Untitled
45 Questions
0 Views

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

Which of the following is the most accurate definition of an 'effective' algorithm?

  • An algorithm that is feasible and always produces the correct result. (correct)
  • An algorithm that is easy to understand but may not produce the correct result.
  • An algorithm that uses natural language for its representation.
  • An algorithm that is written in pseudocode.

When would using pseudocode be most advantageous over using natural language to represent an algorithm?

  • When the algorithm needs to be executed directly by a computer.
  • When the algorithm needs to be easily understood by non-programmers.
  • When the algorithm needs a precise and code-like representation. (correct)
  • When the algorithm is very simple and straightforward.

What characteristic distinguishes Python lists from other data structures?

  • Lists are immutable, meaning they cannot be changed once created.
  • Lists are ordered collections, allowing duplicate values and modification. (correct)
  • Lists can only contain elements of the same data type.
  • Lists use curly braces `{}` to define their elements.

If you need to store a collection of items where the order matters and you anticipate needing to add or remove items, which data structure would be most suitable?

<p>A list, because it is ordered and mutable. (A)</p> Signup and view all the answers

Consider the following Python code:

my_list = [10, "apple", 3.14, True]
print(len(my_list))

What will be the output of this?

<p>4 (C)</p> Signup and view all the answers

Which of the following statements is correct regarding the data types of items within a single Python list?

<p>Items can be of any data type, including mixed types. (B)</p> Signup and view all the answers

Given the list my_list = ['apple', 'banana', 'cherry'], how can you access the second item ('banana')?

<p>my_list[1] (D)</p> Signup and view all the answers

What will be the output of the following Python code?

my_list = [10, 20, 30, 40, 50]
print(my_list[1:4])

<p>[20, 30, 40] (D)</p> Signup and view all the answers

Which of the following scenarios best illustrates the Last In, First Out (LIFO) principle of a stack data structure?

<p>Undoing the most recent action in a text editor. (B)</p> Signup and view all the answers

When deciding on the most suitable data structure for a program, why is it important to consider access patterns?

<p>Different access patterns affect the efficiency of data retrieval and manipulation. (C)</p> Signup and view all the answers

Which data structure is most suitable for implementing a 'call history' feature, where the most recent calls need to be accessed quickly?

<p>Stack (D)</p> Signup and view all the answers

An algorithm is designed to sort a list of numbers. Which of the following is NOT a required characteristic of this algorithm?

<p>The algorithm must use the least amount of memory possible at all costs. (B)</p> Signup and view all the answers

A program uses a queue to manage print jobs. What is the most likely outcome if the program adds print jobs faster than the printer can process them?

<p>The queue will grow, potentially leading to increased memory usage. (D)</p> Signup and view all the answers

In the context of algorithm design, what does 'definiteness' refer to?

<p>Each step in the algorithm must be precisely and unambiguously defined. (D)</p> Signup and view all the answers

Which of the following best describes a scenario where a tree data structure would be more appropriate than a linked list or an array?

<p>Representing a company's organizational hierarchy. (A)</p> Signup and view all the answers

Why is the finiteness property crucial for an algorithm to be considered effective?

<p>Without finiteness, the algorithm might never produce a result. (B)</p> Signup and view all the answers

What will be the output of the following Python code snippet?

thislist = ["apple", "banana", "cherry"]
thislist.pop(1)
print(thislist)

<p><code>['apple', 'cherry']</code> (C)</p> Signup and view all the answers

What happens when you try to execute the following Python code?

thislist = ["apple", "banana", "cherry"]
del thislist
print(thislist)

<p>The program raises a <code>NameError</code> because <code>thislist</code> is no longer defined. (D)</p> Signup and view all the answers

Which of the following statements accurately describes a tuple in Python?

<p>Tuples are immutable, ordered collections of items that can contain elements of different data types. (A)</p> Signup and view all the answers

Which of the following is a primary reason for using tuples in Python?

<p>Tuples guarantee data integrity because their immutability prevents accidental modification. (D)</p> Signup and view all the answers

What is the output of the following Python code?

coordinates = (3, 4)
new_coordinates = coordinates + (5,)
print(len(coordinates))
print(3 in coordinates)

<p><code>2\nTrue</code> (D)</p> Signup and view all the answers

Given the tuple my_tuple = (1, 2, 3, 4, 5), what will the following code print?

my_tuple = (1, 2, 3, 4, 5)
if 6 in my_tuple:
  print("6 is present in the tuple")
else:
  print("6 is not present in the tuple")

<p><code>6 is not present in the tuple</code> (A)</p> Signup and view all the answers

What will be the output of the following Python Code:

name = ("ana", "boy", "cherry")
print(name[-2:-1])

<p><code>('boy',)</code> (A)</p> Signup and view all the answers

How can you modify a tuple in Python, given that tuples are immutable?

<p>Tuples can be modified by first converting them to a list, making the necessary changes, and then converting the list back to a tuple. (C)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def index():
    thislist = ["apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"]
    print(thislist[2:5])
index()

<p><code>['cherry', 'orange', 'kiwi']</code> (A)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def index_remove():
    thislist = ["apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"]
    print(thislist[:4])
index_remove()

<p><code>['apple', 'banana', 'cherry', 'orange']</code> (B)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def index_negative():
    thislist = ["apple", "banana", "cherry", "orange", "kiwi", "melon", "mango"]
    print(thislist[-4:-1])
index_negative()

<p><code>['orange', 'kiwi', 'melon']</code> (C)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def index_list1():
    fruits = ["apple", "banana", "cherry"]
    fruits = "melon"
    print(fruits)
index_list1()

<p><code>melon</code> (A)</p> Signup and view all the answers

What will be the output of the following Python code?

def index_change():
    fruits = ["apple", "banana", "cherry", "orange", "kiwi", "mango"]
    fruits[1:2] = ["pineapple", "watermelon"]
    print(fruits)
index_change()

<p><code>['apple', 'pineapple', 'watermelon', 'orange', 'kiwi', 'mango']</code> (B)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def add_list():
    fruits = ["apple", "banana", "cherry"]
    fruits.insert(2, "watermelon")
    print(fruits)
add_list()

<p><code>['apple', 'banana', 'watermelon', 'cherry']</code> (C)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def insert():
    thislist = ["apple", "banana", "cherry"]
    tropical = ["mango", "pineapple", "papaya"]
    thislist.extend(tropical)
    print(thislist)
insert()

<p><code>['apple', 'banana', 'cherry', 'mango', 'pineapple', 'papaya']</code> (D)</p> Signup and view all the answers

What will be printed when the following Python code is executed?

def list_remove():
    thislist = ["apple", "banana", "cherry"]
    thislist.remove("banana")
    print(thislist)
list_remove()

<p><code>['apple', 'cherry']</code> (D)</p> Signup and view all the answers

What type of object is returned when using the .keys() method on a dictionary in Python?

<p>A view object that displays a list of all the keys in the dictionary. (B)</p> Signup and view all the answers

Given the dictionary student = {"name": "Alice", "age": 20, "city": "New York"}, what will len(student) return?

<p>3 (C)</p> Signup and view all the answers

What is the primary difference between using my_dict = {} and del my_dict when working with dictionaries?

<p><code>my_dict = {}</code> clears the dictionary's contents, while <code>del my_dict</code> deletes the dictionary from memory. (C)</p> Signup and view all the answers

Which method returns a view object that displays a list of a dictionary's key-value pairs?

<p>items() (D)</p> Signup and view all the answers

If student = {"name": "Alice", "age": 20, "city": "New York"}, what data type will be the elements in the view object returned by student.values()?

<p>string and integer (D)</p> Signup and view all the answers

What is the primary difference between using square bracket access (e.g., student['age']) and the get() method (e.g., student.get('age')) when accessing dictionary values?

<p><code>get()</code> returns <code>None</code> if the key is not found, while square bracket access raises a <code>KeyError</code>. (C)</p> Signup and view all the answers

What is the result of running this code?

name = ["ana", "boy", "chery"]
name1 = ("den", "bing")
name += name1
print(name)

<p><code>[&quot;ana&quot;, &quot;boy&quot;, &quot;chery&quot;, &quot;den&quot;, &quot;bing&quot;]</code> (D)</p> Signup and view all the answers

Given the dictionary student = {"name": "Alice", "age": 20, "city": "New York"}, what happens when you execute del student['age']?

<p>The key-value pair ('age', 20) is removed from the dictionary. (A)</p> Signup and view all the answers

What is the purpose of the in keyword when used with a dictionary in Python?

<p>To check if a specific key exists within the dictionary's keys. (B)</p> Signup and view all the answers

What is the output of the following code?

student = {"name": "Alice", "age": 20, "city": "New York"}
student.pop("age")
print(student)

<p><code>{'name': 'Alice', 'city': 'New York'}</code> (B)</p> Signup and view all the answers

What is the result of the following code?

names = ["ana", "boy", "chery"]
names1 = ("den", "bing")
concatenated_names = [*names, *names1]
print(concatenated_names)

<p><code>['ana', 'boy', 'chery', 'den', 'bing']</code> (B)</p> Signup and view all the answers

Which of the following statements best describes a Python dictionary?

<p>An unordered collection of key-value pairs where keys must be unique and immutable. (D)</p> Signup and view all the answers

Given student = {"name": "Alice", "age": 20, "city": "New York"}, what will student.keys() return?

<p><code>dict_keys(['name', 'age', 'city'])</code> (D)</p> Signup and view all the answers

Flashcards

Data Structures

Ways data is organized, stored, and manipulated in a program.

Arrays

A collection of elements identified by an index number.

Linked Lists

Linear data where each element points to the next.

Stacks

Last In, First Out (LIFO) data structure.

Signup and view all the flashcards

Queues

First In, First Out (FIFO) data structure.

Signup and view all the flashcards

Trees

Hierarchical data with a root node and child nodes.

Signup and view all the flashcards

Algorithm

Step-by-step recipe for solving a problem.

Signup and view all the flashcards

Algorithm input

Data the algorithm takes in.

Signup and view all the flashcards

Algorithm Effectiveness

An algorithm's ability to be practically executable and produce a correct result.

Signup and view all the flashcards

Natural Language (Algorithms)

Using common language to describe the steps of an algorithm.

Signup and view all the flashcards

Flowcharts

Diagrams that represent the flow of control in an algorithm.

Signup and view all the flashcards

Pseudocode

A mix of natural language and code-like syntax to describe an algorithm.

Signup and view all the flashcards

Python Lists

Ordered, changeable collections of items in Python.

Signup and view all the flashcards

List Item Data Types

Lists can hold various data types (strings, numbers, booleans).

Signup and view all the flashcards

Ordered Lists

Items in a list have a specific sequence, and this order is maintained.

Signup and view all the flashcards

Changeable Lists

You can change, add, or remove items after the list has been created.

Signup and view all the flashcards

dictionary.keys()

Returns all keys from a dictionary.

Signup and view all the flashcards

dictionary.values()

Returns all values from a dictionary.

Signup and view all the flashcards

dictionary.items()

Returns key-value pairs (items) from a dictionary.

Signup and view all the flashcards

len(dictionary)

Returns the number of key-value pairs in a dictionary.

Signup and view all the flashcards

dictionary = {} or del dictionary

Empties a dictionary.

Signup and view all the flashcards

List Index Range

Accesses a range of items in a list using their indexes.

Signup and view all the flashcards

List Start Index Range

Accesses a range from the beginning of the list up to a specified index.

Signup and view all the flashcards

Negative List Index Range

Accesses a range using negative indexes, starting from the end of the list.

Signup and view all the flashcards

Change List Item

Changes the value of a specific item in a list.

Signup and view all the flashcards

Change List Item Range

Modifies several list items within a defined range.

Signup and view all the flashcards

Insert List Item

Inserts an item into a list at a specific index, shifting other elements.

Signup and view all the flashcards

Append List Item

Adds an item to the end of a list.

Signup and view all the flashcards

Extend List

Adds elements from another list to the end of the current list.

Signup and view all the flashcards

List pop(index)

Removes the item at the specified index from a list.

Signup and view all the flashcards

del keyword in lists

The del keyword removes the item at the specified index or can delete the entire list.

Signup and view all the flashcards

Tuples

Ordered, immutable collections of items, created using parentheses ().

Signup and view all the flashcards

Why use Tuples?

Tuples are efficient and useful for maintaining data integrity because they are immutable.

Signup and view all the flashcards

Tuple Operations

Access specific elements, combine tuples, find length, and check membership.

Signup and view all the flashcards

Membership Testing (in/not in)

Checks if an element is present in a tuple.

Signup and view all the flashcards

Access Tuple Items

Access tuple items using their position (index), starting from 0. Negative indexing starts from the end (-1).

Signup and view all the flashcards

Modify a tuple

Modify a tuple by converting it to a list, making changes, and then converting it back to a tuple.

Signup and view all the flashcards

List += operator

Adds elements from another iterable (like a tuple) to an existing list.

Signup and view all the flashcards

* operator for lists

Unpacks elements from multiple iterables (like lists or tuples) into a new combined list.

Signup and view all the flashcards

Dictionary (Python)

An unordered collection of key-value pairs, mutable and defined using curly braces {}.

Signup and view all the flashcards

Dictionary Characteristics

Unordered, mutable, uses key-value pairs, and is defined using curly braces.

Signup and view all the flashcards

Dictionary .get() method

Safely retrieves a value by key; returns None (or a default) if the key is absent.

Signup and view all the flashcards

Dictionary del keyword

Removes a key-value pair from a dictionary, given the key.

Signup and view all the flashcards

Dictionary .pop() method

Removes a key-value pair and returns the value, given the key.

Signup and view all the flashcards

Dictionary in operator

Checks if a key exists in a dictionary, returning True or False.

Signup and view all the flashcards

Study Notes

  • Data structures are fundamental building blocks in computer programming.
  • Data structures define how data is organized, stored, and manipulated in a program.
  • Common data structures: arrays, linked lists, stacks, queues and trees.

Common Data Structures

Arrays

  • Arrays are a collection of elements, each identified by an index.
  • An example is a shopping list where each item is stored in a numbered position.

Linked Lists

  • Linked Lists are a linear collection of data elements where each element points to the next.
  • A playlist where each song points to the next one is an example.

Stacks

  • Stacks are a LIFO (Last In, First Out) structure.
  • New elements are added and removed from the top.
  • A stack of plates where the last plate placed is the first one taken out is an example

Queues

  • Queues a FIFO (First In, First Out) structure.
  • Elements are added at the rear and removed from the front.
  • A waiting line at a ticket counter is an example.

Trees

  • Trees are a hierarchical structure with a root node and child nodes.
  • A file system structure with folders and files is an example.
  • The choice of data structure depends on the specific problem being solved. Key factors to consider include access patterns, insertion and deletion, memory usage and performance.

Classification of Data Structures

  • Data structures can be classified as linear or non-linear.
  • Linear data structures can be further classified as static or dynamic.
    • Static Data Structures: Array
    • Dynamic Data Structure: Queue, Stack, Linked list
    • Non-Linear Data Structures: Tree, Graph

Algorithms

  • An algorithm is a step-by-step recipe for solving a problem, composed of a set of instructions a computer can follow to accomplish a task.
  • A good algorithm should be correct and produce the right answer, and efficient, using minimal resources such as time and memory.
  • The steps for finding the largest number in a list provides an example, composed of a set of instructions that a computer can follow to accomplish a task.

Criteria for Algorithms

  • Input: Algorithms must clearly specify what data they take as input.
  • Output: Algorithms must clearly define their result.
  • Definiteness: Algorithm steps must be clear.
  • Finiteness: Algorithms must terminate after a finite number of steps.
  • Effectiveness: Algorithms must be feasible and produce the correct result.

Representing Algorithms

  • Algorithms can be represented in Natural Language using everyday language to describe steps
  • Or they can be represented in Flowcharts using diagrams for the flow of control,
  • Or in Pseudocode, a mixture of natural language and code-like syntax.
  • Natural language can be use to find the factorial of a number n by starting with a variable results and set it to 1, then looping through every number i from 1 to n and multiplying result by i.
  • After completing all multiplications, the result will be the factorial of n.
  • Pseudocode example for calculating the factorial of a number:
    • Function factorial(n):
      • result = 1
      • For i = 1 to n:
        • Result = result * i
        • Return result

Python's Built-In Collections

Lists

  • Lists are ordered collections of items, are mutable and can be changed.
  • Use square brackets [] to create lists
    • Ex: numbers = [1,2,3,4,5]

Characteristics of Python Lists

  • List items are ordered, changeable, and allow duplicate values.
  • List items are indexed, the first item has index [0], the second item has index [1] etc.
  • The items have a defined order, and that order will not change. If new items are added to a list, the new items will be placed at the end of the list.
  • Lists are changeable, allowing items to be changed, added, and removed in a list after it has been created.

Lists Length

  • Use the len() to determine how many items a list has.

Lists Items Data Types

  • List items can be of any data type such as String, int and boolean data types.

Access List Items

  • List items are indexed and can be accessed them by referring to the index number.
  • Range of Indexes can be specified by specifying where to start and where to end the range.
  • Range of negative indexes can be useful to start the search from the end of the list.

Change List Items.

  • Change the value of a specific item, by referring to the index number..
  • A range of list item values can be changed.
  • New list items can be inserted to the list without replacing any of the existing values using the insert) method.
  • Items can be appended to the end of the list using the append() method.
  • To append elements from another list to the current list, use the extend() method.
  • The remove() method removes the specified item in a list.
  • Also, the pop() method removes the specified index in a list, and the del keyword also removes the specified index.

Python's Built-In Collections

Tuples

  • Tuples are ordered collections of items.
  • Tuples contain elements of different data types.
  • Tuples are immutable (cannot be changed); parentheses () create tuples.
    • Example: coordinate = (3,4)
  • Tuples promote efficiency and data integrity

Tuple operations

  • Indexing and slicing: Access specific elements or tuples.
  • Concatenation: Combine tuples using the + operator.
  • Length: Find the number of elements using len().
  • Membership testing: Check if an element is present using in and not in.
  • Tuples can be accessed directly by specifying the index, while negative numbers are useful by referring to the values from the end.

Tuple Modification

  • Python does not allow modification of tuples after they are created.
  • Tuples can be maniouplated by converting to a list, and back.
  • The + operator or * operator can concatenate values and return the values inside a new list.

Python's Built-In Collections Cont

Dictionaries

  • Dictionaries are unordered collections of key-value pairs and they are mutable using curly braces {} to create.
    • Example: person = {"name": "Alice", "age": 30, "city": "New York"}

Key Characteristics of Python Dictionary

  • Unordered
  • Mutable
  • Uses Key Value Pairs surrounded by Curly Braces

Dictionary Operations

  • The get() method provides a safer method to access values in a dictionary and returns a default value if the key is not found, preventing a KeyError.
  • Using del deletes a key-value pair.
  • The pop() method removes and return an element from a dictionary.
  • Using in checks if a specific key exists within a dictionary.
  • keys() extracts all the keys from a dictionary.
  • values() returns a view of the dictionary's values.
  • items() returns a view of the dictionary's key-value pairs.
  • len(my_dict) returns the number of key-value pairs.
  • my_dict = {} / del my_dict empties or deleted the dictionary

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Quiz Team

Related Documents

More Like This

Untitled Quiz
6 questions

Untitled Quiz

AdoredHealing avatar
AdoredHealing
Untitled
44 questions

Untitled

ExaltingAndradite avatar
ExaltingAndradite
Untitled
6 questions

Untitled

StrikingParadise avatar
StrikingParadise
Untitled Quiz
50 questions

Untitled Quiz

JoyousSulfur avatar
JoyousSulfur
Use Quizgecko on...
Browser
Browser