Best Way to Split a Numpy Array

Best Way to Split a Numpy Array , Know in 2 Steps Only

You must know about how to join or append two or more arrays into a single array. Splitting a Numpy array is just the opposite of it. Here you have to use the numpy split() method. In this entire tutorial of “How to,” you will learn how to Split a Numpy Array for both dimensions 1D and 2D -Numpy array.

Splitting a 1 D Numpy array

In this section, you will learn how to split a one dimension numpy array with various examples.

Execute the following steps to split a numpy array.

Step 1: Import the necessary library

I am using only the numpy array so only import this module.

import numpy as np

Step 2: Create a One Dimensional Array

The creation of a Numpy array requires the array() method, use it.

array_1d = np.array([10,20,30,40,50,60])
array_1d
1 D Numpy Array Creation
1 D Numpy Array Creation

Step 3: Split the Array

You can split the array as many parts you want using the split() method. Let’s say I want to split the array into 3 and 4 Parts. then I will pass the 3 and 4 value as the argument inside the split() method.

#split the array into 3 parts
np.array_split(array_1d,3)
#split the array into 4 parts
np.array_split(array_1d,4)
Splitting the Numpy Array in 3 and 4 Sub Arrays
Splitting the Numpy Array in 3 and 4 Sub Arrays
You can also access the subpart of the array in the same way as you access the simple array.
#print each array
print(split_array[0])
print(split_array[1])
print(split_array[2])
Displaying Each Split Array
Displaying Each Split Array

Splitting a 2 D Numpy array

Unlike 1-D Numpy array there are other ways to split the 2D numpy array. Here you have to take care of which way to split the array that is row-wise or column-wise. Let’s create a 2-D numpy array and split it.

Execute the following steps

Step 1  : Create a 2D Numpy array.

array_2d = np.array([[10,20,30],[40,50,60],[70,80,90],[100,110,120],[130,140,150]])
array_2d
2 D Numpy Array Creation
2 D Numpy Array Creation

Step 2: Split the array

There are two ways to split the array one is row-wise and the other is column-wise. By default, the array is split in row-wise (axis =0 ). If you want to split the array in column-wise use axis =1.

Row Wise Split

np.array_split(array_2d,2) #or
np.array_split(array_2d,2,axis=0)
Splitting the 2D Numpy Array RowWise
Splitting the 2D Numpy Array RowWise

The above code will split the given array into two 2-D arrays. In the same, you can split the array into 3 parts passing value in split() method to 3.

Colum Wise Split

np.array_split(array_2d,2,axis=1)
np.array_split(array_2d,3,axis=1)

Here I am only passing the axis =1 to split the 3D array through column-wise. The output of the code is given below.

Splitting the 2D Numpy Array Column Wise
Splitting the 2D Numpy Array Column Wise

These are the ways to split the numpy array for both One and two-dimension. Hope you have understood it. If you have any query then comment below or personally contact us.

Source:

Official Split Numpy Documentation

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