13.3 sort() and sorted() function

Duration: 5 min

This video lesson is available to enrolled students.

Return to /learn/MPPSC-ASSISTANT-PROFESSOR-COMPUTER-SCIENCE-PAPER-2/python/collections-strings/lists/asset-133-sort-and-sorted-function after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. Paper 1 | General Studies: State Wise GK
  3. Paper 1 | Information and Communication Technology: Role of Internet and Web Services, Security in Mobile and Wireless Computing
  4. Paper 1 | Current Affairs: GK- Current Affairs
  5. Paper 2 | Discrete Mathematical Structure: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Set Theory, Relations, Functions, Graph Theory, Group Theory, Propositional and Predicate Logic, Probability
  6. Paper 2 | Digital Computer Organization And Architecture: Number System, Number Representation, Sequential Circuits, Combinational Circuit, Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Pipelining, Instr Formats & Modes, Register Transfer and Microoperations, Control Unit Design, Programming the Basic Computer
  7. Paper 2 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  8. Paper 2 | Programming Languages & Object-Oriented Programming Concepts: Java, OOPS with C++, Java Fundamentals, Array, String, IO & References
  9. Paper 2 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  10. Paper 2 | Data Structure And Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Minimum Spanning Trees, Advanced Algorithms
  11. Paper 2 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Unix OS
  12. Paper 2 | Theory Of Computation: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Complexity Theory
  13. Paper 2 | Compiler Design: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization, Run Time Environment
  14. Paper 2 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Algebra, SQL, Transaction Management, Concurrency Control, Database Recovery, Database Security & Authorization, Enhanced Data Models
  15. Paper 2 | Computer Network And Information Security: Introduction to CN, Data Communication, Application Layer, Hardware basics, Cyber Threats and Malware Attacks, Network Security, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP
  16. Paper 2 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  17. Paper 2 | Current Trends & Technologies: Emerging Tech Trends, Approaches to AI, Search Algorithms, Game Playing, Knowledge Representation, Planning, Multi Agent Systems, Fuzzy Sets, Natural Language Processing, Artificial Neural Networks, Genetic Algorithms, Artificial Intelligence, Data Warehousing & Mining, Electronic Data Interchange and E-Commerce, Terms & Abbreviations
  18. Paper 2 | Full Length Mock Tests:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This educational video provides a comprehensive comparison of two Python sorting methods: the list method `sort()` and the built-in function `sorted()`. The lecture begins by introducing the `sort()` method, defining it as a list method that modifies the original list in-place and sorts elements in ascending order by default. The instructor demonstrates this with a code example using a list of numbers, showing the original list being altered. The video then transitions to the `sorted()` function, explaining that it returns a new sorted list without modifying the original, and can work on any iterable, including tuples and strings. A code example demonstrates sorting a tuple, which requires converting the result back to a tuple. The lesson concludes with a summary table that contrasts the two methods on key features such as type, return value, and the data they work on, emphasizing that `sort()` is a method for lists only, while `sorted()` is a versatile function for any iterable.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video opens with a title slide showing the text 'sort(), sort()'. The instructor then introduces the 'sort() - List Method' on a digital blackboard. The slide provides a definition: 'sort() is a list method', 'It modifies the original list', and 'Sorts elements in ascending order by default'. The instructor explains these points, emphasizing that the method changes the original list. The on-screen text clearly states that the method modifies the original list, which is a key characteristic being taught.

  2. 2:00 – 4:46 02:00-04:46

    The instructor transitions to the 'sorted() - Built-in Function' slide. The slide lists its features: it returns a new sorted list, the original list remains unchanged, and it works on any iterable (list, tuple, string). The instructor demonstrates this with a code example: `numbers = [40, 10, 30, 20]`, `new_list = sorted(numbers)`, `print(new_list)`, `print(numbers)`. The on-screen text shows the output `[10, 20, 30, 40]` for the new list and `[40, 10, 30, 20]` for the original, visually confirming the non-destructive nature of `sorted()`. The video then shows an example of sorting a tuple `t = (5, 2, 9, 1)`, with the code `print(sorted(t))` and the output `[1, 2, 5, 9]`, illustrating that `sorted()` can handle tuples. The final slide presents a comparison table, summarizing that `sort()` is a list method that modifies the original list and returns `None`, while `sorted()` is a built-in function that returns a new list and works on any iterable.

The video systematically teaches the difference between Python's `sort()` method and `sorted()` function. It first establishes that `sort()` is a method that operates directly on a list, modifying it in-place, which is useful when the original order is not needed. It then introduces `sorted()` as a more flexible, non-destructive function that creates a new list, preserving the original. The core lesson is the trade-off: use `sort()` for efficiency when you want to change the original list, and use `sorted()` when you need to keep the original data intact or when working with non-list iterables. The comparison table at the end effectively consolidates these key differences for the learner.

Loading lesson…