Ratio of baby diapers sale to adult diapers sale

2022_11_10_population_collapse.R

library(tidyverse)
library(readxl)
library(MetBrewer)
theme_set(ggthemes::theme_clean())

setwd("/Users/harshvardhan/Desktop/Dump/diapers/")

# its funny how something so simple requires such ninja skills
# 1. Data from Statista is sometimes in millions, sometimes in billions
# 2. You cannot download more than three countries of data at a time
# 3. Even if you have the premium (Thanks UTK for the Statista Premium access! Libraries are best)

# babies come in crying loud!
baby = read_excel("data.xlsx", sheet = "Baby Diapers") %>% 
   janitor::clean_names() %>% 
   pivot_longer(!year, names_to = "country", values_to = "baby") %>% 
   mutate(baby = as.numeric(baby),
          year = as.numeric(year))

baby

# adults go out silently on a life support, sed...
adult = read_excel("data.xlsx", sheet = "Incontinence") %>% 
   janitor::clean_names() %>% 
   pivot_longer(!year, names_to = "country", values_to = "adult") %>% 
   mutate(adult = as.numeric(adult),
          year = as.numeric(year))

adult

# baby + adult = huggies
diapers = inner_join(baby, adult, by = c("year", "country")) %>% 
   pivot_longer(!c(year, country), names_to = "type", values_to = "volume") %>% 
   mutate(volume = as.numeric(volume))

diapers %>% 
   garlic::show_in_excel()

countries = unique(diapers$country)

# ggplot2
diapers %>% 
   filter(country == "india") %>% 
   ggplot(aes(x = year, y = volume, fill = type)) +
   geom_bar(stat = "identity", position = position_dodge(), alpha = 0.75) +
   #scale_fill_discrete(labels = c("Adult", "Baby")) +
   scale_fill_manual(labels = c("Adult", "Baby"), 
                     values = met.brewer("Java", 2)) + #Java is okay
   #MetBrewer::scale_color_met_d("VanGogh3") +
   labs(x = "Year", y = "Sales in million USD",
        fill = "Type")




plot_country = function(oc)
{
   p = diapers %>% 
      filter(country == oc) %>% 
      ggplot(aes(x = year, y = volume, fill = type)) +
      geom_bar(stat = "identity", position = position_dodge(), alpha = 0.75) +
      
      # See MetBrewer::colorblind_palettes
      scale_fill_manual(labels = c("Adult Diapers", "Baby Diapers"), 
                        #Java is okay
                        values = met.brewer("Java", 2)) +
      
      scale_x_continuous(breaks=seq(2014, 2027, 1)) +
      labs(x = "Year", y = "Sales in million USD",
           fill = "Type", title = toupper(oc))
   ggsave(paste0("plots/", oc, ".png"), plot = p)
   return(p)
}

plot_country("china")

lapply(countries, plot_country)