Python Collection Data Types

Python Collection Data Types

• Python provides various data structures for efficiently storing and managing multiple data points.
• These structures are categorized into sequence and non-sequence types.

Sequence Data Types

• Sequence data types maintain a specific order for elements, enabling indexed access.
• Common examples include strings (str), ranges, lists (list), and tuples (tuple).
• Strings store sequences of characters.
• Ranges represent a sequence of numbers.
• Lists are mutable ordered collections allowing for any data type.
• Tuples are immutable sequences, supporting various data types.

Non-Sequence Data Types

• Non-sequence types, such as dictionaries (dict) and sets (set), do not maintain a specific order of elements.
• Elements are typically accessed using a key, not an index.
• Dictionaries store key-value pairs; keys must be unique and immutable (e.g., strings, numbers, or tuples).
• Sets store unique elements only, ensuring no duplicate values.

Lists (list)

• Lists are mutable, ordered collections in Python.
• They can store elements of different data types.
• Elements are accessed using zero-based indexing.

Built-in Functions

• len(): Returns the number of items in the list.
• type(): Returns the data type of the list.
• max(): Returns the largest value in the list.
• min(): Returns the smallest value in the list.
• sum(): Calculates the total of all numeric values.

Accessing Elements

• Use positive indices (starting from 0) to access elements.
• Use negative indices (starting from -1) to access elements from the end of the list.

List operations

• append(x): Add an item to the end of the list.
• insert(i, x): Insert an item x at index i in the list.
• remove(x): Delete the first item x from the list.
• pop([i]): Remove the item at index i or the last item and return it.
• extend(iterable): Extend the list by appending elements of an iterable (e.g., list or tuple).

List Packing

• +=:Concatenates or extends a list

Methods:

• sort(): Sorts the list in ascending order.
• reverse(): Reverses the order of the list elements.
• copy(): Returns a shallow copy of the list.
• clear(): Empties the list.

Tuples (tuple)

• Tuples are immutable, ordered collections of items in Python.
• Once created, elements within a tuple cannot be changed.
• Accessing tuple elements is done using zero-based indexing.
• Suitable for storing data that shouldn't be modified.

Tuple Operations

• count(x): Returns the number of times x appears in the tuple.
• index(x): Returns the index of the first occurrence of x in the tuple.

Dictionary (dict)

• Dictionary's store key-value pairs.
• Keys are unique identifiers that are immutable (e.g., strings, numbers, or tuples).
• Values are the associated information associated with each key and can be of any data type.

Dictionary Operations

• get(key, default)Returns a value associated with the key or a default value if the key is not found.
• keys(): Returns a view object of all keys.
• values(): Returns a view object of all values.
• items(): Returns a view object of (key, value) pairs as tuples.
• copy(): Creates a copy of the dictionary.
• update(): Updates a dictionary with key-value pairs from another dictionary or iterable.
• clear(): Empties the contents of the dictionary

Sets (set)

• Sets are unordered and mutable collections that contain only unique elements, so duplicate values are not allowed.
• Sets are typically created with curly brackets {}.

Set Operations

• add(): Add an item to the set
• remove(): Remove an item from the set; raises an exception if the item's not found.
• discard(): Remove an item from the set; does not raise an error if the element is not found.
• clear(): Remove all elements from a set
• update(): Add all elements from an iterable to the set

Other useful function

• enumerate(): Returns an iterator of (index, value) pairs, generating both the index
• zip(): Takes multiple iterables, returning an iterator of tuples, where each tuple contains elements from each iterable at the corresponding index.

Explore the various collection data types in Python, including both sequence and non-sequence types. This quiz covers essential concepts such as lists, tuples, dictionaries, and sets, providing you with a comprehensive understanding of how to manage multiple data points in Python effectively.