Lab 5

library(completejourney)
library(tidyverse)
transactions <- transactions_sample
promotions <- promotions_sample

demographics %>%  
  inner_join(transactions, by = "household_id") %>% 
  inner_join(coupon_redemptions, by = "household_id") %>% 
  group_by(income, day = lubridate::wday(redemption_date, label = TRUE)) %>%
  summarize(Total_redemptions = n()) %>% 
  ggplot(aes(x = Total_redemptions, y = income, color = income)) +
  geom_point() + 
  facet_wrap(~ day, nrow = 2) +
  scale_x_continuous( name = "Total Redemptions", labels = scales::label_number_si(""))+
  labs(title = "Coupon Redemptions by Income on Specific Day of Week",
       x = "Total Redemptions",
       y = "Income Class",
       color = "Income Class")

transactions %>% 
  inner_join(products, by = "product_id") %>% 
  group_by(department, month = lubridate::month(transaction_timestamp, label = TRUE)) %>% 
  summarize(sales = sum(sales_value)) %>% 
  ggplot(aes(x = sales, y = department, fill = department))+
  geom_col()+
  theme(axis.text.y = element_text(size=4))+
  theme(axis.text.x = element_text(size = 4))+
  scale_x_continuous( name = "Sales", labels = scales::label_number_si(""))+
  facet_wrap(~month, nrow = 2)+ 
  labs(title = "Sales per Department by Month",
       subtitle = "Department sales collected",
       x = "Sales",
       y = "Departments",
       color = "Departments")

promotions %>% 
  inner_join(transactions, by = "product_id") %>% 
  group_by(mailer_location,product_id) %>% 
  summarize(Total_sales = sum(sales_value)) %>% 
  ggplot(aes(fct_reorder(mailer_location,Total_sales), y = Total_sales, fill = mailer_location)) + 
  geom_col()+
  scale_y_continuous(name = "Total Sales", labels = scales::label_dollar())+
  scale_x_discrete(name = "Locations")+
  labs(title = "Sales by Mailer Location",
       subtitle = "Mailer Locations based on the promotions of products",
       x = "Mailer Location",
       y = "Total Sales",
       color = "Locations")