One common task in scientific computing is to create arrays with specific values, such as an array with values from 0 to 1 exclusive. This can be easily accomplished using NumPy’s There are many methods and logics available to create a vector array with definite size having values from 0 to 1 (both excluded) in NumPy. In this thread, we will create an array with size 10 values ranging from 0 to 1, both are excluded.

#### 1. Using "linspace()" function with "slicing":

NumPy’s `linspace()`

function is used to generate arrays of evenly spaced values. It generates a specified number of values between a given start and end point. The `linspace()`

function takes three arguments: the start point, the end point, and the number of values to generate.

`Linspace()`

is particularly useful when we want to generate an array with a specific number of values, or when we want to ensure that the step size is exactly what we need for a particular application.

let’s see the example given below to gain better understanding:

In the above code, we can use the linspace() method to generate a sequence of 12 values ranging from 0 to 1, inclusive. Then, slicing is used to exclude the first and last values, resulting in a vector of size 10 with values ranging from 0 to 1 (both excluded).

#### 2. Using "random.uniform()" function :

The `random.uniform()`

function in NumPy is used to generate an array of random numbers with a specified shape and within a specified range. he function takes several parameters, including the shape of the output array and the minimum and maximum values of the range.

The `random.uniform()`

function can be useful in simulations, statistical analysis, and other applications where random numbers are required

You can used `random.uniform()`

method to generate a vector of size 10 with random values ranging from 0 to 1 (both excluded). Let’s see the example given below to gain better understanding:

The above code uses NumPy’s `random.uniform()`

function to generate an array of 10 random numbers between 0 and 1, which are stored in the variable `vector`

. The function takes three arguments: the range of values, and the size of the output array.

#### 3. Using "arange()" function with scaling :

In NumPy, the `arange()`

function is used to create an array of evenly spaced values within a specified interval. It takes three arguments: the start of the interval (inclusive), the end of the interval (exclusive), and the step size between values.

The `arange()`

function is useful for generating sequences of numbers to use in mathematical operations, simulations, and visualizations.

In the above example, `np.arange()`

the function is used to create an array containing values ranging from 0.1 (inclusive) to 1 (exclusive), incremented by 0.1. The resulting array is stored in the variable vector and printed to the console using the print function.