https://numpy.org › doc › stable › reference › arrays.dtypes.html
Data type objects (dtype) — NumPy v2.1 ManualLearn how to create and use data type objects (dtype) to describe the memory layout and interpretation of array items in NumPy. See examples of scalar, structured and sub-array data types, and how to specify byte order, size and alignment.
The N-dimensional array (ndarray)#An ndarray is a (usually fixed-size) multidimensional container of items of the same type and size. The number of dimensions and items in an array is defined by its shape, which is a tuple of N non-negative integers that specify the sizes of each dimension. The type of items in the array is specified by a separate data-type object (dtype), one of which is ...
Datetime and timedelta arithmetic#. NumPy allows the subtraction of two datetime values, an operation which produces a number with a time unit. Because NumPy doesn’t have a physical quantities system in its core, the timedelta64 data type was created to complement datetime64.The arguments for timedelta64 are a number, to represent the number of units, and a date/time unit, such as (D)ay, (M ...
NumPy supports a much greater variety of numerical types than Python does. This section shows which are available, and how to modify an array’s data-type. NumPy numerical types are instances of numpy.dtype (data-type) objects, each having unique characteristics.
Create a data type object. A numpy array is homogeneous, and contains elements described by a dtype object. A dtype object can be constructed from different combinations of fundamental numeric types. Parameters: dtype. Object to be converted to a data type object. alignbool, optional.
https://numpy.org › doc › stable › user › basics.types.html
Data types — NumPy v2.1 ManualLearn how to create and manipulate arrays with different data types in NumPy, such as numerical, string, byte and void types. See the correspondence between NumPy and C data types and how to specify parameters like byte order.
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https://numpy.org › doc › stable › reference › generated › numpy.dtype.html
numpy.dtype — NumPy v2.1 ManualLearn how to create and use numpy.dtype objects to describe the elements of a homogeneous array. See examples of different types, formats, fields, and metadata.
https://docs.scipy.org › doc › numpy-1.13.0 › reference › arrays.dtypes.html
Data type objects (dtype) — NumPy v1.13 Manual - SciPy.orgA data type object (an instance of numpy.dtype class) 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 (how many bytes is in e.g. the integer)
https://runebook.dev › fr › docs › numpy › reference › arrays.dtypes
NumPy - dtype object [fr] - Runebook.devUn objet de type de données (une instance de la classe numpy.dtype ) décrit comment les octets du bloc de mémoire de taille fixe correspondant à un élément du tableau doivent être interprétés. Il décrit les aspects suivants des données : Type de données (entier, float, objet Python , etc.)
https://docs.scipy.org › doc › numpy-1.13.0 › user › basics.types.html
Data types — NumPy v1.13 Manual - SciPy.orgData-types can be used as functions to convert python numbers to array scalars (see the array scalar section for an explanation), python sequences of numbers to arrays of that type, or as arguments to the dtype keyword that many numpy functions or methods accept. Some examples:
https://stackoverflow.com › questions › 9457037
python - what does .dtype do? - Stack OverflowA data type object (an instance of numpy.dtype class) describes how the bytes in the fixed-size block of memory corresponding to an array item should be interpreted. ints and floats don't have the same bit patterns, meaning you can't just look at the memory for an int and it would be the same number when you look at it as a float.
https://www.slingacademy.com › article › a-detailed-guide-to-ndarray-dtype-attribute-in...
A detailed guide to ndarray.dtype attribute in NumPy (5 examples)Learn how to use the ndarray.dtype attribute in NumPy to define, change and check the data type of arrays. See examples of basic, complex and structured data types, and how they affect performance and operations.
https://numpy.org › doc › stable › › reference › routines.dtypes.html
Data type classes (numpy.dtypes) — NumPy v2.1 ManualLearn about the classes of NumPy dtype instances and scalar types defined in the dtypes module. See the source code and examples of each class and how to use them in isinstance checks or direct instantiation.
https://docs.scipy.org › doc › numpy-1.17.0 › user › basics.types.html
Data types — NumPy v1.17 Manual - SciPy.orgData-types can be used as functions to convert python numbers to array scalars (see the array scalar section for an explanation), python sequences of numbers to arrays of that type, or as arguments to the dtype keyword that many numpy functions or methods accept. Some examples:
