NumPy: Test whether each element of a 1-D array

Last update on August 29 2025 12:49:54 (UTC/GMT +8 hours)

1D Array Element Check in Another Array

Write a NumPy program to test whether each element of a 1-D array is also present in a second array.

Pictorial Presentation:

Python NumPy: Test whether each element of a 1-D array

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Creating an array 'array1' using NumPy
array1 = np.array([0, 10, 20, 40, 60])

# Printing the contents of 'array1'
print("Array1: ", array1)

# Creating a Python list 'array2'
array2 = [0, 40]

# Printing the contents of 'array2'
print("Array2: ", array2)

# Comparing each element of 'array1' with 'array2'
print("Compare each element of array1 and array2")
print(np.in1d(array1, array2))

Sample Output:

Array1:  [ 0 10 20 40 60]                                              
Array2:  [0, 40]                                                       
Compare each element of array1 and array2                              
[ True False False  True False]

Explanation:

In the above code –

array1 = np.array([0, 10, 20, 40, 60]): Creates a NumPy array with elements 0, 10, 20, 40, and 60.

array2 = [0, 40]: Creates a Python list with elements 0 and 40.

print(np.in1d(array1, array2)): The np.in1d function checks if each element of ‘array1’ is present in ‘array2’. It returns a boolean array of the same shape as ‘array1’, with True at positions where the element is present in ‘array2’ and False otherwise. The output will be [ True False False True False]

For more Practice: Solve these Related Problems:

Check if each element of a 1D array exists in another array using np.in1d.
Return a boolean mask for an array indicating membership in a second array.
Create a function that compares two arrays element-wise and returns indices where matches occur.
Utilize set operations to simulate element membership and then convert the result to a boolean array.

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