2、直方图 #Histogramplotwithmeanlinesandmarginalrug#:::::::::::::::::::::::::::::::::::::::::::::::::::#Changeoutlineandfillcolorsbygroups("sex")#Usecustomcolorpalettegghistogram(wdata,x="weight",add="mean",rug=T
ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") + facet_grid(cond ~ .) 3.14、分面多组数据直方图添加均值线 # With mean lines, using cdat from above ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") ...
ggplot(birthwt,aes(x=bwt,fill=smoke))+ geom_histogram(position = 'identity',alpha=0.4) #3.2.2 使用分面 #各声部歌手身高的分布,根据voice.part因子水平进行颜色填充 p414 #str(singer) data(singer,package='lattice') ggplot(singer,aes(x=height,fill=voice.part))+ geom_histogram()+ facet_wrap(...
ggdensity(df,x="weight",add = "mean",rug = TRUE,color = "sex",fill = "sex",palette= c("#00AFBB", "#E7B800")) 柱状图 } 1 gghistogram(df,x="weight",add = "mean",rug = TRUE,color = "sex",fill = "sex",palette ...
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 meancolor="red",linetype="dashed",size=1) Histogram and density plots with multiple groups ...
histograms with geom_vline means library(plotly) library(plyr) cdat <- ddply(dat, "cond", summarise, rating.mean=mean(rating)) # With mean lines p <- ggplot(dat, aes(x=rating)) + geom_histogram(binwidth=.5, colour="black", fill="white") + facet_grid(cond ~ .) + geom_vline...
# Basic histogram with mean lineggplot(iris, aes(Sepal.Length)) + geom_histogram(bins =20, fill ="white", color ="black") + geom_vline(aes(xintercept = mean(Sepal.Length)), linetype =2)# Add density curvesggplot(iris, aes(Sepal.Length, stat(density))) + ...
main = "Colored histogram with 12 bins") x <- mtcars$mpg xfit <- seq(min(x),max(x),length=40) xfit #生成正太密度曲线 yfit <- dnorm(xfit,mean = mean(x),sd = sd(x)) #对概率密度值进行修正让他可以匹配直方图 #hist()中的mids为每个分组的中心点,diff是为了获得相邻两项的差 ...
# alpha is the transparency of the overlaid color ggplot2.histogram(data=weight, xName='weight', groupName='sex', legendPosition="top", alpha=0.5 ) # Histogram plots with mean lines ggplot2.histogram(data=weight, xName='weight', groupName='sex', legendPosition="top", alpha=0.5, add...
当使用点密度分箱(bin)方式时,分箱的位置是由数据和binwidth决定的,会根据数据进行变化,但不会大于binwidth指定的宽度;当使用直方点分箱方式时,分箱有固定的位置和固定的宽度,就像由点构成的直方图(histogram)。 bin是分箱的意思,在统计学中,数据分箱是一种把多个连续值分割成多个区间的方法,每一个小区间叫做...