Create A Record Array From A List Of Individual Records

To create a record array from a list of individual records, you can use the numpy.rec.array() function in NumPy. The rec.array() function allows you to create a structured array where each element in the array corresponds to a record with multiple fields. Here’s an example:

import numpy as np

# Define the individual records
record1 = (1, "John", 25)
record2 = (2, "Alice", 30)
record3 = (3, "Bob", 28)

# Create the record array
records = np.rec.array([record1, record2, record3], dtype=[('id', int), ('name', object), ('age', int)])

print(records)

Output:

[(1, 'John', 25) (2, 'Alice', 30) (3, 'Bob', 28)]

In this example, we define three individual records as tuples: record1, record2, and record3. Each record consists of multiple fields, such as ‘id’, ‘name’, and ‘age’.

We then use the np.rec.array() function to create the record array records. The dtype parameter is used to specify the data type of each field in the record array. In this case, we define the data type as [('id', int), ('name', object), ('age', int)], which indicates that the ‘id’ and ‘age’ fields are of integer type, and the ‘name’ field is of an object type.

Run Code In Live & Test

Conclusion:

The resulting records array is a structured array where each element represents a record with multiple fields. You can access individual fields using the field names, e.g., records['id'], records['name'], records['age'], and perform operations and manipulations on the record array as needed.

Leave a Reply

Your email address will not be published. Required fields are marked *