Initial

convert.py

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+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)