I'm trying to fill a 20x20 grid randomly according to a given probability. For example, if I was given a probability of 67%, I would want to fill a random 268 squares with blue, and leave the other ones empty.
Can anyone help me with this? Appreciate it!
Thanks
Figured it out!
win.prob <- .67
heatmap <- matrix(ifelse(runif(400, min = 0, max = 1)<=win.prob,1,0), nrow = 20)
heatmap.m <- melt(heatmap) %>% mutate("Majority" = ifelse(value>0.5,"Democratic","Republican"))
library(reshape)
ggplot(heatmap.m, aes(x = X1, y = X2,fill=Majority)) +
geom_tile(color = "black") +
theme_void() +
scale_fill_manual(values=c("Democratic" = "blue","Republican"="red"))
Related
I have a dataframe (dat) with two columns 1) Month and 2) Value. I would like to highlight that the x-axis is not continuous in my boxplot by interrupting the x-axis with two angled lines on the x-axis that are empty between the angled lines.
Example Data and Boxplot
library(ggplot2)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black"))
The ideal figure would look something like below. How can I make this discontinuous axis in ggplot?
You could make use of the extended axis guides in the ggh4x package. Alas, you won't easily be able to create the "separators" without a hack similar to the one suggested by user Zhiqiang Wang
guide_axis_truncated accepts vectors to define lower and upper trunks. This also works for units, by the way, then you have to pass the vector inside the unit function (e.g., trunc_lower = unit(c(0,.45), "npc") !
library(ggplot2)
library(ggh4x)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
# this is to make it slightly more programmatic
x1end <- 3.45
x2start <- 3.55
p <-
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_classic() +
theme(axis.line = element_line(colour = "black"))
p +
guides(x = guide_axis_truncated(
trunc_lower = c(-Inf, x2start),
trunc_upper = c(x1end, Inf)
))
Created on 2021-11-01 by the reprex package (v2.0.1)
The below is taking user Zhiqiang Wang's hack a step further. You will see I am using simple trigonometry to calculate the segment coordinates. in order to make the angle actually look as it is defined in the function, you would need to set coord_equal.
# a simple function to help make the segments
add_separators <- function(x, y = 0, angle = 45, length = .1){
add_y <- length * sin(angle * pi/180)
add_x <- length * cos(angle * pi/180)
## making the list for your segments
myseg <- list(x = x - add_x, xend = x + add_x,
y = rep(y - add_y, length(x)), yend = rep(y + add_y, length(x)))
## this function returns an annotate layer with your segment coordinates
annotate("segment",
x = myseg$x, xend = myseg$xend,
y = myseg$y, yend = myseg$yend)
}
# you will need to set limits for correct positioning of your separators
# I chose 0.05 because this is the expand factor by default
y_sep <- min(dat$Value) -0.05*(min(dat$Value))
p +
guides(x = guide_axis_truncated(
trunc_lower = c(-Inf, x2start),
trunc_upper = c(x1end, Inf)
)) +
add_separators(x = c(x1end, x2start), y = y_sep, angle = 70) +
# you need to set expand to 0
scale_y_continuous(expand = c(0,0)) +
## to make the angle look like specified, you would need to use coord_equal()
coord_cartesian(clip = "off", ylim = c(y_sep, NA))
I think it is possible to get what you want. It may take some work.
Here is your graph:
library(ggplot2)
set.seed(321)
dat <- data.frame(matrix(ncol = 2, nrow = 18))
x <- c("Month", "Value")
colnames(dat) <- x
dat$Month <- rep(c(1,2,3,10,11,12),3)
dat$Value <- rnorm(18,20,2)
p <- ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black"))
Here is my effort:
p + annotate("segment", x = c(3.3, 3.5), xend = c(3.6, 3.8), y = c(14, 14), yend = c(15, 15))+
coord_cartesian(clip = "off", ylim = c(15, 25))
Get something like this:
If you want to go further, it may take several tries to get it right:
p + annotate("segment", x = c(3.3, 3.5), xend = c(3.6, 3.8), y = c(14, 14), yend = c(15, 15))+
annotate("segment", x = c(0, 3.65), xend = c(3.45, 7), y = c(14.55, 14.55), yend = c(14.55, 14.55)) +
coord_cartesian(clip = "off", ylim = c(15, 25)) +
theme_classic()+
theme(axis.line.x = element_blank())
Just replace axis with two new lines. This is a rough idea, it may take some time to make it perfect.
You could use facet_wrap. If you assign the first 3 months to one group, and the other months to another, then you can produce two plots that are side by side and use a single y axis.
It's not exactly what you want, but it will show the data effectively, and highlights the fact that the x axis is not continuous.
dat$group[dat$Month %in% c("1", "2", "3")] <- 1
dat$group[dat$Month %in% c("10", "11", "12")] <- 2
ggplot(data = dat, aes(x = factor(Month), y = Value)) +
geom_boxplot() +
labs(x = "Month") +
theme_bw() +
theme(panel.grid = element_blank(),
text = element_text(size = 16),
axis.text.x = element_text(size = 14, color = "black"),
axis.text.y = element_text(size = 14, color = "black")) +
facet_wrap(~group, scales = "free_x")
* Differences in the plot are likely due to using different versions of R where the set.seed gives different result
I want to combine a bar and line plot and label line plot.
This is what I got: plot
this is my code:
df %>%
ggplot(aes(reorder(NAME, pval),y = pval)) +
geom_col(aes(x = NAME, y = pval), size = 1, color = "royalblue", fill = "white") +
geom_line(aes(x = NAME, y = 10*Ratio), size = 1.5, color="#c4271b", group = 1) + geom_text(aes(label = Ratio))+coord_flip()
I want to label line plot, but the bar plot gets the labels?
My second question:
How to rearrange the y-axis from the largest -log(pvalue) to lowest one?
Any help will be really appreciated!
try set the x and y aes in geom_text() with the same in geom_line()
geom_text(aes(x = NAME, y = 10*Ratio, label = Ratio))
Hi, I have two columns of data. They are over the same time period but column one generates data every 1000ms, and column 2 generates data every 500ms. How can i plot them on the same graph looking of equal length. The x-axis doesnt have to be "Time". Thank you.
plt.rcParams['figure.figsize'] = [40,20]
x = df['Time']
y1 = df['Engine RPM']
y2 = df['FMS RPM']
plt.plot(x,y1,color='r', label='column1',linewidth=2)
plt.plot(x,y2,color='b', label='column2',linewidth=2)
I can have both lines looking equal using the following code, but on seperate graphs.
x = np.linspace(0, 100,100)
x2 = np.linspace(0,200,200)
f, ((ax1, ax2)) = plt.subplots(2)
y1 = df['Engine RPM']
y2 = df1['FMS RPM']
ax1.plot(x,y1, label = 'column1')
ax2.plot(x2,y2, label = 'column2')
Try this:
x = np.linspace(0, 100,100)
x2 = np.linspace(0,200,200)
f, ax = plt.subplots(1,1)
ax2 = ax1.twiny()
ax.plot(x,y1,color='r', label='column1',linewidth=2)
ax2.plot(x,y2,color='b', label='column2',linewidth=2)
I have set up a line graph in shiny. The x axis has dates covering 2014 to current date.
I have set up various vertical lines using geom_vline() to highlight points in the data.
I'm using dateRangeInput() so the user can choose the start/end date range to look at on the graph.
One of my vertical lines is in Feb 2014. If the user uses the dateRangeInput() to look at dates from say Jan 2016 the vertical line for Feb 2014 is still showing on the graph. This is also causing the x axis to go from 2014 even though the data line goes from Jan 2016 to current date.
Is there a way to stop this vertical line showing on the graph when it's outside of the dataRangeInput()? Maybe there's an argument in geom_vline() to deal with this?
library(shiny)
library(tidyr)
library(dplyr)
library(ggplot2)
d <- seq(as.Date("2014-01-01"),Sys.Date(),by="day")
df <- data.frame(date = d , number = seq(1,length(d),by=1))
lines <- data.frame(x = as.Date(c("2014-02-07","2017-10-31", "2017-08-01")),
y = c(2500,5000,7500),
lbl = c("label 1", "label 2", "label 3"))
#UI
ui <- fluidPage(
#date range select:
dateRangeInput(inputId = "date", label = "choose date range",
start = min(df$date), end = max(df$date),
min = min(df$date), max = max(df$date)),
#graph:
plotOutput("line")
)
#SERVER:
server <- function(input, output) {
data <- reactive({ subset(df, date >= input$date[1] & date <= input$date[2])
})
#graph:
output$line <- renderPlot({
my_graph <- ggplot(data(), aes(date, number )) + geom_line() +
geom_vline(data = lines, aes(xintercept = x, color = factor(x) )) +
geom_label(data = lines, aes(x = x, y = y,
label = lbl, colour = factor(x),
fontface = "bold" )) +
scale_color_manual(values=c("#CC0000", "#6699FF", "#99FF66")) +
guides(colour = "none", size = "none")
return(my_graph)
})
}
shinyApp(ui = ui, server = server)
As mentioned by Aimée in a different thread:
In a nutshell, ggplot2 will always plot all of the data that you provide and the axis limits are based on that unless you specify otherwise. So because you are telling it to plot the line & label, they will appear on the plot even though the rest of the data doesn't extend that far.
You can resolve this by telling ggplot2 what you want the limits of your x axis to be, using the coord_cartesian function.
# Set the upper and lower limit for the x axis
dateRange <- c(input$date[1], input$date[2])
my_graph <- ggplot(df, aes(date, number)) + geom_line() +
geom_vline(data = lines, aes(xintercept = x, color = factor(x) )) +
geom_label(data = lines, aes(x = x, y = y,
label = lbl, colour = factor(x),
fontface = "bold" )) +
scale_color_manual(values=c("#CC0000", "#6699FF", "#99FF66")) +
guides(colour = "none", size = "none") +
coord_cartesian(xlim = dateRange)
I have two time series (ts-variables) with different time length. It’s yearly data and they are stored as separate ts.objects. The first series starts in 1936 and the other starts in 1943 and both ends in 2012. Problem: I cannot find the R-script (commands) for plotting these series in one, single, nice figure which includes all observations. Great if someone can help.
Regards
If the data are on a comparable scale then you just need to set the x-axis limits to the range of the entire data, e.g.
set.seed(2) ## reproducible
dat1 <- data.frame(Year = seq(1936, 2012, by = 1), Y = runif(77))
dat2 <- data.frame(Year = seq(1943, 2012, by = 1), Y = runif(70))
ylim <- range(dat1$Y, dat2$Y)
xlim <- range(dat1$Year, dat2$Year)
plot(Y ~ Year, data = dat1, type = "l", col = "red", xlim = xlim,
ylim = ylim)
lines(Y ~ Year, data = dat2, type = "l", col = "blue")
I'll leave you to prettify the plot.
Just noticed you said ts variables, so the following will work too
ts1 <- ts(runif(77), start = 1936, freq = 1)
ts2 <- ts(runif(70), start = 1943, freq = 1)
xlim <- c(1936, 2012)
ylim <- range(ts1, ts2)
plot(ts1, ylim = ylim, xlim = xlim, col = "red")
lines(ts2, col = "blue")
With your data, replace runif(n) with the real data for the two time series.