library(dplyr) library(forecast) library(lubridate) # Assuming 'data' is your dataframe and already loaded # 1. Filter data for Store 1 and aggregate weekly sales store1_data % filter(store == 1) %>% # Filter for Store 1 mutate(date = as.Date(date)) %>% # Parse date group_by(week = floor_date(date, "week")) %>% # Group by week summarise(total_weekly_sales = sum(weekly_sales, na.rm = TRUE)) %>% # Sum sales for all departments arrange(week) # Ensure chronological order #