R Notebook

library(readr)
library(lubridate)
library(dplyr)
nypd <- read_csv("~/ShinyApps/madlan/nypd.csv")
nypd$year<-year(mdy(nypd$CMPLNT_FR_DT))
nypd<-nypd%>%filter(year>2005)
crime<-subset(nypd, !is.na(nypd$Latitude))
crime<-subset(crime, !is.na(crime$Longitude))
save(crime, file="crime.rda")

library(lubridate)
library(ggplot2)
library(dplyr)
load("crime.rda")
crime_table<-crime%>%group_by(OFNS_DESC)%>%summarize(n=sum(!is.na(year)))%>%arrange(desc(n))
crime_table

boro_table<-crime%>%group_by(BORO_NM)%>%summarize(n=sum(!is.na(year)))%>%arrange(desc(n))
#add population size
boro_table

crime%>%filter(LAW_CAT_CD=="FELONY")%>%group_by(BORO_NM)%>%summarize(n=sum(!is.na(year)))%>%arrange(desc(n))

man_fal%>%group_by(OFNS_DESC)%>%summarize(n=sum(!is.na(year)))%>%arrange(desc(n))