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In Python, grades_dict = {'Wally': [87,96,70],                'Eva': [100,87,90],                 'Sam': [94,77,90],                 'Katie': [100,81,82],                 'Bob': [83,65,85]} Write your own describe function that produces the same 8 statistical results, for each one of the columns, that the built-in describe() function does. Note 1: Use the sample standard deviation formula (that is, the denominator is: N-1) Note 2: Your algorithm should work for any number of columns not just for 5 Note 3: You can use the np.percentile() for the 25% and 75% percentile as well as the sort()

In Python, grades_dict = {'Wally': [87,96,70],                'Eva': [100,87,90],                 'Sam': [94,77,90],                 'Katie': [100,81,82],                 'Bob': [83,65,85]} Write your own describe function that produces the same 8 statistical results, for each one of the columns, that the built-in describe() function does. Note 1: Use the sample standard deviation formula (that is, the denominator is: N-1) Note 2: Your algorithm should work for any number of columns not just for 5 Note 3: You can use the np.percentile() for the 25% and 75% percentile as well as the sort()

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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In Python,

grades_dict = {'Wally': [87,96,70],
               'Eva': [100,87,90], 
               'Sam': [94,77,90], 
               'Katie': [100,81,82], 
               'Bob': [83,65,85]}
Write your own describe function that produces the
same 8 statistical results, for each one of the columns, that the built-in describe() function does.
Note 1: Use the sample standard deviation formula (that is, the denominator is: N-1)
Note 2: Your algorithm should work for any number of columns not just for 5
Note 3: You can use the np.percentile() for the 25% and 75% percentile as well as the sort()
built-in functions
 
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