numpy string operations | rsplit() function

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(['zambiatek for zambiatek']) print ("Input array : ", in_arr)   # output array out_arr = geek.char.rsplit(in_arr) print ("Output splitted array: ", out_arr) |
Input array : ['zambiatek for zambiatek'] Output splitted array: [['zambiatek', 'for', 'zambiatek']]
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Code #2 :
# 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) |
Input array : ['Num-py' 'Py-th-on' 'Pan-das'] Output splitted array: [['Num', 'py'] ['Py', 'th', 'on'] ['Pan', 'das']]
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Code #3 :
# 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) |
Input array : ['Num-py' 'Py-th-on' 'Pan-das'] Output splitted array: [['Num', 'py'] ['Py-th', 'on'] ['Pan', 'das']]



