library(readr)
library(dplyr)
library(knitr)
VoterData<-read_csv("/Users/juliushunte/Downloads/VOTER_Survey_July17_Release1-csv copy.csv")
urbanreligon<-VoterData%>%
 mutate(Demographics = ifelse(urbancity_baseline==1,"City",
                        ifelse(urbancity_baseline==2,"Suburb",
                        ifelse(urbancity_baseline==3,"Town",
                        ifelse(urbancity_baseline==4,"Rural Area",
                        ifelse(urbancity_baseline==5,"Other",NA))))),
 ft_muslims = ifelse(ft_muslim_2017==997,NA,ft_muslim_2017))%>%
select(Demographics,ft_muslims)

urbanreligon%>%
  filter(Demographics=="Suburb"|
           Demographics=="Rural Area")%>%
  group_by(Demographics)%>%
  summarise(ft_muslims = mean(ft_muslims,na.rm=TRUE))%>%
  kable()
Demographics ft_muslims
Rural Area 43.26636
Suburb 50.81413 
library(ggplot2)
urbanreligon%>%
  ggplot()+
  geom_histogram(aes(x=ft_muslims),fill="green")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 3257 rows containing non-finite values (stat_bin).

urbanreligon%>%
  filter(Demographics=="Suburb")%>%
  ggplot()+
  geom_histogram(aes(x=ft_muslims),fill="orange")+
  geom_vline(aes(xintercept=mean(urbanreligon$ft_muslims,na.rm = TRUE)))+
  ggtitle("Feelings towards Muslims stronger in Suburb as opposed to Rural areas")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 1205 rows containing non-finite values (stat_bin).