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Split NumPy Structured array based on condition

NumPy: Structured Arrays Exercise-11 with Solution

Splitting Structured Arrays:

Write a NumPy program to split a structured array created with fields for 'name' (string), 'age' (integer), and 'height' (float) based on a condition (e.g., age > 25).

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)
# Split the array based on the condition age > 25
condition = structured_array['age'] > 25
array_above_25 = structured_array[condition]
array_25_and_below = structured_array[~condition]

# Print the resulting arrays
print("\nArray with age > 25:")
print(array_above_25)

print("\nArray with age <= 25:")
print(array_25_and_below)

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)]

Array with age > 25:
[('Albin Acha', 30, 5.8) ('Zerach Hav', 35, 6.1) ('Edmund Ter', 40, 5.9)
 ('Laura Feli', 28, 5.7)]

Array with age <= 25:
[('Lehi Piero', 25, 5.5)]

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'.
  • Define the condition:
    • Define a condition to split the array based on age. The condition checks if 'age' is greater than 25.
  • Split Array:
    • Split the array into two based on the condition:
      • array_above_25: contains records where age > 25.
      • array_25_and_below: contains records where age <= 25.
  • Print the Resulting Arrays:
    • Print the resulting arrays to verify the split.

Python-Numpy Code Editor: