The converted data-type.
After constructing the format_parser object, the dtype attribute is the converted data-type: dtype = format_parser(formats, names, titles).dtype
The format description, either specified as a string with comma-separated format descriptions in the form 'f8, i4, a5'
, or a list of format description strings in the form ['f8', 'i4', 'a5']
.
The field names, either specified as a comma-separated string in the form 'col1, col2, col3'
, or as a list or tuple of strings in the form ['col1', 'col2', 'col3']
. An empty list can be used, in that case default field names ('f0', 'f1', ...) are used.
Sequence of title strings. An empty list can be used to leave titles out.
If True, align the fields by padding as the C-compiler would. Default is False.
If specified, all the fields will be changed to the provided byte-order. Otherwise, the default byte-order is used. For all available string specifiers, see :None:None:`dtype.newbyteorder`
.
Class to convert formats, names, titles description to a dtype.
>>> np.format_parser(['<f8', '<i4', '<a5'], ['col1', 'col2', 'col3'],
... ['T1', 'T2', 'T3']).dtype dtype([(('T1', 'col1'), '<f8'), (('T2', 'col2'), '<i4'), (('T3', 'col3'), 'S5')])
:None:None:`names`
and/or :None:None:`titles`
can be empty lists. If :None:None:`titles`
is an empty list, titles will simply not appear. If :None:None:`names`
is empty, default field names will be used.
>>> np.format_parser(['f8', 'i4', 'a5'], ['col1', 'col2', 'col3'],
... []).dtype dtype([('col1', '<f8'), ('col2', '<i4'), ('col3', '<S5')])
>>> np.format_parser(['<f8', '<i4', '<a5'], [], []).dtype dtype([('f0', '<f8'), ('f1', '<i4'), ('f2', 'S5')])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.rec.fromstring
numpy.typing
numpy.rec.fromrecords
numpy.rec.fromarrays
numpy.rec.array
numpy.rec.fromfile
numpy.recarray
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