Summary of Operators in Python

Types of Arithmetic Operators in Python

Symbol	Description	Return Value
+	Addition	Varies depending on the data types
-	Subtraction	Varies depending on the data types
*	Multiplication	Varies depending on the data types
/	Division	Returns a floating-point value
//	Floor Division	Returns an integer value
%	Modulus	Returns a floating-point value
**	Exponentiation	Varies depending on the data types
and	Logical AND	Returns True or False
or	Logical OR	Returns True or False
<	Less than	Returns True or False
>	Greater than	Returns True or False
<=	Less than or equal to	Returns True or False
>=	Greater than or equal to	Returns True or False
==	Equal to	Returns True or False

+, -, *, /, //, %, **, <, >, <=, >= Table

A	B	Result
int	int	int A + B result
int	float	float A + B result
int	bool-True	int A + 1 result
int	bool-False	int A + 0 result
int	None	TypeError
int	string	TypeError
float	bool-True	float A + 1 result
float	bool-False	float A + 0 result
float	None	TypeError
float	string	TypeError
bool	None	TypeError
bool	string	TypeError
None	string	TypeError

In the early days of computer generation and the inception of programming languages, 1 represented True, and 0 represented False.

== Table

A	B	Result
int	int	Boolean result
int	float	Boolean result
int	bool	Boolean result
int	None	Boolean result
int	string	Boolean result
float	bool	Boolean result
float	None	Boolean result
float	string	Boolean result
bool	None	Boolean result
bool	string	Boolean result
None	string	Boolean result

Unlike Java, this doesn't compare classes. It compares values. Since all are objects, these comparisons are possible.

and, or Truth Tables

A	B	and	or
False	False	False	False
False	True	False	True
True	False	False	True
True	True	True	True

As shown in the table above, "and" and "or" are operations on True and False.

When different data types are used, the "or" operation returns the value of B, while the "and" operation returns the value of A.

What is Python Variables

what is Variable

symbol represent some number or String that may change.

data types

scalar and non-scalar both object

scalar

• int : integer
• float : real number
• bool : True or False
• none : Null

non-scalar

• String : data values that are made up of ordered sequences of characters, such as "hello world"

How to check data type

print(type(Variable))

addtional infomation

Case-Sensitive

a and A are different variable

Casting

x = str(4)    # "4"
y = int(4)    # 4
z = float(4) # 4.0

Setting up Anaconda and PyCharm virtual environments: Step-by-step guide

 

Definition

Anaconda is a package for Python and R languages, providing a convenient conditional free open-source package manager that manages dependencies and distributions.

Since 2020, it has become free only for individual users, universities, non-profit organizations, and small businesses with less than 200 employees. It is now a paid service for government and companies with 200 or more employees.

Reasons to Use Virtual Environments

The reason for using Anaconda is to manage the libraries and versions of Python. By setting up and naming virtual environments, you can easily keep track of the versions and libraries stored in each environment. This makes it convenient to move environments to different locations or reinstall them when needed.

Setting up Anaconda Virtual Environments

Anaconda Installation

1. Download Anaconda from https://www.anaconda.com/ and install it.
2. It is recommended to use the default installation path.
3. If you choose a different installation path, additional configurations may be required based on the IDE you use.
4. The default path is usually C:\Users\[your computer account name]\anaconda3.

Configuration in PyCharm

When creating a new project in PyCharm, you can create a new virtual environment.

Installing Libraries in PyCharm

Sometimes, the default terminal in PyCharm is PowerShell. In such cases, you need to activate the virtual environment and then install libraries.

To activate the virtual environment:

conda activate (virtual environment name)

Controlling Virtual Environments with Anaconda Console

Opening Anaconda Prompt

Start menu - Anaconda Prompt

Finding Possible Python Versions

conda search python

Creating a Virtual Environment

conda create -n (virtual environment name) python=(desired version)

After that, a list of packages to be installed will be displayed. Type 'y' to proceed with the installation.

Activating the Virtual Environment

If the activation is successful, you will see the virtual environment name instead of (base) in the terminal.

From: (base)current/path>

To: (virtual environment name)current/path>

conda activate (virtual environment name)

Deactivating the Virtual Environment

conda deactivate

Listing Virtual Environments

conda env list