Currently. working with strings in numpy is not very convenient. You have to use a separate set of functions in a separate namespace, and those functions are relatively limited and poorly-documented.
A solution several other projects, including pandas [0] and xarray [1], have found are string accessor methods. These are a set of methods attached to a `str` attribute of the class. These have the advantage that they are always available and have a well-defined object they operate on. On non-str dtypes, it would raise an exception. This would also provide a standardized set of methods and behaviors that are part of the numpy api that other classes could depend on. An example would be something like this: >>> mystr = np.array(["test first", "test second", "test third"]) >>> mystr.str.title() array(['Test First', 'Test Second', 'Test Third'], dtype='<U11') [0] https://pandas.pydata.org/pandas-docs/stable/user_guide/text.html#string-methods [1] https://xarray.pydata.org/en/stable/generated/xarray.core.accessor_str.StringAccessor.html
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