The goal of this computational filter was to save company time, but right now it's pretty inefficient to manually add each candidate one at a time. Your earlier functions like filter_no_fail(cand) returned a True/False for a single applicant (in this case no score below 65). Create a new version of this function which processes a whole list of applicants like the one below. def filter_all_nf(applicants_list): This version should take in a list of applicants (each of which is itself represented by a list), and return a list of the indexes of the candidates which have no score below 65. You must call filter_no_fail as part of your filter_all_nf function. Example: >>> applicants 0 1 2 3 4 5 ] [ [100, 95, 80, 89, 61, 75, 83], # [ 95, 99, 92, 86, 88], # [75, 40, 55, 70, 85, 62, 90], # 70, 99, 100, 81, 82, 91, 90], # 92, 99, 95, 97, 60], # [85, [ 86, [ 64, >>> [1, 3, 4] = 75, 89, 94, 90, 88, 89, 91, filter_all_nf(applicants) 91], #
The goal of this computational filter was to save company time, but right now it's pretty inefficient to manually add each candidate one at a time. Your earlier functions like filter_no_fail(cand) returned a True/False for a single applicant (in this case no score below 65). Create a new version of this function which processes a whole list of applicants like the one below. def filter_all_nf(applicants_list): This version should take in a list of applicants (each of which is itself represented by a list), and return a list of the indexes of the candidates which have no score below 65. You must call filter_no_fail as part of your filter_all_nf function. Example: >>> applicants 0 1 2 3 4 5 ] [ [100, 95, 80, 89, 61, 75, 83], # [ 95, 99, 92, 86, 88], # [75, 40, 55, 70, 85, 62, 90], # 70, 99, 100, 81, 82, 91, 90], # 92, 99, 95, 97, 60], # [85, [ 86, [ 64, >>> [1, 3, 4] = 75, 89, 94, 90, 88, 89, 91, filter_all_nf(applicants) 91], #
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
Related questions
Question
In python
![>>>
[1, 3, 4]
filter_all_nf(applicants)
Use our original set of test cases and test that the function
returns the correct indices for qualifying candidates.
Figure out in advance what the output of this test case
should be before you test it.
]
applicants
[
[95, 93, 50, 91, 98, 90, 82],
[65, 75, 85, 95, 100, 100, 85],
[100, 100, 95, 85, 75, 65, 80],
[98, 70, 55, 61, 98, 90, 90],
[100, 95, 55, 61, 75, 95, 90],
[95, 90, 98, 88, 93, 95, 94],
[90, 80, 80, 100, 70, 75, 90],
[80, 83, 79, 83, 77, 77, 82],
[90, 100, 100, 98, 100, 99, 55],
[77, 82, 92, 100, 95, 92, 70]
=](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9ee05586-824d-4bf4-9ad8-ce0eac686f7d%2F2b27eba8-75e3-49d3-8437-e374c440ba7a%2Fbci6p4o_processed.jpeg&w=3840&q=75)
Transcribed Image Text:>>>
[1, 3, 4]
filter_all_nf(applicants)
Use our original set of test cases and test that the function
returns the correct indices for qualifying candidates.
Figure out in advance what the output of this test case
should be before you test it.
]
applicants
[
[95, 93, 50, 91, 98, 90, 82],
[65, 75, 85, 95, 100, 100, 85],
[100, 100, 95, 85, 75, 65, 80],
[98, 70, 55, 61, 98, 90, 90],
[100, 95, 55, 61, 75, 95, 90],
[95, 90, 98, 88, 93, 95, 94],
[90, 80, 80, 100, 70, 75, 90],
[80, 83, 79, 83, 77, 77, 82],
[90, 100, 100, 98, 100, 99, 55],
[77, 82, 92, 100, 95, 92, 70]
=
![The goal of this computational filter was to save company
time, but right now it's pretty inefficient to manually add
each candidate one at a time. Your earlier functions like
filter_no_fail(cand) returned a True/False for a
single applicant (in this case no score below 65). Create a
new version of this function which processes a whole list
of applicants like the one below.
def
filter_all_nf(applicants_list):
This version should take in a list of applicants (each of
which is itself represented by a list), and return a list of
the indexes of the candidates which have no score below
65. You must call filter_no_fail as part of your
filter_all_nf function.
Example:
>>> applicants
0
1
2
3
4
5
]
[
[100, 95, 80
>
[95,
[ 75,
[85,
[ 64,
99,
›››
[1, 3, 4]
70,
=
92,
75,
40, 55, 70,
99, 100, 81, 82, 91], #
[ 86, 90, 88, 89, 91, 91, 90], #
89, 61, 75, 83], #
89, 94, 86, 88], #
92,
85, 62, 90], #
99, 95, 97, 60], #
filter_all_nf(applicants)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9ee05586-824d-4bf4-9ad8-ce0eac686f7d%2F2b27eba8-75e3-49d3-8437-e374c440ba7a%2Ficd63bj_processed.jpeg&w=3840&q=75)
Transcribed Image Text:The goal of this computational filter was to save company
time, but right now it's pretty inefficient to manually add
each candidate one at a time. Your earlier functions like
filter_no_fail(cand) returned a True/False for a
single applicant (in this case no score below 65). Create a
new version of this function which processes a whole list
of applicants like the one below.
def
filter_all_nf(applicants_list):
This version should take in a list of applicants (each of
which is itself represented by a list), and return a list of
the indexes of the candidates which have no score below
65. You must call filter_no_fail as part of your
filter_all_nf function.
Example:
>>> applicants
0
1
2
3
4
5
]
[
[100, 95, 80
>
[95,
[ 75,
[85,
[ 64,
99,
›››
[1, 3, 4]
70,
=
92,
75,
40, 55, 70,
99, 100, 81, 82, 91], #
[ 86, 90, 88, 89, 91, 91, 90], #
89, 61, 75, 83], #
89, 94, 86, 88], #
92,
85, 62, 90], #
99, 95, 97, 60], #
filter_all_nf(applicants)
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