The array type

The objects used to manipulate vectors, matrices, and more general tensors in NumPy are called arrays. In this section, we examine their essential properties, how to create them, and how to access their information.

Array properties

Arrays are essentially characterized by three properties, which is given in the following table (Table 4.2):

Name

Description

shape

It describes how the data should be interpreted, as a vector, a matrix or as a higher order tensor, and it gives the corresponding dimension. It is accessed with the shape attribute.

dtype

It gives the type of the underlying data (float, complex, integer, and so on).

strides

This attribute specifies in which order the data should be read. For instance, a matrix ...

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