In mathematics it can be quite tedious to re-calculate values every time for a non-changing value or list. Thus look-up tables are handy to have to save time on re-calculating values. This can also be useful in computer science to save time on getting a stored result in a database vs. recalculating the the result.
In mathematics it can be quite tedious to re-calculate values every time for a non-changing value or list. Thus look-up tables are handy to have to save time on re-calculating values. This can also be useful in computer science to save time on getting a stored result in a database vs. recalculating the the result.
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...
Related questions
Question
Python
![In mathematics it can be quite tedious to re-calculate values every time for a non-changing value or list.
Thus look-up tables are handy to have to save time on re-calculating values. This can also be useful in
computer science to save time on getting a stored result in a database vs. recalculating the the result.
Define a function lookup_table() that takes in 2 parameters:
operations is a dictionary that has function names as its keys and function objects as its values
• input_value (list, float, or integer) is the input value on which you want to run all the defined functions
in the operations dictionary.
The function will return a dictionary that contains the key names from the operations parameter dictionary
and the values will be results obtained by applying functions stored in operations dictionary values to the
given input_value.
For example:
a = {'sum': sum, 'avg’: np.median}
result = lookup_table(a, [2, 4, 6])
. The result would be
{'sum': 12, 'avg’: 4.0}
Your solution should not import numpy.
Hint do not over think this question, or be held up by how functions can be passed into a function and then
called again. Its as simple as:
result = operations ['sum'](input_value)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff893683d-d70a-429c-ae30-ce98a9dc5e96%2Fb1045d0b-98bc-4ce0-96d4-ac58fbfc1f75%2Ft2a8iqo_processed.png&w=3840&q=75)
Transcribed Image Text:In mathematics it can be quite tedious to re-calculate values every time for a non-changing value or list.
Thus look-up tables are handy to have to save time on re-calculating values. This can also be useful in
computer science to save time on getting a stored result in a database vs. recalculating the the result.
Define a function lookup_table() that takes in 2 parameters:
operations is a dictionary that has function names as its keys and function objects as its values
• input_value (list, float, or integer) is the input value on which you want to run all the defined functions
in the operations dictionary.
The function will return a dictionary that contains the key names from the operations parameter dictionary
and the values will be results obtained by applying functions stored in operations dictionary values to the
given input_value.
For example:
a = {'sum': sum, 'avg’: np.median}
result = lookup_table(a, [2, 4, 6])
. The result would be
{'sum': 12, 'avg’: 4.0}
Your solution should not import numpy.
Hint do not over think this question, or be held up by how functions can be passed into a function and then
called again. Its as simple as:
result = operations ['sum'](input_value)
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 2 steps
Recommended textbooks for you
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Computer Networking: A Top-Down Approach (7th Edi…
Computer Engineering
ISBN:
9780133594140
Author:
James Kurose, Keith Ross
Publisher:
PEARSON
Computer Organization and Design MIPS Edition, Fi…
Computer Engineering
ISBN:
9780124077263
Author:
David A. Patterson, John L. Hennessy
Publisher:
Elsevier Science
Network+ Guide to Networks (MindTap Course List)
Computer Engineering
ISBN:
9781337569330
Author:
Jill West, Tamara Dean, Jean Andrews
Publisher:
Cengage Learning
Concepts of Database Management
Computer Engineering
ISBN:
9781337093422
Author:
Joy L. Starks, Philip J. Pratt, Mary Z. Last
Publisher:
Cengage Learning
Prelude to Programming
Computer Engineering
ISBN:
9780133750423
Author:
VENIT, Stewart
Publisher:
Pearson Education
Sc Business Data Communications and Networking, T…
Computer Engineering
ISBN:
9781119368830
Author:
FITZGERALD
Publisher:
WILEY