Create a Structured array with Name, Age, and Height in NumPy
1. Structured Array Creation
Creating a Structured Array:
Write a NumPy program that creates a structured array with fields for 'name' (string), 'age' (integer), and 'height' (float). Populate it with sample data for five individuals.
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 the structured array
print("Structured Array:")
print(structured_array)
Output:
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)]
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'.
- Print the structured array to display the populated data.
For more Practice: Solve these Related Problems:
- Write a Numpy program to create a structured array with additional fields (e.g., 'weight') and populate it with sample data, ensuring proper dtype alignment.
- Write a Numpy program to generate a structured array from a list of tuples and verify the field names and dtypes.
- Write a Numpy program to create a structured array with non-uniform string lengths for the 'name' field and test its memory usage.
- Write a Numpy program to build a structured array with fields 'name', 'age', and 'height', and then dynamically update the dtypes of each field.
Python-Numpy Code Editor:
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Next: Access and print 'Name' Field from NumPy Structured array.
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