Diwali

top_prods <- diwali |>
  group_by(Product_Category) |>
  count() |>
  ungroup() |>
  slice_max(n = 3, order_by = n)

diwali |>
  filter(Product_Category %in% top_prods$Product_Category) |>
  mutate(us_Amount = round(Amount*0.012,2)) |>
  group_by(Product_Category, Gender, `Age Group`) |>
summarize(size = n()) |>
  d3_nest(value_cols = "size") |>
  sund2b(showLabels = TRUE,rootLabel = ' ')

top_jobs <- diwali |>
  group_by(Occupation) |>
  count() |>
  arrange(desc(n)) |>
  ungroup() |>
  slice_head(n = 6)

df <- diwali |>
  filter(Occupation %in% top_jobs$Occupation) |>
  mutate(us_Amount = round(Amount*0.012,0)) |>
  drop_na() |>
  group_by(Occupation) |>
  summarise(sum = sum(us_Amount)) |>
  rbind(c("NA", 0)) |>
    mutate(sum = as.numeric(sum)) |>
  mutate(Occupation_2 = if_else(Occupation == "NA", NA, Occupation))

 df$Occupation <- factor(df$Occupation, levels = c("NA", "Hospitality", "Govt", "Banking", "Aviation", "Healthcare", "IT Sector"))
 
  
 gg_plot <- df |>
  ggplot(aes(x = Occupation, y = sum, fill = Occupation_2, color = Occupation_2)) +
  geom_col_interactive(width = 0.65, alpha = 0.5, aes(tooltip = paste0(Occupation,":\n",sum))) +
  coord_polar(theta = "y")+
  ylim(c(0, 200000))+
  xlab("") +
  ylab("Total Amount Spent (in USD)")+
   ggtitle("Total Diwali Spending (in USD)\n for Different Occupations")+
  geom_text(aes(y = 0, label = Occupation_2), hjust = 1.1, size = 3)+
  scale_color_discrete(na.value = "white")+
  theme_minimal()+
  theme(legend.position = "none", axis.text.y = element_blank(), plot.title = element_text(hjust = 0.5))
 
girafe(ggobj = gg_plot) |>
  girafe_options(opacity = 1, opts_tooltip(use_fill = TRUE))