Prev Next

Python Data Types

In Python, every value has a data type. Python’s dynamic nature means that the data type of a variable is inferred when a value is assigned to it. Understanding Python's various data types helps in writing efficient and effective code. Python supports different types of numbers, collections, sequences, and more.

Common Python Data Types

Numbers (Integers and Floats)

Python supports integers (whole numbers) and floating-point numbers (numbers with decimals). Integers do not have a decimal point, while floats include a decimal.

Example

# Working with integers and floats
x = 10  # Integer
y = 3.14  # Float

print(x)
print(y)

Output

10

3.14

Explanation: The variable x holds an integer value, and y holds a floating-point number. Python automatically assigns the correct type based on the value provided.

Complex Numbers

Python natively supports complex numbers. A complex number consists of a real part and an imaginary part. The imaginary part is denoted with a j.

Example

# Working with complex numbers
z = 2 + 3j
print(z)
print(z.real)
print(z.imag)

Output

(2+3j)

2.0

3.0

Explanation: The variable z holds a complex number. Using z.real and z.imag retrieves the real and imaginary parts of the complex number.

Strings

Strings are sequences of characters enclosed in single, double, or triple quotes. Python strings are immutable, meaning once created, they cannot be modified.

Example

# Working with strings
name = "Python"
print(name)

long_text = """This is a multi-line
string in Python."""
print(long_text)

Output

Python

This is a multi-line
string in Python.

Explanation: Strings can be defined with single, double, or triple quotes. Triple quotes allow multi-line strings, which are useful for longer text blocks.

Booleans

Booleans represent truth values: either True or False. They are commonly used in conditions and comparisons.

Example

# Working with booleans
is_python_fun = True
print(is_python_fun)

print(10 > 5)  # Comparison returns a boolean

Output

True

True

Explanation: Boolean variables hold values of True or False. Comparisons like 10 > 5 return boolean values as well.

Lists

Lists are ordered, mutable collections of items. They are defined using square brackets and can hold any type of data, including numbers, strings, or even other lists.

Example

# Working with lists
fruits = ["Apple", "Banana", "Cherry"]
print(fruits)

fruits.append("Mango")
print(fruits)

Output

["Apple", "Banana", "Cherry"]

["Apple", "Banana", "Cherry", "Mango"]

Explanation: Lists are mutable, meaning you can change, add, or remove elements after the list has been created. The append() method adds an item to the list.

Tuples

Tuples are similar to lists, but they are immutable, meaning their values cannot be changed after they are created. They are defined using parentheses.

Example

# Working with tuples
coordinates = (10, 20)
print(coordinates)

Output

(10, 20)

Explanation: The variable coordinates holds a tuple with two values, 10 and 20. Tuples are immutable, so once created, their values cannot be modified.

Dictionaries

Dictionaries are collections of key-value pairs. They are unordered, mutable, and defined using curly braces. You can access values by using their corresponding keys.

Example

# Working with dictionaries
person = {"name": "Alice", "age": 30}
print(person["name"])
print(person["age"])

Output

Alice

30

Explanation: The variable person is a dictionary that holds the key-value pairs for a person's name and age. You can access the values by using their keys, such as person["name"].

Sets

Sets are unordered collections of unique items. They are defined using curly braces or the set() function. Duplicate values are automatically removed in sets.

Example

# Working with sets
unique_numbers = {1, 2, 3, 3, 2, 1}
print(unique_numbers)

Output

{1, 2, 3}

Explanation: The variable unique_numbers is a set, and any duplicate values are removed automatically. In this case, {1, 2, 3} remains after removing duplicates.

Ranges

The range() function returns a sequence of numbers. It is often used in loops and can take three parameters: start, stop, and step.

Example

# Working with range
numbers = range(1, 6)
for number in numbers:
    print(number)

Output

1

2

3

4

5

Explanation: The range() function generates a sequence of numbers from 1 to 5. It is often used in loops to iterate over a series of numbers.

None Type

The None data type represents the absence of a value. It is commonly used to signify that a variable has no value or to return a null value from a function.

Example

# Using None
x = None
print(x)

Output

None

Explanation: The variable x is assigned the value None, which signifies that it holds no value. None is often used to indicate the absence of a value.

Prev Next