# 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 n-dimensional array.

Raise `ValueError`

if the last dimension of the 1st 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.