install.packages("ggplot2")
library(ggplot2)
install.packages("dplyr")
library(dplyr)
install.packages("readxl")
library(readxl)
test<- read.csv("c:/gimalproject/부산지하철_와이파이.csv")


#전체 호선 통신사 3사 나누기
test %>% filter(회사명=="SKT")
dim(test %>% filter(회사명=="SKT")) #109개
dim(test %>% filter(회사명=="KT"))#103개
dim(test %>% filter(회사명=="LGU+"))#100개
tong<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
                 sum=c(109,103,100))
tong
ggplot(data=tong,aes(x=tongsinsa,y=sum))+geom_col()


#2호선 통신사 3사 비율
test %>% filter(회사명=="SKT" & 호선 =="1호선") 
dim(test %>% filter(회사명=="SKT" & 호선 =="1호선")) #40개
dim(test %>% filter(회사명=="KT" & 호선 =="1호선"))#37개
dim(test %>% filter(회사명=="LGU+" & 호선 =="1호선"))#37개
onehosun<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
                     sum=c(40,41,42))
onehosun

ggplot(data=onehosun,aes(x=tongsinsa, y= sum))+geom_col()
#호선별로 통신사 3사 분류
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선"))#40개
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))#41개
dim(test %>% filter(회사명=="LGU+" & 호선 =="2호선"))#42개
dim(test %>% filter(회사명=="SKT" & 호선 =="3호선"))#17개
dim(test %>% filter(회사명=="KT" & 호선 =="3호선"))#14개
dim(test %>% filter(회사명=="LGU+" & 호선 =="3호선"))#12개
dim(test %>% filter(회사명=="SKT" & 호선 =="4호선"))#12개
dim(test %>% filter(회사명=="KT" & 호선 =="4호선"))#11개
dim(test %>% filter(회사명=="LGU+" & 호선 =="4호선"))#9개
hosun<-data.frame(tongsinsa=c("SKT","KT","LGU+","SKT","KT","LGU+","SKT","KT","LGU+","SKT","KT","LGU+"),
                  hosun=c("1호선","1호선","1호선","2호선","2호선","2호선","3호선","3호선","3호선","4호선","4호선","4호선"),
                  gatsu=c(40,37,37,40,41,42,17,14,12,12,11,9))
hosun
ggplot(data=hosun, aes(x=tongsinsa, y=gatsu, fill=hosun)) +geom_col() +scale_x_discrete(limits=c("SKT","KT","LGU+"))

