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

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

Logical Statements

And, Or, Not Operators

Boost Your Logical Skills

Dealing With Not Statement

Work With 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

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

Converting: float()

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Everything was clear?

Section 4. Chapter 3

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Course Content

Data Types in Python

Converting: float()

Given that we have already acquired an understanding of the int() operation, it is unnecessary to reiterate the same information. The float() function serves a similar purpose, with the distinction of converting data into the floating-point data type.Look at this simple example:😁

It seems to me that one fascinating feature of the float() function should be noted. Not only can we represent regular numbers, but we can also represent concepts like infinity and Not a Number (NaN).

Task

You should take everything with a grain of salt! Try to check the output of the statements that are given in the task. They should be clear for Python too. Just output the code.

NaN - values that were not defined

Everything was clear?

Section 4. Chapter 3

toggle bottom row

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