NumPy ndarray itemset() Method | Insert Scalar in ndarray
Last Updated :
31 Jan, 2024
The NumPy ndarray.itemset() method inserts a scalar into an array.
Key Points:
- ndarray.itemset function needs at least one argument.
- The last argument you pass in the function is considered an “item“.
- arr.itemset(*args) is a quicker way to do same thing as arr[args] = item.
- The item should be a scalar value and args must select a single item in the array.
Syntax
numpy.ndarray.itemset(*args)
Parameters:
- *args :
- If one argument: a scalar, only used in case arr is of size 1.
- If two arguments: the last argument is the value to be set and must be a scalar, the first argument specifies a single array element location. It is either an int or a tuple.
Examples
Let’s look at this example of the ndarray.itemset() method of the NumPy library.
Example 1:
Python3
import numpy as np
np.random.seed( 345 )
arr = np.random.randint( 9 , size = ( 3 , 3 ))
print ( "Input array : " , arr)
arr.itemset( 4 , 0 )
print ( "Output array : " , arr)
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Output :
Input array : [[8 0 3]
[8 4 3]
[4 1 7]]
Output array : [[8 0 3]
[8 0 3]
[4 1 7]]
Example 2:
Python3
import numpy as geek
geek.random.seed( 345 )
arr = geek.random.randint( 9 , size = ( 3 , 3 ))
print ( "Input array : " , arr)
arr.itemset(( 2 , 2 ), 9 )
print ( "Output array : " , arr)
|
Output:
Input array : [[8 0 3]
[8 4 3]
[4 1 7]]
Output array : [[8 0 3]
[8 4 3]
[4 1 9]]
Note: While the ndarray.itemset method is fast and efficient, but many people avoid it because this method can complicate the code and it might waste space if the array is not fully populated.
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