An array with a specified range of values in each row can be generated using NumPy. Such arrays are useful for numerical computations where the rows represent observations or data points, and the values in each row represent a specific parameter or variable. The range of values can be customized based on the requirements of the computation or analysis. In this thread, we will discuss various methods of creating 2D array with specified range of row values.

#### 1. By "zeros()" function and "broadcasting" :

In NumPy, `zeros()`

function takes one required argument n (shape) , returns an array having all values zero’s. NumPy enables performing operations on arrays of different sizes or dimensions using a technique known as `broadcasting`

, which adjusts the arrays by adding dimensions or replicating elements as required.

You can create a 2D matrix with row values within a specific range by using the `zeros()`

function to create a matrix of zeros. We then add the row number to each row using `broadcasting`

,

For example, creating a 5x5 matrix and using `broadcasting`

.

The above code creates a 5x5 array of zeros using NumPy’s `zeros`

function. It then generates an array with values from 0 to 4 using NumPy’s `arange`

function, and adds these values to each row of the 5x5 array of zeros using broadcasting. The resulting array is stored in the variable `arr`

and printed to the console using the `print`

function.

#### 2. Using "tile()" and "arange()" function :

The `tile()` function repeats an input array along specified dimensions, while the `arange()` function generates an array of sequential values within a specified range.To create a 5x1 array and a 1x5 array of sequential numbers from 0 to 4, the `tile()`

and `arange()`

functions can be used. These arrays can be used with the `broadcast_to()`

function to create a 5x5 matrix with the same value in each row and column.

The above code generates two arrays using NumPy’s `tile`

, `arange`

, and `broadcast_to`

functions. It creates a 5x5 array of numbers from 0 to 4 using `tile`

, and another 5x5 array using `broadcast_to`

. These two arrays are added together using the `+`

operator and the result is printed to the console using the `print`

function.

#### 3. Using "ones()" function :

The `numpy.ones()`

function is used to create an array filled with ones. The function takes a tuple as input that specifies the dimensions of the array.

You can create a 5x5 matrix of ones and then multiplies it with the row values ranging from 0 to 4 using `broadcasting`

. For example:

The above code uses NumPy’s `ones`

function to create a 5x5 array of ones, and then multiplies each element of the array with the corresponding element of an array generated using NumPy’s `arange`

function. The resulting array is broadcasted to match the shape of the array of ones, stored in a variable and printed to the console using the `print`

function.