Python variable

 

Hi...

Let's go through some factors about Python Variables in this blog

1. What variables are?

2. Create our first variables in Python 

3. Learn about variable " type() " 

So let's get started

Well to understand easily we can consider Variable as a box where we can store data. Data can be of any type such as text, images, video, audios, etc.

Now, the variable contains two things :
1. Name
2. Value

A) Assign " Integer type " value in the variable name Number.
here "Number" is the variable name and the value assigned in it is "10" 👇.

Whenever we type the Number, it will show the contained value here "10"☝.

B). Now, We can assign " String type " data on the same variable
Number = "JK"

C). Now, We can assign "Float type " data on the same variable

let's check the type of value stored in our variable "Number"

How??

Yea!... you got it right it's now time to use  " type( ) " keyword :👇👇

Important Points :

#1. Python variables are case sensitive means variable name "Number" is different from "number".

#2. Python variables are Dynamically typed variable means there is no need to define a variable type like int, float, char, etc before assigning value. But in another languages like C, C++, Java, etc we need to define data type before assigning any value in the variables.  C, C++, Java are the statically typed() whereas python is Dynamically typed.

#3. The last value stored is retained in the variable.

Review :

1. Variables are like boxes that store data.

2. Variables can be defined as -     variable = value

3. In Python, Variable type can be changed Dynamically.

4. Use the type() variable to get variable type.

Great, enjoy practising till next blog comes☺...

Python Boolean Operations

Python Boolean Operations: and, or, not 

Boolean operators such and, or, and not are also called logical operators.

" and " and " or "operators requires two variables whereas " not " operators need only one variable. 

1. "and " operator test example :

It is interesting to know that "and" is a short-circuit operator, it checks both the arguments if both the operands are true or both are false then it returns true. Whereas if any one of the operands is true and other operands are false then it returns false.

# boolean "and" operator test program

x= 5
y=10
print(x);
print(y);
if (x>3 and y>1):
   print("true")
else:
   print("false") 

2. "or " operator test example :

Like "and" the "or" is also short-circuit operator, it also checks both the argument if any operand is true it returns true. Whereas, if all operands are false then it returns false.

# boolean "or" operator test program

x= 5
y=10
print(x);
print(y);
if (x>10 or y>12):
   print("true")
else:
   print("false") 

3. " not " operator test example :

This operator is also called inverter operator which actually clarifies it's nature or function. It just provides the inverted output. Means if an operand is true then it returns false and vice-versa. It requires only one operand.

# boolean "not" operator test program

x= 5
y=10
print(x);
print(y);
if not (x > 10) :
   print("true")
else:
   print("flase") 

Easiest Way to Start Python Coding

 

How to Get Started With Python using Google Colab?

In this blog, we will learn to use Google colab web editor and run code on a cloud platform. Once done with it, we'll write our first Python program using Colab.

Introduction 

Jupyter Editor :

The Jupyter Notebook is an open-source editor application that permits us to make and share the code as well as documents. It contains live code, conditions, perceptions and text. It utilizations include data preprocessing (like data cleaning, data combining, data noise reduction, etc ), numerical manipulation, mathematical simulation, factual displaying, information representation, AI, and significantly more.

Google colab : 

Google colab is similar to Jupyter Notebook. We can say" Colab is a Jupyter Notebook stored on google drive". We find the same structure and look of code editor consisting code and text cells as in Python. The benefit here is the cloud space and the speed due to the allocated server RAM. Basically, it reduces the struggling of execution delay while dealing with a large dataset or a larger number of epochs which makes use of colab best while working with the Machine Learning, Deep Learning and other AI domains.

Alright so let's get started...

Step 1: You should have a Gmail account.

Step 2: Search "colab" in google search engine.

Step 3: Colaboratory or " colab" window will appear.

Step 4: Then Go to the file and open a new notebook window.

Step 5: New Untitled window will appear.

Now we can start writing our first python coding on colab editor.

Type below-mentioned code on the editor :

print (" My first Python Code in Colab") 

then press left side arrow button  and run the code.

Congratulations! We just wrote our first Python program in Colab editor.

See how simple it is... 

This is the magnificence of Python programming language.