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starting_project_2_rapp.md

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Sketch

OLD OUTDATE SKETCH

NEW UPDATED SKETCH

Plot 1

Code

#Boxplot test us_gross 
boxplot_test <- df_movies_raw %>% 
  mutate(us_gross = us_gross/1000000) %>% 
  mutate(release_year = as.factor(release_year)) %>% 
  group_by(release_year) %>%
  ggplot( aes(x=release_year, us_gross))+
  geom_boxplot()+
  ggtitle(paste0(usd_box, " VS. ", year))+
  xlab(year)+
  ylab(usd_box)+
  scale_y_continuous(labels = dollar)+
  theme_bw()+ 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
                    panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))

Plot

Plot 1 Will show a box plot of each of the year in one of the four metrics of box office/profit/bits/budget reported in gross or adjusted for inflation. However, it only shows gross box-office Hover tip needs to be added because most of the fun is looking at the outlier cases.

Plot 2

Code

#line dotplot median boxoffic test us_gross 
median_line_test <- df_movies_raw %>% 
  mutate(us_gross = us_gross/1000000) %>% 
  group_by(release_year) %>%
  mutate(median_metric = median(us_gross)) %>% 
  ggplot(aes(x=release_year, y=median_metric))+
  geom_line()+
  geom_point()+
  ggtitle(paste0(usd_box_median, " VS. ", year))+
  xlab(year)+
  ylab(usd_box_median)+
  scale_y_continuous(labels = dollar)+
  theme_bw()+ 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))

Plot

Plot 2 Will show the median line of one of the four metrics for movies for each year and reported in gross or adjusted for inflation. However, due to time limitation only the default of gross and box-office has been implemented.

LAST MINUTE UPDATE: we had a last-minute change of heart and decided to change our sketch and swap plot 2 to a top 20 bar chart of one of the four metrics and reported in gross or adjusted instead of the median line chart. Due to time limitation there has not been an opportunity to write test code and the code above is outdated.

Plot 3

Code

movies = list("Alice in Wonderland", "Despicable Me", "Easy A")

movie_comp_bar <-df_movies_raw %>% 
  mutate(us_gross = us_gross/1000000) %>% 
  filter(title %in% movies) %>% 
  ggplot(aes(x=title,y=us_gross))+
  geom_bar(stat="identity", position="dodge")+
  ggtitle(paste0("Comparison Movie Title(s) for ", usd_box))+
  xlab("Movie Title(s)")+
  ylab(usd_box)+
  scale_y_continuous(labels = dollar)+
  theme_bw()+ 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))

Plot

Plot 3 Will be a bar chart (potentially swap to another type of chart) that the user can input into search bar above to compare the movies and it will show the metric selected and reporting type from the radio button at the top of the screen above plot 1. A hover tooltip that shows the other metrics should be included to make the analysis tool more robust. The filter list from the search bar functionality is off to a good start and it will not take much more to get it going.

LAST MINUTE MINOR CHANGE: we decided to swap the code from a vertical bar chart to a horizontal bar chart.