Homework_5

library(readxl)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

file_path <- "bike_orderlines.xlsx"
bike_data <- read_excel(file_path)

filtered_data <- bike_data %>%
  filter(category_1 %in% c("Mountain", "Road"))

customer_preferences <- filtered_data %>%
  group_by(bikeshop_name, category_1) %>%
  summarise(quantity = sum(quantity), .groups = "drop")

top_customers <- customer_preferences %>%
  group_by(category_1) %>%
  slice_max(quantity, n = 3)

print(top_customers)

## # A tibble: 6 × 3
## # Groups:   category_1 [2]
##   bikeshop_name                category_1 quantity
##   <chr>                        <chr>         <dbl>
## 1 Kansas City 29ers            Mountain       2484
## 2 Denver Bike Shop             Mountain       1623
## 3 Ithaca Mountain Climbers     Mountain        953
## 4 Kansas City 29ers            Road            987
## 5 Oklahoma City Race Equipment Road            822
## 6 Phoenix Bi-peds              Road            697