In python matrix can be implemented as 2D list or 2D Array. Forming matrix from latter, gives the additional functionalities for performing various operations in matrix. These operations and array are defines in module “numpy“.
Operation on Matrix :
1. add() :- This function is used to perform element wise matrix addition.
2. subtract() :- This function is used to perform element wise matrix subtraction.
3. divide() :- This function is used to perform element wise matrix division.
The element wise addition of matrix is : [[ 8 10] [13 15]] The element wise subtraction of matrix is : [[-6 -6] [-5 -5]] The element wise division of matrix is : [[ 0.14285714 0.25 ] [ 0.44444444 0.5 ]]
4. multiply() :- This function is used to perform element wise matrix multiplication.
5. dot() :- This function is used to compute the matrix multiplication, rather than element wise multiplication.
The element wise multiplication of matrix is : [[ 7 16] [36 50]] The product of matrices is : [[25 28] [73 82]]
6. sqrt() :- This function is used to compute the square root of each element of matrix.
7. sum(x,axis) :- This function is used to add all the elements in matrix. Optional “axis” argument computes the column sum if axis is 0 and row sum if axis is 1.
8. “T” :- This argument is used to transpose the specified matrix.
The element wise square root is : [[ 1. 1.41421356] [ 2. 2.23606798]] The summation of all matrix element is : 34 The column wise summation of all matrix is : [16 18] The row wise summation of all matrix is : [15 19] The transpose of given matrix is : [[1 4] [2 5]]
This article is contributed by Manjeet Singh 100 🙂 . If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
Attention reader! Don’t stop learning now. Get hold of all the important DSA concepts with the DSA Self Paced Course at a student-friendly price and become industry ready.
- Pandas | Basic of Time Series Manipulation
- Python program to Convert a Matrix to Sparse Matrix
- Python - Convert Matrix to Custom Tuple Matrix
- Python - Convert Integer Matrix to String Matrix
- Maximize sum of N X N upper left sub-matrix from given 2N X 2N matrix
- Circular Matrix (Construct a matrix with numbers 1 to m*n in spiral way)
- Find trace of matrix formed by adding Row-major and Column-major order of same matrix
- Count frequency of k in a matrix of size n where matrix(i, j) = i+j
- Program to check diagonal matrix and scalar matrix
- Check if it is possible to make the given matrix increasing matrix or not
- Program to check if a matrix is Binary matrix or not
- Program to convert given Matrix to a Diagonal Matrix
- Check if matrix can be converted to another matrix by transposing square sub-matrices
- Maximum trace possible for any sub-matrix of the given matrix
- Minimum number of steps to convert a given matrix into Upper Hessenberg matrix
- Minimum steps required to convert the matrix into lower hessenberg matrix
- Minimum number of steps to convert a given matrix into Diagonally Dominant Matrix
- C++ program to Convert a Matrix to Sparse Matrix
- Convert given Matrix into sorted Spiral Matrix
- Check if a given matrix can be converted to another given matrix by row and column exchanges