当x和y都是分类变量时,Marimekko / Mosaic图是一个很好的默认图。使用ggplot创建这些内容的最佳方法是什么?
我能找到的唯一参考是这个4yo blog post,但这似乎有点过时了。现在是否有更好或更简单的实施方法可供选择? GGally包有一个函数ggally_ratio
,但这会产生一些完全不同的东西:
答案 0 :(得分:24)
我是前一段时间做过的,只使用geom_bar
,我把它变成了一个通用函数,所以它应该适用于任何两个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)
答案 1 :(得分:13)
一段时间后,我对一个项目有同样的问题。我的解决方案是将geom_bar
与scales="free_x", space="free_x"
中的facet_grid
选项一起使用,以适应不同的条形宽度:
# 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()
答案 2 :(得分:10)
第一次尝试。我不知道如何将因子标签放在轴上。
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)"));
}
示例:
makeplot_mosaic(mtcars, vs, gear)
答案 3 :(得分:4)
你可以使用名为&#34; ggmosaic&#34;的ggplot2扩展包。 (https://github.com/haleyjeppson/ggmosaic)。
这里给出了带有示例代码和可视化结果的详尽教程https://cran.r-project.org/web/packages/ggmosaic/vignettes/ggmosaic.html。
答案 4 :(得分:3)
Plotluck是一个基于 ggplot2 的库,旨在根据1-3个变量的特征自动选择绘图类型。它包含马赛克图的功能。例:
plotluck(mtcars,vs,gear)
答案 5 :(得分:1)
根据user2030503的建议,以下是使用ggmosaic
的版本。 (请注意,ggplot 3.0 broke some piece of ggmosaic是最新版本。)
library(tidyverse)
library(ggmosaic)
# Data copied from linked blog post
df <- data.frame(
segment = LETTERS[1:4],
segpct = c(40, 30, 20, 10),
Alpha = c(60, 40, 30, 25),
Beta = c(25, 30, 30, 25),
Gamma = c(10, 20, 20, 25),
Delta = c(5, 10, 20, 25)
)
# Convert to "long" for plotting
df_long <- gather(df, key = "greek_letter", value = "pct",
-c("segment", "segpct")) %>%
mutate(
greek_letter = factor(
greek_letter,
levels = c("Alpha", "Beta", "Gamma", "Delta")
),
weight = (segpct * pct) / 10000
)
# Plot
ggplot(df_long) +
geom_mosaic(aes(x = product(greek_letter, segment), fill = greek_letter,
weight = weight))
答案 6 :(得分:1)
感谢所有创建此条目的人,这些条目确实对我有所帮助,因为ggmosaic不能满足我的要求(并且无法正确标记轴)。 Z.Lin的好函数在https://github.com/tidyverse/ggplot2/issues/3142中引发了警告类型的解释,该警告似乎表示警告在内容上在技术上是不真实的,实际上是在警告我们,ggplotocracy祝福他们并感谢他们,感觉到geom_bar不应真正具有可变的宽度。我想我明白了这一点,所以我选择了杰克·费舍尔(Jake Fisher)的功能,并根据自己的需要进行了调整。如果它对其他人有用,那就在这里:
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)