Level1)) +
geom_col() +
scale_fill_viridis_d() +
coord_polar("y")
While the PieDonut works for 2 levels (not shown), it doesn't allow the final level to be included. The ggplot approach also does not work, as seen in the figure below.
How can I get this style of chart in R? Either with ggplot or base plotting.
I think a nice alternative is to use geom_rect here after some data manipulation. Using the fill, color, and alpha scales can help improve the differentiation of categories. I would also use geom_textpath here, though I might go for circumferential labels if there is room to do so:
lexicon %>%
mutate(top_level = Level1) %>%
pivot_longer(1:3) %>%
group_by(name, value) %>%
mutate(width = n()) %>%
unique() %>%
arrange(name) %>%
group_by(name) %>%
mutate(ymid = as.numeric(sub("\\D+", "", name)),
ymax = ymid + 0.5, ymin = ymid - 0.5,
xmin = c(0, head(cumsum(width), -1)),
xmax = cumsum(width),
xmid = (xmax + xmin) / 2) %>%
ggplot(aes(xmid, ymid, fill = top_level)) +
geom_rect(aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax,
alpha = name, color = top_level)) +
geomtextpath::geom_textpath(aes(y = ymid + 0.25, label = value,
group = value)) +
scale_alpha_manual(values = c(1, 0.3, 0.1)) +
scale_fill_manual(values = c("#cd9900", "#00817e")) +
scale_colour_manual(values = c("#cd9900", "#00817e")) +
scale_y_continuous(limits = c(-0.5, 3.6)) +
coord_polar() +
theme_void() +
theme(legend.position = "none")
One option would be to reeshape your data to long and do some manual aggregating before passing to ggplot. Additionally I use geomtextpath::geom_textpath to add the labels:
library(ggplot2)
library(dplyr)
library(geomtextpath)
lexicon <- data.frame("Level1" = c(rep("Flavour", 11), rep("Appearance", 4)),
"Level2" = c(rep("Misc", 6), rep("Pungent", 5), rep("Colour", 4)),
"Level3" = c("Fresh", "Refreshing", "Soapy", "Minty", "Nutty", "Milky", "Peppery", "Sharp", "Horseradish", "Mustard hot", "Spicy", "Colourful"," Fresh Green", "Dark Green", "Bright Green")
)
lexicon_long <- lexicon |>
mutate(fill = Level1) |>
tidyr::pivot_longer(-fill, names_to = "level", values_to = "label") |>
mutate(label = forcats::fct_inorder(label)) |>
count(fill, level, label) |>
group_by(level) |>
mutate(pct = n / sum(n))
ggplot(lexicon_long, aes(level, pct, fill = fill)) +
geom_col(color = "white") +
geom_textpath(aes(label = label, group = label),
position = position_stack(vjust = .5),
upright = TRUE, hjust = .5, size = 3
) +
scale_fill_viridis_d() +
coord_polar("y") +
theme_void() +
guides(fill = "none")
Using this reproducable example from another question. How do I label / colour the center node on which the local neighborhood graph is based. (In this case 'x')
library(tidygraph)
library(ggraph)
# Example
net <- tibble::tibble(A = letters[1:6],
B = rep(c("x", "y"), each = 3)) %>%
tidygraph::as_tbl_graph()
net %>%
tidygraph::convert(to_local_neighborhood,
node = which(.N()$name == "x"),
order = 1,
mode = "all") %>%
ggraph(layout = "nicely") +
geom_edge_link() +
geom_node_point(size = 10, fill = "white", shape = 21) +
geom_node_text(aes(label = name)) +
theme_graph()
What I get:
What I want:
I have the feeling there should be some kind of conditional fill for geom_node_point but I don't know if this is possible...
You can do:
net %>%
tidygraph::convert(to_local_neighborhood,
node = which(.N()$name == 'x'),
order = 1,
mode = "all") %>%
mutate(root = ifelse(node_is_center(), 'red', 'white')) %>%
ggraph(layout = "nicely") +
geom_edge_link() +
geom_node_point(size = 10, aes(fill = root), shape = 21) +
geom_node_text(aes(label = name)) +
scale_fill_identity() +
theme_graph()
I want text labels were above or under of bar cap depending on where is more space for them. Now it's always down which is not always looks good:
Here is my code:
library(tidyr)
library(ggplot2)
library(dplyr)
library(stringr)
library(purrr)
numa.nodes <- tibble (
numa_name = c("numa_01","numa_01","numa_01","numa_01","numa_01","numa_01","numa_02","numa_02","numa_02","numa_02"),
counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
)
numa.nodes <- numa.nodes %>% add_row(
numa_name = c("numa_03","numa_03","numa_03","numa_03","numa_03","numa_03","numa_04","numa_04","numa_04","numa_04"),
counter_name =c("cpu01","cpu02","cpu03","cpu04","memory_used","memory_total","cpu01","cpu02","memory_used","memory_total"),
value = c(sample(0:100,4), sample(0:32,1), 32, sample(0:100,1), sample(0:100,1), sample(0:128,1), 128)
)
numa.nodes <- numa.nodes %>% add_row(
numa_name = c("numa_05","numa_05","numa_05","numa_05","numa_05","numa_05","numa_05"),
counter_name =c("cpu01","cpu02","cpu03","cpu04","cpu05","memory_used","memory_total"),
value = c(sample(1:100,5), sample(1:64,1), 64)
)
numa.nodes <- numa.nodes %>% mutate(counter_name=factor(counter_name,levels = unique(counter_name),ordered = T))
memory_columns <- numa.nodes %>% filter(counter_name=='memory_total')
memory_y_scale <- max(memory_columns$value, na.rm = TRUE) + 6
plot_numa = function(num){
df = numa.nodes %>% filter(str_detect(numa_name, num))
cpu_plot = df %>%
filter(str_detect(counter_name, "cpu")) %>%
ggplot(aes(x = counter_name)) +
geom_col(aes(y = 100), fill = "white", color = "black") +
geom_col(aes(y = value), fill = "#00AFBB", color = "black") +
geom_text(aes(y = value, label = paste0(value,"%")), nudge_y = 5, color = "black") +
theme_bw() +
labs(x = "CPU", y = "")
memory_plot = df %>%
filter(str_detect(counter_name, "memory")) %>%
pivot_wider(names_from = counter_name, values_from = value) %>%
ggplot(aes(x = "") ) +
geom_col(aes(y = memory_total), fill = "white", color = "black") +
geom_col(aes(y = memory_used), fill = "#FC4E07", color = "black") +
geom_text(aes(label = paste(memory_total, "GB"), y = memory_total), nudge_y = 5, color = "black") +
geom_text(aes(label = paste(memory_used, "GB"), y = memory_used), nudge_y = -3, color = "black") +
theme_bw() +
ylim(0, memory_y_scale) +
labs(x = "Memory", y = "")
ggpubr::ggarrange(cpu_plot, memory_plot, ncol = 2) %>% ggpubr::annotate_figure(top = paste("NUMA",num))
}
numa_numbers <- unique(numa.nodes$numa_name) %>% str_remove ("numa_")
ggpubr::ggarrange(plotlist = map(.x = numa_numbers, .f = ~plot_numa(num = .x)))
I tried to change this line:
geom_text(aes(label = paste(memory_used, "GB"), y = memory_used), nudge_y = -3, color = "black")
to something like that:
geom_text(aes(label = paste(memory_used, "GB"), y = memory_used),nudge_y = ifelse( (memory_total-memory_used) > 10, 5, -3)
, color = "black")
But I've got an error:
Error in ifelse((memory_total - memory_used) > 10, 5, -3) :
object 'memory_total' not found
Is there a better way to print labels optimal way?
What am I doing wrong?
How to change color of label to more contrast ie black on white, white on red?
Think of it this way: The nudge value will be different (potentially) for every observation in your data frame. That means that this is something that should be handled within aes(), where stuff is designed to change with your data, rather than nudge_y, which is designed to be a constant (and complains if used otherwise).
So, the solution is to do away entirely with nudge_y and build your ifelse() statement directly into aes(y=...).
In this case, here's the replacement for that particular geom_text() line:
# to see the same plot posted here, put this at the top of your code
set.seed(7331)
...
# plot code...
... +
geom_text(aes(
label = paste(memory_used, "GB"),
y = ifelse((memory_total-memory_used > 10), memory_used + 5, memory_used - 3)),
color = "black") +
My goal is to produce labels with commas, but no decimals. Let's say I have a ggplot with the following section:
geom_text(aes(y = var,
label = scales::comma(round(var))), hjust = 0, nudge_y = 300 )
This is almost what I need. It gives me the commas, but has a decimal. I have seen here (axis labels with comma but no decimals ggplot) that comma_format() could be good, but I think the label in my case needs a data argument, which comma_format() does not take. What can I do?
Update:
As an example of when this problem occurs, see the following, which uses gganimate and has a lot more going on. Code derived from Jon Spring's answer at Animated sorted bar chart with bars overtaking each other
library(gapminder)
library(gganimate)
library(tidyverse)
gap_smoother <- gapminder %>%
filter(continent == "Asia") %>%
group_by(country) %>%
complete(year = full_seq(year, 1)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
group_by(year) %>%
mutate(rank = min_rank(-gdpPercap) * 1) %>%
ungroup() %>%
group_by(country) %>%
complete(year = full_seq(year, .5)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
mutate(rank = approx(x = year, y = rank, xout = year)$y) %>%
ungroup() %>%
arrange(country,year)
gap_smoother2 <- gap_smoother %>% filter(year<=2007 & year>=1999)
gap_smoother3 <- gap_smoother2 %<>% filter(rank<=8)
p <- ggplot(gap_smoother3, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = gdpPercap/2,
height = gdpPercap,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(country, " ")), vjust = 0.2, hjust = 1) +
geom_text(aes(y = gdpPercap,
label = scales::comma(round(gdpPercap))), hjust = 0, nudge_y = 300 ) +
coord_flip(clip = "off", expand = FALSE) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title='{closest_state %>% as.numeric %>% floor}',
x = "", y = "GFP per capita") +
theme(plot.title = element_text(hjust = 0, size = 22),
axis.ticks.y = element_blank(), # These relate to the axes post-flip
axis.text.y = element_blank(), # These relate to the axes post-flip
plot.margin = margin(1,1,1,4, "cm")) +
transition_states(year, transition_length = 1, state_length = 0) +
enter_grow() +
exit_shrink() +
ease_aes('linear')
animate(p, fps = 2, duration = 5, width = 600, height = 500)
In addition to the solution provided by #drf, you need to add scale_y_continuous(scales::comma) to your ggplot commands. But put it before the coord_flip function.
p <- ggplot(gap_smoother3, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = gdpPercap/2,
height = gdpPercap,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = gdpPercap,
label = scales::comma(round(gdpPercap), accuracy=1)),
hjust = 0, nudge_y = 300 ) +
scale_y_continuous(labels = scales::comma) +
... etc.