NumPy offers a variety of functions and tools to work with arrays and matrices, making it an excellent choice for data manipulation and analysis. In this article, we will learn how to build a new vector with ‘n’ consecutive zeros interleaved between each value using NumPy.

- In the following examples, we will suppose that we need
**3 zeros**between each element in our array.

#### 1. Using “np.insert()”:

Here, `num_zeros`

specify *the number of zeros to be inserted*. The `np.insert()`

function is used to insert the zeros between each value of the input vector. The `np.repeat()`

function repeats each index of the input vector `num_zeros`

times to insert `num_zeros`

consecutive zeros after each index. The `np.arange(1, len(input_vec))`

function creates an array of indices starting from `1`

to `len(input_vec)-1`

, which represent the positions where zeros are to be inserted. Finally, the `0`

argument in the `np.insert()`

function specifies the value to be inserted, which is `zero`

in this case.

#### 2. Using “np.kron()”:

The code uses NumPy library to create a new array `new_vector`

by repeating the `original_vector`

4 times and multiplying it element-wise with a pattern array. The pattern array is created by using `np.ones()`

and `np.zeros()`

to create arrays of 1s and 0s, and then using `np.kron()`

to concatenate them into an alternating pattern of 1s and 0s. The resulting new vector with 3 consecutive zeros interleaved between each value is stored in the `new_vector`

variable and printed using `print(new_vector)`

.