Assignment #8 - Clustering Using Python
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St. John's University *
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MISC
Subject
Information Systems
Date
Dec 6, 2023
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docx
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Uploaded by SargentHawkPerson1261
Assignment #8: Clustering Using Python
Submission Instructions
Submit the following
two
files through Canvas>Assignments>To-Dos:
(1)
The completed, working python
script
that produced the analysis for the
12 clusters
scenario.
(2)
The completed
answer sheet
.
If you do not follow the instructions, your assignment will be counted late.
o
Late Assignment policy: Same as before.
Evaluation
Your submission will be graded based on the correctness of the completed answer sheet, with other files
as supporting documents.
Before you start
For this assignment, you’ll be working with the
Restaurant.csv
file and the
Clustering.ipynb
script
(which we used in ICA). This file has data from 627 restaurants that provide 4 dining options: delivery,
dine-in, takeout, and drive-through. The marketing division of the company wants to identify groups
of restaurants that offer a similar mix of dining options so that they can roll out promotions specific to
those restaurants.
The data file contains the following fields:
Variable Name
Variable Description
RestaurantID
Restaurant identification number
Delivery
The number of orders of “delivery” sold last month
DineIn
The number of orders of “dine in” sold last month
TakeOut
The number of orders of “take out” sold last month
DriveThrough
The number of orders of “drive through” sold last month
TotalSold
The total number of orders sold last month
Guidelines
1)
You’ll need to modify the
Clustering.ipynb
script from ICA with the following information to
perform the analysis:
Set the input filename (INPUT_FILENAME) to the store’s dataset (i.e., “Restaurant.csv”).
Set the number of clusters to create (NUM_CLUSTERS) to 6
.
Set the variable list (COLUMNS_FOR_ANALYSIS) to use the delivery, dine in, takeout, and drive
through variables by changing it to the following:
COLUMNS_FOR_ANALYSIS = ["Delivery","DineIn","TakeOut","DriveThrough"]
2)
Once you finish modifying the script, you can set the working directory and run the script.
3)
Based on your script output, answer Questions 1-4 in the answer sheet at the end of this
document.
4)
Now rerun the script, this time with
12 clusters
. Then answer Questions 5-10 in the answer sheet
provided in the separate document.
Page 1
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