SFCrimeclock

#read in SF crime data is at https://www.kaggle.com/c/sf-crime/data
mydata = read.csv("train.csv") 
library(dplyr)

#break up times

mydata$Year <- year(mydata$Dates)
mydata$Month <- month(mydata$Dates)
mydata$Hour <- hour(mydata$Dates)

mydata$Weekend <- mydata$DayOfWeek %in% c("Saturday", "Sunday")

mydata$TimeOfDay <- cut(mydata$Hour, 
                        c(0, 6, 12, 18, 24), 
                        labels = c("Overnight", "Morning", "Afternoon", "Evening"),
                        right = FALSE)

#get one popular crime type
larcen <- filter(mydata,  Category == "LARCENY/THEFT")

#make a graph of it

ggplot(larcen, aes(x = Hour, fill = DayOfWeek)) +
  geom_histogram(breaks = seq(0, 24), width = 1, colour = "blue") + 
  coord_polar(start = 0) +
  theme_minimal() +
  scale_fill_brewer()  +  ylab("Thefts Number")+
  scale_x_continuous("", limits = c(0, 24), breaks = seq(0, 24),
                     labels = seq(0, 24))+
    ggtitle("SF Thefts per Hour and Day")

    ggsave("theftClock.png")