![Assignment #7 - Cluster Analysis Using the provided dataset, please answer the following questions. Use screen shots to back](https://media.cheggcdn.com/media/f84/f842b400-9ff9-480b-9163-27c82fb32c56/phpoa3OfJ.png)
![Questions For this analysis, please be sure to select all other variables except for ID and Award? in your column selection.](https://media.cheggcdn.com/media/680/680d2b5f-5867-4ba8-bdb4-f752f6c2a190/phpiKMyJx.png)
The first 10 rows from EastWestAirlinesCluster.csv:
![ID# Balance Qual_miles cc1_miles cc2_miles cc3_miles Bonus_miles Bonus_trans Flight_miles_12mo Flight_trans_12 Days_since_enr](https://media.cheggcdn.com/media/c10/c104a217-b4f9-4ac7-a280-73c55af0ef91/phpHRLGkz.png)
**Just need a sample code to help or as much of an answer assomeone can give for direction on how to answer**
Assignment #7 - Cluster Analysis Using the provided dataset, please answer the following questions. Use screen shots to back up your answers. In addition to those screenshots, please make sure that you clearly state your answer. I want your assignment submitted in a MS Word document. I do not want your data files but I want your Python code. Also, want your answers to the questions on page 2 in a Word document! If it is NOT a Word Document, you will receive a zero! You will be graded on organization and formatting in addition to coming up with the correct answer. I want you to both submit the assignment on Blackboard. You will use the data file, East WestAirlines Cluster.csv. Data Description This data set consists of 3,999 customers of your airline. Your job is to categorize your customers into easily identified clusters in order to tailor your offerings. Below is a table of the variables and the description of each: Field Name ID# Balance Qual miles ccl_miles cc2_miles cc3_miles note: miles bins: Description Unique ID Number of miles eligible for award travel Number of miles counted as qualifying for Topflight status Number of miles earned with freq. flyer credit card in the past 12 months: Number of miles earned with Rewards credit card in the past 12 months: Number of miles earned with Small Business credit card in the past 12 months: | 1 = under 5,000 25,000 - 10,000 | 3 = 10,001 - 25,000 4= 25,001 - 50,000 5 = over 50,000 Number of miles earned from non-flight bonus transactions in the past 12 months Number of non-flight bonus transactions in the past 12 months Number of flight miles in the past 12 months Number of flight transactions in the past 12 months Number of days since Enroll date Dummy variable for Last award (1-not null, O-null) Bonus miles Bonus trans Flight miles 12mo Flight trans 12 Days_since_enroll Award? Questions For this analysis, please be sure to select all other variables except for ID and Award? in your column selection. Select the number of clusters to be 7 (seven). 1. Which cluster has the most number of customers? 2. List the characteristics of one customer in each cluster. Hint: use the output file and sort your clusters. 3. What is your interpretation of these cluster results? 4. Please describe the characteristics of the first cluster (cluster #0) 5. Which cluster has the highest balance average? Why do you think it is the highest? Base your opinion on the cluster's characteristics. 6. Which cluster has the lowest balance average? Why do you think it is the lowest? Base your opinion on the cluster's characteristics. 7. To improve your analysis, what missing dimension would you add to your data set? Why? 8. Run the cluster again but prune your variables to simplify your model. a. Which variables did you keep? Why? b. How many clusters did you choose? c. Describe the cluster with the highest balance average. ID# Balance Qual_miles cc1_miles cc2_miles cc3_miles Bonus_miles Bonus_trans Flight_miles_12mo Flight_trans_12 Days_since_enroll Award? 28143 174 7000 | 19244 215 6968 0 1 4123 7034 500 6952 41354 14776 97752 16420 43300 6935 6942 6 2077 0 0 250 84914 27482 5250 6994 6938 20856 443003 104860 1753 28426 3850 1150 6948 6931 10