生物信息学习生信可视化

Barplot 作图代码

2017-11-14  本文已影响23人  正踪大米饭儿
image.png

ggplot2 barplot 分面图代码如下:

library(ggplot2)
Data <- read.table("data.txt",header = TRUE)
Data <- as.data.frame(Data)
attach(Data)
Data$Time <- factor(Time,order=TRUE,levels=c("Early","Mid","Late")) 

## Temperature
 p<-ggplot(data=Data, aes(x=Month, y=Temperature,fill = Time)) + 
  geom_bar(stat="identity", position = position_dodge(width = 0.6),width = 0.5) +
  geom_text(aes(label=Temperature), position = position_dodge(width=0.6), vjust=-0.3) + 
  facet_grid(Year ~ .) + scale_y_continuous(limits = c(0,max(Temperature)))

p <- p + ggtitle(label = "Temperature changes") + theme_light()

数据源(data.txt):

Year    Month   Time    Temperature Rainfall    Light
2017    6   Early   23.6    19.9    66.1 
2017    6   Mid 26.9    22.7    89.2 
2017    6   Late    26.8    21.2    85.5 
2017    7   Early   29.7    4.1     82.7 
2017    7   Mid 29.2    73.1    72.0 
2017    7   Late    25.8    28.3    32.6 
2017    8   Early   28.8    7.3     88.9 
2017    8   Mid 26.9    7.7     64.2 
2017    8   Late    23.9    13.0    38.6 
2017    9   Early   23.1    9.4     38.8 
2017    9   Mid 23.6    6.7     88.0 
2017    9   Late    22.4    9.3     50.2 
over    6   Early   24.97   11.08   111.76 
over    6   Mid 27.09   22.70   107.02 
over    6   Late    27.03   14.45   88.83 
over    7   Early   27.44   46.23   58.67 
over    7   Mid 26.45   55.59   51.99 
over    7   Late    27.84   48.73   74.16 
over    8   Early   26.38   43.68   46.28 
over    8   Mid 26.20   37.09   55.60 
over    8   Late    24.08   17.38   70.74 
over    9   Early   22.07   31.39   43.31 
over    9   Mid 20.56   33.70   50.70 
over    9   Late    19.49   5.20    48.54 
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