Finding the number of rows and columns in a given matrix using Numpy

NumPy provides several ways to find the dimensions of a matrix. The most common method is using the shape attribute, which returns a tuple containing the number of rows and columns.

Creating a Matrix

First, let's create a NumPy matrix to work with ?

import numpy as np

# Create a 2x3 matrix with random numbers
matrix = np.random.rand(2, 3)
print("Matrix:")
print(matrix)

Matrix:
[[0.37454012 0.95071431 0.73199394]
 [0.59865848 0.15601864 0.15599452]]

Finding Rows and Columns Using shape

The shape attribute returns a tuple where the first element is the number of rows and the second is the number of columns ?

import numpy as np

matrix = np.random.rand(2, 3)
print("Matrix shape:", matrix.shape)
print("Number of rows:", matrix.shape[0])
print("Number of columns:", matrix.shape[1])

Matrix shape: (2, 3)
Number of rows: 2
Number of columns: 3

Alternative Methods

Using size and ndim

You can also use size for total elements and ndim for dimensions ?

import numpy as np

matrix = np.array([[1, 2, 3], [4, 5, 6]])
print("Shape:", matrix.shape)
print("Total elements:", matrix.size)
print("Number of dimensions:", matrix.ndim)

Shape: (2, 3)
Total elements: 6
Number of dimensions: 2

Using len() for Rows

For the number of rows only, you can use len() ?

import numpy as np

matrix = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
print("Number of rows using len():", len(matrix))
print("Number of columns:", matrix.shape[1])

Number of rows using len(): 3
Number of columns: 4

Comparison

Conclusion

Use matrix.shape to get both rows and columns as a tuple. For just the row count, len(matrix) is simpler. The shape attribute is the most versatile method for matrix dimensions.