ggplot 相关¶
ggplot同时绘制多个密度图¶
plots <- NULL
for(i in colnames(train)){
plots[[i]] <- ggplot(train) +
geom_density(aes_string(x = i, fill = 'is_black'), alpha = 0.5, show.legend = F) +
xlab("") +
ylab("");
}
plot_grid(plotlist = plots)
ggplot绘制概率密度图¶
adapted from ggplot2绘制概率密度图
Take the Weibull distribution as an example,
f(x) = \begin{cases}
\frac k\lambda \left(\frac x\lambda\right)^{k-1}e^{-(x/\lambda)^k} & x\ge 0\\
0 & x < 0
\end{cases}
where \lambda > 0 is the scale parameter, and k > 0 is the shape parameter. And
- if k=1, it becomes to the exponential distribution
- if k=2, it becomes to the Rayleigh distribution.
d <- seq(0, 5, length.out=10000)
y <- dweibull(d, shape=5, scale=1, log = FALSE)
df <- data.frame(x=d,y)
ggplot(df, aes(x=d, y=y)) +
geom_line(col = "orange") +
ggtitle("Density of Weibull distribution")
h = rweibull(10000, shape=5, scale=1)
ggplot(NULL, aes(x=h)) +
geom_histogram(binwidth=0.01, fill="white", col="red") +
ggtitle("Histogram of Weibull distribution")
ggplot(NULL, aes(x=h)) + geom_density(col = "green")
ggplot(NULL, aes(x=h)) + geom_line(stat = "density", col = "red")
A minor difference is that here is a horizontal line in the above estimated density.
Also refer to Plotting distributions (ggplot2)
legend设置¶
默认情形¶
library(ggplot2)
bp <- ggplot(data=PlantGrowth, aes(x=group, y=weight, fill=group)) + geom_boxplot()
bp
自定义图例的顺序¶
首先移除掉默认图例,有三种方式实现:
# Remove legend for a particular aesthetic (fill)
bp + guides(fill=FALSE)
# It can also be done when specifying the scale
bp + scale_fill_discrete(guide=FALSE)
# This removes all legends
bp + theme(legend.position="none")
再改变默认顺序
bp + scale_fill_discrete(breaks=c("trt1","ctrl","trt2"))
颠倒图例的顺序¶
# These two methods are equivalent:
bp + guides(fill = guide_legend(reverse=TRUE))
bp + scale_fill_discrete(guide = guide_legend(reverse=TRUE))
# You can also modify the scale directly:
bp + scale_fill_discrete(breaks = rev(levels(PlantGrowth$group)))
隐藏图例标题¶
# Remove title for fill legend
bp + guides(fill=guide_legend(title=NULL))
# Remove title for all legends
bp + theme(legend.title=element_blank())
自定义图例的标题及名称¶
两种方式,一种 另一种修改数据集
图例的整体形状¶
# Title appearance
bp + theme(legend.title = element_text(colour="blue", size=16, face="bold"))
# Label appearance
bp + theme(legend.text = element_text(colour="blue", size = 16, face = "bold"))
图例盒子
bp + theme(legend.background = element_rect())
bp + theme(legend.background = element_rect(fill="gray90", size=.5, linetype="dotted"))
图例位置
bp + theme(legend.position="top")
# Position legend in graph, where x,y is 0,0 (bottom left) to 1,1 (top right)
bp + theme(legend.position=c(.5, .5))
# Set the "anchoring point" of the legend (bottom-left is 0,0; top-right is 1,1)
# Put bottom-left corner of legend box in bottom-left corner of graph
bp + theme(legend.justification=c(0,0), legend.position=c(0,0))
# Put bottom-right corner of legend box in bottom-right corner of graph
bp + theme(legend.justification=c(1,0), legend.position=c(1,0))
隐藏图例的slashes¶
# No outline
ggplot(data=PlantGrowth, aes(x=group, fill=group)) +
geom_bar()
# Add outline, but slashes appear in legend
ggplot(data=PlantGrowth, aes(x=group, fill=group)) +
geom_bar(colour="black")
# A hack to hide the slashes: first graph the bars with no outline and add the legend,
# then graph the bars again with outline, but with a blank legend.
ggplot(data=PlantGrowth, aes(x=group, fill=group)) +
geom_bar() +
geom_bar(colour="black", show.legend=FALSE)
Treemaps¶
源于碎片化的饼图是如何制作出来的,能否用excel或者R实现? | 知乎
目前查阅到的有参考价值的为treemap和treemapify,但似乎都只针对矩形,对于原知乎问题中的圆形碎片化尚不能实现,目前想法是阅读这两个package的源代码,看能否找到突破口。
数学公式¶
比如
expression(R[group("", list(hat(F),F),"")]^2)
参考
坐标轴标签字体大小¶
参考Size of labels for x-axis and y-axis ggplot in R
多张图片¶
par(mfrow=c(1,2))
不起作用,要用到 gridExtra
包,如
library(gridExtra)
plot1 <- qplot(1)
plot2 <- qplot(1)
grid.arrange(plot1, plot2, ncol=2)
参考Side-by-side plots with ggplot2
绘制地图¶
参考
scale_fill_manual
和 scale_color_manual
¶
更改颜色命令为
scale_fill_manual(values = c("red", "blue"))
save¶
NOT png()...dev.off()
, use
ggsave("sth.eps",device="eps", width=9)
aes_string
vs aes
¶
在重复绘图时,似乎是作用域的缘故,有时 aes
只能保留最后一个,此时需要用 aes_string
.