This question already has answers here:
Place a border around points
(5 answers)
Closed 1 year ago.
I have a dataset like this:
Year<-rep(2001:2005, each = 5)
name<-c("John","Ellen","Mark","Randy","Luisa")
Name<-c(rep(name,5))
Value<-sample(seq(0,25,by=1),25)
mydata<-data.frame(Year,Name,Value)
And my plot looks like this:
p <- ggplot(mydata, aes(x=Year, y=reorder(Name, desc(Name)), size = Value)) +
geom_point(aes(colour = Value,
alpha = I(as.numeric(Value > 0))))
p <- p + scale_colour_viridis_c(option = "D", direction = -1,
limits = c(1, 25)) +
scale_size_area(guide = "none") +
ylab("Name") +
theme(axis.line = element_blank(),
axis.text.x=element_text(size=11,margin=margin(b=10),colour="black"),
axis.text.y=element_text(size=13,margin=margin(l=10),colour="black",
face="italic"),
axis.ticks = element_blank(),
axis.title=element_text(size=18,face="bold"),
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(),
legend.text = element_text(size=14),
legend.title = element_text(size=18))
I would like to improve it in two ways but I couldn't figure out how.
I would like to add a black border around points. I know I should use pch>20 and specify colour, but because my colours are mapped to a feature of the dataset (they depend on value, in this case), I don't know exactly how to do that. Note that value = 0 points are not plotted. Easy stratagems such as plotting bigger black points under my points seem utopic for me.
I would like to change the breaks of the scale (e.g., instead of having breaks every 5, I'd like to have breaks every 2.5), but it is a continuous scale, and I'm not sure how to do that.
I am not very familiar with ggplo2, thus any help would be appreciated!
You can indeed use a shape >20, e.g. I use shape=21 here. Then you need to change your scale_color_ to scale_fill_, because the color is now black (it is the border of the shape).
For breaks, you could just specify them in the scale itself. Combining both:
ggplot(mydata, aes(x=Year, y=reorder(Name, desc(Name)), size = Value)) +
geom_point(aes(fill = Value,
alpha = I(as.numeric(Value > 0))), shape=21, color = "black") +
scale_fill_viridis_c(option = "D", direction = -1,
limits = c(1, 25), breaks=seq(1, 25, 2.5)) +
scale_size_area(guide = "none") +
ylab("Name") +
theme(axis.line = element_blank(),
axis.text.x=element_text(size=11,margin=margin(b=10),colour="black"),
axis.text.y=element_text(size=13,margin=margin(l=10),colour="black",
face="italic"),
axis.ticks = element_blank(),
axis.title=element_text(size=18,face="bold"),
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(),
legend.text = element_text(size=14),
legend.title = element_text(size=18))
I have created a bar chart which shows the sales of products in a particular category. This is the bar chart. As you can see it is not very clear so I am trying to set limits for the Y axis.
I create the bar chart with the following line:
bakerySales <- ggplot(sales_bakery, aes(ProductName, ProductSales))+
stat_summary(fun.y=sum,geom="bar",colour="red",fill="red",show.legend =
FALSE)
I then go on to apply a theme to the bar chart using:
bakerySales <- bakerySales +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.x = element_text(colour = "black", size = 14, angle = 60,
hjust = 1),
axis.text.y = element_text(colour = "black", size = 14),
panel.background = element_rect(fill = "white"),
panel.grid.minor = element_blank(),
panel.grid.major = element_blank(),
axis.line = element_line(colour = "black", size = 1),
legend.position = "none",
plot.title = element_text(lineheight = 8, face = "bold"))
I have tried to set the limits for the y axis using:
bakerySales <- bakerySales + ylim(5000,10000)
When I do this I lose the content of the bar chart, It looks like this.
Can someone please tell me where I am going wrong.
Thanks
If you want to zoom in on specifix ylimits, you could use the coord_cartesian function. I do not have the bakerysales dataset, this is an example using mtcars data:
ggplot(mtcars, aes(x = gear, y = qsec)) +
stat_summary(fun.y=sum,geom="bar",colour="red",fill="red",show.legend = FALSE) +
coord_cartesian(ylim = c(200, 300))
Maybe you want
+ coord_cartesian(ylim = c(5000,10000))
df <- data.frame(x = c("a","b"), y = c(1000, 2000))
ggplot(df, aes(x=x,y=y)) +
geom_bar(stat="identity") +
coord_cartesian(ylim = c(500,3000))
I'm using ggplot so I can get a gradient onto a map to show data over a large scale. There are points between 0 and 35,000 to be visualised. I have got this to work, but the legend is automatically showing labels for every 10,000.
Ideally I want the legend to show the maximum amount, so probably it would just show 0 at the bottom and 35,000 at the top. Is this doable?
My ggplot code is below if this helps.
ggplot() +
geom_map(data = datafile, aes(map_id = Health_Board, fill = datafile$"2007"), map = Scot) +
geom_polygon(data = Scot, aes(x = long, y = lat, group = group), colour = "gray", fill = NA) +
expand_limits(x = Scot$long, y = Scot$lat) +
scale_fill_gradient(low = ("lightyellow"), high = ("red"), limits = c(0,35000)) +
ggtitle("2007") +
coord_fixed(1.2) +
theme(axis.text.x = element_blank(), axis.text.y = element_blank(),
axis.ticks = element_blank(), axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.border = element_blank(), panel.background = element_blank(),
legend.title = element_text(face = "bold"),
plot.title = element_text(face = "bold", hjust = 0.5))
You can include the "breaks" argument. Like this:
scale_fill_gradient(low = ("lightyellow"), high = ("red"),
breaks=c(min(lat),max(lat)),
limits = c(0,35000)) +
If you want more, its possible to include the "labels" argument.
scale_fill_gradient(low = ("lightyellow"), high = ("red"),
breaks=c(min(lat),max(lat)),
labels=c("Minimum","Maximum"),
limits = c(0,35000)) +
This question already has answers here:
ggplot2 - jitter and position dodge together
(2 answers)
Closed 6 years ago.
I have a data which can be divaded via two seperators. One is year and second is a field characteristics.
box<-as.data.frame(1:36)
box$year <- c(1996,1996,1996,1996,1996,1996,1996,1996,1996,
1997,1997,1997,1997,1997,1997,1997,1997,1997,
1996,1996,1996,1996,1996,1996,1996,1996,1996,
1997,1997,1997,1997,1997,1997,1997,1997,1997)
box$year <- as.character(box$year)
box$case <- c(6.40,6.75,6.11,6.33,5.50,5.40,5.83,4.57,5.80,
6.00,6.11,6.40,7.00,NA,5.44,6.00, NA,6.00,
6.00,6.20,6.40,6.64,6.33,6.60,7.14,6.89,7.10,
6.73,6.27,6.64,6.41,6.42,6.17,6.05,5.89,5.82)
box$code <- c("L","L","L","L","L","L","L","L","L","L","L","L",
"L","L","L","L","L","L","M","M","M","M","M","M",
"M","M","M","M","M","M","M","M","M","M","M","M")
colour <- factor(box$code, labels = c("#F8766D", "#00BFC4"))
In boxplots, I want to display points over them, to see how data is distributed. That is easily done with one single boxplot for every year:
ggplot(box, aes(x = year, y = case, fill = "#F8766D")) +
geom_boxplot(alpha = 0.80) +
geom_point(colour = colour, size = 5) +
theme(text = element_text(size = 18),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank(),
legend.position = "none")
But it become more complicated as I add fill parameter in them:
ggplot(box, aes(x = year, y = case, fill = code)) +
geom_boxplot(alpha = 0.80) +
geom_point(colour = colour, size = 5) +
theme(text = element_text(size = 18),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank(),
legend.position = "none")
And now the question: How to move these points to boxplot axes, where they belong? As blue points to blue boxplot and red to red one.
Like Henrik said, use position_jitterdodge() and shape = 21. You can clean up your code a bit too:
No need to define box, then fill it piece by piece
You can let ggplot hash out the colors if you wish and skip constructing the colors factor. If you want to change the defaults, look into scale_fill_manual and scale_color_manual.
box <- data.frame(year = c(1996,1996,1996,1996,1996,1996,1996,1996,1996,
1997,1997,1997,1997,1997,1997,1997,1997,1997,
1996,1996,1996,1996,1996,1996,1996,1996,1996,
1997,1997,1997,1997,1997,1997,1997,1997,1997),
case = c(6.40,6.75,6.11,6.33,5.50,5.40,5.83,4.57,5.80,
6.00,6.11,6.40,7.00,NA,5.44,6.00, NA,6.00,
6.00,6.20,6.40,6.64,6.33,6.60,7.14,6.89,7.10,
6.73,6.27,6.64,6.41,6.42,6.17,6.05,5.89,5.82),
code = c("L","L","L","L","L","L","L","L","L","L","L","L",
"L","L","L","L","L","L","M","M","M","M","M","M",
"M","M","M","M","M","M","M","M","M","M","M","M"))
ggplot(box, aes(x = factor(year), y = case, fill = code)) +
geom_boxplot(alpha = 0.80) +
geom_point(aes(fill = code), size = 5, shape = 21, position = position_jitterdodge()) +
theme(text = element_text(size = 18),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank(),
legend.position = "none")
I see you've already accepted #JakeKaupp's nice answer, but I thought I would throw in a different option, using geom_dotplot. The data you are visualizing is rather small, so why not forego the boxplot?
ggplot(box, aes(x = factor(year), y = case, fill = code))+
geom_dotplot(binaxis = 'y', stackdir = 'center',
position = position_dodge())