HW08

5.Plot places in administratice areas of Taiwan you have visited so far.

library(choroplethrAdmin1)

## Warning: package 'choroplethrAdmin1' was built under R version 3.2.5

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 3.2.5

taiwanm <- get_admin1_map("taiwan")
taiwanm$visit  <- ifelse(taiwanm$region %in% c("kao-hsiung hsien","pingtung","tainan","hsinchu","yilan",
             "keelung","t'ai-pei shih","taipei","chiayi","hualien" ,
             "nantou","taitung","miaoli","yunlin"), 1 , 0)

ggplot(taiwanm, aes(long, lat, group = group)) +
    geom_polygon(aes(fill = as.factor(visit)), color = "gray") +
    scale_fill_manual(values=c("white","green"),name="Visited",labels=c("No","Yes")) +
    theme_minimal()

Dates & Times 1.Assume that your total life span is 100 years. Find out how often your birthday falls on each day of the week.

table(weekdays(seq(as.Date("1994-10-22"), by = "1 years", length = 100)))

## 
## 星期一 星期二 星期三 星期五 星期六 星期日 星期四 
##     14     14     15     14     14     15     14

2.Reproduce the plot of calls for police assistances around 24 hours in New York City

library(ggplot2)
dta<-read.csv("calls_nyc.csv",h=T)
head(dta)

##   Hour Calls
## 1  0.5  1080
## 2  1.5   910
## 3  2.5   770
## 4  3.5   780
## 5  4.5   380
## 6  5.5   390

calls<-data.frame(Hour=dta$Hour,
            Calls=dta$Calls)
ggplot(data=dta,aes(x=Hour,y=Calls,group=1))+
geom_bar(width=1,stat="identity",fill="cyan",
        color="skyblue",alpha=0.2)+
geom_abline(intercept=mean(dta$Calls),slope = 0,
        size = 1,color="lightpink") +
coord_polar(theta="x",start=-pi/12) +
theme_bw()