生成绘图数据

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), 
                   rating = c(rnorm(200),rnorm(200, mean=.8)))
# View first few rows
head(dat)

直方图和概率密度图

## Basic histogram from the vector "rating". Each bin is .5 wide.
## These both result in the same output:
ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5) # rating作为横轴

image.png

# 
ggplot(dat, aes(x=rating)) +
    geom_histogram(binwidth=.5, 
    colour="black", # 边框颜色 
    fill="white" #填充颜色
 )

image.png

ggplot(dat, aes(x=rating)) + geom_density() # 添加密度曲线

image.png

# Histogram overlaid with kernel density curve
ggplot(dat, aes(x=rating)) + 
    geom_histogram(aes(y=..density..),      # 这一步很重要,使用density代替y轴
                   binwidth=.5,
                   colour="black", fill="white") +
    geom_density(alpha=.2, fill="#FF6666")  # 重叠部分采用透明设置

image.png

添加一条均值线(红色部分)

ggplot(dat, aes(x=rating)) +
    geom_histogram(binwidth=.5, colour="black", fill="white") +
    geom_vline(aes(xintercept=mean(rating, na.rm=T)),   # Ignore NA values for mean
               color="red", linetype="dashed", size=1)

image.png

多组数据的直方图和密度图

# cond作为各组的分类,以颜色填充作为区别
# position的处理很重要,决定数据存在重叠是的处理方式 "identity" 不做处理,但是设置了透明
ggplot(dat, aes(x=rating, fill=cond)) +
    geom_histogram(binwidth=.5, alpha=.5, position="identity")

image.png

# Interleaved histograms
ggplot(dat, aes(x=rating, fill=cond)) +
    geom_histogram(binwidth=.5, position="dodge")

image.png

# dodge 表示重叠部分进行偏离
 
# 密度图
ggplot(dat, aes(x=rating, colour=cond)) + geom_density()

image.png

# 半透明的填充
ggplot(dat, aes(x=rating, fill=cond)) + geom_density(alpha=.3)

image.png

# Find the mean of each group
library(plyr)
# 以 cond 作为分组, 计算每组的rating的均值
cdat <- ddply(dat, "cond", summarise, rating.mean=mean(rating))
cdat

# 绘制两组数据的均值
ggplot(dat, aes(x=rating, fill=cond)) +
    geom_histogram(binwidth=.5, alpha=.5, position="identity") +
    geom_vline(data=cdat, aes(xintercept=rating.mean,  colour=cond),
               linetype="dashed", size=1)

image.png

密度图

ggplot(dat, aes(x=rating, colour=cond)) +
geom_density() +
geom_vline(data=cdat, aes(xintercept=rating.mean, colour=cond),
linetype="dashed", size=1)

image.png

使用分面

# 按照 cond 进行分面处理, 上图为A,下图为B
ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") + 
    facet_grid(cond ~ .)

image.png

# 添加均值线
ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") + 
    facet_grid(cond ~ .) +
    geom_vline(data=cdat, aes(xintercept=rating.mean),
               linetype="dashed", size=1, colour="red")

image.png