Module 5 Visualization Lab

library(tidyverse)
library(completejourney)
library(dplyr)
library(stringr)
library(lubridate)
library(ggplot2)

transactions <- get_transactions()
promotions <- get_promotions()

transactions %>%
  inner_join(coupon_redemptions) %>%
  filter(yday(transaction_timestamp) == yday(redemption_date)) %>%
  inner_join(demographics) %>%
  filter(marital_status != "NA") %>%
  mutate(month = month(transaction_timestamp, label = TRUE, abbr = FALSE)) %>%
  group_by(month, marital_status) %>%
  summarise(total_redemptions = n()) %>%
  slice_max(order_by = total_redemptions, n = 3) %>%
  ggplot(aes(x = month, y = total_redemptions, color = marital_status, group = marital_status)) +
  geom_point(size = 2) +
  geom_line(size = 1) +
  scale_color_brewer(palette = "Pastel1") +
  scale_y_continuous(labels = scales::comma) +
  labs(title = "Figure 1. Total Coupon Usage per Month by Marital Status During Year 2017",
       subtitle = "People who were married typically used more coupons. 
May, August, and November witnessed remarkable spikes in coupon redemptions for both groups. ",
       y = "Total Coupon Redemption",
       x = "Month") +
  theme(axis.title.x = element_text(face = "bold"),
        axis.text.x = element_text(angle = 45, hjust = 1),
        axis.title.y = element_text(face = "bold"),
        plot.title = element_text(face = "bold", size = 13),
        plot.subtitle = element_text(size = 8, face = "italic"))