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NumPy Tutorial

NumPy: Data type

Data type

A data type object describes how the bytes in the fixed-size block of memory corresponding to an array item should be interpreted. It describes the following aspects of the data:

  • Type of the data (integer, float, Python object, etc.)
  • Size of the data (number of bytes is in e.g. the integer)
  • Byte order of the data (little-endian or big-endian)
  • If the data type is structured, an aggregate of other data types,
    • Type of the data (integer, float, Python object, etc.)
    • Size of the data (how many bytes is in e.g. the integer)
    • Byte order of the data (little-endian or big-endian)
    • If the data type is structured, an aggregate of other data types, (e.g., describing an array item consisting of an integer and a float),
  • If the data type is a sub-array, what is its shape and data type.
Data type routines
Name Description Syntax
can_cast() Returns True if cast between data types can occur according to the casting rule numpy.can_cast(from_, to, casting='safe')
promote_types() Returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. numpy.promote_types(type1, type2)
min_scalar_type() Returns the data type with the smallest size and smallest scalar kind which can hold its value. numpy.min_scalar_type(a)
result_type() Returns the type that results from applying the NumPy type promotion rules to the arguments. numpy.result_type(*arrays_and_dtypes)
common_type() Return a scalar type which is common to the input arrays. numpy.common_type(*arrays)
obj2sctype() Return the scalar dtype or NumPy equivalent of Python type of an object. numpy.obj2sctype(rep, default=None)
Creating data types
Name Description Syntax
dtype Create a data type object. class numpy.dtype(obj, align=False, copy=False)
format_parser Class to convert formats, names, titles description to a dtype. class numpy.format_parser(formats, names, titles, aligned=False, byteorder=None)
Data type information
Name Description Syntax
finfo() Machine limits for integer types. class numpy.finfo(dtype)
iinfo() Machine limits for integer types. class numpy.iinfo(type)
MachAr() Diagnosing machine parameters. class numpy.MachAr(float_conv=<class 'float'>, int_conv=<class 'int'>, float_to_float=<class 'float'>, float_to_str=<function MachAr.<lambda>>, title='Python floating point number')
Data type testing
Name Description Syntax
issctype() Determines whether the given object represents a scalar data-type. numpy.iinfo(type)
issubdtype() Returns True if first argument is a typecode lower/equal in type hierarchy. numpy.issubdtype(arg1, arg2)
issubsctype() Determine if the first argument is a subclass of the second argument. numpy.issubsctype(arg1, arg2)
issubclass_() Determine if a class is a subclass of a second class. numpy.issubclass_(arg1, arg2)
find_common_type() Determine common type following standard coercion rules. numpy.find_common_type(array_types, scalar_types)
Miscellaneous
Name Description Syntax
typename() Return a description for the given data type code. numpy.typename(char)
sctype2char() Return the string representation of a scalar dtype. numpy.sctype2char(sctype)
mintypecode() Return the character for the minimum-size type to which given types can be safely cast. numpy.mintypecode(typechars, typeset='GDFgdf', default='d')

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