[英]plot r two categorical variables
我正在使用以下命令在R中绘制两个类别变量
性别有2个级别,收入有9个级别。
spineplot(main$Gender,main$Income, xlab="Gender", ylab="Income levels: 1 is lowest",xaxlabels=c("Male","Female"))
21%
? 添加可复制的示例
fail <- factor(c(2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1,2,2,2,2), levels = c(1, 2), labels = c("male", "female")) gender <- factor(rep(c(1:9),3)) spineplot(fail,gender)
我认为使用barplot
进行此操作可能会更容易,因为spineplot
不会返回任何有用的信息。
默认值是以下值,但您可以将条形的宽度调整为其他变量(可以看到返回了x轴坐标):
par(mfrow = 1:2)
(barplot(table(gender, fail)))
# [1] 0.7 1.9
(barplot(table(gender, fail), width = table(fail)))
# [1] 10.7 26.9
经过最后的修改,我们得到了
tbl <- table(gender, fail)
prp <- prop.table(tbl, 2L)
yat <- prp / 2 + apply(rbind(0, prp[-nrow(prp), ]), 2L, cumsum)
bp <- barplot(prp, width = table(fail), axes = FALSE, col = rainbow(nrow(prp)))
axis(2L, at = yat[, 1L], labels = levels(gender), lwd = 0)
axis(4L)
text(rep(bp, each = nrow(prp)), yat, sprintf('%0.f%%', prp * 100), col = 0)
相比于
spineplot(fail, gender, col = rainbow(nlevels(gender)))
@rawr有趣的解决方案的替代方法是:
fail <- factor(c(2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1,
1, 1, 1, 2, 1, 1, 1, 1, 1,2,2,2,2),
levels = c(1, 2), labels = c("male", "female"))
gender <- factor(rep(c(1:9),3))
mypalette <- colorRampPalette(c("lightblue","darkblue"))
tbl <- spineplot(fail, gender, xlab="Gender", ylab="Income levels: 1 is lowest",
xaxlabels=c("Male","Female"), col=mypalette(nlevels(gender)) )
print(tbl)
# Income levels: 1 is lowest
# Gender 1 2 3 4 5 6 7 8 9
# male 2 1 2 1 3 2 2 2 1
# female 1 2 1 2 0 1 1 1 2
print.perc <- function(k, tbl, ndigits=2, str.pct="%") {
# These lines of codes are the same used by from spineplot
# for the calculation of the x-position of the stacked bars
nx <- nrow(tbl)
off <- 0.02
xat <- c(0, cumsum(prop.table(margin.table(tbl, 1)) + off))
posx <- (xat[1L:nx] + xat[2L:(nx + 1L)] - off)/2
# Proportions by row (gender)
ptbl <- prop.table(tbl,1)
# Define labels as strings with a given format
lbl <- paste(format(round(100*ptbl[k,], ndigits), nsmall=ndigits), str.pct, sep="")
# Print labels
# cumsum(ptbl[k,])-ptbl[k,]/2 is the vector of y-positions
# for the centers of each stacked bar
text(posx[k], cumsum(ptbl[k,])-ptbl[k,]/2, lbl)
}
# Print income levels for males and females
strsPct <- c("%","%")
for (k in 1:nrow(tbl)) print.perc(k, tbl, ndigits=2, str.pct=strsPct[k])
希望它能对您有所帮助。
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