Time And Space Complexity

Time Complexity And SPace complexity  these play an important role on how efficient the algorithm or code gonna work  

Firstly Time Complexity  it is the amount of time taken as function of input size (n) considering all the operations .
It is Reprsented In BIG O notation  because it calculates the worst case complexity and Upper bound Ccomplexity rather than using Theta notation ( average Complexity)  and Omega Notation( Lower bound Complexity)

Three rules to be generally followed 
 1. Always compute the worst case scenario 
 2. Avoid Constants or Considered them as 1
 3. Avoid lower values (for example in this " n^5+n^2+1 " in this u can ignore "l") 

This is generalized graph for Time Complexity 

https://adrianmejia.com/images/time-complexity-examples.png

Secondly Space Complexity is  the amount of memory an algorithm or data structure needs to solve a problem, as a function of the input size. 
It is also  represented in BIG O Notation
Space complexity = Auxillary space ( Space that we take to code ) + Input space ( Space that is used to the Input )

For consider (C=A+B ) as an space complexity 
  C represnts the auxillary space 
  A,B Represnts the Input Space 

Important note Is: Never do Data Manipulation in space complexity to reduce the space acquired 

Graph is similar to that of time complexity 

https://cdn.botpenguin.com/assets/website/Space_Complexity_155761920b.webp


Checkout these links for the better Understanding 
 https://www.youtube.com/watch?v=PwKv8fOcriM   (Hindi)

https://www.youtube.com/watch?v=pULw1Fpru0E   from 6:49 Time complexity ( english)
https://www.youtube.com/watch?v=oQ5sAfT_3V4   from 2:55 Space complexity ( english)