# Set a 1-D iterator over a Numpy array

For a 1-D iterator over the array, use the numpy.flat() method in Python Numpy. This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object.

NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.

## Steps

At first, import the required library −

import numpy as np

Create a 2d array −

arr = np.array([[36, 36, 78, 88], [92, 81, 98, 45], [22, 67, 54, 69 ], [69, 80, 80, 99]])

Displaying our array −

print("Array...",arr)

Get the datatype −

print("Array datatype...",arr.dtype)


Get the dimensions of the Array −

print("Array Dimensions...",arr.ndim)

Get the shape of the Array −

print("Our Array Shape...",arr.shape)

Get the number of elements of the Array −

print("Elements in the Array...",arr.size)

For a 1-D iterator over the array, use the numpy.flat() method in Python Numpy −

print("Result...",arr.flat[2])
print("Result...",arr.flat[7])
print("Result...",arr.flat[9])

Get the type of the flat iterator −

print("Get the type...",type(arr.flat))

## Example

import numpy as np

# Create a 2d array
arr = np.array([[36, 36, 78, 88], [92, 81, 98, 45], [22, 67, 54, 69], [69, 80, 80, 99]])

# Displaying our array
print("Array...",arr)

# Get the datatype
print("Array datatype...",arr.dtype)

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

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

# Get the number of elements of the Array
print("Elements in the Array...",arr.size)

# For a a 1-D iterator over the array, use the numpy.flat() method in Python Numpy
print("Result...",arr.flat[2])
print("Result...",arr.flat[7])
print("Result...",arr.flat[9])

# Get the type of the flat iterator
print("Get the type...",type(arr.flat))

## Output

Array...
[[36 36 78 88]
[92 81 98 45]
[22 67 54 69]
[69 80 80 99]]

Array datatype...
int64

Array Dimensions...
2

Our Array Shape...
(4, 4)

Elements in the Array...
16

Result...
78

Result...
45

Result...
67

Get the type...
<class 'numpy.flatiter'>