How to convert a dictionary into a NumPy array?
Last Updated :
05 Mar, 2023
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
import numpy as np
dict = { 1 : 'Geeks' ,
2 : 'For' ,
3 : 'Geeks' }
result = dict .items()
data = list (result)
numpyArray = np.array(data)
print (numpyArray)
|
Output:
[['1' 'Geeks']
['2' 'For']
['3' 'Geeks']]
Time Complexity: O(n)
Space Complexity: O(n)
Example 2:
Python
import numpy as np
dict = { 1 : 'Geeks' ,
2 : 'For' ,
3 : { 'A' : 'Welcome' ,
'B' : 'To' ,
'C' : 'Geeks' }
}
result = dict .items()
data = list (result)
numpyArray = np.array(data)
print (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
import numpy as np
dict = { 'Name' : 'Geeks' ,
1 : [ 1 , 2 , 3 , 4 ]}
result = dict .items()
data = list (result)
numpyArray = np.array(data)
print (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.
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