numpy.apply_along_axis() in Python

The numpy.apply_along_axis() function helps us to apply a required function to 1D slices of the given array. 
1d_func(ar, *args) : works on 1-D arrays, where ar is 1D slice of arr along axis.

Syntax : 

numpy.apply_along_axis(1d_func, axis, array, *args, **kwargs) 

Parameters :  

1d_func : the required function to perform over 1D array. It can only be applied in 
 1D slices of input array and that too along a particular axis. 
axis : required axis along which we want input array to be sliced
array : Input array to work on 
*args : Additional arguments to 1D_function 
**kwargs : Additional arguments to 1D_function 

What *args and **kwargs actually are? 

Both of these allow you to pass a variable no. of arguments to the function. 
*args : allow to send a non-keyword variable length argument list to the function. 

Output : 

use of args : 
 [3, 4, 5, 6, 7]

**kwargs: allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function. 

Output : 

in1: geeks
in2: No.
in3: 1

Code 1: Python code explaining the use of numpy.apply_along_axis().  

Output : 

axis=0 : [ 8 10 12]


axis=1 : [ 4 10 16]

Code 2: Sorting using apply_along_axis() in NumPy Python 

Output : 

Sorted as per axis 1 : 
 [[1 7 8]
 [3 4 9]
 [2 5 6]]


Sorted as per axis 0 : 
 [[4 1 6]
 [5 2 7]
 [8 3 9]]

Note : 
These codes won't run on online IDE's. So please, run them on your systems to explore the working.