Python Datatypes

 Python Datatypes

In Python, think of data types as different containers for storing information. Just like in real life, where you might store your clothes in a wardrobe, your books on a shelf, and your snacks in a pantry, Python has its own "containers" for different kinds of data. For example, there's the integer (int) container for whole numbers like 42, the float container for numbers with decimals like 3.14, the string (str) container for text like 'hello', and more. Each container has its own unique properties and behaviors, making it important to choose the right one for the type of data you're working with. So, whether you're organizing your wardrobe or your Python code, knowing your containers – or data types – is key to keeping everything neat and tidy!

Numeric Data Types in Python

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

Integers : In Python, Integers are represented as "int" class. Integers are whole numbers, like 1, 2, 3, -1, -2, -3, etc. You can do math with integers, like adding, subtracting, multiplying, and dividing them.

Floating-point numbers : Float are represented as "float" class. Floats are numbers with decimal points, like 3.14, 2.5, -0.5, etc. They are used when you need more precision in your calculations, such as dealing with money or scientific measurements.

Complex numbers (complex): Complex numbers are used in advanced math. They have a real part and an imaginary part, like 3 + 2j, where '3' is the real part and '2j' is the imaginary part.

These numeric data types help you work with different kinds of numbers in Python, allowing you to perform calculations and solve various problems in your programs.

This code showcases the use of the type() function in Python to identify the data type of variables.

type() function is used to identify the type of data type.

Sequence Data Type in Python

In Python, a sequence data type is like a list of items, where you can put things in a certain order. It's like making a list of groceries you need to buy. There are three main types of sequences in Python:

Lists: Lists are like containers where you can put lots of things, like numbers, words, or even other lists. You can add, remove, or change things in a list easily.

Tuples: Tuples are similar to lists, but once you create them, you can't change what's inside. They're like a fixed list that you can't modify.

Strings: Strings are sequences of characters, like words or sentences. You can think of them as a sequence of letters or symbols that you can manipulate and work with in your code.
These sequence data types help you organize and work with collections of items in Python programs, allowing you to store and manipulate data in a structured way.

Boolean Data Type in Python

In Python, the Boolean data type is like a light switch that can be either on or off, represented by two values: True and False. It helps us make decisions in our code, like answering yes or no questions. For example, we can ask Python if something is true or false, and it will give us an answer. 

Note – True and False with capital ‘T’ and ‘F’ are valid booleans otherwise python will throw an error.

Set Data Type in Python

In Python, a set is like a collection of unique items, kind of like a group of friends where each friend is different. It doesn't allow duplicate elements, so if you add the same thing twice, it only keeps one. Sets are useful for quickly checking whether something is in a group or for removing duplicates from a list. They're also handy for performing mathematical operations like union, intersection, and difference between sets. Think of them as a way to organize and work with distinct elements efficiently in your Python code.

 

Dictionary Data Type in Python

In Python, a dictionary is like a phone book where you can look up information based on a specific key, like finding a person's phone number by their name. It's a collection of key-value pairs, where each key maps to a corresponding value. Dictionaries are useful for storing and retrieving data quickly, and they allow you to organize information in a structured way. You can add, remove, and update entries in a dictionary, making it a versatile data structure for various tasks in Python programming.