library(RSQLite)
library(DBI)
library(tidyr) # For reshaping the data
library(readr) # For exporting data to CSV
# Define the path to your SQLite database
db_path <- "/home/jbyungrokim/CSV/CSV.db"
# Connect to the SQLite database
conn <- dbConnect(RSQLite::SQLite(), dbname = db_path)
# Adjust the query to calculate the sum for each item by year and month
query <- "
SELECT
strftime('%Y-%m', '20' || substr(Date_Transaction, 7, 2) || '-' || substr(Date_Transaction, 1, 2) || '-' || substr(Date_Transaction, 4, 2)) AS YearMonth,
Item,
SUM(Pay_Amount) AS Total_Spent
FROM
'지출-액수_2024_08_20'
GROUP BY
YearMonth, Item
ORDER BY
YearMonth, Total_Spent DESC;
"
# Execute the query and store the result in a data frame
monthly_sum <- dbGetQuery(conn, query)
# Print the result
print("Sum of Pay_Amount by Item for each Year/Month:")
print(monthly_sum)
# Reshape the data into a wide format for better readability in a spreadsheet
monthly_sum_wide <- spread(monthly_sum, YearMonth, Total_Spent, fill = 0)
# Export the data to a CSV file
output_path <- "/home/jbyungrokim/CSV/monthly_sum_by_item.csv"
write_csv(monthly_sum_wide, output_path)
# Print the location of the saved file
print(paste("Data has been saved to:", output_path))
# Close the connection to the SQLite database
dbDisconnect(conn)