• It is in movie studios’ interest to ensure that their films generate revenue, in order to build funds to produce more movies.
• Studios engage in significant market research to learn what types of movies will gross the most money in the future. Audiences’ interest in different genres is one such factor.

• For this project I used a data set published by Rounak Banik on Kaggle featuring data on more than 6,000 movies released from 1986 to 2016. This includes information on genre, year released, and gross box office revenue.
• With this data, we can ask certain questions like, “Will a movie generally gross more revenue if it is an animation movie or a drama?”

• For the year 2016, let’s calculate the mean gross revenue for animation movies and dramas.
• This helps us see that the animation genre will generally yield more revenue.

library(dplyr)
movieData <- read.csv("movies.csv", header=TRUE)
movieData <- movieData %>% filter(genre %in% c("Animation", "Drama") & year==2016)
aggregate(gross ~ genre, data=movieData, FUN=mean)

##       genre     gross
## 1 Animation 135826391
## 2     Drama  14249386

Charting all genres helps us get the full picture over time.

• My shiny app shows this chart but allows the user to select which genres they would like to see. They can easily compare two genres without seeing a crowded chart.
• They can also choose between median and mean for the statistic being charted. This is helpful because a few blockbuster movies can skew the mean revenue statistic upward. Using median helps for envisioning what a typical movie might yield.
• You can find my app at: https://petergranville.shinyapps.io/DDPCourseProject/