如何使用 R 有效地创建 5x3 条形图

Question

我有以下数据：

Project Topic    C10    C14     C03     C11     C16     C08
P1      T1      0.24    0.00    0.00    0.04    0.04    0.00
P1      T2      0.00    0.30    0.00    0.00    0.00    0.00
P1      T3      0.04    0.04    0.00    0.24    0.00    0.00
P1      T4      0.00    0.00    0.00    0.04    0.33    0.04
P1      T5      0.00    0.09    0.21    0.00    0.00    0.00
P1      T6      0.00    0.09    0.00    0.00    0.00    0.34

P2      T1      0.20    0.00    0.00    0.04    0.00    0.04
P2      T2      0.00    0.22    0.04    0.00    0.00    0.00
P2      T3      0.04    0.00    0.00    0.24    0.00    0.00
P2      T4      0.00    0.00    0.04    0.00    0.33    0.00
P2      T5      0.04    0.00    0.21    0.00    0.00    0.00
P2      T6      0.00    0.04    0.00    0.00    0.00    0.34

P3      T1      0.20    0.00    0.00    0.00    0.08    0.00
P3      T2      0.00    0.17    0.00    0.00    0.00    0.00
P3      T3      0.00    0.00    0.00    0.08    0.00    0.00
P3      T4      0.00    0.04    0.00    0.04    0.24    0.00
P3      T5      0.00    0.00    0.21    0.00    0.00    0.04
P3      T6      0.00    0.09    0.00    0.00    0.00    0.22
    ......

我想要做的是将上述数据创建到以下图中：

在这个草图中，条的高度属于 C#s 的值，它应该有六种颜色。每个条形图都属于 P#s 数据集。

我尝试使用以下代码，将每个 P#s 数据集复制到 .csv 文件中，并使用 par(mfrow=c(5,3)) 将其绘制在同一图框中：

library(e1071)
topics <- read.csv("P1.csv", head=TRUE)
dput(head(topics))
pdf("cosinesimilarityplots.pdf", family="Times")
par(mfrow=c(5,3))
colours <- c("red", "orange", "yellow", "green","blue"," black")
barplot(as.matrix(topics), main="Project Name", ylab="", cex.lab = 1.5, cex.main = 1.4, beside=TRUE, col=colours,ylim=c(0, 0.5))
title(ylab=expression(paste("Cose(", theta, ")")),xlab="Seeded-LDA topics", line=2, cex.lab=1.2)
legend("topleft", c("C10: Resource Management (RM)","C14:Cross Site Scripting (XSS)","C03:Authentication Abuse (AA)","C11:Buffer Overflow (BoF)","C16:Access  Privileges (AP)","C08:SQL  Injection (SI)"), cex=0.85, bty="n", fill=colours)
dev.off()

dput(head(topics))的结果如下：

structure(list(T1 = c(0.24, 0, 0, 0.04, 0.04, 0), T2 = c(0.24, 
0.3, 0, 0, 0, 0), T3 = c(0.04, 0.04, 0, 0.24, 0, 0), T4 = c(0, 
0, 0, 0.04, 0.33, 0.04), T5 = c(0, 0.09, 0.21, 0, 0, 0), T6 = c(0, 
0.09, 0, 0, 0, 0.34)), .Names = c("T1", "T2", "T3", "T4", "T5", 
"T6"), row.names = c(NA, 6L), class = "data.frame")

然后，我意识到条形图质量变得非常低，如果 P#s 的数量大于 15，则将每个 P#s 数据绘制在单独的 .csv 文件中将花费很长时间。

如何有效地绘制主数据集文件而不将其拆分为较小的文件？最好使用R

Answer 1

在dplyr 和reshape2 的帮助下，您可以使用ggplot2 和gridextra 创建一个类似于您所描绘的情节。通常情况下，仅仅因为你有能力在 R 中做某事并不意味着它是直观的。基本上你必须为每个项目创建一个单独的绘图对象，去掉图例，然后使用grid.arrange() 重新组合所有内容。

library(tidyverse) # ggplot2, dplyr, etc
library(reshape2)  # Outdated but still works
library(gridExtra) # Allows us to put plots into grids

# Generate some dummy data
data <- tibble(
  Project =   rep(paste0("P", 1:6), length = 30),
  C10 = abs(rnorm(30)),
  C14 = runif(30),
  C03 = sample(1:30) / 50,
  C11 = rnorm(30) ^ 2,
  C16 = abs(rnorm(30) / 2),
  C08 = abs(rnorm(30) * 2)
)

data <- data %>%
  arrange(Project) %>%
  mutate(Topic = rep(paste0("T", 1:5), length = 30))

# Melt the data from wide to long format
data <- melt(data, id.vars = c("Project", "Topic"))

#########################################################
# Now you can actually create the chart
#########################################################

# Use a function to create a version of the plot for each Project
plot_proj <- function(projnum) {
  filter(data, Project == projnum) %>%
    rename(Legend = variable) %>%
    ggplot(., aes(x = Topic, y = value, fill = Legend)) +
    geom_bar(stat = "identity", position = "dodge") +
    labs(x = "", y = "", title = projnum) +
    theme_bw() +
    theme(plot.title = element_text(hjust = 0.5),
          panel.border = element_blank())
}

# Create a separate plot for each Project
plots <- map(unique(data$Project), plot_proj)

# This function was borrowed from an older StackOverflow answer
# Source: http://stackoverflow.com/questions/13649473/add-a-common-legend-for-combined-ggplots
g_legend <- function(a.gplot) {
  tmp <- ggplot_gtable(ggplot_build(a.gplot))
  leg <- which(sapply(tmp$grobs, function(x)
    x$name) == "guide-box")
  legend <- tmp$grobs[[leg]]
  return(legend)
}

mylegend <- g_legend(plots[[1]])

# Combine the plots and add one
grid.arrange(
  arrangeGrob(
    plots[[1]] + theme(legend.position = "none"),
    plots[[2]] + theme(legend.position = "none"),
    plots[[3]] + theme(legend.position = "none"),
    plots[[4]] + theme(legend.position = "none"),
    plots[[5]] + theme(legend.position = "none"),
    plots[[6]] + theme(legend.position = "none"),
    left = mylegend
  )
)