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Create a chararray.
Deprecated since version 2.5: chararray is deprecated. Use an ndarray with a string or
bytes dtype instead.
Note
This class is provided for numarray backward-compatibility.
New code (not concerned with numarray compatibility) should use
arrays of type bytes_ or str_ and use the free functions
in numpy.char for fast vectorized string operations instead.
Versus a NumPy array of dtype bytes_ or str_, this
class adds the following functionality:
values automatically have whitespace removed from the end when indexed
comparison operators automatically remove whitespace from the end when comparing values
vectorized string operations are provided as methods
(e.g. chararray.endswith)
and infix operators (e.g. +, *, %)
itemsize is the number of characters per scalar in the resulting array. If itemsize is None, and obj is an object array or a Python list, the itemsize will be automatically determined. If itemsize is provided and obj is of type str or unicode, then the obj string will be chunked into itemsize pieces.
If true (default), then the object is copied. Otherwise, a copy
will only be made if __array__ returns a copy, if obj is a
nested sequence, or if a copy is needed to satisfy any of the other
requirements (itemsize, unicode, order, etc.).
When true, the resulting chararray can contain Unicode
characters, when false only 8-bit characters. If unicode is
None and obj is one of the following:
then the unicode setting of the output array will be automatically determined.
Specify the order of the array. If order is C (default), then the array will be in C-contiguous order (last-index varies the fastest). If order is F, then the returned array will be in Fortran-contiguous order (first-index varies the fastest). If order is A, then the returned array may be in any order (either C-, Fortran-contiguous, or even discontiguous).
Examples
>>> import numpy as np
>>> char_array = np.char.array(['hello', 'world', 'numpy','array'])
>>> char_array
chararray(['hello', 'world', 'numpy', 'array'], dtype='<U5')
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