gistfile1.txt

film <- mutate(film, Month = format(film$`Release Date`,'%b'))
c <- filter(film, film$Month == 'Dec'|film$Month == 'Sep'|film$Month == 'Nov'|film$Month == 'Oct')
c <- mutate(c, Timing = 2)
d <- filter(film, film$Month == 'May'|film$Month == 'Jun'|film$Month == 'Jul')
d <- mutate(d, Timing = 3)
e <- filter(film, film$Month == 'Mar'|film$Month == 'Apr')
e<- mutate(e, Timing = 4)
f <- filter(film, film$Month == 'Aug'|film$Month == 'Jan'|film$Month == 'Feb')
f<- mutate(f, Timing = 1)
b <- rbind(c,d,e,f)
film <- b
film$Timing <- as.factor(film$Timing)

y <- filter(film, film$`Worldwide Grosses` >= 1000000000)
y <- mutate(y, Billion = -1)
z <- filter(film, film$`Worldwide Grosses` >= 800000000 & film$`Worldwide Grosses` < 1000000000)
z <- mutate(z, Billion = 1)
v <- filter(film, film$`Worldwide Grosses` < 800000000 & film$`Worldwide Grosses` >= 531000000)
v <- mutate(v, Billion = 2)
j <- filter(film, film$`Worldwide Grosses` < 531000000)
j <- mutate(j, Billion = 3)
x <- rbind(y,z,v,j)
film <- x