Create Structured array with nested fields in NumPy

NumPy: Structured Arrays Exercise-17 with Solution

Creating a Structured Array with Nested Fields:

Write a NumPy program that creates a structured array with nested fields, such as 'person' (which has sub-fields 'name' and 'age') and 'score' (integer).

Sample Solution:

Python Code:

import numpy as np

# Define the data type for the structured array with nested fields
dtype = [('person', [('name', 'U10'), ('age', 'i4')]), ('score', 'i4')]

# Create the structured array with sample data
structured_array = np.array([
    (('Elsi Eunomia', 25), 85),
    (('Sonia Husein', 30), 90),
    (('Carmen Hildur', 35), 95),
    (('Lino Prakash', 40), 80),
    (('Eshe Waldemar', 28), 88)
], dtype=dtype)

# Print the structured array with nested fields
print("Structured Array with Nested Fields:")
print(structured_array)

Output:

Structured Array with Nested Fields:
[(('Elsi Eunom', 25), 85) (('Sonia Huse', 30), 90)
 (('Carmen Hil', 35), 95) (('Lino Praka', 40), 80)
 (('Eshe Walde', 28), 88)]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Define Data Type:
• Define the data type for the structured array with nested fields. The data type is specified as a list of tuples, where:
• 'person' is a field that contains sub-fields 'name' (a string of up to 10 characters) and 'age' (a 4-byte integer).
• 'score' is a field that is a 4-byte integer.
• Create a Structured Array:
• Created the structured array using np.array(), providing sample data for five individuals. Each individual is represented as a tuple with values for 'person' (which includes 'name' and 'age') and 'score'.
• Finally print the structured array to display the data with nested fields.

Python-Numpy Code Editor:

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