In this experiment, we tracked presence or absence of bacterial infection in our subject animals. We were able to isolate which type of bacteria was present in our animals and created a plot that has Week Since Experiment Start on the X axis, and Percentage of Animals Positive for bacterial infection on the Y axis. This is a stacked identity ggplot where each geom_bar contains the different identities of the bacteria that were in the infected animals each week. Here is a sample dataset with the corresponding ggplot code and result:
DummyData <- data.frame(matrix(ncol = 5, nrow = 78))
colnames(DummyData) <- c('WeeksSinceStart','BacteriaType','PositiveOccurences','SampleSize','NewSampleSize')
DummyData$WeeksSinceStart <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,3,3,3,3,3,3,3,3,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,7,7,7,7,7,7,7,7,7,8,8,8,8,8,8,8,9,9,9,9,9,10,10,10,10)
DummyData$BacteriaType <- c("BactA","BactB","BactD","BactB","BactE","BactA","BactS","BactF","BactE","BactH","BactJ","BactK","BactE","BactB","BactS","BactF","BactL","BactE","BactW","BactH","BactS","BactJ","BactQ","BactN","BactW","BactA","BactD","BactE","BactA","BactC","BactD","BactK","BactL","BactE","BactD","BactA","BactS","BactK","BactB","BactE","BactF","BactH","BactN","BactE","BactL","BactZ","BactE","BactC","BactR","BactD","BactJ","BactN","BactK","BactW","BactR","BactE","BactW","BactA","BactM","BactG","BactO","BactI","BactE","BactD","BactM","BactH","BactC","BactM","BactW","BactA","BactL","BactB","BactE","BactA","BactS","BactH","BactQ","BactF")
PosOcc <- seq(from = 1, to = 2, by = 1)
DummyData$PositiveOccurences <- rep(PosOcc, times = 13)
DummyData$SampleSize <- c(78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,78,29,29,29,29,29,10,10,10,10)
DummyData$NewSampleSize <- c(78,NA,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,NA,NA,78,NA,NA,NA,NA,NA,NA,29,NA,NA,NA,NA,10,NA,NA,NA)
numcolor <- 20
plotcolors <- colorRampPalette(brewer.pal(8, "Set3"))(numcolor)
#GGplot for Dummy Data
DummyDataPlot <- ggplot(DummyData, aes(x = WeeksSinceStart, y = PositiveOccurences/SampleSize, fill = BacteriaType)) + geom_bar(position = "stack", stat = "identity") +
geom_text(label = DummyData$NewSampleSize, nudge_y = 0.1) +
scale_y_continuous(limits = c(0,0.6), breaks = seq(0, 1, by = 0.1)) + scale_x_continuous(limits = c(0.5,11), breaks = seq(0,10, by =1)) +
labs(
x = "Weeks Since Start",
y = "Proportion Positive") +
scale_fill_manual(values = plotcolors)
The problem: I cannot seem to find a way to position the labels from geom_text directly over each bar. I would also love to add the text "n = " to the sample size value directly over each bar. Thank you for your help!
I have tried different values for position_dodge statement and nudge_y statement with no success.
Sometimes the easiest approach is to do some data wrangling, i.e. one option would be to create a separate dataframe for your labels:
library(ggplot2)
library(dplyr)
dat_label <- DummyData |>
group_by(WeeksSinceStart) |>
summarise(y = sum(PositiveOccurences / SampleSize), SampleSize = unique(SampleSize))
ggplot(DummyData, aes(x = WeeksSinceStart, y = PositiveOccurences / SampleSize, fill = BacteriaType)) +
geom_bar(position = "stack", stat = "identity") +
geom_text(data = dat_label, aes(x = WeeksSinceStart, y = y, label = SampleSize), inherit.aes = FALSE, nudge_y = .01) +
#scale_y_continuous(limits = c(0, 0.6), breaks = seq(0, 1, by = 0.1)) +
scale_x_continuous(limits = c(0.5, 11), breaks = seq(0, 10, by = 1)) +
labs(
x = "Weeks Since Start",
y = "Proportion Positive"
) +
scale_fill_manual(values = plotcolors)
Suppose we want to plot this data:
library(ggplot2)
library(sf)
library(raster)
library(colorRamps)
min_lon <- 10
max_lon <- 17
min_lat <- 8
max_lat <- 17
grid_size <- 0.5
lon_grids <- 1 + ((max_lon - min_lon)/grid_size)
lat_grids <- 1 + ((max_lat - min_lat)/grid_size)
points <- data.frame(lon = rep(seq(min_lon, max_lon, grid_size), lat_grids), lat = rep(seq(min_lat, max_lat, grid_size), each = lon_grids))
points$Var <- runif(min= 10, max = 48, 285)
points$value <-cut(points$Var, breaks= seq(10.08, 47.80, length.out = 13), dig.lab = 1)
ggplot() +
coord_sf(xlim = c(min_lon, max_lon), ylim = c(min_lat, max_lat)) +
theme_bw()+
geom_raster(data = points, aes(x = lon, y = lat, fill = value), interpolate = FALSE) +
labs(x="Longitude", y="Latitude")+
scale_fill_manual(values = matlab.like(n = 13), name = "[m]",
labels = sprintf("%.2f", seq(10.08, 47.80, length.out = 13)),
guide = guide_legend(reverse = TRUE))+theme(legend.position = "bottom")
This code produces the following graph:
Two problems I am facing here:
To make it discrete, I used the cut function. I chose the breaks= seq(10.08, 47.80, length.out = 13) arbitrary based on the minimum and maximum values with a random length of 13. Is there any criteria to decide the correct range?
Is there any way to make the legend look like this?
One option would be to use e.g. scale_fill_stepsn with guide_binswhich does not require to manually discretize the variable mapped on fill. Additionally I use a custom function to set the breaks of the legend instead of the default mechanism to set the number of breaks.
set.seed(123)
library(ggplot2)
library(colorRamps)
base <- ggplot() +
coord_sf(xlim = c(min_lon, max_lon), ylim = c(min_lat, max_lat)) +
theme_bw() +
geom_raster(data = points, aes(x = lon, y = lat), interpolate = FALSE) +
labs(x = "Longitude", y = "Latitude") +
theme(legend.position = "bottom")
base +
aes(fill = Var) +
scale_fill_stepsn(colors = matlab.like(n = 13), name = "[m]",
breaks = function(x) seq(x[[1]], x[[2]], length.out = 13),
labels = ~ sprintf("%.0f", .x),
guide = guide_bins(axis = FALSE,
show.limits = TRUE))
I am trying to create a plot to track results over days for multiple factors. Ideally I would like my xaxis to be Day, with the day number centered in the middle of the reps for that particular day, the y axis to be result, and the facet will be the Lot (1-4). I am having difficulty making the day centered on the bottom using repeatable text, as the number of reps may vary.
I was using ideas shown in this post: Multi-row x-axis labels in ggplot line chart but have been unable to make any progress.
Here is some code I have been using and the plot that I have so far. The x axis is far too busy and I am trying to consolidate it.
data <- data.frame(System = rep(c("A", "B"), each = 120), Lot = rep(1:4, each = 30),
Day = rep(1:5, each = 6), Rep = rep(1:6, 40), Result = rnorm(240))
library(ggplot2)
ggplot(data, aes(x = interaction(Day, Rep, lex.order = TRUE), y = Result, color = System, group = System)) +
geom_point() +
geom_line() +
theme(legend.position = "bottom") +
facet_wrap(~Lot, ncol = 1) +
geom_vline(xintercept = (which(data$Rep == 1 & data$Day != 1)), color = "gray60")
I'm not 100% sure if this is exactly what you are after but this will center the day on the x-axis.
library(dplyr)
library(tidyr)
library(ggplot2)
df <- data.frame(System = rep(c("A", "B"), each = 120), Lot = rep(1:4, each = 30),
Day = rep(1:5, each = 6), Rep = rep(1:6, 40), Result = rnorm(240))
df <- df %>%
unite(Day_Rep, Day, Rep, sep = ".", remove = F) %>%
mutate(Day_Rep = as.numeric(Day_Rep))
ggplot(df, aes(x = Day_Rep, y = Result, color = System, group = System)) +
geom_point() +
geom_line() +
theme(legend.position = "bottom") +
facet_wrap(~Lot, ncol = 1) +
scale_x_continuous(labels = df$Day, breaks = df$Day + 0.5)+
geom_vline(xintercept = setdiff(unique(df$Day), 1))