# Python Crash Course for Beginners | Python Data Types

Python is a dynamically typed language, which means that the type of a variable is determined at runtime based on the data it holds. In Python, there are several built-in data types that are used to represent different types of data. In this article, we will discuss the most commonly used Python data types, their characteristics, and provide coding examples to illustrate their usage.

# Numeric Data Types

In Python, numeric data types are used to represent numbers. There are three types of numeric data types in Python:

Integers: Integers are whole numbers without a decimal point. For example:

``x = 5``

In this example, we have created a variable named `x` and assigned it the integer value of `5`.

Floating-point numbers: Floating-point numbers are numbers with a decimal point. For example:

``y = 3.14``

In this example, we have created a variable named `y` and assigned it the floating-point value of `3.14`.

Complex numbers: Complex numbers are numbers that have both a real and imaginary part. For example:

``z = 3 + 4j``

In this example, we have created a variable named `z` and assigned it the complex value of `3 + 4j`.

# String Data Types

In Python, string data types are used to represent text. Strings are enclosed in either single quotes (‘ ‘) or double quotes (“ “). For example:

``my_string = "Hello, world!"``

In this example, we have created a variable named `my_string` and assigned it the string value of `"Hello, world!"`.

# Boolean Data Types

In Python, boolean data types are used to represent truth values. The two possible boolean values are `True` and `False`. For example:

``````is_raining = True
is_sunny = False``````

In this example, we have created two variables named `is_raining` and `is_sunny`, each of which is a boolean value.

# List Data Types

In Python, list data types are used to represent a collection of values. Lists are ordered, mutable, and can contain values of different data types. For example:

``my_list = [1, 2, 3, "four", 5.6]``

In this example, we have created a variable named `my_list` and assigned it a list of values that includes an integer, a string, and a floating-point number.

# Tuple Data Types

In Python, tuple data types are similar to lists, but they are immutable (cannot be changed after creation). Tuples are often used to represent fixed sets of values. For example:

``my_tuple = (1, 2, 3, "four", 5.6)``

In this example, we have created a variable named `my_tuple` and assigned it a tuple of values that includes an integer, a string, and a floating-point number.

# Dictionary Data Types

In Python, dictionary data types are used to represent key-value pairs. Dictionaries are unordered, mutable, and can contain values of different data types. For example:

``my_dict = {"name": "John", "age": 30, "city": "New York"}``

In this example, we have created a variable named `my_dict` and assigned it a dictionary of key-value pairs that includes a string, an integer, and another string.

In summary, Python provides a wide range of built-in data types that are used to represent different types of data such as numbers, text, and collections of values. Understanding these data types and how to use them is essential for creating powerful and flexible Python programs. By practicing with coding examples, you can gain a deeper understanding of Python data types and their characteristics. Additionally, Python also provides the ability to create custom data types through object-oriented programming, which allows developers to create complex data structures to represent real-world concepts. By mastering the various Python data types and their usage, developers can create robust and effective Python programs that can handle a wide range of data processing and manipulation tasks.

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