NumPy - subtract() function

The NumPy subtract() function is used to subtract arguments element-wise. The syntax for using this function is given below:

Note: It is equivalent to x1 - x2 in terms of array broadcasting.

Syntax

```numpy.subtract(x1, x2, out=None)
```

Parameters

 `x1, x2` `Required. `Specify the arrays to be subtracted. If x1.shape != x2.shape, they must be broadcastable to a common shape. `out` `Optional. `Specify a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.

Return Value

Returns difference of x1 and x2, element-wise.

Example:

The example below shows the usage of subtract() function.

```import numpy as np
Arr1 = np.array([[10,20],[30,40]])
Arr2 = np.array([[2,3]])
Arr3 = np.array([[2],[3]])
Arr4 = np.array([[2,3],[4,5]])

#subtract 5 from each element of Arr1
print("subtract(Arr1, 5) returns:")
print(np.subtract(Arr1, 5))

#subtracting elements of Arr2 from Arr1
print("\nsubtract(Arr1, Arr2) returns:")
print(np.subtract(Arr1, Arr2))

#subtracting elements of Arr3 from Arr1
print("\nsubtract(Arr1, Arr3) returns:")
print(np.subtract(Arr1, Arr3))

#subtracting elements of Arr4 from Arr1
print("\nsubtract(Arr1, Arr4) returns:")
print(np.subtract(Arr1, Arr4))
```

The output of the above code will be:

```subtract(Arr1, 5) returns:
[[ 5 15]
[25 35]]

subtract(Arr1, Arr2) returns:
[[ 8 17]
[28 37]]

subtract(Arr1, Arr3) returns:
[[ 8 18]
[27 37]]

subtract(Arr1, Arr4) returns:
[[ 8 17]
[26 35]]
```

❮ NumPy - Functions

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