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main.py
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main.py
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import pandas as pd
from datetime import timedelta, datetime
from normalize import NormalizeTable
from averageSales import AverageSales
from analysis import Analysis
if __name__ == "__main__":
product = pd.read_csv("datasets/ptable.csv")
sales = pd.read_csv("datasets/sales.csv")
inventory = pd.read_csv("datasets/inventorydata.csv")
normalized_sales = NormalizeTable(sales)
normalized_sales.drop_dublices()
normalized_sales.drop_nulls()
sales = normalized_sales.new_df(product)
sales.to_csv('datasets/normalized_sales.csv')
normalized_sales = NormalizeTable(inventory)
normalized_sales.drop_dublices()
normalized_sales.drop_nulls()
inventory = normalized_sales.new_df(product)
inventory.to_csv('datasets/normalized_inventory.csv')
normalized_sales = NormalizeTable(product)
normalized_sales.drop_dublices()
normalized_sales.drop_nulls()
ptable = normalized_sales.cleared_column()
ptable.to_csv('datasets/normalized_ptable.csv')
sales = pd.read_csv("datasets/normalized_sales.csv")
inventory = pd.read_csv("datasets/normalized_inventory.csv")
product = pd.read_csv("datasets/normalized_ptable.csv")
averageSales = AverageSales(sales, inventory)
averageSales.merge()
averageSales.convert_datetime()
averageSales.before_days_calculation()
averageSales.average()
averageSales.to_csv()
analysis = Analysis(sales, inventory, product)
analysis.last_7_days_sales()
analysis.last_30_days_sales()
analysis.last_year_following_7days_sales()
analysis.most_recent_inventory_value()
analysis.last30_days_positive_inventory()
analysis.average()
analysis.merge_product()
analysis.to_csv()