numpy string operations | rsplit() function
Last Updated :
05 Feb, 2019
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numpy.core.defchararray.rsplit(arr, sep=None, maxsplit=None)
is another function for doing string operations in numpy. It returns a list of the words in the string, using sep as the delimiter string for each element in arr. The rsplit()
method splits every string array element into a list, starting from the right whereas the split()
method splits every string array element into a list, 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
# importing numpy
import 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:
Code #2 :
Input array : ['geeks for geeks'] Output splitted array: [['geeks', 'for', 'geeks']]
# Python program explaining
# numpy.char.rsplit() method
# importing numpy
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:
Code #3 :
Input array : ['Num-py' 'Py-th-on' 'Pan-das'] Output splitted array: [['Num', 'py'] ['Py', 'th', 'on'] ['Pan', 'das']]
# Python program explaining
# numpy.char.rsplit() method
# importing numpy
import numpy as geek
# input array
in_arr = geek.array(['Num-py', 'Py-th-on', 'Pan-das'])
print ("Input array : ", in_arr)
# output array when maximum splitting
# of every array element is 1
out_arr = geek.char.rsplit(in_arr, sep ='-', maxsplit = 1)
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']]