【R语言】ggplot2画图

library(readxl)
orders<-read_excel("global-superstore.xlsx","订单")
str(orders)    #查看数据

library(tidyr)
orders0<- orders %>%
  separate(col =orderid,
           into =c('center','year','product'),
           sep ='-')
str(orders0)   #查看数据

# 例1：求出各个市场的总销售额
orders %>% group_by(market) %>%
summarise(totalsales = sum(sales))

# 例2：用图形表示各个市场总销售额
library(dplyr)
library(ggplot2)
orders %>% group_by(market) %>%
summarise(totalsales = sum(sales)) %>%
  ggplot(.,mapping=aes(x=market,y=totalsales))+
  geom_bar(stat='identity')+
  xlab('市场')+ylab('总销售额')

# 总利润
library(dplyr)
library(ggplot2)
orders %>% group_by(market) %>%
       summarise(totalprofit = sum(profit)) %>%
       ggplot(.,mapping=aes(x=market,y=totalprofit))+
       geom_bar(stat='identity')+
       xlab('市场')+ylab('总利润')

# 例3：拉丁美洲各地区的总销售额
orders %>% filter(market == '拉丁美洲') %>%
  group_by(area) %>%
  summarise(totalsales = sum(sales))

# 例4：求出采购量最大的五个客户
orders %>%
  group_by(custname) %>%
  summarise(totalsales = sum(sales)) %>%
  top_n(5, totalsales) %>%
  arrange(desc(totalsales))

# 例5：求出每个客户采购量最大的两个类型的产品
orders %>% group_by(custname,type)%>%
  summarise(totalsales=sum(sales))%>%
  top_n(2,totalsales)

# 例6：各个市场不同类别的细分市场的销售数量
y_axis_formatter=function(x){
  return(paste(x/1000,'K',sep=""))
}
ggplot(orders,aes(x=segment,y=quantity))+
  geom_bar(stat='identity')+
  facet_grid(type~market)+
  scale_y_continuous(labels=y_axis_formatter)+
  xlab("细分市场")+
  ylab("数量")+
  coord_flip()

# 例7：按年份汇总销售量 
orders%>%mutate(year=lubridate::year(purchasedate))%>%
  group_by(year)%>%
  summarise(totalsales=sum(sales))

# 例8.1：不同年份各季度的汇总
orders%>%mutate(year=lubridate::year(purchasedate),
                quarter=lubridate::quarter(purchasedate)
)%>%
  group_by(year,quarter)%>%
  summarise(totalsales=sum(sales))%>%
  ggplot(.,aes(x=year,y=totalsales))+
  geom_line()+
  facet_grid(.~quarter)

# 例8.2：不同年份各季度的汇总
orders%>%mutate(year=lubridate::year(purchasedate),
                quarter=lubridate::quarter(purchasedate)
)%>%
  group_by(year,quarter)%>%
  summarise(totalsales=sum(sales))%>%
  ggplot(.,aes(x=quarter,y=totalsales))+
  geom_line()+
  facet_grid(.~year)

# 例8.3：横轴是季度，以不同折线表示年份
orders%>%mutate(year=
                  lubridate::year(purchasedate),
                quarter=
                  lubridate::quarter(purchasedate)
)%>%
  group_by(year,quarter)%>%
  summarise(totalsales=sum(sales))%>%
  ggplot(.,aes(x=quarter,y=totalsales,colour=
                 factor(year)))+
  geom_line()

# 例9：不同年份按月汇总
orders%>%mutate(year=lubridate::year(purchasedate),
                   month=lubridate::month(purchasedate)
)%>%
  group_by(year,month)%>%
  summarise(totalsales=sum(sales))%>%
  ggplot(.,aes(x=month,y=totalsales,colour=
                  factor(year)))+
  geom_line()

# 例10：算同比增长率
orders%>%mutate(year=lubridate::year(purchasedate),
  month=lubridate::month(purchasedate))%>%
  group_by(month,year)%>%
  summarise(totalsales=sum(sales))%>%
  mutate(ratio=(totalsales- lag(totalsales))/lag(totalsales))%>%
  ggplot(.,aes(x=month,y=ratio,colour=factor(year)))+
  geom_line()

# 例11：不同类别各年按月汇总的趋势
orders%>%mutate(year=
lubridate::year(purchasedate),
  month=lubridate::month(purchasedate))%>%
  group_by(type,year,month)%>%
  summarise(totalsales=sum(sales))%>%
  ggplot(.,aes(x=month,y=totalsales,
  colour=factor(year)))+
  geom_line()+
  scale_x_continuous(breaks=1:12)+
  facet_grid(type~.)

# 例12：各类别产品各年各月的总销售额
orders%>%mutate(year=lubridate::year(purchasedate),
month=lubridate::month(purchasedate,label=T))%>%
  group_by(type,year,month)%>%
  summarise(totalsales=sum(sales))%>%
  tidyr::spread(month,totalsales)

【R语言】ggplot2画图

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