Today

강의

R프로그램 시즌 2 7강

결과

스터디 내용

ADsP 3일차 & 문제 풀이

6. 실업률 그래프 reshape, tidyr, ggplot2

raw_df <- read.csv("C:\\Users\\park\\Downloads\\unemployment_rate.csv", header = T, fileEncoding =  'CP949')
head(raw_df)
summary(raw_df)

install.packages("reshape2")

library(tidyr)
library(reshape2)
library(ggplot2)

#### Reshape wide 한 data 를 long 하게 변경

df_m <- melt(raw_df, id.var = c("성별","연령계층별"))
head(df_m)

#### cleaning

df_m$year = substr(df_m$variable, 2, 5)
df_m$month = substr(df_m$variable, 8, 9)
head(df_m)

df_m$year_month = paste(df_m$year, df_m$month, sep = "-")
df_m$year_month = as.Date(paste(df_m$year_month, "-01", sep = ""))
head(df_m)

df_select = df_m[,c("성별","연령계층별","year_month", "value")]

summary(df_select)

7. 실업률2

df_cleaned$new_age_group = gsub("세|이상", "", df_cleaned$age_group)# x라 되어있는 것을 모두 y로 변경
df_cleaned$new_age_group = gsub("계", "Total", df_cleaned$new_age_group)

df_final = df_cleaned[, c("sex","new_age_group","year_month","value")]
df_final

df_20s = df_final[which(df_final$new_age_group == "20 - 29"),]
df_30s = df_final[which(df_final$new_age_group == "30 - 39"),]
df_40s = df_final[which(df_final$new_age_group == "40 - 49"),]
df_50s = df_final[which(df_final$new_age_group == "50 - 59"),]

plotF <- function(df, title){
  ggplot(df, aes(x = year_month, y = value, group = sex, colour = sex)) + 
    geom_point() + geom_line() + ggtitle(title)
}

ggplot(df_20s, aes(x = year_month, y = value, group = sex, colour = sex)) + geom_point() + geom_line()

plotF(df_20s, "20 - 29 실업률")
plotF(df_30s, "30 - 39 실업률")
plotF(df_40s, "40 - 49 실업률")
plotF(df_50s, "50 - 59 실업률")

Tomorrow

• adsp 4일치, R 8강 실습

Summary

• 통계청 실업률 데이터를 바탕으로 실습 진행 -> 20대 실업률 우상향 추이 확인