Introduction to Python: Lists, Tuples, Sets
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Introduction to Python: Lists, Tuples, Sets

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Questions and Answers

A list is an ordered, mutable collection of ______ that can contain duplicates.

items

To add an item to the end of a list, you can use the ______ method.

append

A tuple is an ordered, ______ collection of items that cannot be modified after creation.

immutable

The method ______ combines two sets in Python.

<p>union</p> Signup and view all the answers

You create a set using curly ______ to define its items.

<p>braces</p> Signup and view all the answers

A dictionary contains key-value ______ and is created using curly braces.

<p>pairs</p> Signup and view all the answers

To iterate over a list using a for loop, the syntax begins with 'for ______ in my_list:'.

<p>item</p> Signup and view all the answers

In Python, the while loop repeats as long as a certain ______ is true.

<p>condition</p> Signup and view all the answers

The ______ method in a dictionary returns a view of all keys.

<p>keys</p> Signup and view all the answers

To remove the first occurrence of an item from a list, you would use the ______ method.

<p>remove</p> Signup and view all the answers

Study Notes

Introduction to Python

Lists

  • Definition: Ordered, mutable collection of items (can contain duplicates).
  • Creation: my_list = [1, 2, 3]
  • Common Methods:
    • append(item): Adds item to the end.
    • insert(index, item): Inserts item at specified index.
    • remove(item): Removes the first occurrence of item.
    • pop(index): Removes item at index and returns it.
    • sort(): Sorts the list in place.
    • reverse(): Reverses the list in place.

Tuples

  • Definition: Ordered, immutable collection of items (can contain duplicates).
  • Creation: my_tuple = (1, 2, 3)
  • Properties:
    • Cannot be modified after creation.
    • Can contain mixed data types.
  • Common Methods:
    • count(item): Returns the number of occurrences of item.
    • index(item): Returns the index of the first occurrence of item.

Sets

  • Definition: Unordered collection of unique items (no duplicates).
  • Creation: my_set = {1, 2, 3}
  • Common Methods:
    • add(item): Adds item to the set.
    • remove(item): Removes item from the set (raises error if not found).
    • discard(item): Removes item (does not raise error).
    • union(set2): Combines two sets.
    • intersection(set2): Returns common items.

Dictionaries

  • Definition: Unordered collection of key-value pairs.
  • Creation: my_dict = {"key1": "value1", "key2": "value2"}
  • Common Methods:
    • get(key): Returns value for the specified key.
    • keys(): Returns a view of all keys.
    • values(): Returns a view of all values.
    • items(): Returns a view of key-value pairs.
    • pop(key): Removes and returns value for the specified key.

Loops

  • For Loop:

    • Used to iterate over sequences (like lists, tuples).
    • Syntax:
      for item in my_list:
          # do something with item
      
  • While Loop:

    • Repeats as long as a condition is true.
    • Syntax:
      while condition:
          # do something
      
  • Loop Control Statements:

    • break: Exits the loop.
    • continue: Skips the current iteration and continues with the next.
    • else: Optional block that runs after loop completes (not terminated by break).

Lists

  • Ordered and mutable collections that can hold duplicate items.
  • Created using square brackets: my_list = [1, 2, 3].
  • Common Methods:
    • append(item): Adds an item to the end of the list.
    • insert(index, item): Inserts an item at a specified index.
    • remove(item): Removes the first occurrence of a specified item.
    • pop(index): Removes and returns the item at the specified index.
    • sort(): Sorts the list in ascending order in place.
    • reverse(): Reverses the order of items in the list in place.

Tuples

  • Ordered and immutable collections that can include duplicates.
  • Created using parentheses: my_tuple = (1, 2, 3).
  • Properties include:
    • Inability to modify after creation.
    • Capability to hold mixed data types.
  • Common Methods:
    • count(item): Counts occurrences of a specified item.
    • index(item): Returns the index of the first occurrence of a specified item.

Sets

  • Unordered collections of unique items, meaning no duplicates are allowed.
  • Created using curly braces: my_set = {1, 2, 3}.
  • Common Methods:
    • add(item): Adds an item to the set.
    • remove(item): Removes a specified item (raises an error if the item does not exist).
    • discard(item): Removes a specified item without raising an error if the item does not exist.
    • union(set2): Combines the items of two sets into one.
    • intersection(set2): Returns items that are common to both sets.

Dictionaries

  • Unordered collections consisting of key-value pairs.
  • Created using curly braces with colon separation: my_dict = {"key1": "value1", "key2": "value2"}.
  • Common Methods:
    • get(key): Retrieves the value associated with a specified key.
    • keys(): Provides a view of all the keys in the dictionary.
    • values(): Provides a view of all the values in the dictionary.
    • items(): Provides a view of all key-value pairs in the dictionary.
    • pop(key): Removes and returns the value corresponding to the specified key.

Loops

  • For Loop:

    • Iterates over a sequence such as lists or tuples.
    • Syntax example:
      for item in my_list:
          # do something with item
      
  • While Loop:

    • Continues executing as long as a specified condition remains true.
    • Syntax example:
      while condition:
          # do something
      
  • Loop Control Statements:

    • break: Immediately exits the loop.
    • continue: Skips the current iteration and moves to the next one.
    • else: An optional block that executes after the loop ends normally (i.e., not caused by break).

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Description

Explore the foundational concepts of Python's data structures including lists, tuples, and sets. This quiz covers their definitions, creation, and common methods, providing a solid understanding for beginners in Python programming. Test your knowledge in these essential topics of data manipulation.

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