Python - Numpy fromrecords() method Last Updated : 12 Jul, 2025 Comments Improve Suggest changes Like Article Like Report numpy.fromrecords() method is a powerful tool in the NumPy library that allows you to create structured arrays from a sequence of tuples or other array-like objects. Let's understand the help of an example: Python import numpy as np # Define a list of records records = [(1, 'Alice', 25.5), (2, 'Bob', 30.0), (3, 'Charlie', 28.0)] # Define the data type dtype = [('id', 'i4'), ('name', 'U10'), ('age', 'f4')] # Create the structured array structured_array = np.fromrecords(records, dtype=dtype) print(structured_array) Output:[(1, 'Alice', 25.5) (2, 'Bob', 30. ) (3, 'Charlie', 28. )]Table of ContentSyntax of Numpy fromrecords():Accessing Structured Array FieldsSyntax of Numpy fromrecords():numpy.fromrecords(recList, dtype=None, shape=None, aligned=False, byteorder=None)Parameters:recList: A list of tuples or structured data to be converted into a structured NumPy array.dtype (optional): The data type of the resulting structured array. If not provided, NumPy will infer the type from the input data.shape (optional): Shape of the output array. Defaults to one-dimensional.aligned (optional): If True, aligns fields to their natural alignment.byteorder (optional): Specifies the byte order of the output array.Accessing Structured Array FieldsWe can access specific fields (columns) in the structured array by their names. Python import numpy as np # Define a list of records records = [(1, 'Alice', 25.5), (2, 'Bob', 30.0), (3, 'Charlie', 28.0)] # Define the data type dtype = [('id', 'i4'), ('name', 'U10'), ('age', 'f4')] # Create the structured array structured_array = np.fromrecords(records, dtype=dtype) # Access the 'name' field print(structured_array['name']) # Access the 'age' field print(structured_array['age']) Output:[(1, 'Alice', 25.5) (2, 'Bob', 30. ) (3, 'Charlie', 28. )] Comment More info J jitender_1998 Follow Improve Article Tags : Python Python-numpy Explore Python FundamentalsPython Introduction 3 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 5 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 7 min read Python Functions 5 min read Recursion in Python 6 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 5 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 2 min read Python MySQL 9 min read Python Packages 12 min read Python Modules 7 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 6 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 15+ min read StatsModel Library- Tutorial 4 min read Learning Model Building in Scikit-learn 8 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 7 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 7 min read Python | Build a REST API using Flask 3 min read How to Create a basic API using Django Rest Framework ? 4 min read Python PracticePython Quiz 3 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like