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# Return a 2-D array with ones on the diagonal and zeros elsewhere and also set the number of columns in Numpy

The **numpy.eye()** returns a 2-D array with 1’s as the diagonal and 0’s elsewhere. Here, the 1st parameter means the "Number of rows in the output" i.e. 4 means 4x4 array. The 2nd parameter is the number of columns in the output.

The function eye() returns an array where all elements are equal to zero, except for the k-th diagonal, whose values are equal to one. The dtype is the data-type of the returned array. The order suggests whether the output should be stored in row-major (C-style) or column-major (Fortran-style) order in memory.

The like parameter is a reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

## Steps

At first, import the required library −

import numpy as np

Create a 2d array. The numpy.eye() returns a 2-D array with 1’s as the diagonal and 0’s elsewhere. Here, the 1st parameter means the "Number of rows in the output" i.e. 4 means 4x4 array. The 2nd parameter is the number of columns in the output. We have set 3 here −

arr = np.eye(4, 3)

Display the array −

print("Array...\n", arr)

Get the type of the array −

print("\nArray type...\n", arr.dtype)

Get the shape of the array −

print("\nArray shape...\n", arr.shape)

Get the dimensions of the Array −

print("\nArray Dimensions...\n",arr.ndim)

Get the number of elements in the Array −

print("\nArray (count of elements)...\n",arr.size)

## Example

import numpy as np # Create a 2d array # The numpy.eye() returns a 2-D array with 1’s as the diagonal and 0’s elsewhere. # Here, the 1st parameter means the "Number of rows in the output" i.e. 4 means 4x4 array # The 2nd parameter is the number of columns in the output. We have set 3 here arr = np.eye(4, 3) # Display the array print("Array...\n", arr) # Get the type of the array print("\nArray type...\n", arr.dtype) # Get the shape of the array print("\nArray shape...\n", arr.shape) # Get the dimensions of the Array print("\nArray Dimensions...\n",arr.ndim) # Get the number of elements of the Array print("\nArray (count of elements)...\n",arr.size)

## Output

Array... [[1. 0. 0.] [0. 1. 0.] [0. 0. 1.] [0. 0. 0.]] Array type... float64 Array shape... (4, 3) Array Dimensions... 2 Array (count of elements)... 12

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