Data types in Python

Data types in Python

In the Python programming language, there are different data types, each of which is used for specific purposes. In this article, we will review data types and their applications.

  1. Numeric data types

Numeric data types include two main categories:

Integer: This data type is used to display positive and negative integers. Example: x = 42 or y = -10.

Decimal numbers (Float): This data type is used to display decimal numbers. Example: z = 3.14 or w = -2.5.

  1. Types of textual data

Textual data types include two main types:

Strings: This data type is used to display text. Strings can contain letters, numbers, and symbols. Example: name = “John Doe” or message = ‘Hello, World!’.
Characters: In Python, characters are part of strings and are not displayed individually.

  1. Logical data types

Logical data types in Python include a basic type:

Logical values ​​(Boolean): This type of data can display two true values ​​(True) or false (False). Example: is_student = True or is_adult = False.

  1. Mixed data types

Composite data types in Python include several main types:

Lists: This data type is used to display a set of data. Lists can contain different data types. Example: fruits = [“apple”, “banana”, “cherry”] or numbers = [1, 2, 3, 4, 5].

Tuples: This data type is similar to lists, but their values ​​are fixed and cannot be changed. Example: point = (3, 4) or person = (“John”, 25, “Engineer”).
Sets: This data type is used to represent a collection of unique data. Example: colors = {“red”, “green”, “blue”} or unique_numbers = {1, 2, 3, 4, 5}.
Dictionaries: This data type is used to represent a set of key-values. Keys must be unique. Example: person = {“name”: “John”, “age”: 25, “occupation”: “Engineer”} or grades = {“math”: 90, “science”: 85, “english”: 92}.

  1. Advanced data types

In Python, there are also more advanced data types that can be accessed using Python’s standard libraries. Some of these data types are:

Date and Time: The datetime and time libraries are used to work with date and time.
Files: In Python, files are considered a data type and can be accessed using the open() function.

Graphs: Libraries such as networkx and matplotlib are used to create and display graphs.
Matrices: Libraries like numpy are used to work with matrices and perform advanced mathematical calculations.

  1. Conversion of data types

In Python, data types can be converted to each other. This process is known as “casting”. For example, an integer can be converted to a string:

کستینگ عدد صحیح به رشته
Casting an integer to a string

 

Or you can convert a string to an integer:

کستینگ رشته به عدد صحیح
Casting string to integer

 

  1. Applications of data types

Data types in Python are very diverse and powerful, and each one is used for specific purposes. For example:

Integer and decimal numbers are used to perform mathematical calculations.
Strings are used to work with text and generate text output.
Logical values ​​are used to perform logical operations and control program flow.

Lists and dictionaries are used to store and manage a collection of data.

All in all, data types in Python are very broad and flexible and can be used to create diverse and powerful programs.

Click to download Python.