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社区首页 >专栏 >R语言之可视化(34)Grouped, stacked and percent stacked barplot

R语言之可视化(34)Grouped, stacked and percent stacked barplot

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用户1359560
发布2021-01-26 14:47:10
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发布2021-01-26 14:47:10
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文章被收录于专栏:生信小驿站生信小驿站
 # library
library(ggplot2)

# create a dataset
specie <- c(rep("sorgho" , 3) , rep("poacee" , 3) , rep("banana" , 3) , rep("triticum" , 3) )
condition <- rep(c("normal" , "stress" , "Nitrogen") , 4)
value <- abs(rnorm(12 , 0 , 15))
data <- data.frame(specie,condition,value)

# Grouped
ggplot(data, aes(fill=condition, y=value, x=specie)) + 
    geom_bar(position="dodge", stat="identity")
 # library
library(ggplot2)

# create a dataset
specie <- c(rep("sorgho" , 3) , rep("poacee" , 3) , rep("banana" , 3) , rep("triticum" , 3) )
condition <- rep(c("normal" , "stress" , "Nitrogen") , 4)
value <- abs(rnorm(12 , 0 , 15))
data <- data.frame(specie,condition,value)

# Stacked
ggplot(data, aes(fill=condition, y=value, x=specie)) + 
    geom_bar(position="stack", stat="identity")
 # library
library(ggplot2)

# create a dataset
specie <- c(rep("sorgho" , 3) , rep("poacee" , 3) , rep("banana" , 3) , rep("triticum" , 3) )
condition <- rep(c("normal" , "stress" , "Nitrogen") , 4)
value <- abs(rnorm(12 , 0 , 15))
data <- data.frame(specie,condition,value)

# Stacked + percent
ggplot(data, aes(fill=condition, y=value, x=specie)) + 
    geom_bar(position="fill", stat="identity")
 # library  library(ggplot2)  
library(viridis) 
 library(hrbrthemes)  
# create a dataset  
specie <-  c(rep("sorgho" , 3) , rep("poacee" , 3) , rep("banana" , 3) , rep("triticum" , 3) ) 
 condition <-  rep(c("normal" , "stress" , "Nitrogen") , 4) 
 value <-  abs(rnorm(12 , 0 , 15)) 
 data <-  data.frame(specie,condition,value)  
# Small multiple
  ggplot(data, aes(fill=condition, y=value, x=specie)) + geom_bar(position="stack", stat="identity") +  scale_fill_viridis(discrete = T) +  ggtitle("Studying 4 species..") +  theme_ipsum() +  xlab("")
# library
library(ggplot2)
library(viridis)
library(hrbrthemes)

# create a dataset
specie <- c(rep("sorgho" , 3) , rep("poacee" , 3) , rep("banana" , 3) , rep("triticum" , 3) )
condition <- rep(c("normal" , "stress" , "Nitrogen") , 4)
value <- abs(rnorm(12 , 0 , 15))
data <- data.frame(specie,condition,value)

# Graph
ggplot(data, aes(fill=condition, y=value, x=condition)) + 
    geom_bar(position="dodge", stat="identity") +
    scale_fill_viridis(discrete = T, option = "E") +
    ggtitle("Studying 4 species..") +
    facet_wrap(~specie) +
    theme_ipsum() +
    theme(legend.position="none") +
    xlab("")
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