# Numpy numpy.dot Function

Python Numpy`numpy.dot()` function calculates the dot product of two input arrays.

## Syntax of `numpy.dot()`:

``````numpy.dot(a,
b,
out=None)
``````

### Parameters

`a` Array-like. 1st array or scalar whose dot product is be calculated
`b` Array-like. 2nd array or scalar whose dot product is be calculated
`out` Array. An optional argument whose data-type must be the same as the expected data-type of output

### Return

It returns the dot product of input vectors. If both inputs are scalars, it produces a 1-D array otherwise an n-dimensional array.

Raise `ValueError` if the last dimension of the first input array is not equal to the second-to-last dimension of the 2nd input array.

## Example Codes: `numpy.dot()` Method to Find Dot Product

### When Both Inputs Are 1-D Arrays

``````import numpy as np

a=4
b=5

prod=np.dot(a,b)
print(prod)

``````

Output:

``````20
``````

Here, since both `a` and `b` are 1-D arrays, the `np.dot()` function simply returns a scalar, which is a simple product of both the numbers.

### When Both Inputs Are Vectors

``````import numpy as np

a=np.array([3,4])
b=np.array([4,5])

prod=np.dot(a,b)
print(prod)
``````

Output:

``````32
``````

It calculates the dot product of vectors.

The dot product of two vectors `[x1,y1]` and `[x2,y2]` is given by `x1*x2+y1*y2`.

### When Both Inputs Are 2-Dimensional Arrays

``````import numpy as np

a=np.array([[3,4],
[2,3]])
b=np.array([[4,5],
[2,3]])

prod=np.dot(a,b)
print(prod)
``````

Output:

``````[[20 27]
[14 19]]
``````

It calculates the product of matrices.

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