autonomous_ <- rename(autonomous_, 번호 = X)
## 3-b. subway_ 의 열제목 이름변경하기
subway_ <- rename(subway_, 번호 = X)
autonomous_ <- rename(autonomous_, 날짜 = 기준일ID)
autonomous_ <- rename(autonomous_, 총인구수 = 총생활인구수)
############################### 4. 필요한 데이터 추출하기 (autonomous_)
autonomous_190601 <- autonomous_ %>%
filter(날짜 == '20190601') %>%
select(번호, 날짜, 시군구명, 총인구수)
View(autonomous_190601)
############################### 4. 필요한 데이터 추출하기 (autonomous_)
autonomous_190608 <- autonomous_ %>%
filter(날짜 == '20190608') %>%
select(번호, 날짜, 시군구명, 총인구수)
View(autonomous_190608)
autonomous_190608 <- autonomous_190608 %>%
filter(- 시군구명 == '서울시')
autonomous_190608 <- autonomous_190608 %>%
-filter(시군구명 == '서울시')
autonomous_190608 <- autonomous_190608 %>%
filter(-시군구명 == '서울시')
autonomous_190608 <- autonomous_190608 %>%
filter(시군구명 != '서울시')
autonomous_190608 <- autonomous_190608 %>%
filter(시군구명 != '서울시') %>% arrange(desc(총인구수))
View(autonomous_190608)
############################### 4. 필요한 데이터 추출하기 (autonomous_)
autonomous_190608 <- autonomous_ %>%
filter(날짜 == '20190608', 시군구명 != '서울시') %>%
select(번호, 날짜, 시군구명, 총인구수) %>%
arrange(desc(총인구수))
View(autonomous_190608)
subway_ <- rename(subway_, 승차 = 승차총승객수)
subway_ <- rename(subway_, 하차 = 하차총승객수)
############################### 5. 필요한 데이터 추출하기 (subway_)
subway_190608 <- subway_ %>%
filter(날짜 == '20190608') %>%
select(번호, 사용일자, 호선명, 역명, 승차, 하차) %>%
mutate(총승하차 = 승차 + 하차) %>%
arrange(desc(총승하차))
subway_ <- rename(subway_, 날짜 = 사용일자)
############################### 5. 필요한 데이터 추출하기 (subway_)
subway_190608 <- subway_ %>%
filter(날짜 == '20190608') %>%
select(번호, 사용일자, 호선명, 역명, 승차, 하차) %>%
mutate(총승하차 = 승차 + 하차) %>%
arrange(desc(총승하차))
############################### 5. 필요한 데이터 추출하기 (subway_)
subway_190608 <- subway_ %>%
filter(날짜 == '20190608') %>%
select(번호, 날짜, 호선명, 역명, 승차, 하차) %>%
mutate(총승하차 = 승차 + 하차) %>%
arrange(desc(총승하차))
View(subway_190608)
# Create data
autonomous_190608_chart <- data.frame(group=metro_4_All$역명, value=metro_4_All$승차)
# Create data
autonomous_190608_chart <- data.frame(group=autonomous_190608$시군구명, value=autonomous_190608$총인구수)
# Generate the layout. sizetype can be area or radius, following your preference on what to be proportional to value.
packing <- circleProgressiveLayout(autonomous_190608_chart$value, sizetype='area')
############################### 6. 그래프
install.packages("packcircles")
library(packcircles)
install.packages("viridis")
library(viridis)
library(viridis)
# Generate the layout. sizetype can be area or radius, following your preference on what to be proportional to value.
packing <- circleProgressiveLayout(autonomous_190608_chart$value, sizetype='area')
autonomous_190608_chart = cbind(autonomous_190608_chart, packing)
dat.gg <- circleLayoutVertices(packing, npoints=50)
# 1 -- Custom the color: whatever palette. (see ggplot2 section for more explanation)
ggplot() +
geom_polygon(autonomous_190608_chart = dat.gg, aes(x, y, group = id, fill=as.factor(id)), colour = "black", alpha = 0.6) +
scale_fill_manual(values = magma(nrow(autonomous_190608_chart))) +
geom_text(autonomous_190608_chart = autonomous_190608_chart, aes(x, y, size=value, label = group)) +
scale_size_continuous(range = c(1,4)) +
theme_void() +
theme(legend.position="none") +
coord_equal()
# 1 -- Custom the color: whatever palette. (see ggplot2 section for more explanation)
ggplot() +
geom_polygon(autonomous_190608_chart = dat.gg, aes(x, y, group = id, fill=as.factor(id)), colour = "black", alpha = 0.6) +
scale_fill_manual(values = magma(nrow(autonomous_190608_chart))) +
geom_text(autonomous_190608_chart = autonomous_190608_chart, aes(x, y, size=value, label = group)) +
scale_size_continuous(range = c(1,4)) +
theme_void() +
theme(legend.position="none") +
coord_equal()
# Create data
data <- data.frame(group=autonomous_190608$시군구명, value=autonomous_190608$총인구수)
# Generate the layout. sizetype can be area or radius, following your preference on what to be proportional to value.
packing <- circleProgressiveLayout(data$value, sizetype='area')
data = cbind(data, packing)
dat.gg <- circleLayoutVertices(packing, npoints=50)
# 1 -- Custom the color: whatever palette. (see ggplot2 section for more explanation)
ggplot() +
geom_polygon(data = dat.gg, aes(x, y, group = id, fill=as.factor(id)), colour = "black", alpha = 0.6) +
scale_fill_manual(values = magma(nrow(data))) +
geom_text(data = data, aes(x, y, size=value, label = group)) +
scale_size_continuous(range = c(1,4)) +
theme_void() +
theme(legend.position="none") +
coord_equal()
# 1 -- Custom the color: whatever palette. (see ggplot2 section for more explanation)
ggplot() +
geom_polygon(data = dat.gg, aes(x, y, group = id, fill=as.factor(id)), colour = "black", alpha = 0.6) +
scale_fill_manual(values = magma(nrow(autonomous_190608_chart))) +
geom_text(data = autonomous_190608_chart, aes(x, y, size=value, label = group)) +
scale_size_continuous(range = c(1,4)) +
theme_void() +
theme(legend.position="none") +
coord_equal()
# 1 -- Custom the color: whatever palette. (see ggplot2 section for more explanation)
autonomous_190608_chart_circle <- ggplot() +
geom_polygon(data = dat.gg, aes(x, y, group = id, fill=as.factor(id)), colour = "black", alpha = 0.6) +
scale_fill_manual(values = magma(nrow(autonomous_190608_chart))) +
geom_text(data = autonomous_190608_chart, aes(x, y, size=value, label = group)) +
scale_size_continuous(range = c(1,4)) +
theme_void() +
theme(legend.position="none") +
coord_equal()
autonomous_190608_chart_circle
autonomous_190608_chart_circle
## 7-a. 지하철 호선명 데이터 프레임 생성
subway_190608 %>% group_by(호선명)
## 7-a. 지하철 호선명 데이터 프레임 생성
subway_190608 %>%
group_by(호선명) %>%
summarise(mean_총 = mean(총승하차),
n = n())
## 7-a. 지하철 호선명 데이터 프레임 생성
subway_190608_chart <- subway_190608 %>%
group_by(호선명) %>%
summarise(mean_총 = mean(총승하차),
n = n())
View(subway_190608_chart)
## 7-a. 지하철 호선명 데이터 프레임 생성
subway_190608_chart <- subway_190608 %>%
group_by(호선명) %>%
summarise(mean_총 = mean(총승하차),
n = n()) %>%
arrange(desc(mean_총))
View(subway_190608_chart)
## 7-a. 지하철 호선명 데이터 프레임 생성
subway_190608_chart <- subway_190608 %>%
group_by(호선명) %>%
summarise(mean_총 = mean(총승하차)) %>%
arrange(desc(mean_총))
View(subway_190608_chart)
subway_190608_chart <- as.data.frame(subway_190608_chart)
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총))
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총))
subway_190608_chart_graph
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col() + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(desc) + coord_flip()
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes) + coord_flip()
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총))
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = mmean_총)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = mean_총)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
y = reorder(subway_190608_chart$mean_총)) +
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = reorder(subway_190608_chart$mean_총))) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = reorder(subway_190608_chart$호선명),
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명))
subway_190608_chart_graph
## 7-b.
subway_190608_chart_graph <- ggplot(data = subway_190608_chart,
aes(x = subway_190608_chart$호선명,
y = subway_190608_chart$mean_총)) +
geom_col(aes(fill = 호선명)) + coord_flip()
subway_190608_chart_graph
View(subway_190608_chart)
############################### 8.
subway_190608_2호선 <- subway_190608 %>%
filter(호선명 == '2호선')
View(subway_190608_2호선)
############################### 8.
subway_190608_2호선 <- subway_190608 %>%
filter(호선명 == '2호선') %>%
arrange(desc(총승하차))
View(subway_190608_2호선)
############################### 8.
subway_190608_2호선 <- subway_190608 %>%
filter(호선명 == '2호선')
View(subway_190608_2호선)
subway_190608_3호선 <- subway_190608 %>%
filter(호선명 == '3호선')
View(subway_190608_3호선)
############################### 8.
subway_190608_2 <- subway_190608 %>%
filter(호선명 == '2호선')
View(subway_190608_2)
View(subway_190608_2)
subway_190608_3 <- subway_190608 %>%
filter(호선명 == '3호선')
View(subway_190608_3)
subway_190608_1 <- subway_190608 %>%
filter(호선명 == '1호선')
View(subway_190608_1)
subway_190608_4 <- subway_190608 %>%
filter(호선명 == '4호선')
View(subway_190608_4)
subway_190608_4 <- subway_190608 %>%
filter(호선명 == '4호선') %>% head(5)
View(subway_190608_4)
############################### 8.
subway_190608_2 <- subway_190608 %>%
filter(호선명 == '2호선') %>% head(5)
View(subway_190608_2)
subway_190608_1 <- subway_190608 %>%
filter(호선명 == '1호선') %>% head(5)
View(subway_190608_1)
subway_190608_3 <- subway_190608 %>%
filter(호선명 == '3호선') %>% head(5)
View(subway_190608_3)
subway_190608_4 <- subway_190608 %>%
filter(호선명 == '4호선') %>% head(5)
View(subway_190608_4)
subway_190608_Seoul-Incheon <- subway_190608 %>%
filter(호선명 == '경인선') %>% head(5)
subway_190608_Seoul_Incheon <- subway_190608 %>%
filter(호선명 == '경인선') %>% head(5)
View(subway_190608_Seoul_Incheon)
address <- read_excel("서울교통공사 지하철역 주소 및 전화번호 정보.xlsx")
address_c <- write.csv(address, file = "address.csv")
address_ <- read.csv("address.csv", stringsAsFactors = F)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
View(address_)
address <- read_excel("서울교통공사 지하철역 주소 및 전화번호 정보.xlsx")
address_c <- write.csv(address, file = "address.csv")
address_ <- read.csv("address.csv", stringsAsFactors = F) #복사본
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
View(address_)
## 3-c. address_ 의 열제목 이름변경하기
address_ <- rename(address_, 번호 = X)
subway_190608 <- subway_ %>%
filter(날짜 == '20190608') %>%
select(날짜, 호선명, 역명, 승차, 하차) %>%
mutate(총승하차 = 승차 + 하차) %>%
arrange(desc(총승하차))
autonomous_190608 <- autonomous_ %>%
filter(날짜 == '20190608', 시군구명 != '서울시') %>%
select(날짜, 시군구명, 총인구수) %>%
arrange(desc(총인구수))
## 8-a. 2호선
subway_190608_2 <- subway_190608 %>%
filter(호선명 == '2호선') %>% head(5)
## 8-b. 1호선
subway_190608_1 <- subway_190608 %>%
filter(호선명 == '1호선') %>% head(5)
## 8-c. 4호선
subway_190608_4 <- subway_190608 %>%
filter(호선명 == '4호선') %>% head(5)
## 8-d. 경인선
subway_190608_Seoul_Incheon <- subway_190608 %>%
filter(호선명 == '경인선') %>% head(5)
## 8-e. 3호선
subway_190608_3 <- subway_190608 %>%
filter(호선명 == '3호선') %>% head(5)
address_subway_2 <- address_ %>%
filter(호선 == '2호선',
역명 == '홍대입구',
역명 == '강남',
역명 == '잠실(송파구청)',
역명 == '신림',
역명 == '신도림') %>%
select(호선, 역명, 구주소)
View(address_subway_2)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 == '홍대입구' &
역명 == '강남',
역명 == '잠실(송파구청)' &
역명 == '신림' &
역명 == '신도림') %>%
select(호선, 역명, 구주소)
View(address_subway_2)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 == '홍대입구' &
역명 == '강남' &
역명 == '잠실(송파구청)' &
역명 == '신림' &
역명 == '신도림') %>%
select(호선, 역명, 구주소)
View(address_subway_2)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 == '홍대입구') %>%
select(호선, 역명, 구주소)
View(address_subway_2)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 %in% c('홍대입구', '강남', '잠실(송파구청)', '신림', '신도림')) %>%
select(호선, 역명, 구주소)
View(address_subway_2)
View(subway_190608_1)
View(subway_190608_4)
View(subway_190608_3)
address <- read_excel("서울교통공사 지하철역 주소 및 전화번호 정보.xlsx")
address_c <- write.csv(address, file = "address.csv")
address_ <- read.csv("address.csv", stringsAsFactors = F) #복사본
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 %in% c('홍대입구', '강남', '잠실(송파구청)', '신림', '신도림')) %>%
select(호선, 역명, 구주소)
## 3-c. address_ 의 열제목 이름변경하기
address_ <- rename(address_, 번호 = X)
## 9-a. subway_190608_1 에 있는 역의 주소만 추출
address_subway_1 <- address_ %>%
filter(호선 == '1호선' &
역명 %in% c('서울역', '종로3가', '종각', '종로5가', '청량리(서울대입구)')) %>%
select(호선, 역명, 구주소)
View(address_subway_1)
## 9-a. subway_190608_4 에 있는 역의 주소만 추출
address_subway_4 <- address_ %>%
filter(호선 == '4호선' &
역명 %in% c('명동', '혜화', '수유(강북구청)', '회현(남대문시장)', '미아사거리')) %>%
select(호선, 역명, 구주소)
View(address_subway_4)
## 9-a. subway_190608_4 에 있는 역의 주소만 추출
address_subway_4 <- address_ %>%
filter(호선 == '4호선' &
역명 %in% c('명동', '혜화', '수유(강북구청)', '회현(남대문시장)', '미아사거리')) %>%
select(호선, 역명, 구주소)
View(address_subway_4)
## 9-a. subway_190608_4 에 있는 역의 주소만 추출
address_subway_4 <- address_ %>%
filter(호선 == '4호선' &
역명 %in% c('명동', '혜화', '수유(강북구청)', '회현(남대문시장)', '미아사거리')) %>%
select(호선, 역명, 구주소)
View(address_subway_4)
address <- read_excel("서울교통공사 지하철역 주소 및 전화번호 정보.xlsx")
address_c <- write.csv(address, file = "address.csv")
address_ <- read.csv("address.csv", stringsAsFactors = F) #복사본
## 3-c. address_ 의 열제목 이름변경하기
address_ <- rename(address_, 번호 = X)
## 9-a. subway_190608_2 에 있는 역의 주소만 추출
address_subway_2 <- address_ %>%
filter(호선 == '2호선' &
역명 %in% c('홍대입구', '강남', '잠실(송파구청)', '신림', '신도림')) %>%
select(호선, 역명, 구주소)
## 9-a. subway_190608_1 에 있는 역의 주소만 추출
address_subway_1 <- address_ %>%
filter(호선 == '1호선' &
역명 %in% c('서울역', '종로3가', '종각', '종로5가', '청량리(서울대입구)')) %>%
select(호선, 역명, 구주소)
## 9-a. subway_190608_4 에 있는 역의 주소만 추출
address_subway_4 <- address_ %>%
filter(호선 == '4호선' &
역명 %in% c('명동', '혜화', '수유(강북구청)', '회현(남대문시장)', '미아사거리')) %>%
select(호선, 역명, 구주소)
View(address_subway_4)
## 9-a. subway_190608_3 에 있는 역의 주소만 추출
address_subway_3 <- address_ %>%
filter(호선 == '3호선' &
역명 %in% c('고속터미널', '연신내', '신사', '남부터미널(예술의전당)', '압구정')) %>%
select(호선, 역명, 구주소)
View(address_subway_3)
View(autonomous_190608)
View(subway_190608)
View(address_subway_3)
## 10-a. 2호선
subway_And_address_2 <- left_join(subway_190608_2, address_subway_2, by = "역명")
View(subway_And_address_2)
subway_And_address_2 <- subway_And_address_2 %>%
select(날짜, 호선명, 역명, 총승하차, 구조사)
View(subway_And_address_2)
subway_And_address_2 <- subway_And_address_2 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_2)
## 10-b. 1호선
subway_And_address_3 <- left_join(subway_190608_3, address_subway_3, by = "역명")
subway_And_address_3 <- subway_And_address_3 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_3)
## 10-c. 4호선
subway_And_address_4 <- left_join(subway_190608_4, address_subway_4, by = "역명")
subway_And_address_4 <- subway_And_address_4 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_4)
## 10-d. 3호선
subway_And_address_3 <- left_join(subway_190608_3, address_subway_3, by = "역명")
subway_And_address_3 <- subway_And_address_3 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_3)
View(subway_And_address_2)
View(subway_And_address_3)
View(subway_And_address_4)
View(subway_And_address_3)
## 10-b. 1호선
subway_And_address_1 <- left_join(subway_190608_1, address_subway_1, by = "역명")
subway_And_address_1 <- subway_And_address_1 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_1)
View(subway_And_address_4)
View(subway_And_address_3)
## 10-b. 1호선
subway_And_address_1 <- left_join(subway_190608_1, address_subway_1, by = "역명")
subway_And_address_1 <- subway_And_address_1 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_1)
View(address_subway_1)
## 10-b. 1호선
subway_And_address_1 <- left_join(subway_190608_1, address_subway_1, by = "역명")
subway_And_address_1 <- subway_And_address_1 %>%
select(날짜, 호선명, 역명, 총승하차, 구주소)
View(subway_And_address_1)
View(autonomous_190608)
View(autonomous_190608)
############################### 11. 전체 데이터 합치기
subway_And_address_All <- bind_rows(subway_190608_2, subway_190608_1, subway_190608_4, subway_190608_3)
View(subway_And_address_All)
subway_And_address_All <- subway_And_address_All %>% arrange(desc(총승하차))
View(subway_And_address_All)
############################### 11. 전체 데이터 합치기
subway_And_address_All <- bind_rows(subway_And_address_2, subway_And_address_1, subway_And_address_4, subway_And_address_3)
subway_And_address_All <- subway_And_address_All %>% arrange(desc(총승하차))
View(subway_And_address_All)
View(autonomous_190608)
View(address_)
## 2-c. 복사본 확인하기
View(autonomous_)
View(autonomous_190608)
View(subway_190608_2호선)
View(autonomous_)
## 6-d. [결과] 자치구별 원으로 된 표
autonomous_190608_chart_circle
View(subway_)
View(subway_190608)
View(address_)
View(subway_190608_2)
View(subway_190608_1)
View(subway_190608_4)
View(subway_190608_3)
View(address_subway_2)
View(address_subway_1)
View(address_subway_4)
View(address_subway_3)
View(subway_And_address_2)
View(subway_And_address_1)
View(subway_And_address_4)
View(subway_And_address_3)
View(subway_And_address_All)
View(address_subway_1)
autonomous_190608_chart = cbind(autonomous_190608_chart, packing)
