dotsize=1, stackgroups = FALSE, origin = NULL, right =TRUE, width=0.9, drop = FALSE, na.rm = FALSE, show.legend =NA, inherit.aes= TRUE) 常用的参数注释: mapping:使用aes()来设置点图美学特征,参数x是因子,参数y是数值 data:数据框对象 position:位置调整(Position adjustment),默认值是identity...
ggplot(mtcars, aes(x=wt, y=mpg, group=cyl)) + geom_point(aes(shape=cyl, color=cyl, size=cyl))+ scale_shape_manual(values=c(3, 16, 17))+ scale_color_manual(values=c('#999999','#E69F00', '#56B4E9'))+ scale_size_manual(values=c(1.5,2,3))+ theme(legend.position...
可以使用labs() 和 scale functions (fill, color, size, shape, . . . ) 来改变legend p +labs(title="Plot of length \n by dose", x ="Dose (mg)", y = "Teeth length")+labs(fill = "Dose (mg)")
p+ guides(color = guide_legend(order=1),size=guide_legend(order=2),shape=guide_legend(order=3)) 取消一些legend的展示 p+guides(color =FALSE, size =FALSE) 如果是连续性变量,则使用guide_colourbar(order=)来调整顺序 也可以用其他方式去除相应的legend p + scale_shape(guide=FALSE)p + scale_siz...
dotsize = 1, stackgroups = FALSE, origin = NULL, right = TRUE, width = 0.9, drop = FALSE, na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) 1. 2. 3. 4. 5. 6. 常用的参数注释: mapping:使用aes()来设置点图美学特征,参数x是因子,参数y是数值 ...
(color = "red", size = 16), line =element_line(color = "blue"), rect = element_rect(fill = "white"))) p +theme(panel.background = element_rect(fill = "transparent", color = "gray"), legend.key= element_rect(fill = "transparent", color = "transparent"), axis.text =element...
outlier.size=4) 1. 2. 3. 4. 5. 6. 2.3 带点箱线图 #初始箱线图 p <- ggplot(ToothGrowth, aes(x=dose, y=len)) + geom_boxplot() #显示每个值 p + geom_dotplot(binaxis='y', stackdir='center', dotsize=1) 1. 2. 3. ...
首先在legend中也是同样的处理,只不过根据此legend映射的美学不同而选择不同scale函数:如scale_color、scale_fill、scale_size等等。而对于过长的字符串,可以考虑手动截断,比如: 代码语言:javascript 复制 iris%>%mutate(Species=fct_recode(Species,setosasetosasetosasetosasetosa="setosa"))%>%ggplot(aes(x=Sepal....
qplot(sex, weight, data = wdata, geom = "dotplot", stackdir="center", binaxis="y", dotsize=0.5, color=sex) 直方图、密度图 直方图 qplot(weight, data = wdata, geom = "histogram", fill=sex) 密度图 qplot(weight, data = wdata, geom = "density", color=sex, linetype=sex)...
p <- ggplot(df) + geom_segment(aes(x=1, xend=2, y=`1952`, yend=`1957`, col=class), size=.75, show.legend=F) + geom_vline(xintercept=1, linetype="dashed", size=.1) + geom_vline(xintercept=2, linetype="dashed", size=.1) + ...