Data Types in Python

Data Types in Python

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1. Getting Familiar With Numbers in Python

Numeric data types are crucial in Python, so it is important to start with them. Here you will work with simple math operations and find out the purposes of learning different types of numerical data.

Numerical Data Type in General

Mutable or Immutable?

Integer Numbers

Compulsory Math

Complicated Math

Challenge: Time Calculation

How to Define a Type

2. True or False?

The main goal of this section is to clarify the boolean data types; it's a sub type of numeric data, but indeed it is more challenging. Since it is always better to excel in the more difficult topics, this section is a valuable part of your curriculum.

Introduction to Boolean Data Type

Challenge: Comparison Operators

And, Or, Not Operators

Challenge: Boosting Logical Skills

Challenge: The Not Statement

Challenge: Logical Statements

3. Strings

Strings are a way for us to implement your phrases in Python, that is, to give instructions to users who are the target audience of your program. Indeed, it is always better to be able to work with strings because they should be used in your code. You'll understand why soon.

Print Your String

Quotation Marks

Get Acquainted With Indexation

Negative Indexation

Slice the Phrase

How to Find the String Length

Get the Index of the Symbol

Find the Word Index

Challenge: Slicing with Index Function

Is String Mutable?

4. Bring All the Topics Together

This chapter consists of practical tasks that combine all the examined topics together with a bit of theory.

Useful Converting

Converting: float()

Converting: bool()

Converting: str()

Math in Strings

Compare Strings

Course Content

Data Types in Python

Data Types in Python

Numerical Data Type in General

Before anything else, it's essential to familiarize ourselves with numeric data types, which are typically the ones we use the most.

Numeric data types typically include two primary built-in categories: integers (int) and floating-point numbers (float). To clarify, 'built-in' indicates that Python can handle them from the start, eliminating the need for us to define them in advance. So, you can simply use int/ float in Python without any additional specifications.

Integer represents the whole numbers you commonly encounter in your daily life, such as 1, 2, 45, or 456566.

On the other hand, floating-point numbers include values like pi (3.14159265359) and Euler's number (2.71828).

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Section 1. Chapter 1

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