NumPy: Test whether specified values are present in an array
NumPy: Array Object Exercise-65 with Solution
Write a NumPy program to test if specified values are present in an array.
Pictorial Presentation:
Sample Solution:
Python Code:
# Importing the NumPy library with an alias 'np'
import numpy as np
# Creating a 2x3 NumPy array 'x' with specific float values
x = np.array([[1.12, 2.0, 3.45], [2.33, 5.12, 6.0]], float)
# Displaying the original array 'x'
print("Original array:")
print(x)
# Checking if 2 is present in the array 'x'
print(2 in x)
# Checking if 0 is present in the array 'x'
print(0 in x)
# Checking if 6 is present in the array 'x'
print(6 in x)
# Checking if 2.3 is present in the array 'x'
print(2.3 in x)
# Checking if 5.12 is present in the array 'x'
print(5.12 in x)
Sample Output:
Original array: [[ 1.12 2. 3.45] [ 2.33 5.12 6. ]] True False True False True
Explanation:
In the above exercise -
‘x = np.array([[1.12, 2.0, 3.45], [2.33, 5.12, 6.0]], float)’ creates a 2D NumPy array x with the specified floating-point values.
The following statements use the in operator to check if the specified values are present in the array x:
- print(2 in x): Checks if 2 is present in the array. Prints True because 2.0 is present.
- print(0 in x): Checks if 0 is present in the array. Prints False because 0 is not present.
- print(6 in x): Checks if 6 is present in the array. Prints True because 6.0 is present.
- print(2.3 in x): Checks if 2.3 is present in the array. Prints False because 2.3 is not present.
- print(5.12 in x): Checks if 5.12 is present in the array. Prints True because 5.12 is present.
Python-Numpy Code Editor:
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