install.packages("ggplot2")
library(ggplot2)
library(ggplot2)
library(ggplot2)''
library(ggplot2)
library(ggplot2)
install.packages("foreign")
library(foreign)
library(dplyr)
install.packages("dplyr")
library(dplyr)
install.packages("readxl")
install.packages("readxl")
ggplot(data = mpg, aes(x = displ, y = hwy)) + geom_point()
ride <- read.csv("ride.csv")
View(ride)
dim(ride)
qplot(ride$ownership)
ride <- read.csv("ride.csv")
ride <- read.csv("ride.csv")
View(ride)
View(ride)
ride <- read.csv("ride.csv")
View(ride)
table(ride$ownership)
class(ride$ownership)
table(ride$people)
table(ride$people)
ride$people <- ifelse(ride$people == 9, NA, ride$people)
table(ride$people)
table(ride$people)
ride$people <- ifelse(ride$people == 9, NA, ride$people)
table(ride$people)
table(is.na(ride$people))
table(ride$people)
ride$people <- ifelse(ride$people == 1, "people", "nopeople")
table(ride$people)
qplot(ride$people)
table(ride$fee)
table(ride$fee)
table(is.na(ride$fee))
ride$fee <- ifelse(ride$fee == 1, "free", "fee")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 2, "free", "fee")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 1, "free", "fee")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 1, "free", "charge")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 3, "free", "charge")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 1, "free", "charge")
table(ride$fee)
ride$fee <- ifelse(ride$fee == 1, "fee", "free")
table(ride$fee)
table(ride$fee)
table(ride$ownership)
table(ride$cradle)
summary(ride$ownership)
qplot(ride$ownership)
table(is.na(ride$ownership))
ride$ownership <- ifelse(ride$ownership == 9999, NA, ride$ownership)
table(is.na(ride$ownership))
ride$fee <- ifelse(ride$fee == 1, "fee", "free")
table(ride$fee)
table(is.na(ride$ownership))
table(ride$Bicycle.Rental.Shop)
table(ride$address)
list_region <- data.frame(address = c(1:9),
region = c("안산시",
"오산시",
"수원시",
"시흥시",
"부천시",
"고양시",
"과천시",
"양평군",
"연천군",
))
list_region <- data.frame(address = c(1:9),
region = c("안산시",
"오산시",
"수원시",
"시흥시",
"부천시",
"고양시",
"과천시",
"양평군",
"연천군"))
list_region
region_own <- ride %>%
group_by(address, ownership) %>%
summarise(n = n ())
region_own
View(region_own)
View(region_own)
View(region_own)
region_own <- ride %>%
group_by(address, ownership) %>%
summarise(n = n ()) %>%
mutate(tot_group = sum(n)) %>%
mutate(pct = round(n/tot_group*100, 2))
region_own
ggplot(data = region_own, aes(x = address, y = ownership))+geom_col()+coord_flip()
ggplot(data = list_region, aes(x = address, y = ownership))+geom_col()+coord_flip()
df <- ride %>%
filter(address == "경기도 안산시") %>%
group_by(manufacturer) %>%
summarise(mean_own = mean(own)) %>%
arrange(desc(mean_own)) %>%
head(5)
df <- ride %>%
filter(address == "경기도 안산시") %>%
group_by(Bicycle.Rental.Shop) %>%
summarise(mean_own = mean(own)) %>%
arrange(desc(mean_own)) %>%
head(5)
df <- ride %>%
filter(address == "경기도 안산시") %>%
group_by(Bicycle.Rental.Shop) %>%
summarise(mean_own = mean(ownership)) %>%
arrange(desc(mean_own)) %>%
head(5)
df
list_region
welfare <- left_join(welfare, list_region, id = "address")
ownership <- left_join(ownership, list_region, id = "address")
list_region <- data.frame(code_region = c(1:9),
region = c("안산시",
"오산시",
"수원시",
"시흥시",
"부천시",
"고양시",
"과천시",
"양평군",
"연천군"))
list_region
address <- left_join(address, list_region, id = "code_region")
list_region <- data.frame(code_region = c(1:9),
region = c("경기도 안산시",
"경기도 오산시",
"경기도 수원시",
"경기도 시흥시",
"경기도 부천시",
"경기도 고양시",
"경기도 과천시",
"경기도 양평군",
"경기도 연천군"))
list_region
address <- left_join(address, list_region, id = "code_region")
ride <- left_join(ride, list_region, id="code_region")
ride <- left_join(ride, list_region, id = "code_region")
ride %>% select(code_region, address) %>% head
ifelse(ride$fee = 무료, "OK", "NO")
ride$test <- ifelse(ride$fee = 무료, "OK", "NO")
ride$test <- ifelse(ride$fee >= 무료, "OK", "NO")
ride$test <- ifelse(ride$fee >= 유료, "OK", "NO")
ride <- read.csv("ride.csv")
View(ride)
ride <- read.csv("ride.csv")
View(ride)
ride$test <- ifelse(ride$fee >= fee, "OK", "NO")
ride <- read.csv("ride.csv")
View(ride)
list_region <- data.frame(code_region = c(1:9),
region = c("경기도 안산시",
"경기도 오산시",
"경기도 수원시",
"경기도 시흥시",
"경기도 부천시",
"경기도 고양시",
"경기도 과천시",
"경기도 양평군",
"경기도 연천군"))
list_region
region_own <- ride %>%
group_by(address, ownership) %>%
summarise(n = n ()) %>%
mutate(tot_group = sum(n)) %>%
mutate(pct = round(n/tot_group*100, 2))
region_own
ggplot(data = list_region, aes(x = address, y = ownership))+geom_col()+coord_flip()
ggplot(data = list_region, aes(x = address, y = ownership)) +   geom_col() +   coord_flip()
ride <- left_join(ride, list_region, id = "code_region")
ride %>% select(code_region, region) %>% head
ride %>% select(address, region) %>% head
ride %>% select(address, ownership) %>% head
ride %>% select(address, ownership) %>% head(300)
ride <- read.csv("ride.csv")
View(ride)
ride %>% select(address, ownership) %>% head(300)
qplot(ride$address)
summary(ride)
ride %>% select(address, ownership) %>% summary(300)
ride %>% select(address) %>% summary(300)
table(ride$fee)
class(ride$address)
summary(ride$address)
table(is.na(ride$address))
table(ride$fee)
qplot(ride$fee)
fird %>% filter(fee == "무료")
fird %>% filter(fee == 무료)
ride %>% filter(class == free)
ride %>% filter(class == "free")
ride %>% select(fee, repair)
ggplot(data = ride, aes(x= ownership, y = cradle )) + geom_line()
ggplot(data = ride, aes(x= fee, y = repair )) + geom_line()
ggplot(data = ride, aes(x= address, y = fee )) + geom_line()
ggplot(data = ride, aes(x = address, y = fee)) + geom_boxplot()
str(ride)
summary(ride$fee)
hist(ride$fee)
hist(ride$cradle)
table(ride$fee)
table(is.na(ride$fee))
address_income <- ride %>%
filter(!is.na(income)) %>%
group_by(address) %>%
summarise(mean_income = mean(income))
address_fee <- ride %>%
filter(!is.na(fee)) %>%
group_by(address) %>%
summarise(mean_income = mean(fee))
summary(ride$fee)
table(ride$fee)
qplot(ride$fee)
