在 r 中制作两个百分比变量的分组条形图

Question

我想制作一个包含两个二项式变量的分组条形图。

我记录了橡树叶子顶部 (P.A) 和底部 (U.PA) 被白粉病感染的情况。它们被组织为存在（用“1”表示）或不存在（用“0”表示）。

This is an image showing the top of my dataframe. 它由日期、叶数、植物 ID 和两个二项式变量 P.A 和 U.PA 组织。

我可以将它们分别绘制在两个条形图中。

Percentage of leaves with Powdery mildew infection upon the upper surface of the leafs

Percentage of leaves with powdery mildew upon the under surface of the leafs

使用此代码：

plot(DFP$P.A ~ DFP$Date, ylim=c(0,0.2), main= "Leaves infected with powdery mildew on the upper surface", ylab = "Percentage of leaves infected", xlab= "Date")

plot(DFP$L.PA ~ DFP$Date, ylim=c(0,0.2), main= "Leaves infected with powdery mildew on the lower surface", ylab = "Percentage of leaves infected", xlab= "Date")

我基本上想将以上两张图片重新合二为一。因此按日期分组 U.PA 和 P.A 的叶子总数中被感染的叶子百分比，但在同一张图表上。

我看到网站上有一些关于分组条形图的主题，但我无法将其应用于我的数据集，可能是因为它是二项式数据？我为自己对 r 的无知表示歉意，但我正在慢慢学习。

如有任何帮助，我们将不胜感激！

我使用 dput(DFY) 作为完整数据的数据子集不适合：

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5, 4, 10, 18, 7, 15, 1, 4, 5, 1, 9, 13, 19, 16, 13, 2, 4, 12, 
8, 1, 1, 11, 2, 6, 5, 14, 10, 3, 5, 1, 5, 1, 2, 2, 1, 6, 6, 3, 
1, 5, 14, 34, 2, 4, 1, 2, 11, 7, 4, 5, 3, 10, 4, 2, 5, 15, 3, 
2, 2, 8, 2, 6, 34, 9, 1, 6, 18, 4, 8, 2, 9, 9, 1, 5, 1, 23, 15, 
5, 2, 6, 14, 5, 2, 2, 3, 4, 6, 13, 7, 6, 8, 1, 22, 2, 7, 11, 
4, 4, 2, 11, 1, 1, 20, 1, 4, 5, 3, 5, 20, 5, 10, 1, 4, 4, 7, 
6, 1, 2, 3, 12, 13, 3, 13, 3, 3, 8, 17, 2, 2, 3, 2, 3, 8, 13, 
1, 6, 11, 2, 4, 1, 6, 3, 5, 9, 2, 4, 1, 8, 5, 1, 13, 8, 3, 7, 
9, 3, 28, 2, 6, 2, 14, 1, 3, 5, 4, 4, 1, 1, 1, 3, 17, 12, 16, 
6, 11, 3, 6, 9, 3, 11, 2, 11, 10, 6, 7, 4, 10, 3, 2, 3, 7, 2, 
6, 4, 6, 7, 4, 6, 2, 4, 7, 3, 3, 6, 8, 4, 1, 3, 1, 3, 6, 1, 1, 
7, 3, 3, 6, 6, 25, 14, 10, 1, 19, 1, 2, 21, 27, 6, 4, 8, 5, 10, 
16, 8, 9, 1, 5, 5, 4, 3, 8, 1, 8, 8, 6, 2, 5, 1, 7, 4, 3, 1, 
1, 5, 3, 18, 12, 15, 2, 6, 5, 8, 6, 5, 9, 6, 12, 3, 6, 13, 4, 
5, 1, 6, 2, 4, 14, 1, 10, 9, 5, 12, 7, 2, 4, 1, 3, 6, 12, 4, 
4, 6, 2, 5, 7, 6, 2, 8, 10, 2, 9, 1, 7, 8, 5, 21, 6, 3, 11, 16, 
14, 3, 8, 11, 1, 2, 1, 5, 5, 8, 5, 6, 1, 15, 9, 4, 14, 10, 2, 
5, 6, 4, 4, 2, 5, 1, 22, 8, 20, 1, 4, 6, 4, 13, 9, 2, 10, 3, 
4, 21, 2, 7, 9, 1, 1, 3, 6, 6, 7, 3, 16, 4, 23, 11, 11, 1, 6, 
2, 4, 7, 19, 4, 9, 4, 9, 7, 5, 3, 18, 5, 5, 3, 13, 15, 3, 10, 
10, 7, 2, 5, 6, 16, 18, 5, 4, 5, 1, 5, 8, 1, 24, 11, 4, 1, 6, 
14, 5, 10, 6, 15, 6, 5, 9, 8, 2, 8, 7, 10, 1, 11, 5, 9, 2, 12, 
8, 11, 18, 7, 3, 14, 19, 2, 2, 2, 1, 5, 7, 13, 8, 9, 12, 13, 
2, 9, 3, 5, 2, 13, 4, 4, 10, 3, 6, 9, 10, 7, 1, 8, 28, 14, 5, 
13, 4, 11, 2, 1, 4, 4, 5, 2, 3, 5, 1, 6, 4, 3, 10, 6, 5, 6, 24, 
5, 4, 8, 14, 2, 2, 11, 20, 3, 23, 18, 8, 5, 4, 10, 3, 4, 2, 11, 
15, 4, 4, 13, 7, 4, 9, 8, 3, 15, 1, 8, 3, 16, 5, 1, 11, 2, 6, 
2, 5, 4, 5, 4, 16, 3, 12, 5, 2, 4, 1, 5, 6, 3, 11, 4, 2, 3, 3, 
7, 1, 1, 18, 2, 21, 1, 3, 1, 2, 6, 3, 2, 2, 4, 13, 1, 2, 11, 
1, 15, 7, 5, 5, 2, 3, 4, 10, 6, 3, 5, 1, 6, 4, 6, 18, 4, 3, 5, 
4, 12, 3, 4, 19, 13, 11, 2, 6, 10, 7, 18, 1, 8, 28, 1, 22, 4, 
9, 8, 1, 6, 5, 14, 9, 1, 1, 10, 4, 16, 18, 1, 1, 6, 9, 7, 3, 
5, 18, 1, 5, 6, 8, 5, 39, 4, 6, 17, 11, 4, 2, 6, 1, 1, 9, 7, 
2, 7, 1, 7, 9, 2, 3, 5, 2, 3, 7), P.A = c(1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 
1, 1, 1, 0, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1), L.PA = c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 
1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 
1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 
1, 1)), .Names = c("Date", "Plant_ID", "Leaf", "P.A", "L.PA"), row.names = c(NA, 
-800L), class = c("tbl_df", "tbl", "data.frame"))

Answer 1

感谢大家的帮助，我最终解决了这个问题，这个问题可能只适用于我自己，但如果其他人有同样的问题，我是如何解决的：

需要重新组织数据框以便于绘图

     DFP.A <- table(DF3$Date,DF3$P.A)
    DFLP.A <- table(DF3$Date,DF3$L.PA)
    dfa<-as.data.frame(DFP.A)
    dfb<-as.data.frame(DFLP.A)

#This gives the frequencies of upper and lower infected leaves on each date in two different data frames
# i then rename the columns mostly to make it easier for myself
    DFP.A
    DFLP.A
    colnames(dfa)[which(names(dfa) == "Var1")] <- "Date"
    colnames(dfa)[which(names(dfa) == "Var2")] <- "infected"
    colnames(dfa)[which(names(dfa) == "Freq")] <- "Upper_infected"

# i remove the Unifected ones from the data frames (those that have a 0)
  dfa<-dfa[dfa$infected!="0",]
    dfa <- subset(dfa, select = - infected)

    colnames(dfb)[which(names(dfb) == "Var1")] <- "Date"
    colnames(dfb)[which(names(dfb) == "Var2")] <- "infected"
    colnames(dfb)[which(names(dfb) == "Freq")] <- "Lower_infected"
    dfb<-dfb[dfb$infected!="0",]
    dfb <- subset(dfb, select = - infected)

    dfc<- merge(dfa,dfb, by = "Date")


    # melt the dataframe to make it more easily graphed

    library(reshape)
    dfd <- melt(dfc, id=c("Date"))

    # now attempt the graphs finally 

    ggplot(dfd, aes(factor(Date), value, fill = variable )) + 
      geom_bar(stat="identity", position = "dodge") + 
      scale_fill_brewer(palette = "Set1")

The final grouped bar chart

在 r 中制作两个百分比变量的分组条形图

Make a grouped Bar chart of two percentage variables in r

grouping

r

percentage

bar-chart