How to convert a dictionary to NumPy structured array?

Given a dictionary, we have to convert it into a NumPy structure array in Python.
By Pranit Sharma Last updated : December 21, 2023

NumPy is an abbreviated form of Numerical Python. It is used for different types of scientific operations in python. Numpy is a vast library in python which is used for almost every kind of scientific or mathematical operation. It is itself an array which is a collection of various methods and functions for processing the arrays.

Problem statement

Suppose that we are given a dictionary that we need to convert to a NumPy structured array.

Dictionary to NumPy structured array conversion

For this purpose, we can directly use the numpy array object to create a numpy array where we can pass the values by extracting them from dictionary using a comprehension statement but sometimes the user might face the following error in doing this:

"expected a readable buffer object"

To avoid this error, we will first convert the items of a dictionary into a list and then we will convert this list into numpy array using the array object. This will create the intermediate list of tuples and we will get a structured array of tuples as a result.

Let us understand with the help of an example,

Python code to convert a dictionary to NumPy structured array

# Import numpy
import numpy as np

# Creating a dict
d = {0:8595, 1:8394, 2: 4718, 3: 4871}

# Defining data type
names = ['id','data']
formats=['f8','f8']
dtype = dict( names = names, formats = formats)

# Creating an array
arr = np.array(list(d.items()),dtype = dtype)

# Display result
print("Created array:\n",arr)