绘制可自定义填充图案的统计图-patternplot

饼图、环形图、柱状图和箱式图是我们论文写作和数据统计经常要绘制的统计图,常常是使用单一的颜色填充(ggplot2大家可能都用烦了吧),小编呕心沥血终于找到一个非常实用又高级的绘图R包。patternplot包不仅可以绘制美观和信息丰富的统计图,它可以用颜色或纹理或png或jpeg格式的任何外部图像填充统计图,让我们一起来看看吧!!

install.packages("patternplot") #安装包library(patternplot) #加载包library(png) #加载png包library(ggplot2) #加载ggplot2包
R包介绍
01
patternpie绘制饼图
data <- read.csv(system.file("extdata", "vegetables.csv", package="patternplot"))fix(data)
输入的数据格式和内容非常的简单,第一列是分组类别,第二列是数据占比,第三列是标签

1. 绘制黑白简约风饼图

pattern.type<-c('hdashes', 'vdashes', 'bricks')#用于填充图形的线条类型#有以下类型 'blank', 'bricks', 'vdashes', 'hdashes',#'crosshatch','dots', 'grid','hlines','nelines',#''nwlines',’vlines’,’waves’,’Rsymbol_0’ to ’Rsymbol_25’pie1<-patternpie(group=data$group,                 pct=data$pct,                 label=data$label,                 ####group,pct,label绘制饼图所用三类数据                 label.size=4,                 #标签大小                 label.color='black',                 #标签颜色                 label.distance=1.3,                 #标签到饼图边缘的距离                 pattern.type=pattern.type,                 #填充类型                 pattern.line.size=c(10, 10, 2),                 #填充线的粗细                 frame.color='black',                 #图形边缘的颜色                 frame.size=1.5,                 #图形边缘的线的粗细                 pixel=12,                 #饼图的像素分辨率                 density=c(8, 8, 10)                 #填充图案的线/点的密度                 )pie1<-pie1+ggtitle('(A) Black and White with Patterns')#ggtitle给饼图加标题

2. 绘制彩色可爱风饼图

pattern.type<-c('hdashes', 'vdashes', 'bricks')pattern.color<-c('red3','green3', 'white' )#指定填充的线条颜色background.color<-c('dodgerblue', 'lightpink', 'orange')#指定填充背景颜色pie2<-patternpie(group=data$group,                 pct=data$pct,label=data$label,                 label.distance=1.3,                 pattern.type=pattern.type,                 pattern.color=pattern.color,                 background.color=background.color,                 pattern.line.size=c(10, 10, 2),                 frame.color='grey40',                 frame.size=1.5,                 pixel=12,                 density=c(8, 8, 10))pie2<-pie2+ggtitle('(B) Colors with Patterns')

3. imagepie绘制指定填充图案的饼图

Tomatoes <- readJPEG(system.file("img", "tomatoes.jpg", package="patternplot"))Peas <- readJPEG(system.file("img", "peas.jpg", package="patternplot"))Potatoes <-  readJPEG(system.file("img", "potatoes.jpg", package="patternplot"))#导入指定填充图片,这里你就可以用自己喜欢的图啦data <- read.csv(system.file("extdata", "vegetables.csv", package="patternplot"))pattern.type<-list(Tomatoes,Peas,Potatoes)#指定填充图片imagepie(group=data$group,pct=data$pct,label=data$label,         pattern.type=pattern.type,         label.distance=1.3,         frame.color='burlywood4',         frame.size=0.8,         label.size=6,         label.color='forestgreen')+   ggtitle('Pie Chart with Images')
02
环形图

1. patternring1绘制彩色环形图

group1<-c('New_England', 'Great_Lakes','Plains',          'Rocky_Mountain', 'Far_West','Southwest',          'Southeast',  'Mideast')#分组信息pct1<-c( 12, 11, 17, 15, 8, 11,  16,  10)#占比信息label1<-paste(group1, " n ", pct1, "%", sep="")#标签信息pattern.type1<-c("hdashes", "blank", "grid",                 "blank", "hlines", "blank",                 "waves", "blank")#环中填充形状pattern.type.inner<-"blank"#内圆填充线/点的形式pattern.color1<-rep("white", 8)#环内线/点的填充颜色,8组background.color1<-c("darkgreen", "darkcyan", "chocolate",                     "cadetblue1", "darkorchid", "yellowgreen",                     "hotpink", "lightslateblue")#环内填充颜色density1<-rep(11.5, length(group1))#环内填充颜色pattern.line.size1=c(10, 1, 6, 1, 10, 1, 6, 1)#环内填充线/点的粗细/大小g<-patternring1(group1, pct1, label1,                label.size1=4,label.color1='black',                label.distance1=1.36, pattern.type1,                #label.size1标签大小,label.distance1标签到图形距离                pattern.color1, pattern.line.size1,                background.color1,                frame.color='black',                frame.size=1.2,                density1,  pixel=13,                #pixel,环的像素分辨率                pattern.type.inner="blank",                #内圆填充线/点的形式                pattern.color.inner="white",                #内圆填充线/点颜色                pattern.line.size.inner=1,                  #内圆填充线/点的粗细/大小                background.color.inner="white",                #内圆填充背景颜色                pixel.inner=10,                #内圆像素分辨率                density.inner=1,                #内圆填充线/点d额分布密度                r1=2.7, r2=4                #r1是内圆半径,r2是外环半径                )g<-g+annotate(geom="text", x=0, y=0,              label="2019 Number of Cases n N=1000",              color="black", size=4)+  scale_x_continuous(limits=c(-7, 7))+  scale_y_continuous(limits=c(-7, 7))#在圆心展示标题,设置标题展示空间g

2. imagering1含有内嵌图形的环形图

location<-gsub('\','/',tempdir(), fixed=T)###定义一个计算机的文件夹位置pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="darkgreen", pixel=8, res=8)#pattern是指生成png格式的模式,运行结束后会在location下生成定义好的blank.png图片#以上是对圆环中的一部分进行定义#type是填充线条/点的类型,density是填充密度,color是线条/点d的颜色#pattern.line.size是填充线/点的粗细/大小,background.color背景颜色#pixel是分辨率, res=是分辨率FarWest<-readPNG(paste(location,'/',"blank",".png", sep=''))#读取location下的blank.png图片以填充图形,该图的颜色为上面语句定义好的背景色pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="darkcyan", pixel=8, res=8)GreatLakes<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="chocolate", pixel=8, res=8)Mideast<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="cadetblue1", pixel=8, res=8)NewEngland<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="darkorchid", pixel=8, res=8)Plains<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="yellowgreen", pixel=8, res=8)RockyMountain<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="hotpink", pixel=8, res=8)Southeast<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white',        pattern.line.size=1, background.color="lightslateblue", pixel=8, res=8)Southwest <-readPNG(paste(location,'/',"blank",".png", sep=''))####以上语句是在location创建所需颜色的图片,调用该图片以填充环内各成分(8个)
 group1<-c('New_England', 'Great_Lakes','Plains',          'Rocky_Mountain', 'Far_West','Southwest',          'Southeast',  'Mideast')pct1<-c( 12, 11, 17, 15, 8, 11,  16,  10)label1<-paste(group1, " n ", pct1, "%", sep="")pattern.type1<-list(NewEngland, GreatLakes,Plains,                    RockyMountain, FarWest,Southwest,                    Southeast,  Mideast)#环中填充的图形(这里用的是上面定义好的)pattern.type.inner<-readPNG(system.file("img", "USmap.png",                                        package="patternplot"))#内环的填充图片g<-imagering1(group1, pct1, pattern.type1,              pattern.type.inner, frame.color='black',              frame.size=1.5, r1=3, r2=4,              label1, label.size1=4,              label.color1='black', label.distance1=1.3              )
#绘制环形图g<-g+annotate(geom="text", x=0, y=-2,              label="2019 Number of Cases n N=1000",              color="black", size=4)+  scale_x_continuous(limits=c(-6, 6))+  scale_y_continuous(limits=c(-6, 6))#指定内圆标题g

3. patternrings2绘制多环图和多环饼图

#设定所需数值:group1<-c("Wind", "Hydro", "Solar", "Coal", "Natural Gas", "Oil")pct1<-c(12, 15, 8, 22, 18, 25)label1<-paste(group1, " n ", pct1 , "%", sep="")#定义第一环绘图数据(内环)group2<-c("Renewable", "Non-Renewable")pct2<-c(35, 65)label2<-paste(group2, " n ", pct2 , "%", sep="")#定义第二环绘图数据(外环)pattern.type1<-rep(c( "blank"), times=6)#第一环的线/点填充类型pattern.type2<-c('grid', 'blank')#第二环的线/点填充类型pattern.type.inner<-"blank"#内圆填充pattern.color1<-rep('white', length(group1))#第一环线/点的填充颜色pattern.color2<-rep('white', length(group2))#第二环线/点的填充颜色background.color1<-c("darkolivegreen1", "white", "indianred",                     "gray81",  "white", "sandybrown" )#第一环背景填充颜色background.color2<-c("seagreen", "deepskyblue")#第二环背景填充颜色density1<-rep(10, length(group1))#第一环线/点的填充密度density2<-rep(10, length(group2))#第二环线/点的填充密度pattern.line.size1=rep(5, length(group1))#第一环线/点的粗细/大小pattern.line.size2=rep(2, length(group2))##第二环线/点的粗细/大小pattern.line.size.inner=1#内圆填充的线/点的粗细/大小

(1)绘制多环图

g<-patternrings2(group1, group2, pct1,pct2,                 label1, label2, label.size1=3,                 label.size2=3.5, label.color1='black',                 label.color2='black', label.distance1=0.75,                 label.distance2=1.4, pattern.type1,                 pattern.type2,  pattern.color1,pattern.color2,                 pattern.line.size1, pattern.line.size2,                 background.color1, background.color2,                 density1=rep(10, length(group1)),                 density2=rep(15, length(group2)),                 pixel=10, pattern.type.inner,                 pattern.color.inner="black",pattern.line.size.inner,                   background.color.inner="white",                   pixel.inner=6,  density.inner=5,                 frame.color='black',frame.size=1.5,                 r1=2.45, r2=4.25, r3=5                 #从内到外的三圆半径                 )g1<-g+annotate(geom="text", x=0, y=0,               label="Earth's Energy",color="black", size=5)+  scale_x_continuous(limits=c(-6, 6))+  scale_y_continuous(limits=c(-6, 6))+  ggtitle("(A) Two Rings")g1

(2)绘制外环饼图

g<-patternrings2(group1, group2, pct1,pct2,                 label1, label2, label.size1=3,                 label.size2=3.5, label.color1='black',                 label.color2='black', label.distance1=0.7,                 label.distance2=1.4, pattern.type1,                 pattern.type2,  pattern.color1,pattern.color2,                 pattern.line.size1, pattern.line.size2,                 background.color1, background.color2,                 density1=rep(10, length(group1)), density2=rep(15, length(group2)),                 pixel=10, pattern.type.inner, pattern.color.inner="black",                 pattern.line.size.inner,  background.color.inner="white",                   pixel.inner=2,  density.inner=5,                 frame.color='black',frame.size=1.5,                 r1=0.005, r2=4, r3=4.75)g2<-g+scale_x_continuous(limits=c(-6, 6))+  scale_y_continuous(limits=c(-6, 6))+  ggtitle("(B) Pie in a Ring")g2

(3)自定义填充图形

#下面是定义第一环的数据、填充图形以及参数group1<-c("Wind", "Hydro", "Solar", "Coal", "Natural Gas", "Oil")pct1<-c(12, 15, 8, 22, 18, 25)label1<-paste(group1, " n ", pct1 , "%", sep="")location<-gsub('\','/',tempdir(), fixed=T)pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="darkolivegreen1",  pixel=20, res=15)Wind<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="white", pixel=20, res=15)Hydro<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="indianred",  pixel=20, res=15)Solar<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="gray81",  pixel=20, res=15)Coal<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="white",  pixel=20, res=15)NaturalGas<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="sandybrown",  pixel=20, res=15)Oil<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern.type1<-list(Wind, Hydro, Solar, Coal, NaturalGas, Oil)
#下面是定义第二环的数据、填充图形以及参数group2<-c("Renewable", "Non-Renewable")pct2<-c(35, 65)label2<-paste(group2, " n ", pct2 , "%", sep="")pattern(type="grid", density=12, color='white', pattern.line.size=5, background.color="seagreen", pixel=20, res=15)Renewable<-readPNG(paste(location,'/',"grid",".png", sep=''))pattern(type="blank", density=1, color='white', pattern.line.size=1, background.color="deepskyblue",  pixel=20, res=15)NonRenewable<-readPNG(paste(location,'/',"blank",".png", sep=''))pattern.type2<-list(Renewable, NonRenewable)
####下面是定义内圆的图形pattern.type.inner<-readPNG(system.file("img", "earth.png", package="patternplot"))
####下面绘图g<-imagerings2(group1, group2,pct1,pct2, label1, label2, label.size1=3,               label.size2=3.5, label.color1='black', label.color2='black',               label.distance1=0.7, label.distance2=1.3, pattern.type1, pattern.type2,               pattern.type.inner, frame.color='skyblue',frame.size=1.5, r1=2.2, r2=4.2, r3=5)g<-g+scale_x_continuous(limits=c(-7, 7))+scale_y_continuous(limits=c(-7, 7))g

 

 

03
patternbar条形图
data <- read.csv(system.file("extdata", "monthlyexp.csv", package="patternplot"))#读入绘图数据fix(data)

 

1. 黑白简约

(1)竖直的条形图

data<-data[which(data$Location=='City 1'),]#提取City 1有关的数据x<-factor(data$Type, c('Housing', 'Food',  'Childcare'))#分组标签y<-data$Amount#绘图所用数值pattern.type<-c('hdashes', 'blank', 'crosshatch')#分别填充的线/点类型pattern.color=c('black','black', 'black')#分别填充的线/点颜色background.color=c('white','white', 'white')#分别填充的背景density<-c(20, 20, 10)##分别填充的线/点密度barp1<-patternbar(data,x, y,group=NULL,ylab='Monthly Expenses, Dollars',                  #ylab是y轴标题                  pattern.type=pattern.type, hjust=0.5,                  #hjust从每个条的顶部边框到标签的水平距离                  pattern.color=pattern.color,                  background.color=background.color,                  pattern.line.size=c(5.5, 1, 4),                  frame.color=c('black', 'black', 'black'),                  density=density)+  scale_y_continuous(limits = c(0, 2800))+  ggtitle('(A) Black and White with Patterns')barp1

(2)水平条形图

p2<-patternbar(data,x, y,group=NULL,ylab='Monthly Expenses, Dollars',                  pattern.type=pattern.type,                  pattern.color=pattern.color,                  background.color=background.color,                  pattern.line.size=c(5.5, 1, 4),                  vjust=0.5, hjust=-0.25, bar.width=0.5,                  frame.color=c('black', 'black', 'black'),                  density=density)+  scale_y_continuous(limits = c(0, 2800))+  ggtitle('(A) Black and White with Patterns')+coord_flip()#coord_flip()翻转坐标轴p2

(3)逆转条形图

p3<-patternbar(data,x, y,group=NULL,ylab='Monthly Expenses, Dollars',               pattern.type=pattern.type,               pattern.color=pattern.color,               background.color=background.color,               pattern.line.size=c(5.5, 1, 4),               vjust=2, hjust=0.5, bar.width=0.75,               frame.color=c('black', 'black', 'black'),               density=density)+  ggtitle('(C) Reverse Bar Chart')+  scale_y_reverse(limits = c(2800,0))p3

2. 彩色填充

pattern.color=c('black','white', 'grey20')background.color=c('darkolivegreen1','lightgreen', 'chocolate')#填充颜色barp2<-patternbar(data,x, y,group=NULL,ylab='Monthly Expenses, Dollars',                  pattern.type=pattern.type,hjust=0.5,                  pattern.color=pattern.color, background.color=background.color,                  pattern.line.size=c(5.5, 1, 4),                  frame.color=c('black', 'black', 'black'), density=density)+  scale_y_continuous(limits = c(0, 2800))+ggtitle('(B) Colors with Patterns')barp2

3. 多组展示

data <- read.csv(system.file("extdata", "monthlyexp.csv", package="patternplot"))x<-factor(data$Location, c('City 1', ' City 2'))group<-factor(data$Type, c('Housing', 'Food',  'Childcare'))#在用x因子分组之后,再用group分组y<-data$Amountpattern.type<-c('Rsymbol_16', 'blank','hdashes')pattern.color=c('yellow', 'chartreuse4',  'pink')background.color=c('grey', 'chartreuse3',  'bisque')barp3<-patternbar(data,x, y,group,ylab='Monthly Expenses, Dollars',                  pattern.type=pattern.type,                  pattern.color=pattern.color,                  background.color=background.color,                  pattern.line.size=c(6, 10,6),                  frame.size=1,frame.color='black',pixel=16,                  density=c(18, 10, 14), legend.type='h',                  #legend.type='h',图例的布局是水平的,如果legend.type=’v’图例的布局是垂直的                  legend.h=12, legend.y.pos=0.49,                  #legend.h图例boxes的高度                  #legend.y.pos 改变y轴上图例位置                  vjust=-1, hjust=0.5,legend.pixel=6,                  #legend.pixel图例的分辨率                  legend.w=0.275,legend.x.pos=1.1                  #legend.w图例boxes的宽度                  #legend.y.pos 改变x轴上图例位置                  ) +  scale_y_continuous(limits = c(0, 3100))+  ggtitle(' Bar Chart with Two Grouping Variables')barp3

4. patternbar_s堆积条形图

x<-data$Locationy<-data$Amountgroup<-data$Type#patternbar_s绘制堆叠条形图patternbar_s(data,x, y, group,xlab='', ylab='Monthly Expenses, Dollar',             label.size=3,pattern.type=c('Rsymbol_16', 'blank','hdashes'),             pattern.line.size=c(5, 10, 10),frame.size=1,             pattern.color=c('yellow','chartreuse4','pink'),             background.color=c('grey','chartreuse3','bisque'),             pixel=16, density=c(18, 10, 10),frame.color='black',             legend.type='h',             legend.h=12, legend.y.pos=0.49,             legend.pixel=6, legend.w=0.275, legend.x.pos=1.05,             bar.width=0.8             #bar.width条形宽度             )+  scale_y_continuous(limits = c(0, 6800))+  ggtitle('Stacked Bar Chart')

5. imagebar自定义填充图片

(1)条形图

library(jpeg)childcare<-readJPEG(system.file("img", "childcare.jpg", package="patternplot"))food<-readJPEG(system.file("img", "food.jpg", package="patternplot"))housing <-readJPEG(system.file("img", "housing.jpg", package="patternplot"))#导入图片data <- read.csv(system.file("extdata", "monthlyexp.csv", package="patternplot"))data<-data[which(data$Location=='City 1'),]x<-factor(data$Type, c('Housing', 'Food',  'Childcare'))y<-data$Amountpattern.type<-list(housing, food, childcare)imagebar(data,x, y,group=NULL,pattern.type=pattern.type,        vjust=-1, hjust=0.5,         #vjust从每个条的顶部边框到标签的垂直距离         #hjust从每个条的顶部边框到标签的水平距离         frame.color='black',         ylab='Monthly Expenses, Dollars')+  ggtitle('Bar Chart with Images')

2多组条形图

data <- read.csv(system.file("extdata", "monthlyexp.csv", package="patternplot"))group<-factor(data$Type, c('Housing', 'Food',  'Childcare'))y<-data$Amountx<-factor(data$Location, c('City 1', ' City 2'))pattern.type<-list(housing, food, childcare)imagebar(data,x, y,group,pattern.type=pattern.type,         vjust=-1, hjust=0.5,         frame.color='black',         ylab='Monthly Expenses, Dollars')+  ggtitle('Image Bar Chart with Two Grouping Variables')

3堆叠条形图

data <- read.csv(system.file("extdata", "monthlyexp.csv", package="patternplot"))x<-data$Locationy<-data$Amountgroup<-data$Typepattern.type<-list(childcare, food, housing)imagebar_s(data,x, y, group, xlab='', ylab='Monthly Expenses, Dollar',             pattern.type=pattern.type, label.size=3.5, frame.size=1.25,           frame.color='black',legend.type='h', legend.h=6,           legend.y.pos=0.49, legend.pixel=20, legend.w=0.2,legend.x.pos=1.1)+  scale_y_continuous(limits = c(0, 6800))+  ggtitle('Stacked Bar Chart with Images')
04
patternboxplot箱式图
data <- read.csv(system.file("extdata", "fruits.csv", package="patternplot"))fix(data)

 

1. 黑白简洁箱式图

y<-data$Weightx<-data$Store #先根据Store分组group<-data$Fruit  #再根据Fruit分组pattern.type<-c('nwlines', 'blank', 'waves')pattern.color=c('black','black', 'black')background.color=c('white','gray80', 'white')frame.color=c('black', 'black', 'black')pattern.line.size<-c(6, 1,6)density<-c(6, 1, 8)box1<-patternboxplot(data,x, y,group,pattern.type=pattern.type,                     pattern.line.size=pattern.line.size, label.size=3,                     pattern.color=pattern.color,                     background.color=background.color,                     frame.color=frame.color,                     density=density,  legend.h=2, legend.x.pos=1.075,                     legend.y.pos=0.499, legend.pixel=10, legend.w=0.18)+  ggtitle('(A) Boxplot with Black and White Patterns')box1

2. 彩色箱式图

pattern.color=c('black','white', 'grey20')background.color=c('gold','lightpink', 'lightgreen')box2<-patternboxplot(data,x, y,group=group,pattern.type=pattern.type,pattern.line.size=pattern.line.size, label.size=3,               pattern.color=pattern.color, background.color=background.color,               frame.color=frame.color, density=density,  legend.h=2, legend.x.pos=1.075, legend.y.pos=0.499, legend.pixel=10, legend.w=0.18)+ggtitle('(B) Boxplot with Colors and Patterns')

3. imageboxplot自定义图片填充

(1)

Orange<-readJPEG(system.file("img", "oranges.jpg", package="patternplot"))Strawberry <-readJPEG(system.file("img", "strawberries.jpg", package="patternplot"))Watermelon<-readJPEG(system.file("img", "watermelons.jpg", package="patternplot"))data <- read.csv(system.file("extdata", "fruits.csv", package="patternplot"))x<-data$Fruity<-data$Weightgroup<-data$Storepattern.type<-list(Orange, Strawberry, Watermelon)box1<-imageboxplot(data,x, y,group=NULL,pattern.type=pattern.type,                   frame.color=c('orange', 'darkred', 'darkgreen'),                   ylab='Weight, Pounds')+  ggtitle('(A) Image Boxplot with One Grouping Variable')box1

(2)

x<-data$Storey<-data$Weightgroup<-data$Fruitpattern.type<-list(Orange, Strawberry, Watermelon)box2<-imageboxplot(data,x, y,group=group, pattern.type=pattern.type,                   frame.color=c('orange', 'darkred', 'darkgreen'),                   linetype=c('solid', 'dashed', 'dotted'),                   frame.size=0.8, xlab='', ylab='Weights, pounds',                   legend.h=2, legend.x.pos=1.1, legend.y.pos=0.499,                   legend.w=0.2)+  ggtitle('(B) Image Boxplot with Two Grouping Variables')box2

小编总结
虽然代码好像很多,但其实都是简单易懂的,在使用的时候修改参数即可,小编就非常喜欢里面的各种线和波点图案,看起来蛮可爱的,如果你想绘制与众不同 的统计图,就来试试这个R包吧!
统计与绘图

ggsci配色R包

2020-8-28 4:15:34

统计与绘图

图形添加文本-ggfittext

2020-8-28 4:22:50

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