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# Return a 2-D array with ones on the diagonal and zeros elsewhere but set a different datatype 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. If None, defaults to the 1st parameter i.e. 4x4 here. The "**dtype**" parameter is used to set a different datatype of the returned array.

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. If None, defaults to the 1st parameter i.e. 4x4 here. The "dtype" parameter is used to set a different datatype of the returned array −

arr = np.eye(4, dtype = float)

Display the array −

print("Array...

", arr)

Get the type of the array −

print("

Array type...

", arr.dtype)

Get the shape of the array −

print("

Array shape...

", arr.shape)

Get the dimensions of the Array −

print("

Array Dimensions...

",arr.ndim)

Get the number of elements in the Array −

print("

Array (count of elements)...

",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. # The "dtype" parameter is used to set a different datatype of the returned array arr = np.eye(4, dtype = float) # Display the array print("Array...

", arr) # Get the type of the array print("

Array type...

", arr.dtype) # Get the shape of the array print("

Array shape...

", arr.shape) # Get the dimensions of the Array print("

Array Dimensions...

",arr.ndim) # Get the number of elements of the Array print("

Array (count of elements)...

",arr.size)

## Output

Array... [[1. 0. 0. 0.] [0. 1. 0. 0.] [0. 0. 1. 0.] [0. 0. 0. 1.]] Array type... float64 Array shape... (4, 4) Array Dimensions... 2 Array (count of elements)... 16