NumPy: Check whether a Numpy array contains a specified row

Last update on April 26 2025 12:38:13 (UTC/GMT +8 hours)

Check if an array contains a specified row.

Write a NumPy program to check whether a Numpy array contains a specified row.

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Generating a NumPy array of integers from 0 to 19 (exclusive) and reshaping it to a 4x5 matrix
num = np.arange(20)
arr1 = np.reshape(num, [4, 5])

# Displaying a message indicating the original array
print("Original array:")
print(arr1)

# Checking if [0, 1, 2, 3, 4] is present as a sublist in the array, converting the array to a list using tolist()
print([0, 1, 2, 3, 4] in arr1.tolist())

# Checking if [0, 1, 2, 3, 5] is present as a sublist in the array, converting the array to a list using tolist()
print([0, 1, 2, 3, 5] in arr1.tolist())

# Checking if [15, 16, 17, 18, 19] is present as a sublist in the array, converting the array to a list using tolist()
print([15, 16, 17, 18, 19] in arr1.tolist()) 

Sample Output:

Original array:
[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]
True
False
True

Explanation:

In the above code -

num = np.arange(20): This code creates a NumPy array with integers from 0 to 19.

arr1 = np.reshape(num, [4, 5]): This code reshapes the NumPy array 'num' into a 4x5 array (4 rows and 5 columns).

[0, 1, 2, 3, 4] in arr1.tolist(): Convert the NumPy array 'arr1' to a nested list using tolist() and check if the list [0, 1, 2, 3, 4] is present as a row in the list.

[0, 1, 2, 3, 5] in arr1.tolist(): Check if the list [0, 1, 2, 3, 5] is present as a row in the list converted from 'arr1'.

[15, 16, 17, 18, 19] in arr1.tolist(): Check if the list [15, 16, 17, 18, 19] is present as a row in the list converted from 'arr1'.

Note: ndarray.tolist()

Return the array as a (possibly nested) list. Return a copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible Python type.

Pictorial Presentation:

For more Practice: Solve these Related Problems:

• Write a NumPy program to check if a given row exists in a 2D array using np.all and broadcasting.
• Create a function that iterates over rows of a matrix and returns True if an exact match is found.
• Implement a solution that converts both the target row and each row of the array to strings for comparison.
• Test the function on arrays with duplicate rows and near-matches to ensure it only returns exact matches.

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