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 !!