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'>

Updated on: 17-Feb-2022

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