Book Image

NumPy: Beginner's Guide

By : Ivan Idris
Book Image

NumPy: Beginner's Guide

By: Ivan Idris

Overview of this book

Table of Contents (21 chapters)
NumPy Beginner's Guide Third Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
NumPy Functions' References
Index

Time for action – creating a record data type


The record data type is a heterogeneous data type—think of it as representing a row in a spreadsheet or a database. To give an example of a record data type, we will create a record for a shop inventory. The record contains the name of the item, a 40-character string, the number of items in the store represented by a 32-bit integer, and, finally, a price represented by a 32-bit float. These consecutive steps show how to create a record data type:

  1. Create the record:

    In: t = dtype([('name', str_, 40), ('numitems', int32), ('price', float32)])
    In: t
    Out: dtype([('name', '|S40'), ('numitems', '<i4'), ('price', '<f4')])
    
  2. View the type (we can view the type of a field as well):

    In: t['name']
    Out: dtype('|S40')
    

If you don't give the array() function a data type, it will assume that it is dealing with floating point numbers. To create the array now, we really have to specify the data type; otherwise, we will get a TypeError:

In: itemz = array([(...