R可视化：基础图形可视化之Ranking（五）

数据分析的图形可视化是了解数据分布、波动和相关性等属性必不可少的手段。数据排列可视化图形主要有：条形图、雷达图、词云、棒棒糖图和平行坐标系统图以及循环条形图。更多知识分享请到 https://zouhua.top/。

条形图 Barplot

library(ggplot2)
library(dplyr)

data <- iris %>% select(Species, Sepal.Length) %>%
  group_by(Species) %>%
  summarise( 
    n=n(),
    mean=mean(Sepal.Length),
    sd=sd(Sepal.Length)
  ) %>%
  mutate( se=sd/sqrt(n))  %>%
  mutate( ic=se * qt((1-0.05)/2 + .5, n-1))
 
ggplot(data)+
  geom_bar(aes(x=Species, y=mean), 
             stat="identity", fill="skyblue", alpha=0.7)+
  geom_errorbar(aes(x=Species, ymin=mean-sd, ymax=mean+sd), 
                  width=0.4, colour="orange", alpha=0.9, size=1.3)+
  # geom_errorbar(aes(x=Species, ymin=mean-ic, ymax=mean+ic), 
  #              width=0.4, colour="orange", alpha=0.9, size=1.5)+   
  # geom_crossbar(aes(x=Species, y=mean, ymin=mean-sd, ymax=mean+sd), 
  #                width=0.4, colour="orange", alpha=0.9, size=1.3)+
  geom_pointrange(aes(x=Species, y=mean, ymin=mean-sd, ymax=mean+sd), 
                 colour="orange", alpha=0.9, size=1.3)+
  scale_y_continuous(expand = c(0, 0),
                     limits = c(0, 8))+
  labs(x="",y="")+
  theme_bw()+
  theme(axis.title = element_text(face = 'bold',color = 'black',size = 14),
                  axis.text = element_text(color = 'black',size = 10),
                  text = element_text(size = 8, color = "black", family="serif"),
                  legend.position = 'right',
                  legend.key.height = unit(0.6,'cm'),
                  legend.text = element_text(face = "bold", color = 'black',size = 10),
                  strip.text = element_text(face = "bold", size = 14))  

• 根据大小控制条形图宽度

library(ggplot2)

data <- data.frame(
  group=c("A ","B ","C ","D ") , 
  value=c(33,62,56,67) , 
  number_of_obs=c(100,500,459,342)
)

data$right <- cumsum(data$number_of_obs) + 30*c(0:(nrow(data)-1))
data$left <- data$right - data$number_of_obs 
 
ggplot(data, aes(ymin = 0))+ 
  geom_rect(aes(xmin = left, 
                xmax = right, 
                ymax = value, 
                color = group, 
                fill = group))+
  xlab("number of obs")+ 
  ylab("value")+
  scale_y_continuous(expand = c(0, 0),
                     limits = c(0, 81))+  
  theme_bw()+
  theme(axis.title = element_text(face = 'bold',color = 'black',size = 14),
                  axis.text = element_text(color = 'black',size = 10),
                  text = element_text(size = 8, color = "black", family="serif"),
                  legend.position = 'right',
                  legend.key.height = unit(0.6,'cm'),
                  legend.text = element_text(face = "bold", color = 'black',size = 10),
                  strip.text = element_text(face = "bold", size = 14)) 

雷达图 radar chart

library(fmsb)
 
set.seed(99)
data <- as.data.frame(matrix( sample( 0:20 , 15 , replace=F) , ncol=5))
colnames(data) <- c("math" , "english" , "biology" , "music" , "R-coding" )
rownames(data) <- paste("mister" , letters[1:3] , sep="-")
data <- rbind(rep(20,5) , rep(0,5) , data)


colors_border <- c(rgb(0.2,0.5,0.5,0.9), 
                   rgb(0.8,0.2,0.5,0.9), 
                   rgb(0.7,0.5,0.1,0.9))
colors_in <- c(rgb(0.2,0.5,0.5,0.4), 
               rgb(0.8,0.2,0.5,0.4), 
               rgb(0.7,0.5,0.1,0.4) )


radarchart(data, axistype=1, 
    pcol=colors_border, pfcol=colors_in, plwd=4, plty=1,
    cglcol="grey", cglty=1, axislabcol="grey", caxislabels=seq(0,20,5), cglwd=0.8,
    vlcex=0.8)
legend(x=1.2, y=1.2, legend=rownames(data[-c(1,2),]), 
       bty = "n", pch=20 , col=colors_in , 
       text.col = "grey", cex=1.2, pt.cex=3)

词云 wordcloud

library(wordcloud2) 

wordcloud2(demoFreq, size = 2.3, 
           minRotation = -pi/6,
           maxRotation = -pi/6, 
           rotateRatio = 1)

平行坐标系统 Parallel Coordinates chart

library(hrbrthemes)
library(GGally)
library(viridis)

data <- iris

p1 <- ggparcoord(data,
    columns = 1:4, groupColumn = 5, order = "anyClass",
    scale="globalminmax",
    showPoints = TRUE, 
    title = "No scaling",
    alphaLines = 0.3)+ 
  scale_color_viridis(discrete=TRUE)+
  theme_ipsum()+
  theme(legend.position="none",
    plot.title = element_text(size=13))+
  xlab("")

p2 <- ggparcoord(data,
    columns = 1:4, groupColumn = 5, order = "anyClass",
    scale="uniminmax",
    showPoints = TRUE, 
    title = "Standardize to Min = 0 and Max = 1",
    alphaLines = 0.3)+ 
  scale_color_viridis(discrete=TRUE)+
  theme_ipsum()+
  theme(legend.position="none",
    plot.title = element_text(size=13))+
  xlab("")

p3 <- ggparcoord(data,
    columns = 1:4, groupColumn = 5, order = "anyClass",
    scale="std",
    showPoints = TRUE, 
    title = "Normalize univariately (substract mean & divide by sd)",
    alphaLines = 0.3)+ 
  scale_color_viridis(discrete=TRUE)+
  theme_ipsum()+
  theme(legend.position="none",
    plot.title = element_text(size=13))+
  xlab("")

p4 <- ggparcoord(data,
    columns = 1:4, groupColumn = 5, order = "anyClass",
    scale="center",
    showPoints = TRUE, 
    title = "Standardize and center variables",
    alphaLines = 0.3)+ 
  scale_color_manual(values=c( "#69b3a2", "#E8E8E8", "#E8E8E8"))+
  theme_ipsum()+
  theme(legend.position="none",
    plot.title = element_text(size=13))+
  xlab("")

cowplot::plot_grid(p1, p2, p3, p4, ncol = 2, align = "hv", labels = LETTERS[1:4])

棒棒糖图 Lollipop plot

library(ggplot2)

data <- data.frame(
  x=LETTERS[1:26],
  y=abs(rnorm(26))) %>%
  arrange(y) %>%
  mutate(x=factor(x, x))


p1 <- ggplot(data, aes(x=x, y=y))+
  geom_segment(aes(x=x, xend=x, y=1, yend=y), color="grey")+
  geom_point(color="orange", size=4)+
  xlab("") +
  ylab("Value of Y")+  
  theme_light()+
  theme(axis.title = element_text(face = 'bold',color = 'black',size = 14),
        axis.text = element_text(color = 'black',size = 10),
        text = element_text(size = 8, color = "black", family="serif"),
        panel.grid.major.x = element_blank(),
        panel.border = element_blank(),
        axis.ticks.x = element_blank(),
        legend.position = 'right',
        legend.key.height = unit(0.6, 'cm'),
        legend.text = element_text(face = "bold", color = 'black',size = 10),
        strip.text = element_text(face = "bold", size = 14)) 

p2 <- ggplot(data, aes(x=x, y=y))+
  geom_segment(aes(x=x, xend=x, y=0, yend=y), 
               color=ifelse(data$x %in% c("A", "D"), "blue", "red"), 
               size=ifelse(data$x %in% c("A", "D"), 1.3, 0.7) ) +
  geom_point(color=ifelse(data$x %in% c("A", "D"), "blue", "red"), 
            size=ifelse(data$x %in% c("A","D"), 5, 2))+
  annotate("text", x=grep("D", data$x),
           y=data$y[which(data$x=="D")]*1.2,
           label="Group D is very impressive",
           color="orange", size=4 , angle=0, fontface="bold", hjust=0)+
  annotate("text", x = grep("A", data$x),
           y = data$y[which(data$x=="A")]*1.2,
           label = paste("Group A is not too bad\n (val=",
                         data$y[which(data$x=="A")] %>% round(2),")",sep=""),
           color="orange", size=4 , angle=0, fontface="bold", hjust=0)+
  theme_ipsum()+
  coord_flip()+
  theme(legend.position="none")+
  xlab("")+
  ylab("Value of Y")+
  ggtitle("How did groups A and D perform?")  

cowplot::plot_grid(p1, p2, ncol = 2, align = "h", labels = LETTERS[1:4])

循环条形图 circular barplot

library(tidyverse)
 
data <- data.frame(
  individual=paste("Mister ", seq(1,60), sep=""),
  group=c(rep('A', 10), rep('B', 30), rep('C', 14), rep('D', 6)) ,
  value=sample( seq(10,100), 60, replace=T)) %>%
  mutate(group=factor(group))

# Set a number of 'empty bar' to add at the end of each group
empty_bar <- 3
to_add <- data.frame(matrix(NA, empty_bar*nlevels(data$group), ncol(data)))
colnames(to_add) <- colnames(data)
to_add$group <- rep(levels(data$group), each=empty_bar)
data <- rbind(data, to_add)
data <- data %>% arrange(group)
data$id <- seq(1, nrow(data))

# Get the name and the y position of each label
label_data <- data
number_of_bar <- nrow(label_data)
angle <- 90 - 360 * (label_data$id-0.5) /number_of_bar
label_data$hjust <- ifelse( angle < -90, 1, 0)
label_data$angle <- ifelse(angle < -90, angle+180, angle)

# prepare a data frame for base lines
base_data <- data %>% 
  group_by(group) %>% 
  summarize(start=min(id), end=max(id) - empty_bar) %>% 
  rowwise() %>% 
  mutate(title=mean(c(start, end)))
 
# prepare a data frame for grid (scales)
grid_data <- base_data
grid_data$end <- grid_data$end[ c( nrow(grid_data), 1:nrow(grid_data)-1)] + 1
grid_data$start <- grid_data$start - 1
grid_data <- grid_data[-1, ]

# Make the plot
p <- ggplot(data, aes(x=as.factor(id), y=value, fill=group))+
  geom_bar(aes(x=as.factor(id), y=value, fill=group), stat="identity", alpha=0.5)+
  # Add a val=100/75/50/25 lines. I do it at the beginning to make sur barplots are OVER it.
  geom_segment(data=grid_data, 
               aes(x = end, y = 80, xend = start, yend = 80), 
               colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE )+
  geom_segment(data=grid_data, 
               aes(x = end, y = 60, xend = start, yend = 60), 
               colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE )+
  geom_segment(data=grid_data, 
               aes(x = end, y = 40, xend = start, yend = 40), 
               colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE )+
  geom_segment(data=grid_data, 
               aes(x = end, y = 20, xend = start, yend = 20), 
               colour = "grey", alpha=1, size=0.3 , inherit.aes = FALSE )+
  # Add text showing the value of each 100/75/50/25 lines
  annotate("text", 
           x = rep(max(data$id),4), 
           y = c(20, 40, 60, 80), 
           label = c("20", "40", "60", "80"), 
           color="grey", size=3, angle=0, fontface="bold", hjust=1) +
  geom_bar(aes(x=as.factor(id), y=value, fill=group), stat="identity", alpha=0.5)+
  ylim(-100,120)+
  theme_minimal()+
  theme(legend.position = "none",
    axis.text = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    plot.margin = unit(rep(-1,4), "cm"))+
  coord_polar()+ 
  geom_text(data=label_data, 
            aes(x=id, y=value+10, label=individual, hjust=hjust), 
            color="black", fontface="bold",alpha=0.6, size=2.5, 
            angle= label_data$angle, inherit.aes = FALSE )+
  
  # Add base line information
  geom_segment(data=base_data, 
               aes(x = start, y = -5, xend = end, yend = -5), 
               colour = "black", alpha=0.8, size=0.6 , inherit.aes = FALSE )  +
  geom_text(data=base_data, 
            aes(x = title, y = -18, label=group), 
            hjust=c(1,1,0,0), colour = "black", 
            alpha=0.8, size=4, fontface="bold", inherit.aes = FALSE)
 
p

参考

1. The R Graph Gallery

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