强烈推荐《HelloBD》和《庄闪闪的R语言手册》这两个公众号，很适合新手小白！如果对R语言有一定了解且很感兴趣的，可以经常逛逛《统计之都》，你一定会有很多收获，认识到很多志同道合的大佬！

数据可视化——以2010年世界杯球员信息为例

#加载包
library(dplyr)
library(ggplot2)
library(faraway)

#加载数据
data(worldcup)
head(worldcup)

1. 每个国家的球员数量(条形图)

player <- worldcup %>% 
    group_by(Team) %>% 
    summarise(value=n()) %>% 
    arrange(desc(value)) %>% 
    as.data.frame()

player_plot <- ggplot(player,aes(x = reorder(Team,value),y = value)) +
    theme_bw(base_family = "STKaiti") +
    geom_bar(aes(fill=value),stat = "identity",show.legend = F) +
    coord_flip() +
    scale_fill_gradient(low = "blue",high = "red") +
    labs(x="国家",y="球员数量",title = "每个国家的球员数量") +
    theme(axis.text.x = element_text(vjust = 0.5),plot.title = element_text(hjust = 0.5))
player_plot

条形图

library(maps)
library(REmap)

colnames(player)<-c("nation","number")
options(remap.js.web=T)
map <- remapC(player,
             maptype='world',
             color=c('red','blue'),
             theme=get_theme("Sky"),
             maxdata=20,
             mindata=14)
print(map)

地图

p <- ggplot(worldcup,aes(x = Time,y = Passes)) +
    theme_bw(base_family = "STKaiti") +
    geom_point(aes(shape = Position)) +
    labs(x="上场的总时间数(min)",y="传球次数") +
    theme(axis.text.x = element_text(hjust = 0.5))
options(repr.plot.width=10, repr.plot.height=6)
p

散点图

p <- ggplot(worldcup,aes(x = Team,y = Shots)) +
    theme_bw(base_family = "STKaiti") +
    geom_histogram(aes(fill=Position),stat = "identity") +
    labs(x="国家",y="射门次数",title = "不同国家球员的射门情况") +
    theme(axis.text.x = element_text(hjust = 0.5,angle = 90),plot.title = element_text(hjust = 0.5))
p

直方图

p <- ggplot(worldcup,aes(x = Position,y = Shots)) +
    theme_bw(base_family = "STKaiti") +
    geom_boxplot(aes(fill=Position),show.legend = F) +
    labs(x="不同位置",y="射门次数",title = "不同位置的射门情况") +
    theme(axis.text.x = element_text(hjust = 0.5),plot.title = element_text(hjust = 0.5))
p

箱线图

library(GGally)
p <- ggpairs(worldcup,columns=c(2,4:7),aes(color=Position),alpha=0.8) +
    theme_bw(base_family="STKaiti") +
    labs(title = "散点矩阵图") +
    theme(plot.title=element_text(hjust=0.5))
p

散点矩阵图