df_family <-read_excel("c:/gimalproject/lovefamily.xlsx")
install.packages("readxl")
library(readxl)
df_family <-read_excel("c:/gimalproject/lovefamily.xlsx")
df_lovefamily<- read_excel("lovefamily.xlsx")
df_lovefamily<- read_excel("c:/giamlproject/lovefamily.xlsx")
df_lovefamily<- read_excel("c:/gimalproject/lovefamily.xlsx")
install.packages("ggplot2")
library(ggplot2)
install.packages("dplyr")
library(dplyr)
install.packages("reaxl")
install.packages("readxl")
library(readxl)
df_lovefamily<- read_excel("c:/gimalproject/lovefamily.xlsx")
df_lovefamily<- read_excel("lovefamily.xlsx")
df_lovefamily
view(df_lovefamily)
View(df_lovefamily)
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter(배우자와의 관계$매우만족)
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter(배우자와의 관계 >= 40.0)
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter("배우자와의 관계" >= 40.0)
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter("배우자와의 관계">= 40.0)
head
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter("배우자와의 관계">= 40.0)
head
# 가구월평균 소득별 배우자의 관계가 매우 만족으로  높은것은?
df_lovefamily %>% filter("배우자와의 관계"$"매우만족">=40.0)
View(df_lovefamily)
df_lovefamily<- read_excel("c:/gimalproject/lovefamily.xlsx")
df_lovefamily<- read_excel("c:/gimalproject/lovefamily.xlsx")
View(df_lovefamily)
View(df_lovefamily)
df_lovefamily<- read.csv("c:/gimalproject/library.csv")
test<- read.csv("c:/gimalproject/library.csv")
test<- read.csv("c:/gimalproject/library.csv")
test<- read.csv("c:/gimalproject/210_DT_20114_2014209_20190610183121.csv")
test<- read_xlsx("c:/gimalproject/library.xlsx")
test<- read_excel("c:/gimalproject/library.xlsx")
install.packages("ggplot2")
library(ggplot2)
install.packages("dplyr")
library(dplyr)
install.packages("readxl")
library(readxl)
test
test<-read.csv("c:gimalproject/부산지하철_와이파이.csv")
install.packages("dplyr")
install.packages("dplyr")
install.packages("dplyr")
install.packages("dplyr")
library(dplyr)
install.packages("dplyr")
library(dplyr)
test<-read.csv("c:gimalproject/부산지하철_와이파이.csv")
test<- read.csv("c:gimalproject/부산지하철_와이파이.csv")
test<- read.csv("c:gimalproject/부산지하철_와이파이.csv")
test<- read.csv("c:gimalproject/부산지하철_와이파이.csv")
install.packages("readxl")
library(readxl)
test<- read.csv("c:gimalproject/부산지하철_와이파이.csv")
install.packages("ggplot2")
library(ggplot2)
test<- read.csv("c:gimalproject/부산지하철_와이파이.csv")
test<- read.csv("c:/gimalproject/부산지하철_와이파이.csv")
#전체 통신사 3사 나누기
#1호선 통신사 3사 비율
test %>% filter(회사명=="SKT" & 호선 =="1호선")
dim(test %>% filter(회사명=="SKT" & 호선 =="1호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="1호선"))
dim(test %>% filter(회사명=="LGU+" & 호선 =="1호선"))
#호선별로 통신사 3사 분류
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))
dim(test %>% filter(회사명=="LGU+" & 호선 =="2호선"))
dim(test %>% filter(회사명=="SKT" & 호선 =="3호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="3호선"))
dim(test %>% filter(회사명=="LGU+" & 호선 =="3호선"))
dim(test %>% filter(회사명=="SKT" & 호선 =="4호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="4호선"))
dim(test %>% filter(회사명=="LGU+" & 호선 =="4호선"))
dim(test %>% filter(회사명=="SKT" & 호선 =="4호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="4호선"))
dim(test %>% filter(회사명=="LGU+" & 호선 =="4호선"))
#호선별로 통신사 3사 분류
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선"))
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))
onehosun<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
sum=c(40,37,37))
onehosun
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(40,37,37,40,50,37,20,17,16,15,12,14))
hosun
ggplot(data=hosun,aes(x = tongsinsa, y=hosun,fill=gatsu))+geom_col()+scale_x_discrete(limits=c("SKT","KT","LGU+"))
ggplot(data=hosun,aes(x = tongsinsa, y=hosun,fill=gatsu))+geom_col()
ggplot(data=hosun,aes(x = hosun, y=tongsinsa, fill=gatsu))+geom_col()
ggplot(data=hosun,aes(x = tongsinsa, y=hosun, fill=gatsu))+geom_col(position = "dodge")+scale_x_discrete(limits=c("SKT","KT","LGU+"))
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(40,37,37,43,43,43,17,17,17,14,14,14))
hosun
ggplot(data=hosun,aes(x = tongsinsa, y=hosun, fill=gatsu))+geom_col(position = "dodge")+scale_x_discrete(limits=c("SKT","KT","LGU+"))
#호선별로 통신사 3사 분류
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선"))#40개
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))#50개
dim(test %>% filter(회사명=="LGU+" & 호선 =="2호선"))#37개
test<- read.csv("c:/gimalproject/부산지하철_와이파이.csv")
#호선별로 통신사 3사 분류
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선"))#40개
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))#50개
dim(test %>% filter(회사명=="LGU+" & 호선 =="2호선"))#37개
dim(test %>% filter(회사명=="SKT" & 호선 =="3호선"))#20개
dim(test %>% filter(회사명=="KT" & 호선 =="3호선"))#17개
dim(test %>% filter(회사명=="LGU+" & 호선 =="3호선"))#16개
dim(test %>% filter(회사명=="SKT" & 호선 =="4호선"))#15개
dim(test %>% filter(회사명=="KT" & 호선 =="4호선"))#12개
dim(test %>% filter(회사명=="LGU+" & 호선 =="4호선"))#14ㄱ
dim(test %>% filter(회사명=="SKT" & 호선 =="1호선")) #40개
dim(test %>% filter(회사명=="LGU+" & 호선 =="1호선"))#37개
dim(test %>% filter(회사명=="LGU+" & 호선 =="1호선"))#37개
#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"))#9RO
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=hosun, fill=gatsu))+geom_col(position = "dodge")+scale_x_discrete(limits=c("SKT","KT","LGU+"))
ggplot(data=hosun, aes(x =tongsinsa, y=hosun, fill=gatsu)) +geom_col()+coord_flip()
ggplot(data=hosun, aes(x =tongsinsa, y=hosun)) +geom_col()+coord_flip()
#전체 통신사 3사 나누기
test %>% filter(회사명=="SKT")
dim(test %>% filter(회사명=="SKT"))
dim(test %>% filter(회사명=="KT"))
dim(test %>% filter(회사명=="LGU+"))
tong<-data.frame(tonsinsa=c("SKT","KT","LGU+"),
sum=c(109,103,100))
tong_a<-tong
tong_a
ggplot(data=tong_a,aes(x=tongsinsa,y=sum))+geom_col()
tong<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
sum=c(109,103,100))
ggplot(data=tong_a,aes(x=tongsinsa,y=sum))+geom_col()
tong<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
sum=c(109,103,100))
tong
tong_a<-tong
ggplot(data=tong,aes(x=tongsinsa,y=sum))+geom_col()
onehosun<-data.frame(tongsinsa=c("SKT","KT","LGU+"),
sum=c(40,37,37))
onehosun
ggplot(data=onehosun,aes(x=tongsinsa, y= sum))+geom_col()
ggplot(data=hosun, aes(x =tongsinsa, y=hosun)) +geom_point()
ggplot(data=hosun, aes(x =tongsinsa, y=gatsu)) +geom_point()
hosun
ggplot(data=hosun, aes(x =tongsinsa, y=gatsu)) +geom_col()
ggplot(data=hosun, aes(x =gatsu)) +geom_bar()
ggplot(data=hosun, aes(x=gatsu)) +geom_bar()
#3호선 통신사 3사 비율
test %>% filter(회사명=="SKT" & 호선 =="3호선")
dim(test %>% filter(회사명=="SKT" & 호선 =="3호선")) #40개
dim(test %>% filter(회사명=="KT" & 호선 =="3호선"))#37개
dim(test %>% filter(회사명=="LGU+" & 호선 =="3호선"))#37개
#3호선 통신사 3사 비율
test %>% filter(회사명=="SKT" & 호선 =="2호선")
dim(test %>% filter(회사명=="SKT" & 호선 =="2호선")) #40개
dim(test %>% filter(회사명=="KT" & 호선 =="2호선"))#37개
dim(test %>% filter(회사명=="LGU+" & 호선 =="2호선"))#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()
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+"))
#3호선 대합실,승강장 wi-fi개수 몇개 있는지 알기
dim(test %>% filter(회사명 == "SKT" & 대합실 & 승강장 ))
dim(test %>% filter(회사명 == "KT" & 대합실 & 승강장 ))
dim(test %>% filter(회사명 == "LGU+" & 대합실 & 승강장 ))
#3호선 대합실,승강장 wi-fi개수 몇개 있는지 알기
dim(test %>% filter(회사명 == "SKT" & 호선=="3호선" & 대합실 & 승강장 ))
dim(test %>% filter(회사명 == "KT" & 호선=="3호선" & 대합실 & 승강장 ))
dim(test %>% filter(회사명 == "LGU+" & 호선=="3호선" & 대합실 & 승강장 ))
test %>% filter(회사명 == "SKT" & 호선=="3호선" & 대합실 & 승강장
test %>% filter(회사명 == "SKT" & 호선=="3호선" & 대합실 & 승강장)
test %>% filter(회사명 == "SKT" & 호선=="3호선" & 대합실 & 승강장)
View(부산지하철_와이파이)
install.packages("ggplot2")
library(ggplot2)
install.packages("dplyr")
library(dplyr)
install.packages("readxl")
library(readxl)
test<- read.csv("c:/gimalproject/부산지하철_와이파이.csv")
test
ggplot(data=test,aes(X=역사명,y=승강장)) +geom_col()
mung <- data.frame(tongsinsa=c("SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT"),
surang=c(12,16,6,8,9,10,5,6,7,7,6,5,4,6,6,7,7,8,7,6,6,6,6,5,13,6,6,6,6,5,6,6,6,6,6,6,7,6,6,3),
muung=c("다대포해수욕장","다대포항","낫개","신장림","장림","동매","신평","하단","당리","사하","괴정","대티","서대신","동대신","토성","자갈치","남포","중앙","부산역","초량","부산진","좌천","범일","범내골","서면","부전","양정","시청","연산","교대","동래","명륜","온천장","부산대","장전","구서","두실","남산","범어사","노포"
))
mung <- data.frame(tongsinsa=c("SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT"),
surang=c(12,16,6,8,9,10,5,6,7,7,6,5,4,6,6,7,7,8,7,6,6,6,6,5,13,6,6,6,6,5,6,6,6,6,6,6,7,6,6,3),
muung=c("다대포해수욕장","다대포항","낫개","신장림","장림","동매","신평","하단","당리","사하","괴정","대티","서대신","동대신","토성","자갈치","남포","중앙","부산역","초량","부산진","좌천","범일","범내골","서면","부전","양정","시청","연산","교대","동래","명륜","온천장","부산대","장전","구서","두실","남산","범어사","노포"
))
mung <- data.frame(tongsinsa=c("SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT"),
surang=c(12,16,6,8,9,10,5,6,7,7,6,5,4,6,6,7,7,8,7,6,6,6,6,5,13,6,6,6,6,5,6,6,6,6,6,6,7,6,6,3),
muung=c("다대포해수욕장","다대포항","낫개","신장림","장림","동매","신평","하단","당리","사하","괴정","대티","서대신","동대신","토성","자갈치","남포","중앙","부산역","초량","부산진","좌천","범일","범내골","서면","부전","양정","시청","연산","교대","동래","명륜","온천장","부산대","장전","구서","두실","남산","범어사","노포"
))
mung <- data.frame(tongsin=c("SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT","SKT"),
surang=c(12,16,6,8,9,10,5,6,7,7,6,5,4,6,6,7,7,8,7,6,6,6,6,5,13,6,6,6,6,5,6,6,6,6,6,6,7,6,6,3),
muung=c("다대포해수욕장","다대포항","낫개","신장림","장림","동매","신평","하단","당리","사하","괴정","대티","서대신","동대신","토성","자갈치","남포","중앙","부산역","초량","부산진","좌천","범일","범내골","서면","부전","양정","시청","연산","교대","동래","명륜","온천장","부산대","장전","구서","두실","남산","범어사","노포"
))
mung<-data.frame(surang=c(12,16,6,8,9,10,5,6,7,7,6,5,4,6,6,7,7,8,7,6,6,6,6,5,13,6,6,6,6,5,6,6,6,6,6,6,7,6,6,3),
muung=c("다대포해수욕장","다대포항","낫개","신장림","장림","동매","신평","하단","당리","사하","괴정","대티","서대신","동대신","토성","자갈치","남포","중앙","부산역","초량","부산진","좌천","범일","범내골","서면","부전","양정","시청","연산","교대","동래","명륜","온천장","부산대","장전","구서","두실","남산","범어사","노포"
))
ggplot(data=mung, aes(x=muung, y=surang)) +geom_col()
