#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 12 20:57:47 2019

@author: ronaldolegrama
"""
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
xl = pd.ExcelFile("SalesData.xlsx")
SalesData = xl.parse("Orders")
Decorating = "\n" + "*"*25 + "\n"

#Top 10% product Sales by SEASON within the past 2 years:
SalesMonth = SalesData
SalesMonth["Month"] = SalesMonth["Order Date"].dt.quarter
#.quarter = quarter
#key error = most likely column error
season_Sales_Cat = SalesData [["Month", "Sales", "Sub-Category",]]
Months = SalesData.Month.unique()

MostFrequent = SalesData["Sub-Category"].value_counts()
total_products = MostFrequent.shape
TopPercent = int (total_products[0]*.1)

print(MostFrequent.head(TopPercent))

for Month in Months:
    season_sales = season_Sales_Cat.loc[season_Sales_Cat["Month"] == Month]
    season_total_sales = season_sales.groupby(by = "Sub-Category").sum().sort_values(by = "Sales", ascending = False)
    season_total_sales = season_total_sales.reset_index()
    print("The top 10  subcategories with the most sales in Quarter " + str (Month) + " are: ")
    print(season_total_sales.head(10))
    print(Decorating)