search
HomeBackend DevelopmentPython TutorialPython program: Swap the positions of the first and last elements in a matrix between columns

Python program: Swap the positions of the first and last elements in a matrix between columns

A matrix is ​​a two-dimensional array consisting of many numbers arranged in rows and columns. Python does not have any data type to represent matrices, but we can use nested lists or NumPy arrays as matrices.

See the following input and output scenarios to learn how to swap the first and last column elements of the matrix.

Input and output scenarios

Suppose we have a 3X3 matrix represented using a list of lists. The output matrix will be the resulting matrix of swapping the first and last column elements.

Input matrix: 
[1, 3, 4]
[4, 5, 6]
[7, 8, 3]
Output matrix: 
[4, 3, 1]
[4, 5, 6]
[3, 8, 7]

Let us consider another matrix where the rows and columns are not equal.

Input matrix: 
['a', 'b']
['c', 'd', 'e']
['f', 'g', 'h', 'i']

Output matrix: 
['b', 'a']
['e', 'd', 'c']
['i', 'g', 'h', 'f']

Let's look at different ways of swapping the first and last elements in a matrix across columns.

Exchange columns

We can simply swap the first and last elements in the matrix across columns by swapping the first and last column elements of the matrix.

Example

Create a matrix using a list of lists so that we can apply list indexing techniques to swap elements.

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

#function for displaying matrix
def display(matrix):
   for row in matrix:
      print(row)
   print()

# displaying original matrix
print("Original matrix: ")
display(matrix)

# swap column elements
def swapColumns(matrix):
   for i in range(len(matrix)):
      t = matrix[i][0]
      matrix[i][0] = matrix[i][-1]
      matrix[i][-1] = t
   return matrix

# displaying changed matrix
print("Changed matrix: ")
display(swapColumns(matrix))

Output

Original matrix: 
[1, 2, 3]
[4, 5, 6]
[7, 8, 9]

Changed matrix: 
[3, 2, 1]
[6, 5, 4]
[9, 8, 7]

The given matrix is ​​a square matrix and we have successfully swapped the first and last elements of the given matrix across columns, this is done by using python positive and negative indexing.

Example

In this example, we will swap the column elements of a non-square matrix.

matrix = [['a', 'b'], ['c', 'd', 'e'], ['f', 'g', 'h', 'i']]

#function for displaying matrix
def display(matrix):
   for row in matrix:
      print(row)
   print()

# displaying original matrix
print("Original matrix: ")
display(matrix)

# swap column elements
def swapColumns(matrix):
   for i in range(len(matrix)):
      t = matrix[i][0]
      matrix[i][0] = matrix[i][-1]
      matrix[i][-1] = t
   return matrix

# displaying changed matrix
print("Changed matrix: ")
display(swapColumns(matrix))

Output

Original matrix: 
['a', 'b']
['c', 'd', 'e']
['f', 'g', 'h', 'i']

Changed matrix: 
['b', 'a']
['e', 'd', 'c']
['i', 'g', 'h', 'f']

Use a for loop to iterate over the matrix rows and swap column elements using the index.

Use list operation methods

In Python, pop(), insert() and append() are list operation methods. And the matrix is ​​created using a list of lists so that we can swap the first and last elements of the matrix across columns using these list manipulation methods.

  • pop() - The pop method deletes the element at the specified position. By default it removes the last element.

grammar

list_obj.pop(index)
  • insert() - This method can be used to insert an element at any desired position. This method accepts two parameters, an element and the index at which the element must be inserted.

grammar

list_obj.insert(index, element)
  • append() - Method is used to add an element at the end of the list.

grammar

list_obj.append(item)

Example

Let us take an example and apply the pop(), insert() and append() methods.

matrix = [[1, 3], [4, 5, 6], [7, 8, 3, 9]]

#function for displaying matrix
def display(matrix):
   for row in matrix:
      print(row)
   print()

# displaying original matrix
print("Original matrix: ")
display(matrix)

# interchanging the element between first and last columns
for row in matrix:
   temp1 = row[-1]
   temp2 = row[0]
   row.pop()
   row.pop(0)
   row.insert(0, temp1)
   row.append(temp2)

# displaying changed matrix
print("Changed matrix: ")
display(matrix)

Output

Original matrix: 
[1, 3]
[4, 5, 6]
[7, 8, 3, 9]

Changed matrix: 
[3, 1]
[6, 5, 4]
[9, 8, 3, 7]

Using temporary variables and list manipulation methods, we successfully swapped column elements.

The above is the detailed content of Python program: Swap the positions of the first and last elements in a matrix between columns. For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:tutorialspoint. If there is any infringement, please contact admin@php.cn delete
Python vs. C  : Understanding the Key DifferencesPython vs. C : Understanding the Key DifferencesApr 21, 2025 am 12:18 AM

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Python vs. C  : Which Language to Choose for Your Project?Python vs. C : Which Language to Choose for Your Project?Apr 21, 2025 am 12:17 AM

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

Reaching Your Python Goals: The Power of 2 Hours DailyReaching Your Python Goals: The Power of 2 Hours DailyApr 20, 2025 am 12:21 AM

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Maximizing 2 Hours: Effective Python Learning StrategiesMaximizing 2 Hours: Effective Python Learning StrategiesApr 20, 2025 am 12:20 AM

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Choosing Between Python and C  : The Right Language for YouChoosing Between Python and C : The Right Language for YouApr 20, 2025 am 12:20 AM

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python vs. C  : A Comparative Analysis of Programming LanguagesPython vs. C : A Comparative Analysis of Programming LanguagesApr 20, 2025 am 12:14 AM

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

2 Hours a Day: The Potential of Python Learning2 Hours a Day: The Potential of Python LearningApr 20, 2025 am 12:14 AM

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool