What data types does Python have?

Python data types are essential for rep­re­sent­ing, pro­cess­ing and using data. By utilizing different data types, you can store in­for­ma­tion in an efficient manner and optimize the per­for­mance of your ap­pli­ca­tion.

What are Python data types?

Python data types are value cat­e­gories that are used to represent different kinds of data. They dictate how in­for­ma­tion can be stored and ma­nip­u­lat­ed. Python provides a range of different data types, including integers (whole numbers), floats (decimal numbers) and strings (character strings). More advanced types include lists, tuples, dic­tio­nar­ies and sets. Data types fa­cil­i­tate data struc­tur­ing and pro­cess­ing, making them pivotal to Python pro­gram­ming.

The primary objective of Python data types is to structure data according to pre­de­fined rules so the needs of diverse ap­pli­ca­tions can be fulfilled. Each data type possesses distinct functions and prop­er­ties. For instance, lists maintain items in an ordered sequence, while dic­tio­nar­ies employ key-value pairs for targeted data retrieval. Selecting suitable data types for your data will make your program flexible and easier to maintain.

What kinds of data types are there in Python?

Python has various built-in data types, including:

• Numeric data types: int, float, complex
• Strings: str
• Se­quen­tial data types: list, tuple, range
• Binary types: bytes, bytearray, memoryview
• Dic­tio­nar­ies: dict.
• Boolean data types: bool.
• Sets: set, frozenset

Numerical data types

There are several Python data types that you can use to work with numbers:

1. Integer (int): The integer type rep­re­sents whole numbers without decimal places.
2. Long (long): Long is used for integers with an unlimited length. As of Python 3, long and int are merged.
3. Float (float): The float type includes numbers with decimal places.
4. Complex (complex): The complex type includes complex numbers with a real part and an imaginary part, indicated by the suffix j.

# Variable with integer value. 
a=3 
 
# Variable with float value. 
b=3.17 
 
# Variable with complex value. 
c=50+7j

Strings

A Python string (str) rep­re­sents a sequence of char­ac­ters. You can mark them with single, double or triple quotation marks.

# Single quotes 
str1 = 'Hello World!' 
 
# Double quotes 
str2 = "This is a string." 
 
# Triple quotes for multiline strings 
str3 = '''This is a multiline string.'''

In Python, strings are immutable, meaning they cannot be changed once created. However, strings support numerous methods and op­er­a­tions for ma­nip­u­la­tion, con­cate­na­tion and analysis. You can store the results in variables to get new strings.

Examples of string op­er­a­tions:

• Length of a string: len(str)
• Slicing: str[start:end]
• Con­cate­nate strings: str1 + str2

Se­quen­tial data types

Se­quen­tial data types in Python are data struc­tures that store an ordered col­lec­tion of elements. They allow access to elements based on their position within the sequence. There are several se­quen­tial Python data types:

Lists (list): Python lists are mod­i­fi­able se­quen­tial data types that represent an ordered col­lec­tion of elements. You can change, add and remove elements in a list. Lists are created using square brackets and contain elements of different data types.

my_list = [1, 2, 3, 'Hello', 'World']

Tuple (tuple): Tuples are un­change­able se­quen­tial data types which, like lists, display an ordered col­lec­tion of elements. In contrast to lists, tuples cannot be changed af­ter­wards. Use round brackets for tuples.

my_tuple = (4, 5, 6, 'Python')

Range (range): This is a special Python data type utilized for gen­er­at­ing sequences of numbers, often used in loops and it­er­a­tions. The range data type creates a sequence of integers within a specified range. The range object generates numbers on demand rather than storing them as a complete list in memory, enhancing ef­fi­cien­cy, par­tic­u­lar­ly with large number sequences.

# Range from 0 to 4 
my_range = range(4) 
for i in my_range: 
    print(i) 
# Output: 0, 1, 2, 3

Binary types

Bytes (bytes): The data type bytes rep­re­sents an un­change­able sequence of bytes. Bytes can be created using the bytes() con­struc­tor or the prefix b.

my_bytes = b'Hello'

bytearray (bytearray): In contrast to bytes, bytearray belongs to the mod­i­fi­able Python data types, rep­re­sent­ing a sequence of bytes. This means that you can modify the values after de­c­la­ra­tion.

my_bytearray = bytearray(b'Python')

Dic­tio­nar­ies

In Python, a dic­tio­nary (dict) is a data structure that stores an unordered col­lec­tion of elements in the form of key-value pairs. Unlike lists or tuples, which contain an ordered sequence of elements, unique keys are used to access elements in a dic­tio­nary.

my_dict = {
    "name": "Max",
    "age": 25,
    "city": "Berlin"
}

Boolean data types

Boolean Python data types represent truth values that can be either true (True) or false (False). This data is crucial for logical eval­u­a­tions and decisions within a program.

a = True
b = False
result_1 = (a and b) # returns False
result_2 = (a or b) # returns True
result_3 = (not a) # returns False

Sets

A set is an unordered col­lec­tion of unique values that doesn’t allow du­pli­cates. You can use it to store multiple elements where each element is unique.

my_set = {1, 2, 3, 4, 5}

A frozenset is an un­change­able version of a set. Once created, elements cannot be added, removed or changed.

my_set = {1, 2, 3, 4, 5}
frozen_set = frozenset(my_set)