NumPy provides an N-dimensional array type, the ndarray, which describes a collection of “items” of the same type. The items can be indexed using for example N integers · All ndarrays are homogeneous: every item takes up the same size block of memory, and all blocks are interpreted in ...

A 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.)

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 ...

Starting in NumPy 1.7, there are core array data types which natively support datetime functionality. The data type is called datetime64, so named because datetime is already taken by the Python standard library · Similar to the Python date class, dates are expressed in the current Gregorian ...