Files
xlp/convert.py
2022-03-18 10:00:54 -05:00

49 lines
1.1 KiB
Python

import pandas as pd
import numpy as np
import sqlite3
import time
start = time.time()
data = pd.read_excel("data.xlsx")
df = pd.DataFrame()
years = []
months = []
level2s = []
level3s = []
skus = []
quantities = []
revenues = []
costs = []
descriptions = []
for index,row in data.iterrows():
if type(row["FiscalYearMonth"]) == str:
years.append(int(row["FiscalYearMonth"][0:4]))
months.append(int(row["FiscalYearMonth"][5:]))
level2s.append(row["Level2"])
level3s.append(row["Level3"])
skus.append(row["MaterialEntered"])
quantities.append(int(row["Quantity"]))
revenues.append(row["SalesRevenue"])
costs.append(row["CostOfGoodsSold"])
descriptions.append(row["ProductDescription"])
df["year"] = years
df["month"] = months
df["level2"] = level2s
df["level3"] = level3s
df["sku"] = skus
df["quantity"] = quantities
df["revenue"] = revenues
df["cost"] = costs
df["description"] = descriptions
conn = sqlite3.connect("data.db")
df.to_sql("data", conn, if_exists='replace')
end = time.time()
print(end-start)