# Developing array with specified range

Developing an array with a specified range is a common task in data analysis, machine learning, and scientific computing. There are numerous ways and functions that can be used to create a matrix. In this thread, we will explore how to develop the arrau with specified range using NumPy.

#### 1. Using "zeros()" function and indexing:

In NumPy, the `zeros()` function is used to create an array of specified shape and data type, filled with zeros. You can use the `zeros()` function to create a matrix with the size of a specified range. Then use indexing to assign the desired values to the matrix. For example:

#### 2. Using "reshape()" and "linspace()" function:

The `linspace()` function in NumPy is used to create an array of evenly spaced numbers over a specified interval. The `reshape()` function in NumPy is used to change the shape of an array without changing its data.
You can used `linspace()` function to create 1D matrix containing values of specified range and then convert it into 2D matrix using `reshape()` function. Example is given below:

#### 3. Using "full()" function and indexing:

The `full()` function in NumPy is used to create a new array with a given shape and type, filled with a specified value or values.
You can used `full()` function to create a 3x3 matrix and use indexing to assign specified range of values. For specified range values, you can also create 1D matrix using `arange()` function. letâ€™s code it below for better understanding.