What are the Basic Data Types in Python?

Understanding the basic data types in Python can be crucial to set up an interview with Python developers that will help you hire python developers for your next software project. They are the fundamental types of data in python and enable proficiency to deal with more complex functions later on. In this post, we will go through what are the basic data types in Python and also provide some examples along with best practices which can help you guys to write more awesome pythonic code for yourself as well as your team.

Data Types in Python

Data Types in Python are the classification of data items. Since Python’s data types are not fixed, they will be interpreted during runtime; this is why many people call it a dynamic type language and provides good usage for various applications.

Basic Data Types in Python

Python has too many data types built-in that you will encounter while programming. Let’s explore each of them:

1. Integer

Description: It represents both positive and negative integers (whole numbers) without fraction or decimals.

Example: x = 10

2. Float

Description: Represents decimal numbers ranging from positive to negative with measured values.

Example: y = 10.5

3. String

Signature: A group of characters enclosed within quotes.commit31828.nextInt

Example: name = "Python"

4. Boolean

A boolean is either True or False.

Example: is_valid = True

5. List

type: An ordered, mutable collection of items.

Example: numbers = [1,2,3,4,,5]

6. Tuple

RealWorldItem: An ordered, immutable collection of items.

For Example : coordinates = (10.0, 20.0)

7. Dictionary

Description: A mapping from unique keys to values

For example, student = {"name": "Alice","age" : 23}

8. Set

Mutable Set: A mutable unordered collection of unique items.

Sample: unique_numbers = {1,2,3,4,5}

Examples of Basic Data Types in Python

Working with Integers and Floats

x = 10 ? ? ? # Integer

y = 10.5 ? ? # Float

result = x + y

print(result)? # Output: 20.5

String Manipulation

name = "Python"

greeting = "Hello, " + name

print(greeting)? # Output: Hello, Python

Using Lists and Tuples

numbers = [1, 2, 3, 4, 5]? # List

coordinates = (10.0, 20.0) # Tuple

print(numbers[0])? # Output: 1

print(coordinates[1])? # Output: 20.0

Managing Data with Dictionaries and Sets

student = {"name": "Alice", "age": 23}? # Dictionary

unique_numbers = {1, 2, 3, 4, 5} ? ? ? # Set

print(student["name"])? # Output: Alice

print(unique_numbers) ? # Output: {1, 2, 3, 4, 5}

Reasons to Hire If You Opt in for Python Developers

Proficient In Python Data-structures

Python developers are able to efficiently handle and manipulate these data types ensuring your code is both lean-efficient as well optimized.

Efficient Code Practices

Experienced Python developers are able to write clean, efficient and maintainable code which is so important for your project in the long-term.

Problem-Solving Skills

By hiring Python developers who are proficient in data types, you can expect quick fixes at the time of troubleshooting which eventually saves a lot of your valuable time and money.