gistfile1.r

library(ggplot2)
library(dplyr)
library(reshape2)

df=structure(list(Year = c(2013L, 2012L, 2011L, 2010L, 2009L, 2008L, 
                            2007L, 2006L, 2005L, 2004L, 2003L, 2002L, 2001L, 2000L, 1999L, 
                            1998L, 1997L), 
                   City = structure(c(14L, 8L, 12L, 13L, 1L, 2L, 
                                      6L, 4L, 14L, 8L, 15L, 5L, 10L, 9L, 7L, 3L, 11L), 
                  .Label = c("Boston", "Chicago", "Dallas", "Houston", "Kansas City", "Long Beach", 
                            "Los Angeles", "Minneapolis", "New Orleans", "Orlando", "Philadelphia",
                            "Seattle", "St. Louis", "Toronto", "Vancouver"), class = "factor"), 
                   Zone = structure(c(2L, 1L, 3L, 1L, 2L, 1L, 3L, 1L, 2L, 1L, 
                                      3L, 1L, 2L, 1L, 3L, 1L, 2L), 
                  .Label = c("Central", "East", "West"), class = "factor"), 
                   Attendance = c(537L, 416L, 477L, 
                  475L, 473L, 474L, 409L, 358L, 430L, 370L, 334L, 230L, 254L, 
                  258L, 249L, 216L, 235L), Membership = c(1435L, 1471L, 1727L, 
                  1464L, 1331L, 1175L, 1130L, 788L, 888L, 884L, 839L, 907L, 
                  871L, 874L, 879L, 877L, 849L), Tracks = c(3L, 3L, 3L, 3L, 
                  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L)), 
              .Names = c("Year", "City", "Zone", "Attendance", "Membership", "Tracks"), 
              class = "data.frame", 
              row.names = c(NA, -17L))

df=df %>% 
  mutate(
       Proportion_Attending=Attendance/Membership,
       SEAttending=sqrt(Proportion_Attending*(1-Proportion_Attending)/Membership),
       Attendees_Per_Track = Attendance / Tracks,
       YearCity = paste(Year,City)) %>%
  select(
        -Tracks
    )    

df$Zone=factor(df$Zone,levels=c("East","Central","West"))

dfl=melt(df,id=c("YearCity","City","Zone","Year"))

p=ggplot(filter(dfl,!(variable %in% c("SEAttending"))),aes(x=YearCity,y=value,group=variable))
p=p+geom_line()
p=p+theme( axis.text.x  = element_text(angle=90, vjust=0.5))
p=p+facet_grid(variable~., scales="free_y")
p=p+theme(axis.title.x=element_blank(),axis.title.y=element_blank())
p
ggsave(plot=p,file="multi.png",width=4,height=8)

p=ggplot(df,aes(x=YearCity,y=Proportion_Attending,group=1,color=Zone))
p=p+geom_point()
p=p+geom_errorbar(width=.1,aes(ymin=Proportion_Attending-SEAttending,ymax=Proportion_Attending+SEAttending))
p=p+ylab("Attendance Rate")
p=p+theme( axis.text.x  = element_text(angle=90, vjust=0.5),legend.position="bottom",axis.title.x=element_blank())
p
ggsave(plot=p,file="cities.c.png",width=4,height=6)

dfs = df %>%
  group_by(Zone) %>%
  summarize(
            going=sum(Attendance),
            not_going=sum(Membership)-sum(Attendance),
            mu=going/(going+not_going),
            se=sqrt((mu*(1-mu))/(going+not_going))
            )



dfs$Zone=factor(dfs$Zone,levels=c("East","Central","West"))
p=ggplot(dfs,aes(x=Zone,y=mu,color=Zone)) 
p=p+geom_point(size=3)
p=p+geom_errorbar(width=.1,aes(ymin=mu-se,ymax=mu+se))
p=p+ylab("Attendance Rate")
p=p+theme( axis.text.x  = element_text(angle=90, vjust=0.5),legend.position="none")
p
ggsave(plot=p,file="attendance.c.png",width=4,height=4)