A data type defines the kind of value a variable contains. In programming, data types are essential because they help to determine the operations that can be performed on the data. Some commonly used Python data types are: integers, floating-point numbers, strings, lists, tuples, and dictionaries. Understanding these types can greatly enhance your coding capabilities and allow for more efficient data manipulation.
Data Type
Example
Used For
int
25
Whole numbers
float
25.5
Decimal numbers
complex
2 + 3j
Complex numbers
str
"Hello"
Text
bool
True
True/False values
list
[10, 20, 30]
Ordered collection
tuple
(10, 20, 30)
Ordered, fixed collection
set
{10, 20, 30}
Unique values
dict
{"name": "Amit"}
Key-value data
None
None
No value
Data Types in Python
An integer is a whole number without a decimal point. It can be positive, negative, or zero and does not include any fractions or decimals. Integers are often used in various mathematical contexts and can be represented on a number line, extending infinitely in both directions.
Input
Explanation
age = 25
print(age)
print(type(age))
Output
25 is a whole number, which means that it belongs to the set of integers. Thus, Python identifies it as an int, allowing developers to use it in calculations and various functions where whole numbers are needed.
25
<class 'int'>
1. Integer (int)
A float is a number that contains a decimal point, and it is commonly used in programming and mathematics to represent fractions or precise values. For instance, in programming languages, a float can be critical in scenarios involving calculations that require a high degree of accuracy. They allow for greater flexibility and enable a wider range of numerical exercises, thus playing an essential role in various computations.
Input
Explanation
price = 99.50
print(price)
print(type(price))
Output
price = 99.50 creates a variable named price and stores the decimal value 99.50 in it. Since the value contains a decimal point, Python treats it as a float (floating-point number).
print(price) displays the value stored in the price variable.
print(type(price)) checks the data type of the variable. Python returns <class 'float'>, confirming that price is a floating-point number.
99.5
<class 'float'>
2. Floating-Point Number (float)
Python also supports complex numbers. A complex number contains a real part and an imaginary part, allowing for operations and computations that involve both dimensions. This makes it a versatile option for mathematical modeling and simulations, especially when dealing with phenomena that require both real and imaginary components.
Input
Explanation
number = 3 + 4j
print(number)
print(type(number))
Output
number = 3 + 4j creates a variable named number and stores a complex number in it. Here, 3 is the real part and 4j is the imaginary part. In Python, j represents the imaginary unit.
print(number) displays the complex number as (3+4j).
print(type(number)) checks the data type of the variable. Python returns <class 'complex'>, confirming that number is a complex data type.
(3+4j)
<class 'complex'>
3. Complex Numbers (complex)
In Python, a string (str) is a sequence of characters used to store text. Strings can be written inside single quotes (' ') or double quotes (" "). They can contain letters, numbers, spaces, and special characters. Strings are commonly used to store names, messages, and other text-based information.
Input
Explanation
first_name = "Rahul"
last_name = "Sharma"
full_name = first_name + " " + last_name
print(full_name)
print(type(full_name))
Output
first_name = "Rahul" stores the first name in the first_name variable, while last_name = "Sharma" stores the last name in the last_name variable.
full_name = first_name + " " + last_name combines both strings using the + operator. The " " adds a space between the first and last name.
print(full_name) displays the complete name as Rahul Sharma.
print(type(full_name)) checks the data type of full_name. Since it contains text, Python returns <class 'str'>, which means it is a string.
Rahul Sharma
<class 'str'>
4.String (str)
A Boolean value represents one of two conditions:
True
False
Input
Explanation
is_student = True
has_passed = False
print(is_student)
print(has_passed)
Output
Boolean values are commonly used when working with conditions and decision-making in Python.
is_student = True creates a variable named is_student and assigns it the Boolean value True. Similarly, has_passed = False creates a variable named has_passed and assigns it the Boolean value False.
print(is_student) displays True, while print(has_passed) displays False. In Python, Boolean values represent one of two possible states: True or False. They are commonly used in conditions and decision-making.
True
False
5. Boolean (bool)
A list is used to store multiple values in a single variable.
Lists are written using square brackets [].
Input
Explanation
Output
fruits stores multiple values in a list, written using [].
A list can contain different data types, such as strings, integers, and floats. print() displays all the values stored in the list.
['Apple', 'Mango', 'Banana']
6. List (list)
fruits = ["Apple", "Mango", "Banana"]
print(fruits)
A list can contain different types of values:
student = ["Amit", 20, 85.5]
print(student)
['Amit', 20, 85.5]
A tuple is similar to a list, but its values cannot normally be changed after creation.
Tuples use parentheses ().
Input
Explanation
Output
colors = ("Red", "Green", "Blue") creates a tuple containing multiple values. Tuples are written using parentheses () and their values cannot normally be changed after creation.
print(colors) displays the values, while print(type(colors)) confirms that colors is a tuple.
('Red', 'Green', 'Blue')
<class 'tuple'>
7. Tuple (tuple)
colors = ("Red", "Green", "Blue")
print(colors)
print(type(colors))
A set is a collection of unique values that are important in various branches of mathematics. Sets use curly brackets {} to denote the elements contained within. For example, a set can represent numbers, characters, or even objects. It is essential to understand the concept of sets, as they provide a foundation for more complex mathematical theories and applications.
Input
Explanation
Output
numbers = {10, 20, 30, 10} creates a set containing multiple values. Sets store only unique values, so the duplicate 10 is automatically removed.
print(numbers) displays the unique values as {10, 20, 30}.
{10, 20, 30}
8. Set (set)
numbers = {10, 20, 30, 10}
print(numbers)
A dictionary stores information in key-value pairs.
These pairs consist of unique keys that map to corresponding values, allowing for efficient data retrieval and organization.
Input
Explanation
Output
student is a dictionary that stores data in key-value pairs. Here, "name" and "age" are keys, while "Amit" and 20 are their values.
print(student) displays the complete dictionary. student["name"] accesses the value stored under the "name" key, so the output is Amit.
Amit
9. Dictionary (dict)
student = { "name": "Amit", "age": 20 } print(student)
You can access a value using its key:
print(student["name"])
{'name': 'Amit', 'age': 20}
None represents the absence of a value.
Input
Explanation
Output
It is quite useful when a variable currently has no meaningful value, as it can help in understanding the absence of data and allows for more effective handling of situations where a value is not yet established or available.
None
<class 'NoneType'>
10. None (NoneType)
result = None
print(result)
print(type(result))
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