Create array using np.where based on condition in NumPy

Last update on December 21 2024 07:36:41 (UTC/GMT +8 hours)

NumPy: Universal Functions Exercise-6 with Solution

Using ufuncs with Conditions:

Write a NumPy program that uses the np.where ufunc to create a new array from two existing arrays based on a condition applied to a third array.

Sample Solution:

Python Code:

import numpy as np

# Create three 1D NumPy arrays
array_1 = np.array([1, 2, 3, 4, 5])
array_2 = np.array([10, 20, 30, 40, 50])
condition_array = np.array([True, False, True, False, True])

# Use np.where ufunc to create a new array based on the condition
result_array = np.where(condition_array, array_1, array_2)

# Print the original arrays and the resulting array
print('Array 1:\n', array_1)
print('Array 2:\n', array_2)
print('Condition array:\n', condition_array)
print('Resulting array using np.where:\n', result_array)

Output:

Array 1:
 [1 2 3 4 5]
Array 2:
 [10 20 30 40 50]
Condition array:
 [ True False  True False  True]
Resulting array using np.where:
 [ 1 20  3 40  5]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create Three 1D NumPy Arrays:
• Created three 1D NumPy arrays: array_1 with values [1, 2, 3, 4, 5], array_2 with values [10, 20, 30, 40, 50], and condition_array with boolean values [True, False, True, False, True].
• Use np.where ufunc:
• Use the np.where "ufunc" to create a new array result_array based on the condition applied to condition_array. If the condition is True, the corresponding element from ‘array_1’ is chosen; otherwise, the element from ‘array_2’ is chosen.
• Print Results:
• Print the original arrays and the resulting array created using np.where.

Python-Numpy Code Editor: