How to read matrix in python

Python: Read a matrix from console and print the sum for each column

Write a Python program to read a matrix from the console and print the sum for each column. As input from the user, accept matrix rows, columns, and elements separated by a space (each row).

Sample Solution:

Python Code:

rows = int(input("Input rows: ")) columns = int(input("Input columns: ")) matrix = [[0]*columns for row in range(rows)] print('Input number of elements in a row (1, 2, 3): ') for row in range(rows): lines = list(map(int, input().split())) for column in range(columns): matrix[row][column] = lines[column] sum = [0]*columns print("sum for each column:") for column in range(columns): for row in range(rows): sum[column] += matrix[row][column] print((sum[column]), ' ', end = '') 

Input rows: 2 Input columns: 2 Input number of elements in a row (1, 2, 3): 1 2 3 4 sum for each column: 4 6

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Documentation references for the modules, constants and functions used above:

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• os.path.realpath(path) (returns «the canonical path of the specified filename, eliminating any symbolic links encountered in the path»)
• os.path.dirname(path) (returns «the directory name of pathname path»)
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Take Matrix input from user in Python

In this tutorial, we are going to learn how to take matric input in Python from the user. We can take input from the user in two different ways. Let’s see two of them.

Method 1

Taking all numbers of the matric one by one from the user. See the code below.

Example

# initializing an empty matrix matrix = [] # taking 2x2 matrix from the user for i in range(2): # empty row row = [] for j in range(2): # asking the user to input the number # converts the input to int as the default one is string element = int(input()) # appending the element to the 'row' row.append(element) # appending the 'row' to the 'matrix' matrix.append(row) # printing the matrix print(matrix)

Output

If you run the above code, then you will get the following result.

Matrix 2

Taking one row at a time with space-separated values. And converting each of them to using map and int function. See the code.

Example

# initializing an empty matrix matrix = [] # taking 2x2 matrix from the user for i in range(2): # taking row input from the user row = list(map(int, input().split())) # appending the 'row' to the 'matrix' matrix.append(row) # printing the matrix print(matrix)

Output

If you run the above code, then you will get the following result.

Conclusion

If you have queries in the tutorial, mention them in the comment section.

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Python Matrix: Transpose, Multiplication, NumPy Arrays Examples

A Python matrix is a specialized two-dimensional rectangular array of data stored in rows and columns. The data in a matrix can be numbers, strings, expressions, symbols, etc. Matrix is one of the important data structures that can be used in mathematical and scientific calculations.

How do Python Matrices work?

The data inside the two-dimensional array in matrix format looks as follows:

Step 1) It shows a 2×2 matrix. It has two rows and 2 columns. The data inside the matrix are numbers. The row1 has values 2,3, and row2 has values 4,5. The columns, i.e., col1, have values 2,4, and col2 has values 3,5.

Step 2) It shows a 2×3 matrix. It has two rows and three columns. The data inside the first row, i.e., row1, has values 2,3,4, and row2 has values 5,6,7. The columns col1 has values 2,5, col2 has values 3,6, and col3 has values 4,7.

So similarly, you can have your data stored inside the nxn matrix in Python. A lot of operations can be done on a matrix-like addition, subtraction, multiplication, etc.

Python does not have a straightforward way to implement a matrix data type.

The python matrix makes use of arrays, and the same can be implemented.

• Create a Python Matrix using the nested list data type
• Create Python Matrix using Arrays from Python Numpy package

Create Python Matrix using a nested list data type

In Python, the arrays are represented using the list data type. So now will make use of the list to create a python matrix.

We will create a 3×3 matrix, as shown below:

• The matrix has 3 rows and 3 columns.
• The first row in a list format will be as follows: [8,14,-6]
• The second row in a list will be: [12,7,4]
• The third row in a list will be: [-11,3,21]

The matrix inside a list with all the rows and columns is as shown below:

List = [[Row1], [Row2], [Row3] . [RowN]]

So as per the matrix listed above the list type with matrix data is as follows:

To read data inside Python Matrix using a list.

We will make use of the matrix defined above. The example will read the data, print the matrix, display the last element from each row.

Example: To print the matrix

M1 = [[8, 14, -6], [12,7,4], [-11,3,21]] #To print the matrix print(M1)

The Matrix M1 = [[8, 14, -6], [12, 7, 4], [-11, 3, 21]]

Example 2: To read the last element from each row

M1 = [[8, 14, -6], [12,7,4], [-11,3,21]] matrix_length = len(M1) #To read the last element from each row. for i in range(matrix_length): print(M1[i][-1])

Example 3: To print the rows in the Matrix

M1 = [[8, 14, -6], [12,7,4], [-11,3,21]] matrix_length = len(M1) #To print the rows in the Matrix for i in range(matrix_length): print(M1[i])

Adding Matrices Using Nested List

We can easily add two given matrices. The matrices here will be in the list form. Let us work on an example that will take care to add the given matrices.

Last will initialize a matrix that will store the result of M1 + M2.

Example: Adding Matrices

To add, the matrices will make use of a for-loop that will loop through both the matrices given.

• The syntax for slicing is – [start:end]
• If the start index is not given, it is considered as 0. For example [:5], it means as [0:5].
• If the end is not passed, it will take as the length of the array.
• If the start/end has negative values, it will the slicing will be done from the end of the array.

[ 8 10 12] [ 2 4 6 8 10] [ 6 8 10 12 14 16] [ 8 10 12 14] [ 2 4 6 8 10 12 14]

Now let us implement slicing on matrix . To perform slicing on a matrix

the syntax will be M1[row_start:row_end, col_start:col_end]

• The first start/end will be for the row, i.e to select the rows of the matrix.
• The second start/end will be for the column, i.e to select the columns of the matrix.

The matrix M1 tthat we are going to use is as follows:

M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]])

There are total 4 rows. The index starts from 0 to 3. The 0 th row is the [2,4,6,8,10], 1 st row is [3,6,9,-12,-15] followed by 2 nd and 3 rd .

The matrix M1 has 5 columns. The index starts from 0 to 4.The 0 th column has values [2,3,4,5], 1 st columns have values [4,6,8,-10] followed by 2 nd , 3 rd , 4 th , and 5 th .

Here is an example showing how to get the rows and columns data from the matrix using slicing. In the example, we are printing the 1 st and 2 nd row, and for columns, we want the first, second, and third column. To get that output we have used: M1[1:3, 1:4]

import numpy as np M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]]) print(M1[1:3, 1:4]) # For 1:3, it will give first and second row. #The columns will be taken from first to third.

Example : To print all rows and third columns

import numpy as np M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]]) print(M1[:,3]) # This will print all rows and the third column data.

Example: To print the first row and all columns

import numpy as np M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]]) print(M1[:1,]) # This will print first row and all columns

Example: To print the first three rows and first 2 columns

import numpy as np M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]]) print(M1[:3,:2])

Accessing NumPy Matrix

We have seen how slicing works. Taking that into consideration, we will how to get the rows and columns from the matrix.

To print the rows of the matrix

In the example will print the rows of the matrix.

import numpy as np M1 = np.array([[3, 6, 9], [5, -10, 15], [4,8,12]]) print(M1[0]) #first row print(M1[1]) # the second row print(M1[-1]) # -1 will print the last row

To get the last row, you can make use of the index or -1. For example, the matrix has 3 rows,

so M1[0] will give you the first row,

M1[1] will give you second row

M1[2] or M1[-1] will give you the third row or last row.

To print the columns of the matrix

import numpy as np M1 = np.array([[2, 4, 6, 8, 10], [3, 6, 9, -12, -15], [4, 8, 12, 16, -20], [5, -10, 15, -20, 25]]) print(M1[:,0]) # Will print the first Column print(M1[:,3]) # Will print the third Column print(M1[:,-1]) # -1 will give you the last column

[2 3 4 5] [ 8 -12 16 -20] [ 10 -15 -20 25]

Summary

• A Python matrix is a specialized two-dimensional rectangular array of data stored in rows and columns. The data in a matrix can be numbers, strings, expressions, symbols, etc. Matrix is one of the important data structures that can be used in mathematical and scientific calculations.
• Python does not have a straightforward way to implement a matrix data type. Python matrix can be created using a nested list data type and by using the numpy library.
• The python library Numpy helps to deal with arrays. Numpy processes an array a little faster in comparison to the list.
• The matrix operation that can be done is addition, subtraction, multiplication, transpose, reading the rows, columns of a matrix, slicing the matrix, etc.
• To add two matrices, you can make use of numpy.array() and add them using the (+) operator.
• To multiply them will, you can make use of the numpy dot() method. Numpy.dot() is the dot product of matrix M1 and M2. Numpy.dot() handles the 2D arrays and perform matrix multiplications.
• The transpose of a matrix is calculated by changing the rows as columns and columns as rows. The transpose() function from Numpy can be used to calculate the transpose of a matrix.
• Slicing of a matrix will return you the elements based on the start /end index given.

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