醫學統計與R語言:百分條圖與雷達圖

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百分條圖-輸入1：

library(ggplot2)
library(ggthemes)
library(ggsci)
library(rio)
percentbar <- import("percentbar.xlsx")
percentbar

結果1：

   year government society Individual
1 2009      21.12   39.34      39.54
2 2010      23.21   38.54      38.25
3 2011      23.14   38.77      38.09
4 2012      22.20   44.65      33.15
5 2013      22.96   43.85      33.19
6 2014      22.45   46.06      31.49
7 2015      22.22   48.29      29.49
8 2016      21.68   50.33      27.99
9 2017      21.18   51.83      26.99

輸入2：

percentbar <- gather(percentbar,key=subject,value=TEH,-year)
percentbar$subject <- factor(percentbar$subject,levels = c("Individual","society","government"))
ggplot(percentbar,aes(x=year,y=TEH,fill=subject))+geom_bar(stat="identity")+
  geom_text(aes(label = paste(TEH,"%")), size=5,col="white",     
  position=position_stack(vjust = 0.5)) +theme_stata()+
  theme(legend.position="bottom", legend.text = element_text(face="bold",size=12),
       legend.title = element_blank())+ scale_x_continuous(breaks=seq(2009,2017,1))+
  scale_y_continuous(labels = paste(c(0,25,50,75,100),'%'))+labs(x="Year", y="Total Expenditure on Health")+
  theme(axis.text= element_text(face="bold",size=12),axis.title =element_text(face="bold",size=14) )+
  theme(axis.line = element_line(size=1.2, colour = "black"),
                            panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
                            panel.border = element_blank(), panel.background = element_blank())+
  scale_fill_lancet()

結果2：

雷達圖-輸入3：

radar <- import("radar.xlsx")
radar

結果3：

                    指標  浙江  江蘇  廣東    全國
1   每千人執業(助理)醫師數  3.33  2.90  2.44  2.59
2         每千人註冊護士數  3.51  3.23  2.95  2.94
3           每千人口床位數  5.79  6.10  4.56  6.03
4 衛生總費用佔GDP比例（%）  5.46  4.30  5.15  6.36
5       居民年平均就診次數 10.94  7.38  7.45  5.96
6            年住院率（%） 17.80 18.00 15.10 18.30                  

輸入4：

install.packages("radarchart")
library(radarchart)
chartJSRadar(radar,labelSize=20, scaleStartValue=0,responsive=T,
             polyAlpha=0,lineAlpha=1, addDots=T,
             scaleStepWidth = 4,maxScale = 20,
             showLegend = T,width = "450", height = "300")

結果4：

輸入5：

install.packages("fmsb")
library(fmsb)
radar1 <- as.data.frame(t(radar[,-1]));radar1
colnames(radar1) <- radar$指標
radar2<- rbind(c(4,4,7,7,11,20) , rep(0,6) , radar1);radar2
library(RColorBrewer)
colors_border<- brewer.pal(4, "Dark2")
library(scales)
colors_in <- alpha(colors_border,0.1)
radarchart(radar2,axistype =2,seg=5,pty=2,plty=2,plwd=2,cglty=1,    
    cglwd=1,cglcol="gray",
    axislabcol="blue", centerzero=T,vlcex=1.3,pcol=colors_border,pfcol=colors_in)

legend(x=1.2 , y=1.4,legend = rownames(radar2[-c(1,2),]), bty = "n",
    pch=2, col=colors_border , text.col = "black", cex=1.5, pt.cex=1.5)

結果5：

The data frame to be used to draw radarchart. If maxmin is TRUE, this must include maximum values as row 1 and minimum values as row 2 for each variables, and actual data should be given as row 3 and lower rows. The number of columns (variables) must be more than 2.