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MARKETING & 
RETAIL 
ANALYTICS 
MILESTONE - 2 
SANDYA VB 
 
z 
PROBLEM STATEMENT 
▪ A Grocery Store shared the transactional data with 
you. Your job is to identify the most popular combos 
that can be suggested to the Grocery Store chain after 
a thorough analysis of the most commonly occurring 
sets of items in the customer orders. The Store 
doesn’t have any combo offers. Can you suggest the 
best combos & offers? 
▪ DATA: dataset_ 
z 
TOOLS USED 
▪ TABLEAU Tool: Used for Exploratory ...
DATA SCIEN Predictive Modeling P
QM 501 Project-Time series Forecasting- Final 2023& study guide with complete solution
import pandas as pd 
import numpy as np 
from sklearn import preprocessing 
from _selection import train_test_split 
from _bayes import GaussianNB 
from cs import accuracy_score 
import seaborn as sns 
import t as plt 
from import zscore 
import warnings 
rwarnings( "ignore") 
from r_model import LinearRegression 
from er import KMeans 
from cs import mean_squared_error 
from ers_influence import variance_inflation_fac 
tor 
import math 
from r_model import LogisticRegression 
from sklearn im...
PROBLEM STATEMENT 
▪ An automobile parts manufacturing company has collected data 
of transactions for 3 years. They do not have any in-house data 
science team, thus they have hired you as their consultant. Your 
job is to use your magical data science skills to provide them 
with suitable insights about their data and their customers. 
▪ DATA: Sales_D 
z 
DATA DICTIONARY 
ORDERNUMBER : Order Number CUSTOMERNAM 
E : customer 
QUANTITYORDERED 
: 
Quantity ordered PHONE : Phone of the custome...
PROBLEM STATEMENT 
▪ An automobile parts manufacturing company has collected data 
of transactions for 3 years. They do not have any in-house data 
science team, thus they have hired you as their consultant. Your 
job is to use your magical data science skills to provide them 
with suitable insights about their data and their customers. 
▪ DATA: Sales_Dat
Problem: 
For this particular assignment, the data of different types 
of wine sales in the 20th century is to be analysed. Both 
of these data are from the same company but of different 
wines. As an analyst in the ABC Estate Wines, you are 
tasked to analyse and forecast Wine Sales in the 20th 
century. 
Dataset - R 
In [1]: import numpy as np 
import pandas as pd 
import seaborn as sns 
from matplotlib import pyplot as plt 
from import rcParams 
rcParams['ze'] = 13, 6 
1. Read the data as ...
1. Read the data as an appropriate Time Series data and plot the data. 
 The two datasets: Rose and Sparkling are imported using the read command. And convert to time series 
data using 
date_range function: 
date = _range(start='01/01/1980', end='08/01/1995', freq='M')date 
df['Time_Stamp'] = pd.DataFrame(date,columns=['Month']) 
() 
o/p: 
ROSE WINE YEAR WISE SALES 
• From the above plot we observe that there is a 
decreasing trend in the initial years and stabilizes 
over the years...
MARKETING & 
RETAIL ANALYTICS
Great Lakes Institute Of Management QM 501>Project-Time series Forecasting- Final