numpy.core.defchararray.rsplit (arr, sep = None, maxsplit = None) — another function to do string operations in numpy. Returns a list of words in a string, using sep as the separator string for each element in arr. The rsplit () method splits each element of the string array into a list starting from the right, while the split () method splits each element of the string array starting from the left.

Parameters:
arr: array_like of str or unicode.Input array.
sep: [str or unicode, optional] specifies the separator to use when splitting the string.
maxsplit: [int, optional] how many maximum splits to do.

Returns: [ndarray] Output Array containing of list objects.

Code # 1:

# Python program explaining # numpy.char.rsplit () method   # numpy imports imp ort numpy as geek   # input array in_arr = geek.array ([ `geeks for geeks` ]) print ( "Input array:" , in_arr )    # output array out_arr = geek.char.rsplit (in_arr) print ( "Output splitted array:" , out_arr)

Output:

 Input array: [`geeks for geeks`] Output splitted array: [ [`geeks`,` for`, `geeks`]] 

Code # 2:

# Python program explaining # numpy.char.rsplit () method    # numpy import import numpy as geek   # input array in_arr = geek.array ([ `Num-py` , ` Py-th-on` , `Pan-das` ]) print ( "Input array:"  , in_arr)      # output array out_arr = geek.char.rsplit (in_arr, sep = ` -` ) print ( "Output splitted array:" , out_arr)

Output :

 Input array: [`Num-py`` Py-th-on` `Pan -das`] Output splitted array: [[`Num`,` py`] [`Py`,` th`, `on`] [` Pan`, `das`]] 

Code # 3:

# Python program explaining # nu mpy.char.rsplit () method   # numpy import import numpy as geek   # input array in_arr = geek.array ([ ` Num-py` , `Py-th-on` , ` Pan-das` ]) print ( "Input array:" , in_arr)      # output array at maximum splitting # of each item array is equal to 1 out_arr = geek. char.rsplit (in_arr, sep = `-` , maxsplit = 1 ) print ( "Output splitted array:" , out_arr)

Exit:

 Input array: [`Num-py`` Py-th-on` `Pan-das`] Output splitted array: [[` Num`, `py`] [` Py-th`, `on`] [` Pan`, `das`]]