Update field value in NumPy Structured array

Last update on March 26 2025 13:18:01 (UTC/GMT +8 hours)

3. Update Age Field

Modifying Field Values:

Write a NumPy program that updates the 'age' field for the first individual in the structured array created in exercise 1 to 30.

Sample Solution:

Python Code:

import numpy as np

# Define the data type for the structured array
dtype = [('name', 'U10'), ('age', 'i4'), ('height', 'f4')]

# Create the structured array with sample data
structured_array = np.array([
    ('Lehi Piero', 25, 5.5),
    ('Albin Achan', 30, 5.8),
    ('Zerach Hava', 35, 6.1),
    ('Edmund Tereza', 40, 5.9),
    ('Laura Felinus', 28, 5.7)
], dtype=dtype)

print("Original Structured Array:")
print(structured_array)


# Update the 'age' field for the first individual to 30
# Access the first element and update the 'age' field
structured_array[0]['age'] = 30

# Print the updated structured array
print("\nUpdated Structured Array:")
print(structured_array)

Output:

Original Structured Array:
[('Lehi Piero', 25, 5.5) ('Albin Acha', 30, 5.8) ('Zerach Hav', 35, 6.1)
 ('Edmund Ter', 40, 5.9) ('Laura Feli', 28, 5.7)]

Updated Structured Array:
[('Lehi Piero', 30, 5.5) ('Albin Acha', 30, 5.8) ('Zerach Hav', 35, 6.1)
 ('Edmund Ter', 40, 5.9) ('Laura Feli', 28, 5.7)]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Define Data Type:
• Define the data type for the structured array using a list of tuples. Each tuple specifies a field name and its corresponding data type. The data types are:
• 'U10' for a string of up to 10 characters.
• 'i4' for a 4-byte integer.
• 'f4' for a 4-byte float.
• Create 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 'name', 'age', and 'height'.
• Update 'Age' Field:
• Access the first element of the structured array and update the 'age' field to 30.
• Print Updated Structured Array:
• Print the updated structured array to verify the changes.

For more Practice: Solve these Related Problems:

• Write a Numpy program to update the 'age' field for the first record and then verify the update by printing the entire record.
• Write a Numpy program to increment the 'age' field for the first individual by a computed value based on their height.
• Write a Numpy program to update the 'age' field conditionally for records that meet a specific criterion (e.g., name starts with 'A').
• Write a Numpy program to apply a vectorized operation that sets the 'age' field of the first two records to a fixed value.

Python-Numpy Code Editor:

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