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Calculate average Age in NumPy Structured array

NumPy: Structured Arrays Exercise-7 with Solution

Calculating Statistics:

Write a NumPy program to calculate and print the average age of individuals in the structured array created with fields for 'name' (string), 'age' (integer), and 'height' (float).

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)

# Calculate the average age of individuals
average_age = np.mean(structured_array['age'])

# Print the average age
print("Average age of individuals:")
print(average_age)

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)]
Average age of individuals:
31.6

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 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 'name', 'age', and 'height'.
  • Calculate the average age:
    • Calculated the average age of individuals by accessing the 'age' field and using np.mean() to compute the mean value.
  • Print Average Age:
    • Print the average age of the individuals in the structured array.

Python-Numpy Code Editor: