Day 3: A Beginner's Guide to Python Lists

Day 3: A Beginner's Guide to Python Lists

Introduction:

Welcome to Day 3 of my Python journey!

Today, I explored the fascinating world of data structures in Python, specifically lists.

These data types is crucial for storing and manipulating complex data.

LIST DATA TYPE / LIST CLASS

Basic :

  • \ list is a **predefined class** avaliable in python* .

  • * to get the manual of list class,

  • \>>> help ( list ) .

  • \ list is a collection of **similar or disimilarly** types of elements/objects.*

  • \ list object is python is represented by **[ ]* .

  • * each element avaliable in list object must be separated by coma ( , ) how to create the object of list class,

  • obj = list ()

  • print ( obj , type ( obj ))

  • obj = list ( [ 11, 22, 33 ] )

  • print ( obj , type ( obj ))

  • obj = [ 11, 22, 33, 44 ]

  • print ( obj , type ( obj ))

  • obj = [ 11, 1.2, 1+2j, True , None ]

  • print ( obj , type ( obj ) )

  • list store the element according to insertion order.

  • list is an ordered data structure. .

  • list supports duplicate element. .

  • to get the number of elements avaliable in a list object we can apply len () function .

  • list object is a mutable object in python because we can modify the list object.

  • Indexing :

  • index is used to perform read write update and delete a specific element in a list object. .

  • to provide index with list object, we have to use subscript operator.

    listObj [ index] .

  • * index must be an integral constant .

  • \ valid index starts from **0 to len - 1* .

  • * invalid index raise IndexError .

  • \ list supports **-ve** index .*

  • * -ve index starts from -len to -1 .

  • \ by using index we can modify a list object in future **as per the demand** of situation.*

  • obj = [ 11, 22, 33, 44, 55 ]

  • print ( obj )

  • # write or update operation

  • obj [ 2 ] = 300

  • # read operation

  • print ( obj [ 0 ] )

  • print ( obj [ 1 ] )

  • print ( obj [ 2 ] )

  • print ( obj [ 3 ] )

  • print ( obj [ 4 ] )

  • print ( obj [ 0 ])

  • #print ( obj [ 0.0 ]) #TypeError

  • #print ( obj [ 10 ]) #IndexError

  • OPERATORS :

  • Basic :

  • all the operators available in python is not going to supported by list object .

  • list object supports some limited operators .

  • ARITHMATIC + *

  • + merging

  • * repetation .

  • RELATIONAL < > <= >= == !=

  • relational operator returns bool type object ( True / False )

  • Whenever we are using comparison operators(==,!=) for List objects then the following should be considered

  • 1. The number of elements

  • 2. The order of elements

  • 3. The content of elements (case sensitive)

  • Note: When ever we are using relatational operators(<,<=,>,>=) between List objects,only first element comparison will be performed.

  • ASSIGNMENT :

  • \= -> it create a copy of list object .

  • MEMBERSHIP : in not in

  • membership operator returns bool type object .

  • IDENTITY : is is not

  • identity operator returns bool type object

  • obj1 = [ 11, 22, 33 ]

  • obj2 = [ 44, 55 ]

  • obj = obj1 + obj2

  • print ( obj1 , obj2 , obj )

  • print ( obj 1 )

  • obj1 = [ 1, 2, 5, 4 ]

  • obj2 = [ 1, 2, 3, 10 ]

  • print ( obj1 < obj2 )

  • print ( 11 in [ 11, 22, 33 ] ) #True

  • print ( 55 in [ 11, 22, 33 ] ) #False

  • print ( 55 not in [ 11, 22, 33 ] ) #True

  • obj1 = [11, 22, 33]

  • obj2 = [11, 22, 33]

  • print (obj1 is obj2) #False

  • obj3 = obj1

  • print (obj1 is obj3 ) #True

  • print (obj1 is not obj2) #True

  • print (obj2 is obj3) #False

  • Ex :

    obj1 = ['dog', 'cat', 'tiger']

    obj2 = ['Dog', 'cat', 'tiger']

    print (obj1 > obj2 )

    print (obj1 != obj2 )

    print (obj1 == obj2 )

  • x = [2,6,4]

    y = [3,4,6]

    z = [0, 6, 4]

    print ( x > y )

    print ( x != z )

  • x1 =['dog']

    x2= ['doh']

    print (x1 > x2 ) #false

    print (x2 > x1 ) #True

  • Challenges:

  • Understanding list comprehension.

  • Handling errors.

Resources:

  1. Official Python Documentation: Data Structures

  2. W3Schools' Python Tutorial: Lists

  3. Scaler's Python Course: Data Structures

Goals for Tomorrow:

  1. Explore sets and tuple , dictionary.

  2. Learn about handling key errors.

Conclusion:

Day 3 was a blast! Lists, tuples, and dictionaries are now under my belt.

What are your favorite data structures in Python? Share in the comments below.

Connect with me:

GitHub: https://github.com/p-archana1

LinkedIn : https://www.linkedin.com/in/archana-prusty-4aa0b827a/

Join the conversation:

Share your own learning experiences or ask questions in the comments.

Next Post:

Day 4: tuple, dictionary

Happy reading :)

THANKS A LOT !!