hw6

library(tidyverse)

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## ✔ purrr     1.1.0     
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library(readxl)
library(writexl)
library(ggplot2)
library(scales)

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bike_orderlines_tbl <- read_csv("/Users/zaari/Downloads/bike_orderlines.csv")

## Rows: 15644 Columns: 13
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (7): model, category_1, category_2, frame_material, bikeshop_name, city...
## dbl  (5): order_id, order_line, quantity, price, total_price
## dttm (1): order_date
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revenue_by_category2 <- bike_orderlines_tbl %>%
  group_by(category_2) %>%
  summarise(revenue = sum(total_price, na.rm = TRUE)) %>%
  arrange(desc(revenue))

2. Plot with ggplot2

ggplot(revenue_by_category2, aes(x = revenue, 
                                 y = reorder(category_2, revenue))) +
  geom_col(fill = "blue") +
  labs(
    x = "revenue",
    y = "category_2",
    title = "Revenue by Bike Subcategory"
  ) +
  scale_x_continuous(labels = label_number()) +  # e.g. 1e+07 → 10M
  theme_minimal()