Online Quiz for Python Lists with Multiple Choice. We covered all the Online Quiz for Python Lists with Multiple Choice in this post for free so that you can practice well for the exam.
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Online Quiz for Python Lists with Multiple Choice for Students
What does the any() function return when given an empty list?
a. True
b. False
c. None
d. It throws an error
Option b – False
What does the len() function count when used on a list containing other lists?
a. The number of sublists inside the main list
b. The total number of elements across all nested lists
c. The number of items in the outermost list
d. The size of the first sublist
Option c – The number of items in the outermost list
In which case is the enumerate() function most commonly used?
a. With the filter() function
b. With the map() function
c. Alongside list comprehensions
d. With the reduce() function
Option c – Alongside list comprehensions
What result does the accumulate() function give when using multiplication on a list of numbers?
a. Total of all the values
b. The result of multiplying all the values together
c. The original list
d. The list arranged in increasing order
Option b – The result of multiplying all the values together
In the filter() function, what role does the lambda function play?
a. It defines which elements should be included
b. It specifies what to exclude from the output
c. It transforms each list element
d. It determines the sorting order for the result
Option a – It defines which elements should be included
What will the map() function output if given an empty list?
a. An empty list
b. None
c. It causes an error
d. A list containing zero
Option a – An empty list
Are lambda functions less complex than standard functions?
a. Yes, they are simpler
b. No, they are equally complex
c. It depends on how they are used
d. There’s no difference at all
Option b – No, they are equally complex
What is the main function of the reduce() method?
a. Apply a function to each individual element
b. Merge items using a specified operation
c. Select items based on a condition
d. Rearrange elements in order
Option b – Merge items using a specified operation
How do sum() and accumulate() differ?
a. sum() calculates totals, while accumulate() can perform custom operations
b. accumulate() computes totals, while sum() allows custom operations
c. sum() only accepts numbers, but accumulate() supports any type
d. There’s no real difference; both work the same
Option a – sum() calculates totals, while accumulate() can perform custom operations
What is the result if enumerate() is applied to something that can’t be iterated?
a. An error is raised
b. An empty list is returned
c. It gives back None
d. It provides a pair with index 0 and the object
Option a – An error is raised
When does the all() function return True?
a. If every item in the list is True
b. If at least one item is True
c. If no item is True
d. If at least one item is False
Option a – If every item in the list is True
Which method retrieves the tuple with the highest value based on a specific element index in a list of tuples?
a. max(list, key=lambda x: x[1])
b. maximum(list, key=lambda x[1])
c. find_max(list, key=lambda x: x[1])
d. max_element(list, key=lambda x: x[1])
Option a – max(list, key=lambda x: x[1])
What does the min() method return when applied to a list that contains dictionaries?
a. The dictionary having the smallest key
b. The dictionary having the largest key
c. The dictionary with the least value
d. The dictionary with the highest value
Option a – The dictionary having the smallest key
Under what condition does the all() function return False?
a. When all elements are True
b. When at least one element is True
c. When all elements are False
d. When one or more elements are False
Option d – When one or more elements are False
In the enumerate() function, what role does the start argument play?
a. Sets the initial index for iteration
b. Defines the final index to stop iteration
c. Determines the interval between indices
d. Specifies the direction for iteration
Option a – Sets the initial index for iteration
When using map() with more than one iterable, how are their elements processed?
a. They are passed together into the given function
b. Only one iterable is considered for the function
c. It throws an error due to multiple iterables
d. Each set of elements is grouped, then passed to the function
Option d – Each set of elements is grouped, then passed to the function
How does the accumulate() function behave when provided with a list of strings?
a. Joins the strings using a custom separator
b. Merges the strings in their original order
c. Adds up the lengths of the strings one by one
d. Arranges the strings in alphabetical order
Option b – Merges the strings in their original order
What happens when filter() is used on a list of non-boolean items without giving it a custom function?
a. It throws an error
b. It removes entries that are None
c. It keeps all the items in the output list
d. It filters using bool() on each item
Option d – It filters using bool() on each item
What result do you get by applying reduce() with a user-defined function on a list of strings?
a. One single string made by joining all of them
b. Total ASCII value of all characters in the list
c. An error because strings are unsupported
d. Product of string lengths in the list
Option a – One single string made by joining all of them
Can a lambda function consist of more than one line?
a. True
b. False
c. Depends on what the function does
d. Only in cases involving map()
Option a – True
Why is the any() function typically used on a list of boolean values?
a. To verify if all elements are True
b. To check if at least one element is True
c. To count the number of True entries
d. To form a list of True elements
Option b – To check if at least one element is True
What distinguishes enumerate() from iterating using range(len(lst))?
a. enumerate() returns both index and item, while range(len(lst)) gives only indices
b. enumerate() returns just indices, while range(len(lst)) returns index-element pairs
c. There is no functional distinction; both approaches yield similar results and can be used as alternatives.
d. enumerate() cannot be used directly with lists.
Option a – enumerate() returns both index and item, while range(len(lst)) gives only indices
What happens when the reduce() function is used on an empty list?
a. It throws an exception
b. It gives None as the output
c. It returns the identity value if one is specified
d. It outputs an empty list
Option c – It returns the identity value if one is specified
What will be the outcome when the str function is mapped over a list of integers using map()?
a. It creates a list of string versions of the integers
b. It produces a list containing the same integers
c. It combines all integers into one long string
d. It results in an error because str can’t be used on integers
Option a – It creates a list of string versions of the integers
When is a lambda function most appropriately used?
a. When a reusable function is needed
b. When the logic spans several lines
c. When a brief, one-time function is required
d. When the function needs to call itself
Option c – When a brief, one-time function is required
What is the result of applying enumerate() to an empty list?
a. Returns an empty list
b. Gives None
c. Produces an error
d. Returns a tuple starting at index 0 with no values
Option a – Returns an empty list
Which list method allows for removing an element in Python?
a. terminate
b. fetch
c. remove
d. delete
Option c – remove
Why is the any() function used with a list of boolean values?
a. To see if all items are True
b. To check if at least one value is True
c. To count how many True values are present
d. To create a list containing only the True values
Option b – To check if at least one value is True
In what way does enumerate() differ from using range(len(lst)) to loop over a list?
a. enumerate() provides both index and item, whereas range(len(lst)) gives only the index
b. enumerate() returns just the index, and range(len(lst)) gives index-item pairs
c. They function the same and can be used interchangeably
d. enumerate() cannot be used on lists
Option a – enumerate() provides both index and item, whereas range(len(lst)) gives only the index
What does the map() function return?
a. A list with the same number of elements as the input
b. A list that is twice as long as the original
c. A single combined result
d. A tuple that includes the results of the mapping
Option a – A list with the same number of elements as the input
If no function is passed to filter() and it’s used on a list of numbers, what happens?
a. An error is raised
b. It removes items that are None
c. It keeps all elements in the output list
d. It filters the list based on the bool() value of each item
Option d – It filters the list based on the bool() value of each item
Using reduce() with a custom function on a string list will result in:
a. One string made by joining all list elements
b. The total ASCII value of all characters in the list
c. An error because it doesn’t support string data
d. The product of the lengths of all strings in the list
Option a – One string made by joining all list elements
Is a lambda function limited to one line?
a. Yes
b. No
c. It depends on how complex the logic is
d. Only when it’s used with map()
Option a – Yes
You are creating a shopping cart system and need to add a new product to the user’s cart. Which function definition would you choose?
a. def add_product_to_cart(cart, product):
b. def insert_item_in_cart(product, user_cart):
c. def update_cart_with_item(new_item):
d. def append_product_to_cart(cart, item):
Option a – def add_product_to_cart(cart, product):
You want to count how many times a specific word appears in a list of text. Which function would you create?
a. def count_word_occurrences_in_list(text_list, target_word):
b. def word_count_in_list(words, search_word):
c. def find_word_occurrences(word_list, target_term):
d. def analyze_word_occurrences(text, search_word):
Option a – def count_word_occurrences_in_list(text_list, target_word):
You need to combine two lists and remove any duplicates. Which function definition fits the task?
a. def combine_and_remove_duplicates(list1, list2):
b. def merge_lists_without_duplicates(list1, list2):
c. def merge_and_remove_duplicates_from_lists(list1, list2):
d. def merge_lists_unique(list_one, list_two):
Option a – def combine_and_remove_duplicates(list1, list2):
In a task management app, you need to mark a task as completed and remove it from the active task list. Which function signature would you use?
a. def mark_task_as_completed(task_list, task_id):
b. def set_task_as_done(tasks, task_to_complete):
c. def remove_task_from_active_list(task_list, task):
d. def finish_task_and_remove_from_list(task_id, active_tasks):
Option a – def mark_task_as_completed(task_list, task_id):
You have a list of exam scores for students, and you want to calculate the average excluding the highest and lowest scores. Which function would you implement?
a. def calculate_average_excluding_extremes(scores):
b. def get_average_after_excluding_extremes(exam_results):
c. def calculate_average_without_outliers(results):
d. def average_excluding_high_and_low(student_scores):
Option a – def calculate_average_excluding_extremes(scores):
a. def filter_inappropriate_posts(timeline, forbidden_words):
b. def screen_posts_for_bad_words(posts, inappropriate_words):
c. def sanitize_timeline_for_offensive_content(timeline, offensive_terms):
d. def remove_inappropriate_content_from_timeline(timeline, words_to_exclude):
Option a – def filter_inappropriate_posts(timeline, forbidden_words):
You want to write a function that identifies the most frequent element in a list. Which function signature would you use?
a. def find_most_frequent_element(lst):
b. def get_most_common_element_from_list(elements):
c. def identify_most_common_item(items_list):
d. def most_common_element(data):
Option a – def find_most_frequent_element(lst):
In a classroom management system, you need to calculate the average student score and identify those who scored above a specific threshold. Which function prototype would you use?
a. def evaluate_scores(students_scores, threshold):
b. def analyze_student_performance(grades, cutoff):
c. def calculate_average_and_identify_above_threshold(students, limit):
d. def check_students_above_threshold(scores, threshold):
Option a – def evaluate_scores(students_scores, threshold):
You want to create a function to reverse the order of elements in a list. What would be the appropriate function signature?
a. def reverse_elements_in_list(lst):
b. def flip_list_elements(elements):
c. def invert_elements_order(data):
d. def reverse_sequence(sequence):
Option a – def reverse_elements_in_list(lst):
You have a list of distances in kilometers and wish to convert them into miles using a conversion factor. Which function would you define?
a. def convert_to_miles(distance_list, conversion_factor):
b. def miles_conversion(distances, factor):
c. def km_to_miles_converter(distances, conversion):
d. def perform_distance_conversion(km_distances, factor):
Option a – def convert_to_miles(distance_list, conversion_factor):
In a grading system, how would you assign letter grades to students based on their numerical scores? Which function prototype would you use?
a. def assign_letter_grades(scores):
b. def convert_to_letters(grades):
c. def grade_students(numerical_scores):
d. def map_to_letter_grades(grade_list):
Option a – def assign_letter_grades(scores):
When developing a weather application, how would you filter out temperatures below freezing from a list? Which function prototype would you define?
a. def filter_freezing_temps(temperature_list):
b. def remove_cold_temps(temperatures):
c. def exclude_below_freezing(degrees):
d. def select_non_freezing(temperature_values):
Option a – def filter_freezing_temps(temperature_list):
Which function prototype would you choose to check if a given list is sorted in ascending order?
a. def is_sorted_ascending(input_list):
b. def check_sort_order(data):
c. def validate_sorting(order_list):
d. def verify_ascending_sequence(sequence):
Option a – def is_sorted_ascending(input_list):
What would be the function signature for counting the occurrences of each unique word in a list of sentences?
a. def count_word_occurrences(sentence_list):
b. def tally_unique_words(sentences):
c. def track_word_frequencies(texts):
d. def analyze_sentence_occurrences(sentence, unique_words):
Option a – def count_word_occurrences(sentence_list):
If you are building a calendar application and need to find the number of events scheduled for a specific date, which function prototype would you use?
a. def count_events_for_date(events, target_date):
b. def find_date_occurrences(schedule, date):
c. def identify_event_count(events_list, specified_date):
d. def check_events_on_date(event_list, target_date):
Option a – def count_events_for_date(events, target_date):
If you have a list of car prices and need to filter out the ones exceeding a set budget, which function would you implement?
a. def filter_expensive_cars(car_prices, budget_limit):
b. def remove_overpriced(cars, max_price):
c. def exclude_high_priced(cars_list, threshold):
d. def select_affordable_cars(prices, limit):
Option a – def filter_expensive_cars(car_prices, budget_limit):
What function would you create to find and display the most common character in a list of strings?
a. def find_most_common_character(strings):
b. def display_max_occurrence(characters):
c. def most_common_string_char(words):
d. def identify_most_common_char(char_list):
Option a – def find_most_common_character(strings):
When creating a voting system, how would you check if a candidate has received enough votes to win? Which function prototype would you use?
a. def check_win_condition(candidate_votes, required_votes):
b. def validate_candidate_victory(votes, threshold):
c. def verify_win(candidate_votes_list, required_count):
d. def has_reached_required_votes(vote_count, required_votes):
Option a – def check_win_condition(candidate_votes, required_votes):
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