Data Types Python

Sure! Let’s go through the main data types in Python: numbers, lists, sets, tuples, and dictionaries, along with their methods and examples.

1. Numbers

Python supports three types of numeric data:

• Integers: Whole numbers, e.g., 5, -3
• Floats: Decimal numbers, e.g., 3.14, -0.001
• Complex Numbers: Numbers with a real and imaginary part, e.g., 2 + 3j

Example:

a = 5          # Integer
b = 3.14       # Float
c = 2 + 3j     # Complex number

print(type(a))  # Output: <class 'int'>
print(type(b))  # Output: <class 'float'>
print(type(c))  # Output: <class 'complex'>

2. Lists

A list is an ordered collection of items which can be of different types. Lists are mutable, meaning they can be changed after creation.

Methods:

• append(): Adds an item to the end of the list.
• extend(): Adds all items of a list to another list.
• insert(): Inserts an item at a given position.
• remove(): Removes the first occurrence of an item.
• pop(): Removes and returns an item at a given position.
• clear(): Removes all items from the list.
• index(): Returns the index of the first occurrence of an item.
• count(): Returns the count of the number of items.
• sort(): Sorts the list in ascending order.
• reverse(): Reverses the order of the list.
• copy(): Returns a shallow copy of the list.

Example:

fruits = ["apple", "banana", "cherry"]
fruits.append("orange")
print(fruits)  # Output: ['apple', 'banana', 'cherry', 'orange']

3. Sets

A set is an unordered collection of unique items. Sets are mutable but do not allow duplicate elements.

Methods:

• add(): Adds an element to the set.
• update(): Adds multiple elements to the set.
• remove(): Removes an element from the set. Raises KeyError if the element is not found.
• discard(): Removes an element from the set if it is a member. Does nothing if the element is not found.
• pop(): Removes and returns an arbitrary set element. Raises KeyError if the set is empty.
• clear(): Removes all elements from the set.
• union(): Returns a set containing all elements from both sets.
• intersection(): Returns a set containing only elements that are in both sets.
• difference(): Returns a set containing elements that are in the first set but not in the second.
• symmetric_difference(): Returns a set containing elements that are in either set but not in both.

Example:

fruits = {"apple", "banana", "cherry"}
fruits.add("orange")
print(fruits)  # Output: {'banana', 'cherry', 'apple', 'orange'}

4. Tuples

A tuple is an ordered collection of items which can be of different types. Tuples are immutable, meaning they cannot be changed after creation.

Methods:

• count(): Returns the number of times a specified value occurs in a tuple.
• index(): Searches the tuple for a specified value and returns the position of where it was found.

Example:

fruits = ("apple", "banana", "cherry")
print(fruits[1])  # Output: banana

5. Dictionaries

A dictionary is an unordered collection of key-value pairs. Keys must be unique and immutable, while values can be of any type.

Methods:

• get(): Returns the value for a specified key.
• keys(): Returns a list containing the dictionary’s keys.
• values(): Returns a list of all the values in the dictionary.
• items(): Returns a list containing a tuple for each key-value pair.
• update(): Updates the dictionary with the specified key-value pairs.
• pop(): Removes the element with the specified key.
• popitem(): Removes the last inserted key-value pair.
• clear(): Removes all elements from the dictionary.
• copy(): Returns a copy of the dictionary.

Example:

person = {"name": "John", "age": 30, "city": "New York"}
print(person["name"])  # Output: John
person["email"] = "john@example.com"
print(person)  # Output: {'name': 'John', 'age': 30, 'city': 'New York', 'email': 'john@example.com'}