install.packages("ggplot2")
library(ggplot2)
# mpg 데이터가 ggplpt2 패키지 내장데이터
ggplot(
  data = mpg,
  aes(x=displ,y=hwy)
)+geom_point()+xlim(3,6)+ylim(10,30)
# [1] 건강보험심사 평가원 보건의료 빅데이터 개방시스템에서
# 18000여개의 관찰치와 8개의 변수가 있는 대장암  환자데이터를 통해 가장 많은 대장암이 발생하는 연령대를 
# 그래프를 통해 표현하시오.
# step 1
cancer <- read.csv("https://www.dropbox.com/s/dw59m4q1vaqwayl/example_cancer.csv?dl=1")
head(cancer)
# step 2
class(cancer)
str(cancer)
# step 3 : 연령대별 도수 (= 구간별갯수) 값 구하기
degree_of_age <- table(cut(cancer$age,breaks=(1:8)*10))
# step 4 : 열값의 이름변경
head(degree_of_age)
rownames(degree_of_age) <- 
  c('10대','20대','30대','40대','50대','60대','70대')
head(degree_of_age)

# step 5 : 시각화
ggplot(
  data = cancer,
  aes(x=age)
)+geom_freqpoly(
  binwidth=10,size=1.4,color='red'
)
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