How to Convert a Dictionary into a NumPy Array

Last Updated : 21 Jun, 2025

In this article, we will learn how to convert a Python Dictionary into a numpy array which is more efficient for numerical operations and provides powerful tools for matrix and array manipulations

Key Steps to Convert a Dictionary to a NumPy Array

Use dict.items(): This returns key-value pairs from the dictionary.
Convert to a list: Use list() to convert the key-value pairs to a list.
Convert to a NumPy array: Use numpy.array() to convert the list of pairs into a NumPy array.

Syntax

numpy.array(object, dtype = None, *, copy = True, order = 'K', subok = False, ndmin = 0)

Parameters:

object: The input array-like object (e.g., list, tuple, dictionary items).
dtype: Desired data type of the resulting array.
copy: Whether to copy the data (default is True).
order: Memory layout order (default is 'K' for default).
subok: If True, subclasses of ndarray will be passed through (default is False).
ndmin: Minimum number of dimensions for the resulting array (default is 0).

Returns: ndarray (An array object satisfying the specified requirements).

Let's look at some examples for a better insight.

Example 1: Using np.array()

In this example, we'll convert a simple dictionary with integer keys and string values into a NumPy array.

Python

import numpy as np

dict_data = {1: 'Geeks', 2: 'For', 3: 'Geeks'}

result = dict_data.items()

data = list(result)

np_arr = np.array(data)

print(np_arr)

Output

[['1' 'Geeks']
 ['2' 'For']
 ['3' 'Geeks']]

Explanation:

dict.items(): This returns a view of the dictionary's key-value pairs as tuples.
list(result): Converts the key-value pairs into a list of tuples.
np.array(data): Converts the list into a NumPy array.

Example 2: Converting a Dictionary with Nested Data

Now, let’s work with a dictionary that has nested data as values (a nested dictionary).

Python

import numpy as np

dict_data = {1: 'Geeks', 2: 'For', 3: {'A': 'Welcome', 'B': 'To', 'C': 'Geeks'}}

res = dict_data.items()

data = list(res)

np_arr = np.array(data)

print(np_arr)

Output

[[1 'Geeks']
 [2 'For']
 [3 {'A': 'Welcome', 'C': 'Geeks', 'B': 'To'}]]

Explanation:

Nested dictionary: The value for key 3 is another dictionary, which is included in the conversion.
np.array(data): The nested dictionary will be treated as a single object within the NumPy array.

Example 3: Converting a Dictionary with Mixed Key Types

In this case, we'll work with a dictionary that has mixed key types: a string and an integer.

Python

import numpy as np

dict_data = {'Name': 'Geeks', 1: [1, 2, 3, 4]}

res = dict_data.items()

data = list(res)

np_arr = np.array(data)

print(np_arr)

Output

[[1 list([1, 2, 3, 4])]
 ['Name' 'Geeks']]

Explanation:

Mixed data types: The dictionary has a string key 'Name' and an integer key 1, with values that are a string and a list respectively.
np.array(data): The list containing both types of values is converted into a NumPy array, maintaining its structure.