Remain zero-terminated bytes and numpy.string_ continues to alias Type-object: for example, flexible data-types haveĪ default itemsize of 0, and require an explicitly given sizeįor backward compatibility with Python 2 the S and a typestrings Note that not all data-type information can be supplied with a This is true for their sub-classes as well. The 24 built-in array scalar type objects all convert to an associated data-type object. What can be converted to a data-type object is described below: dtype object Whenever a data-type is required in a NumPy function or method, eitherĪ dtype object or something that can be converted to one canīe supplied. array (, dtype = dt ) > x ('John', ) > x array() > type ( x ) > type ( x ) Specifying and constructing data types # Sub-arrays always have a C-contiguous memory layout. Structured type behave differently, see Field access. The dimensions of the sub-array are appended to the shape If an array is created using a data-type describing a sub-array, Structured sub-array data types in their fields.įinally, a data type can describe items that are themselves arrays of Structured data types may also contain nested Parent is nearly always based on the void type which allowsĪn arbitrary item size. Type should be of sufficient size to contain all its fields the Structured data types are formed by creating a data type whoseįield contain other data types. They can be used in place of one whenever a data type specification is Note that the scalar types are not dtype objects, even though Scalar type associated with the data type of the array. An item extracted from anĪrray, e.g., by indexing, will be a Python object whose type is the Of integers, floating-point numbers, etc. Scalar types in NumPy for various precision To describe the type of scalar data, there are several built-in If the data type is a sub-array, what is its shape and data type. Which part of the memory block each field takes. What are the names of the “ fields” of the structure, If the data type is structured data type, an aggregate of otherĭata types, ( e.g., describing an array item consisting of the integer)īyte order of the data ( little-endian or big-endian) Size of the data (how many bytes is in e.g. Type of the data (integer, float, Python object, etc.) A data type object (an instance of numpy.dtype class)ĭescribes how the bytes in the fixed-size block of memoryĬorresponding to an array item should be interpreted.
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