Python Supports multiple modules and functions for performing various kinds of mathematical computation. “**Numpy**” is the most popular package in Python for Numerical computation. Using different “Numpy” functions in programming can increase the productivity and efficiency of the Program.

This write-up will cover an in-depth overview of the Python Numpy function named “**np.dot()**” to calculate the dot product of two arrays.

The following outcomes are explained in this Python article:

**What is a Numpy Dot Product in Python?****Example 1: Numpy Dot Product of Scalar and Vector Quantity****Example 2: Numpy Dot Product of 1D Array****Example 3: Numpy Dot Product of 2D Array**

So let’s begin!

**What is a Numpy Dot Product in Python?**

Scalar products are also referred to as “dot products” in Mathematics. This algebraic operation takes two equal values of a scalar or vector number and returns a single particular number.

The “**Numpy**” module offers an “**np.dot()**” function, which is used to calculate the dot product of any two scaler numbers or arrays. The syntax of the “**np.dot()**” function is shown below:

```
numpy.dot(x, y, out=None)
```

In the above syntax:

- The “
**x**” parameter takes the first value of an array. - The “
**y**” parameter takes the second value of an array. - The “
**out**” parameter is optional and used for performance.

The following points provide the outcomes of specific input given into the function of “**np.dot()**”:

- If both input variables are scalar quantities or zero-dimensional, then the output of the “
**np.dot()**” function is the multiplication of two numbers. - If the input arrays are 1-dimensional, then the “np.dot()” function returns the inner product of the vector.
- If the input arrays are 2-dimensional, then the “np.dot()” function returns the matrix multiplication of the given arrays.
- If either parameter “
**x**” or“**y**” is n-dimensional, then the “np.dot()” function returns the sum of the product of x and y. - If the parameter values of the given function are “
**n and m**” dimensional. The “**numpy.dot()**” function retrieves the product sum over the ‘last axis’ of the first number and the second to last axis of the second number.

**Example 1: Numpy Dot Product of Scalar and Vector Quantity**

In the following example, the “**np.dot()**” function is used to create a dot product of two scalars and vector quantities. The 2d vector quantity is initialized in the form of a complex number.

**Code:**

```
import numpy as np
# numpy dot product of Scalars
dot_product = np.dot(10, 10)
print("Dot Product of scalar: ", dot_product)
# numpy dot product of vectors
vector_1 = 2 + 3j
vector_2 = 4 + 5j
dot_product = np.dot(vector_1, vector_2)
print("Dot Product of vectors: ", dot_product)
```

In the above code:

- The “
**NumPy**” library is imported as “**np**” at the start of Program. - Firstly, the “
**np.dot()**” function finds the dot product of two scalar numbers by taking its value as an argument. - Secondly, two values of the 1d array are initialized as a vector quantity and stored in a variable.
- The “np.dot()” function takes the variable value as an argument and returns the dot product of the 1d-arrays vector.

**Output:**

The above output shows the dot product of the scalar and 1d-array vector.

**Example 2: Numpy Dot Product of 1D Array**

In the following example, the function “**np.dot()**” is used to calculate the dot product of a 1-d array. Lets understand the concept by the following code:

**Code:**

```
import numpy as np
Number_1 = np.array([4, 7, 15])
Number_2 = np.array([7, 3, 17])
#dot product
Result = np.dot(Number_1, Number_2)
print('Dot Product: ',Result)
```

In the above code:

- Two 1d-arrays are generated using the function named “
**np.array()**”. - The “
**np.dot()**” takes the variable value as a parameter value and returns the dot product of the following 1d-array.

**Output:**

The output shows the dot product of the “1-D” array.

The mathematical calculation of the dot product of a “1-D” array is shown below:

**Example 3: Numpy Dot Product of 2D Array**

In the following example, the NumPy module function named “**np.dot()**” takes the 2-d variable value as input and returns the dot product.

**Code:**

```
import numpy as np
Number_1 = np.array([[12, 11], [15, 14]])
Number_2 = np.array([[13, 14], [17, 18]])
#dot product
dot_product = np.dot(Number_1, Number_2)
print(dot_product)
```

In the above code:

- The function named “
**np.array()**” is used here to create 2-D arrays. - The value of 2-D arrays stored in a variable named “
**Number_1**” and “**Number_2**”. - The “
**np.dot()**” function takes the variable value inside the parentheses and returns the dot product of the 2-D arrays.

**Output:**

The above output shows the dot product of the “2-D” array.

The mathematical calculation of the dot product of a “2-D” array is shown below:

That’s all from this Python!

**Conclusion**

In Python, the “**np.dot()**” function of the “**Numpy**” package is used to calculate the dot product of scalar, vectors, 1-D arrays, and 2-D arrays. The “np.dot()” function returns the scalar value if both input numbers are scalar or 1-Dimensional. When a “1-D” or “2-D” array is passed into the “np.dot()” function then it returns the output as inner product multiplication and matrix multiplication. This write-up provided all the details related to the Numpy dot product with multiple examples.