Data types in Python define the type of value stored in a variable and determine the operations that can be performed on that data. Since Python treats everything as an object, each value is associated with a specific data type.

• Helps the interpreter understand how to store and process different kinds of data efficiently.
• Enables correct operations by ensuring only valid actions are performed on compatible data types.

Below code assigns different types of values to variable x. With each new assignment, the previous value is replaced and x changes to the new data type.

x = 50
x = 60.5
x = "Hello World"
x = ["geeks", "for", "geeks"]
x = ("geeks", "for", "geeks")

Numeric Data Types

In, Python Numeric data types are used to store numeric values. It can be an integer, floating number or even a complex number. It supports three main numeric types:

• Integers: value is represented by int class. It contains positive or negative whole numbers (without fractions or decimals).
• Float: value is represented by float class. It is a real number with a floating-point representation. It is specified by a decimal point.
• Complex: It is represented by a complex class. It stores numbers with real and imaginary parts. For example: 2+3j

a = 5
b = 5.0
c = 2 + 4j

print(type(a))
print(type(b))
print(type(c))

<class 'int'>
<class 'float'>
<class 'complex'>

Sequence Data Types

A sequence is an ordered collection of items, which can be of similar or different data types. Elements in a sequence can be accessed using indexing.

1. String

Strings are used to store text data. A string is represented using the str class and can be created using single, double or triple quotes.

s = 'Welcome to the Geeks World'
print(s)
print(type(s))

# access string with index
print(s[1])
print(s[-1])

Welcome to the Geeks World
<class 'str'>
e
d

2. List

Lists are ordered and mutable collections used to store multiple items in a single variable. Elements in a list can be of different data types and are accessed using indexing.

a = [1, 2, 3]
print(a)

b = ["Geeks", "For", "Geeks", 4, 5]
print(b[3])
print(b[-3])

[1, 2, 3]
4
Geeks

3. Tuple

Tuples are ordered and immutable collections used to store multiple items in a single variable. Once created, tuple elements cannot be modified and are accessed using indexing.

Note: A tuple with a single element must include a trailing comma, otherwise Python treats it as a normal value instead of a tuple.

t1 = (1,)
print(type(t1))

t2 = ('Geeks', 'For', 'Geeks', 1, 2)
print(t2[3])
print(t2[-3])

<class 'tuple'>
1
Geeks

Boolean Data Type

Boolean data type represents one of two values: True or False. It is mainly used in conditions and comparisons and is represented by the bool class.

print(type(True))
print(type(False))

<class 'bool'>
<class 'bool'>

Truthy and Falsy Values

truthy and falsy values are values that evaluate to True or False in a Boolean context. Truthy values behave like True, while falsy values behave like False when used in conditions.

if 1:
    print("1 is truthy")

if not 0:
    print("0 is falsy")

1 is truthy
0 is falsy

Set Data Type

Sets are unordered and mutable collections used to store unique elements. Since sets are unordered, elements cannot be accessed using indexing. Elements are usually accessed by iterating through the set using a loop.

s1 = {"a", "a", "b", "c", "b"}
print(s1)

s2 = {"Geeks", "For", "Geeks"}
for i in s2:
    print(i)

{'b', 'a', 'c'}
Geeks
For

Note: Sets in Python are unordered, so the order of elements when printed may vary each time the code is run.

Dictionary Data Type

Dictionaries are used to store data in key:value pairs. Each key in a dictionary must be unique and values are accessed using their keys with square brackets [] or get() method.

Note: Dictionary keys are case sensitive, the same name but different cases of Key will be treated distinctly.

d = {1: 'Geeks', 2: 'For', 3: 'Geeks'}
print(d[1])    
print(d.get(2))