numpy.char.lstrip#

char.lstrip(a, chars=None)[source]#

For each element in a, return a copy with the leading characters removed.

Calls str.lstrip element-wise.

Parameters

aarray-like, {str, unicode}: Input array.
chars{str, unicode}, optional: The chars argument is a string specifying the set of characters to be removed. If omitted or None, the chars argument defaults to removing whitespace. The chars argument is not a prefix; rather, all combinations of its values are stripped.

Returns

outndarray, {str, unicode}: Output array of str or unicode, depending on input type

See also

str.lstrip

Examples

>>> c = np.array(['aAaAaA', '  aA  ', 'abBABba'])
>>> c
array(['aAaAaA', '  aA  ', 'abBABba'], dtype='<U7')

The ‘a’ variable is unstripped from c[1] because whitespace leading.

>>> np.char.lstrip(c, 'a')
array(['AaAaA', '  aA  ', 'bBABba'], dtype='<U7')

>>> np.char.lstrip(c, 'A') # leaves c unchanged
array(['aAaAaA', '  aA  ', 'abBABba'], dtype='<U7')
>>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, '')).all()
... # XXX: is this a regression? This used to return True
... # np.char.lstrip(c,'') does not modify c at all.
False
>>> (np.char.lstrip(c, ' ') == np.char.lstrip(c, None)).all()
True

numpy.char.lower

numpy.char.partition