It’s sometimes required to convert a dictionary in Python into a NumPy array and Python provides an efficient method to perform this operation. Converting a dictionary to NumPy array results in an array holding the key-value pairs in the dictionary. Python provides numpy.array() method to convert a dictionary into NumPy array but before applying this method we have to do some pre-task. As a pre-task follow this simple three steps
- First of all call dict.items() to return a group of the key-value pairs in the dictionary.
- Then use list(obj) with this group as an object to convert it to a list.
- At last, call numpy.array(data) with this list as data to convert it to an array.
Syntax:
numpy.array(object, dtype = None, *, copy = True, order = ‘K’, subok = False, ndmin = 0)
Parameters:
object: An array, any object exposing the array interface
dtype: The desired data-type for the array.
copy: If true (default), then the object is copied. Otherwise, a copy will only be made if __array__ returns a copy
order: Specify the memory layout of the array
subok: If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default)
ndmin: Specifies the minimum number of dimensions that the resulting array should have.
Returns:
ndarray: An array object satisfying the specified requirements.
Example 1:
Python
# Python program to convert# dictionary to numpy array# Import required packageimport numpy as np# Creating a Dictionary# with Integer Keysdict = {1: 'Geeks', 2: 'For', 3: 'Geeks'}# to return a group of the key-value# pairs in the dictionaryresult = dict.items()# Convert object to a listdata = list(result)# Convert list to an arraynumpyArray = np.array(data)# print the numpy arrayprint(numpyArray) |
Output:
[['1' 'Geeks'] ['2' 'For'] ['3' 'Geeks']]
Time Complexity: O(n)
Space Complexity: O(n)
Example 2:
Python
# Python program to convert# dictionary to numpy array# Import required packageimport numpy as np# Creating a Nested Dictionarydict = {1: 'Geeks', 2: 'For', 3: {'A': 'Welcome', 'B': 'To', 'C': 'Geeks'} }# to return a group of the key-value# pairs in the dictionaryresult = dict.items()# Convert object to a listdata = list(result)# Convert list to an arraynumpyArray = np.array(data)# print the numpy arrayprint(numpyArray) |
Output:
[[1 'Geeks']
[2 'For']
[3 {'A': 'Welcome', 'B': 'To', 'C': 'Geeks'}]]
Time complexity: O(n), where n is the number of key-value pairs in the dictionary.
Auxiliary space: O(n), to store the list of key-value pairs in the dictionary.
Example 3:
Python
# Python program to convert# dictionary to numpy array# Import required packageimport numpy as np# Creating a Dictionary# with Mixed keysdict = {'Name': 'Geeks', 1: [1, 2, 3, 4]}# to return a group of the key-value# pairs in the dictionaryresult = dict.items()# Convert object to a listdata = list(result)# Convert list to an arraynumpyArray = np.array(data)# print the numpy arrayprint(numpyArray) |
Output:
[['Name' 'Geeks'] [1 list([1, 2, 3, 4])]]
Time complexity: The time complexity of converting a dictionary to a numpy array is O(n), where n is the number of elements in the dictionary.
Space complexity: The space complexity of converting a dictionary to a numpy array is O(n), where n is the size of the numpy array.
