Refactor and Modularize R Code for Sales Analysis with Distance Calculation

# Function to connect to the database
connect_to_database <- function() {
  rm(list=ls())
  library(RJDBC)
  library(rJava)
  library(dplyr)

  # Connect to the server 
  drv <- JDBC(driverClass  = "com.microsoft.sqlserver.jdbc.SQLServerDriver", classPath = "/home/user/R/Projects/R-DCM/Drivers/sqljdbc_7.0/enu/mssql-jdbc-7.0.0.jre8.jar")
  
  # Replace 'example-server', 'example-database', 'your-username', and 'your-password' with your specific information
  conn <- dbConnect(drv,'jdbc:sqlserver://example-server:1433;databaseName=example-database','your-username','your-password')

  # Get table list 
  table.list <- dbGetQuery(conn, "SELECT * FROM INFORMATION_SCHEMA.TABLES")
  table.list$queryname <- paste0(table.list$TABLE_SCHEMA, ".", table.list$TABLE_NAME)

  return(conn)
}

# Function to retrieve sales data by zip
get_sales_data_by_zip <- function(conn) {
  query <- "SELECT TOP 1000 * FROM YourSchema.YourSalesTable"  # Replace with your schema and table names
  sales_data <- dbGetQuery(conn, query)
  return(sales_data)
}

# Function to calculate distance
calculate_distance <- function(store_data, zipcode_data, radius_limit = 200) {
  # (Your distance calculation code)
  return(distance_result)
}

# Function to merge sales data
merge_sales_data <- function(sales_data, distance_data) {
  # (Your merge code)
  return(merged_data)
}

# Function to calculate store radius
calculate_store_radius <- function(merged_data) {
  # (Your store radius calculation code)
  return(store_radius_data)
}

# Function to perform rolling sum for 75% of sales
rolling_sum_75_percent <- function(merged_data) {
  # (Your rolling sum code)
  return(rolling_sum_data)
}

# Main function to execute the entire analysis
main_analysis <- function() {
  conn <- connect_to_database()
  sales_data <- get_sales_data_by_zip(conn)
  distance_data <- calculate_distance(store_data, zipcode_data)
  merged_data <- merge_sales_data(sales_data, distance_data)
  store_radius_data <- calculate_store_radius(merged_data)
  rolling_sum_data <- rolling_sum_75_percent(merged_data)

  # Save the results to CSV files
  write.csv(store_radius_data, "~/R/Projects/R-DCM/Clients/Analysis/Assets/Outputs/Store_Radius.csv")
  write.csv(rolling_sum_data, "~/R/Projects/R-DCM/Clients/Analysis/Assets/Outputs/Store_75pct.csv")
  
  # (Additional code or analysis if needed)
  
  # Close the database connection
  dbDisconnect(conn)
}

# Execute the main analysis
main_analysis()