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Get the number of rows and number of columns in Pandas Dataframe

Find the number of rows and columns of a given matrix using NumPy

Last Updated : 05 Mar, 2024

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The shape attribute of a NumPy array returns a tuple representing the dimensions of the array. For a two-dimensional array, the shape tuple contains two values: the number of rows and the number of columns.

In this article, let’s discuss methods used to find dimensions of the matrix.

How to Find the Number of Rows and Columns of a Matrix?

We can find matrix dimension with three ways:

Using shape Attribute
Using Indexing
Using numpy.reshape()

Way 1: Using .shape Attribute

Here we are finding the number of rows and columns of a given matrix using Numpy.shape.

Python

   import numpy as np
matrix = np.array([[9, 9, 9], [8, 8, 8]])
 
dimensions = matrix.shape
rows, columns = dimensions
 
print("Rows:", rows)
print("Columns:", columns)
 
  

Output:

Rows: 2 
Columns: 3

Way 2: Using Indexing

Here we are finding the number of rows and columns of a given matrix using Indexing.

Python

   import numpy as np
 
matrix = np.array([[4, 3, 2], [8, 7, 6]])
rows = matrix.shape[0]
columns = matrix.shape[1]
 
print("Rows:", rows)
print("Columns:", columns)
 
  

Output:

Rows: 2 
Columns: 3

Way 3: Using numpy.reshape()

Here we are using numpy.reshape() to find number of rows and columns of a matrix, numpy.reshape in NumPy is used for changing the shape of an array without modifying the underlying data.

When using np.arange(start, stop), remember that the stop element is not included in the generated array. So, np.arange(1, 10) will create an array with values from 1 to 9 (inclusive).

Python

   import numpy as np
matrix= np.arange(1,10).reshape((3, 3))
 
print(matrix) # Original matrix
print(matrix.shape) # Number of rows and columns of the said matrix

Output:

[[1 2 3]
[4 5 6]
[7 8 9]]
(3,3)

Get the number of rows and number of columns in Pandas Dataframe

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Article Tags :

Python
Python numpy-Matrix Function
Python-numpy

Practice Tags :

python

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