Pandas Visualization - Copy.py

import pandas as pd
import pyodbc as con
import matplotlib.pyplot as plt

con=con.connect('Driver={SQL Server};server=VIKAS-HP\SQLEXPRESS;database=Northwind')#connection to northwind database

Employees= pd.read_sql('select * from Employees',con) #Employees table
Orders= pd.read_sql('select * from Orders',con) #Orders table
Order_Details= pd.read_sql('select * from [Order Details]',con) #Order_Details table
Categories= pd.read_sql('select * from Categories',con) #Categories table
Products= pd.read_sql('select * from Products',con) #Products table

name=['Beverages','Dairy Products','Produce']


df=Categories[Categories.CategoryName.isin(name)].merge(Products,how='inner',on='CategoryID').merge(Order_Details,how='inner',on='ProductID').groupby(['CategoryName','ProductName'])['Quantity'].agg({'Total_Sales':sum,'No_of_Orders':'count'})#this is the shortest formif we have to aggregate based on one column only
df1= df.groupby('CategoryName').agg({'Total_Sales':sum,'No_of_Orders':sum})
df2= df.groupby('ProductName').agg({'Total_Sales':sum,'No_of_Orders':sum})
#print(df)
#print(df1)
#print(df2)


df1.plot(kind = 'bar')
df2.plot(kind = 'bar')
plt.show()