The Marimekko/Mosaic plot is a nice default plot when both x and y are categorical variables. What is the best way to create these using ggplot?
Thanks all who created this entry which really helped me as ggmosaic wasn't doing what I wanted (and not labelling axes properly). The nice function from Z.Lin throws a warning sort of explained in https://github.com/tidyverse/ggplot2/issues/3142 which seems to say that warning, which is technically untrue in its content, is really warning us that the ggplotocracy, bless and thank them, feel that geom_bar shouldn't really have variable widths. I guess I see the point so I went for the function from Jake Fisher and tweaked it to my own needs. In case it's useful to others, here it is:
makeplot_mosaic2 <- function(data, x, y, statDigits = 1, residDigits = 1, pDigits = 3, ...){
### from https://stackoverflow.com/questions/19233365/how-to-create-a-marimekko-mosaic-plot-in-ggplot2,
### this from Jake Fisher (I think)
xvar <- deparse(substitute(x))
yvar <- deparse(substitute(y))
mydata <- data[c(xvar, yvar)]
mytable <- table(mydata)
widths <- c(0, cumsum(apply(mytable, 1, sum)))
heights <- apply(mytable, 1, function(x){c(0, cumsum(x/sum(x)))})
alldata <- data.frame()
allnames <- data.frame()
for(i in 1:nrow(mytable)){
for(j in 1:ncol(mytable)){
alldata <- rbind(alldata, c(widths[i], widths[i+1], heights[j, i], heights[j+1, i]))
}
}
colnames(alldata) <- c("xmin", "xmax", "ymin", "ymax")
alldata[[xvar]] <- rep(dimnames(mytable)[[1]],rep(ncol(mytable), nrow(mytable)))
alldata[[yvar]] <- rep(dimnames(mytable)[[2]],nrow(mytable))
chisq <- chisq.test(mytable)
df <- chisq$parameter
pval <- chisq$p.value
chisqval <- chisq$statistic
# stdResids <- chisq$stdres
alldata$xcent <- (alldata$xmin + alldata$xmax)/2
alldata$ycent <- (alldata$ymin + alldata$ymax)/2
alldata$stdres <- round(as.vector(t(chisq$stdres)), residDigits)
# print(chisq$stdres)
# print(alldata)
titleTxt1 <- paste0("Mosaic plot of ",
yvar,
" against ",
xvar,
", ")
titleTxt2 <- paste0("chisq(",
df,
") = ",
round(chisqval, statDigits),
", p = ",
format.pval(pval, digits = pDigits))
titleTxt <- paste0(titleTxt1, titleTxt2)
subTitleTxt <- "Cell labels are standardised residuals"
ggplot(data = alldata,
aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)) +
geom_rect(color="black", aes_string(fill=yvar)) +
geom_text(aes(x = xcent, y = ycent, label = stdres)) +
xlab(paste0("Count of '",
xvar,
"', total = ",
max(alldata$xmax))) + # tweaked by CE
ylab(paste0("Proportion of '",
yvar,
"' per level of '",
xvar,
"'")) +
ggtitle(titleTxt,
subtitle = subTitleTxt) +
theme_bw() +
theme(plot.title = element_text(hjust = .5),
plot.subtitle = element_text(hjust = .5))
}
makeplot_mosaic2(mtcars, vs, gear)
makeplot_mosaic2(diamonds, cut, clarity)
I had the same issue for a project some time back. My solution was to use geom_bar
together with the scales="free_x", space="free_x"
option in facet_grid
to accommodate different bar widths:
# using diamonds dataset for illustration
df <- diamonds %>%
group_by(cut, clarity) %>%
summarise(count = n()) %>%
mutate(cut.count = sum(count),
prop = count/sum(count)) %>%
ungroup()
ggplot(df,
aes(x = cut, y = prop, width = cut.count, fill = clarity)) +
geom_bar(stat = "identity", position = "fill", colour = "black") +
# geom_text(aes(label = scales::percent(prop)), position = position_stack(vjust = 0.5)) + # if labels are desired
facet_grid(~cut, scales = "free_x", space = "free_x") +
scale_fill_brewer(palette = "RdYlGn") +
# theme(panel.spacing.x = unit(0, "npc")) + # if no spacing preferred between bars
theme_void()
I did it myself a time ago, using just geom_bar
, I turned it into a general function so it should work on any two factors
.
ggMMplot <- function(var1, var2){
require(ggplot2)
levVar1 <- length(levels(var1))
levVar2 <- length(levels(var2))
jointTable <- prop.table(table(var1, var2))
plotData <- as.data.frame(jointTable)
plotData$marginVar1 <- prop.table(table(var1))
plotData$var2Height <- plotData$Freq / plotData$marginVar1
plotData$var1Center <- c(0, cumsum(plotData$marginVar1)[1:levVar1 -1]) +
plotData$marginVar1 / 2
ggplot(plotData, aes(var1Center, var2Height)) +
geom_bar(stat = "identity", aes(width = marginVar1, fill = var2), col = "Black") +
geom_text(aes(label = as.character(var1), x = var1Center, y = 1.05))
}
ggMMplot(diamonds$cut, diamonds$clarity)
You may use the ggplot2 extension package called "ggmosaic" (https://github.com/haleyjeppson/ggmosaic).
Extensive tutorial with example code and visual results is given here https://cran.r-project.org/web/packages/ggmosaic/vignettes/ggmosaic.html.
Plotluck is a library based on ggplot2 that aims at automating the choice of plot type based on characteristics of 1-3 variables. It contains a function for mosaic plots. Example:
plotluck(mtcars,vs,gear)
A first attempt. I'm not sure how to put the factor labels on the axis though.
makeplot_mosaic <- function(data, x, y, ...){
xvar <- deparse(substitute(x))
yvar <- deparse(substitute(y))
mydata <- data[c(xvar, yvar)];
mytable <- table(mydata);
widths <- c(0, cumsum(apply(mytable, 1, sum)));
heights <- apply(mytable, 1, function(x){c(0, cumsum(x/sum(x)))});
alldata <- data.frame();
allnames <- data.frame();
for(i in 1:nrow(mytable)){
for(j in 1:ncol(mytable)){
alldata <- rbind(alldata, c(widths[i], widths[i+1], heights[j, i], heights[j+1, i]));
}
}
colnames(alldata) <- c("xmin", "xmax", "ymin", "ymax")
alldata[[xvar]] <- rep(dimnames(mytable)[[1]],rep(ncol(mytable), nrow(mytable)));
alldata[[yvar]] <- rep(dimnames(mytable)[[2]],nrow(mytable));
ggplot(alldata, aes(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)) +
geom_rect(color="black", aes_string(fill=yvar)) +
xlab(paste(xvar, "(count)")) + ylab(paste(yvar, "(proportion)"));
}
Example:
makeplot_mosaic(mtcars, vs, gear)