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This is documentation for an old release of NumPy (version 1.19). Read this page in the documentation of the latest stable release (version 2.2).

numpy.char.lstrip

numpy.char.lstrip(a, chars=None)

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