I've been struggling to change my fill legend shape from squares to circles. I just tried to replicate this issue in a vanilla rstudio.cloud environment, and it still isn't working:
library(tidyverse)
library(tigris)
options(tigris_class = "sf")
options(tigris_use_cache = TRUE)
df_ohio <- counties(state = "OH", cb = T, resolution = "20m") %>%
mutate(defiance = if_else(NAME == "Defiance", 1, 0))
ggplot() +
geom_sf(data = df_ohio, color = "black",
aes(fill = as.factor(defiance)), size = .1, alpha = .75) +
scale_fill_manual(values = c('#BB0000','navy'),
labels = c('No','Yes'),
name = "Defiance County?") +
theme_void() +
guides(fill = guide_legend(override.aes = list(shape = 20)))
When I try this I still get the result below, which has the fill legend shape as squares (shape 15, I guess) instead of circles (shape 20) like I specified. Any ideas?
You could add a layer of geom_point without data just to create a legend, and then set show.legend = F in the geom_sf layer to hide the squares, as suggested here:
ggplot() +
geom_sf(data = df_ohio, color = "black", aes(fill = as.factor(defiance)), size = .1, alpha = .75, show.legend = F) +
geom_point(data = df_ohio, aes(x = -83, y = 40, color = as.factor(defiance)), size=8, alpha = 0) +
scale_color_manual(values = c('#BB0000','navy'),
labels = c('No','Yes'),
name = "Defiance County?") +
scale_fill_manual(values = c('#BB0000','navy')) +
guides(color = guide_legend(override.aes = list(alpha = 1))) +
theme_void()
Within the geom_point layer you can change the shape with override.aes, but the default is a circle as you want.
You can specify the legend shape if you are working with points rather than polygons. Fortunately, geom_sf allows you to override the default and use point for legend, even if the underlying geom is a polygon, by specifying show.legend = "point".
Demonstration with a built-in dataset:
nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
ggplot(nc) +
geom_sf(aes(fill = AREA >= 0.15), show.legend = "point") +
scale_fill_manual(values = c('#BB0000','navy'),
labels = c('No','Yes'),
name = "Defiance County?") +
theme_void() +
guides(fill = guide_legend(override.aes = list(shape = 21, size = 5)))
(Since it's used in fill, shape 21 seems more appropriate than shape 20; I've also increased the size for ease of view.)
Related
I have horizontal dots plot replotted via ggplotly
df <- data.frame (origin = c("A","B","C","D","E","F","G","H","I","J"),
Percentage = c(23,16,32,71,3,60,15,21,44,60),
rate = c(10,12,20,200,-25,12,13,90,-105,23),
change = c(10,12,-5,12,6,8,0.5,-2,5,-2)
library(ggplot2)
plt <- ggplot(df, aes(x = rate, y = factor(origin, rev(origin)))) +
geom_hline(aes(yintercept = origin), color = 'gray') +
geom_vline(xintercept = 0, linetype = 2, color = 'gray') +
geom_point(aes(color = 'Rate'), size = 10) +
geom_text(aes(label = rate), color = 'white') +
geom_point(aes(x = change, color = 'Change'), size = 10) +
geom_text(aes(label = change, x = change)) +
theme_minimal(base_size = 16) +
scale_x_continuous(labels = ~paste0(.x, '%'), name = NULL) +
scale_color_manual(values = c('#aac7c4', '#5f9299')) +
theme(panel.grid = element_blank(),
axis.text.y = element_text(color = 'gray50')) +
labs(color = NULL, y = NULL)
ggplotly(plt)
The only issue is that when I hide one of the dot from the figure, texts are still appeared (see below), so is there way to tackle this issue and hide text with circle by clicking on legend?
P.S
(setting text colour in white color = 'white' is not option for me)
You can use the fill aesthetic for the points (as long as they are shape = 21) and use the color aesthetic for the text. As long as these have the same labels for aesthetic mapping, the interactivity for both points and text will be linked.
One minor annoyance is that this changes the plotly legend labels, even though they are correct in the ggplot version. This requires a little direct manipulation of the plotly object itself:
plt <- ggplot(df, aes(x = rate, y = factor(origin, rev(origin)))) +
geom_segment(aes(x = -100, xend = 200,
y = origin, yend = origin), color = 'gray') +
geom_vline(xintercept = 0, linetype = 2, color = 'gray') +
geom_point(aes(fill = 'Rate'), shape = 21, size = 10, color = NA) +
geom_text(aes(label = rate, color = 'Rate')) +
geom_point(aes(x = change, fill = 'Change'),
color = NA, shape = 21, size = 10) +
geom_text(aes(label = change, x = change, color = "Change")) +
theme_minimal(base_size = 16) +
scale_x_continuous(labels = ~paste0(.x, '%'), name = NULL) +
scale_fill_manual(values = c('#aac7c4', '#5f9299')) +
scale_color_manual(values = c("black", "white")) +
theme(panel.grid = element_blank(),
axis.text.y = element_text(color = 'gray50')) +
labs(color = NULL, y = NULL, fill = NULL)
p <- ggplotly(plt)
p$x$data[[3]]$name <- p$x$data[[3]]$legendgroup <-
p$x$data[[4]]$name <- p$x$data[[4]]$legendgroup <- "Rate"
p$x$data[[5]]$name <- p$x$data[[5]]$legendgroup <-
p$x$data[[6]]$name <- p$x$data[[6]]$legendgroup <- "Change"
p
This gives us the following plot:
Now clicking on Rate we get:
And clicking on Change we get
I would like to create a raincloud plot. I have successfully done it. But I would like to know if instead of the density curve, I can put a histogram (it's better for my dataset).
This is my code if it can be usefull
ATSC <- ggplot(data = data, aes(y = atsc, x = numlecteur, fill = numlecteur)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0), alpha = .5) +
geom_point(aes(y = atsc, color = numlecteur), position = position_jitter(width = .15), size = .5, alpha = 0.8) +
geom_point(data = sumld, aes(x = numlecteur, y = mean), position = position_nudge(x = 0.25), size = 2.5) +
geom_errorbar(data = sumld, aes(ymin = lower, ymax = upper, y = mean), position = position_nudge(x = 0.25), width = 0) +
guides(fill = FALSE) +
guides(color = FALSE) +
scale_color_brewer(palette = "Spectral") +
scale_y_continuous(breaks=c(0,2,4,6,8,10), labels=c("0","2","4","6","8","10"))+
scale_fill_brewer(palette = "Spectral") +
coord_flip() +
theme_bw() +
expand_limits(y=c(0, 10))+
xlab("Lecteur") + ylab("Age total sans check")+
raincloud_theme
I think we can maybe put the "geom_histogram()" but it doesn't work
Thank you in advance for your help !
(sources : https://peerj.com/preprints/27137v1.pdf
https://neuroconscience.wordpress.com/2018/03/15/introducing-raincloud-plots/)
This is actually not quite easy. There are a few challenges.
geom_histogram is "horizontal by nature", and the custom geom_flat_violin is vertical - as are boxplots. Therefore the final call to coord_flip in that tutorial. In order to combine both, I think best is switch x and y, forget about coord_flip, and use ggstance::geom_boxploth instead.
Creating separate histograms for each category is another challenge. My workaround to create facets and "merge them together".
The histograms are scaled way bigger than the width of the points/boxplots. My workaround scale via after_stat function.
How to nudge the histograms to the right position above Boxplot and points - I am converting the discrete scale to a continuous by mapping a constant numeric to the global y aesthetic, and then using the facet labels for discrete labels.
library(tidyverse)
my_data<-read.csv("https://data.bris.ac.uk/datasets/112g2vkxomjoo1l26vjmvnlexj/2016.08.14_AnxietyPaper_Data%20Sheet.csv")
my_datal <-
my_data %>%
pivot_longer(cols = c("AngerUH", "DisgustUH", "FearUH", "HappyUH"), names_to = "EmotionCondition", values_to = "Sensitivity")
# use y = -... to position boxplot and jitterplot below the histogram
ggplot(data = my_datal, aes(x = Sensitivity, y = -.5, fill = EmotionCondition)) +
# after_stat for scaling
geom_histogram(aes(y = after_stat(count/100)), binwidth = .05, alpha = .8) +
# from ggstance
ggstance::geom_boxploth( width = .1, outlier.shape = NA, alpha = 0.5) +
geom_point(aes(color = EmotionCondition), position = position_jitter(width = .15), size = .5, alpha = 0.8) +
# merged those calls to one
guides(fill = FALSE, color = FALSE) +
# scale_y_continuous(breaks = 1, labels = unique(my_datal$EmotionCondition))
scale_color_brewer(palette = "Spectral") +
scale_fill_brewer(palette = "Spectral") +
# facetting, because each histogram needs its own y
# strip position = left to fake discrete labels in continuous scale
facet_wrap(~EmotionCondition, nrow = 4, scales = "free_y" , strip.position = "left") +
# remove all continuous labels from the y axis
theme(axis.title.y = element_blank(), axis.text.y = element_blank(),
axis.ticks.y = element_blank())
Created on 2021-04-15 by the reprex package (v1.0.0)
I'm trying to fix my caption but I'm having trouble creating it. I wanted a caption for the classes (fill), the shape limit (color), the points (color) and the grid (fill=NA). I put them all in aes () but I don't have the expected result. Can anybody help me? Thanks!
library(geobr)
library(sf)
library(ggplot2)
library(ggspatial)
#Directory
getwd()
#Download spatial data ------------------------------------------------
download.file(url = "http://geo.fbds.org.br/SP/RIO_CLARO/USO/SP_3543907_USO.dbf",
destfile = "SP_3543907_USO.dbf", mode = "wb")
download.file(url = "http://geo.fbds.org.br/SP/RIO_CLARO/USO/SP_3543907_USO.prj",
destfile = "SP_3543907_USO.prj", mode = "wb")
download.file(url = "http://geo.fbds.org.br/SP/RIO_CLARO/USO/SP_3543907_USO.shp",
destfile = "SP_3543907_USO.shp", mode = "wb")
download.file(url = "http://geo.fbds.org.br/SP/RIO_CLARO/USO/SP_3543907_USO.shx",
destfile = "SP_3543907_USO.shx", mode = "wb")
#Import spatial data --------------------------------------------------
uso <- sf::st_read("SP_3543907_USO.shp")
uso
plot(uso$geometry)
#Area limit
rio_claro_limit <- geobr::read_municipality(code_muni = 3543907, year = 2015)
rio_claro_limit
plot(rio_claro_limit$geom)
#Random sample points
set.seed(123)
pts <- st_sample(uso, size = 20, type="random") %>% st_sf
#Grid 50km x 50km
grid_50 <- st_make_grid(uso, cellsize = c(5000, 5000)) %>%
st_sf(grid_id = 1:length(.))
#Labels grid
grid_lab <- st_centroid(grid_50) %>% cbind(st_coordinates(.))
#Points in grid
pts %>% st_join(grid_50, join = st_intersects) %>% as.data.frame
#Map --------------------------------------------------------------------
ggplot() +
geom_sf(data = uso, aes(fill = CLASSE_USO, color = NA)) +
geom_sf(data = rio_claro_limit, aes(color = 'black', fill = NA)) +
geom_sf(data = pts, aes(color = 'red'), size = 1.7) +
geom_sf(data = grid_50, aes(fill=NA), lwd = 0.3) +
geom_text(data = grid_lab, aes(x = X, y = Y, label = grid_id), size = 2) +
xlab("")+
ylab("")+
scale_fill_manual(name="Classes de Uso", values = c("blue", "orange", "gray30", "forestgreen", "green", NA))+
scale_color_identity(guide = "legend")
Your desired result could be achieved like so:
I moved all fill=NA and color=NA out of the aes() statements. As usual if you want to fix a color, fill or more generally any aes on a specific value then it's best to put it outside of aes() except for the case that you want it to appear in the legend.
Set the so called key_glyph, i.e. the icon drawn in the legend, of the "point" layers to "point".
As these steps also removed the black border around the fill keys I added a guides layer to get that back. Personally I would remove the black border, but hey, it's your plot. (:
library(geobr)
library(sf)
library(ggplot2)
library(ggspatial)
ggplot() +
geom_sf(data = uso, aes(fill = CLASSE_USO), color = NA) +
geom_sf(data = rio_claro_limit, aes(color = 'black'), fill = NA, key_glyph = "point") +
geom_sf(data = pts, aes(color = 'red'), size = 1.7, key_glyph = "point") +
geom_sf(data = grid_50, fill = NA, lwd = 0.3) +
geom_text(data = grid_lab, aes(x = X, y = Y, label = grid_id), size = 2) +
xlab("")+
ylab("")+
scale_fill_manual(name="Classes de Uso", values = c("blue", "orange", "gray30", "forestgreen", "green", NA)) +
guides(fill = guide_legend(override.aes = list(color = "black"))) +
scale_color_identity(guide = "legend")
I'm trying to make a map with points plotted for the Canadian prairie provinces, but I'm having no luck adding in a legend to my map. I'm very new to mapping in r, so I'm not understanding how I should include aes to get a legend. My data for siteDataTrees is from an excel csv file and the top looks like this:
siteDataTrees
and the data for siteDataBoth is also from a csv file and the top looks like this:
siteDataBoth.
Here's what I have so far for my code:
library(maps)
library(ggplot2)
library(sf)
prairies1 <- map("worldHires","Canada", xlim = c(-120,-87), ylim = c(49,61),
plot = FALSE, fill = TRUE)
prairies <- st_as_sf(prairies1)
ggplot(data = prairies) +
geom_sf() +
geom_point(data = siteDataTrees, aes(x = long, y = lat), size = 2.5, pch = 21,
fill = "purple", show.legend = TRUE) +
geom_point(data = siteDataBoth, aes(x = long, y = lat), size = 2.5, pch = 21,
fill = "light green", show.legend = TRUE) +
geom_text(data = locations, aes(x = long, y = lat, label = name),
size = 2, col = "black", check_overlap = FALSE) +
annotation_scale(location = "tr", width_hint = 0.2) +
ggtitle("Climate Stations and Tree Chronology Locations for South AB") +
labs(x = "latitude", y = "longitude") +
theme(legend.position = "right") +
coord_sf(xlim = c(-115, -110), ylim = c(48.9, 50.49), expand = FALSE)
I've also included a map to show what it looks like without the legend.
How should I take the data frame prairies and use it with aes to include a legend? Is there another way to add in a legend in ggplot2 without using the aes function? Thank you in advance for your help and please let me know if something is missing as this is my first posting
Let me give you a couple of examples on how to work out a legend using a slightly modified example from r-spatial.
First we prepare the data:
library(maps)
library(ggplot2)
library(sf)
library(rnaturalearth)
library(rnaturalearthdata)
world <- ne_countries(scale = "medium", returnclass = "sf")
(sites <- data.frame(longitude = c(-80.144005, -80.109),
latitude = c(26.479005,26.83),
type = c("tree", "station")))
Now we plot. Case 1: color is not an issue
ggplot(data = world) +
geom_sf() +
geom_point(data = sites,
aes(x = longitude, y = latitude, fill = type),
size = 4,
shape = 23) +
coord_sf(xlim = c(-88, -78), ylim = c(24.5, 33), expand = FALSE) +
theme(legend.position = "bottom")
Case 2: fill color is an issue.
Here we can use a named vectors to pass the colors and the labels we want by type of point. For example:
mapfill <- c('tree' = "forestgreen", 'station' = "purple")
maplab <- c('tree' = "trees in prairies", 'station' = "Stations in prairies")
Then we plot combining both mapfill and maplab:
ggplot(data = world) +
geom_sf() +
geom_point(data = sites, aes(x = longitude, y = latitude, fill = type), size = 4,
shape = 23) +
scale_fill_manual(values = mapfill, labels = maplab) +
coord_sf(xlim = c(-88, -78), ylim = c(24.5, 33), expand = FALSE) +
theme(legend.position = "bottom")
Remark 1 If you do not want type in the legend title you can either delete it using legend. title = element_blank() within theme
Remark 2 If, instead of fill, you are using color, use function scale_color_manual. If you are combining both fill and color do the same with scale_***_manual
In spirit of full disclosure, if you do not mind the colors and you want a quick fix (and I cannot stress this enough) you can also code fill = "TextYouWantInLegend" within aes. See following example:
ggplot(data = world) +
geom_sf() +
geom_point(data = sites[1,], aes(x = longitude, y = latitude, fill = "toto"), size = 4,
shape = 23) +
geom_point(data = sites[2,], aes(x = longitude, y = latitude, fill = "koko"), size = 4,
shape = 23) +
coord_sf(xlim = c(-88, -78), ylim = c(24.5, 33), expand = FALSE) +
theme(legend.position = "bottom")
I need to create a European map to show the distribution of a variable across countries. I need the map in black and white. I rely on ggplot and followed this approach as an example. I changed the legend based on this blogpost. All this works fine with this result:
My question is how to change the map in a way that the countries where I am missing the information for fill and are shown as pure white have a texture over-them (I am thinking diagonal lines)?
Since my script is a bit messy, I just show the ggplot here, without the data preparation part:
require(ggplot2)
plotCoords <- read.csv("http://eborbath.github.io/stackoverflow/PlotCoords.csv")
showCoords <- read.csv("http://eborbath.github.io/stackoverflow/showCoords.csv")
ggplot() +
geom_polygon(
data = plotCoords,
aes(x = long, y = lat, group = group),
fill = "white", colour = "darkgrey", size = 0.6) +
geom_polygon(
data = showCoords,
aes(x = long, y = lat, group = group),
fill = "grey", colour = "black", size = 0.6) +
geom_polygon(
data = showCoords,
aes(x = long, y = lat, group = group, fill = sh_left),
colour = "black", size = 0.1) +
scale_fill_gradient(
low = "gray90", high = "gray0",
name = "Share of left-wing protesters",
guide = guide_colorbar(
direction = "horizontal",
barheight = unit(2, units = "mm"),
barwidth = unit(50, units = "mm"),
draw.ulim = F,
title.position = 'top',
title.hjust = 0.5,
label.hjust = 0.5
)) +
scale_x_continuous(element_blank(), breaks = NULL) +
scale_y_continuous(element_blank(), breaks = NULL) +
coord_map(xlim = c(-26, 47), ylim = c(32.5, 73)) +
theme_bw() +
theme(legend.justification = c(-0.4, 1.2), legend.position = c(0, 1))
The first geom_polygon is for the background, I assume I have to edit the fill there. Obviously, this is important to differentiate no information from low values of the variable I plot. Given I have to rely on black and white I came up with the idea of using textures, but I am open to alternative suggestions.
Thanks!
it's technically possible with gridSVG, but not sure it's worth the effort.
I created a new geom based on GeomPolygon, and modified the draw_panel method to return,
gl <- by(munched, munched$group,
function(m){
g <- polygonGrob(m$x, m$y, default.units = "native")
patternFillGrob(g,
pattern = pattern(linesGrob(gp=gpar(col="red",lwd=3)),
width = unit(2, "mm"), height = unit(2, "mm"),
dev.width = 1, dev.height = 1))
}, simplify = FALSE)
gTree(children = do.call(gList, gl))