Arrays can be created in a number of ways, for instance from other data structures, by reading files on disk, or from the Web. For the purposes of this chapter, whose aim is to familiarize us with the core characteristics of a NumPy array, we will be creating arrays using lists or various NumPy functions.
The simplest way to create an array is using the array function. To create a valid array object, arguments to array functions need to adhere to at least one of the following conditions:
- It has to be a valid iterable value or sequence, which may be nested
- It must have an
__array__method that returns a valid numpy array
Consider the following snippet:
In [32]: x = np.array([1, 2, 3]) In [33]: y = np.array(['hello', 'world'])
The first condition is always true for Python lists and tuples. When creating an array from lists or tuples, the input may consist of different (heterogeneous) data types. The array function, however, will normally...
