Type Conversion

Lesson 2 Chapter 1

Now, let's turn a list to a Numpy array. For now, let's just focus on the data types and conversion, later in this course, you will learn how to define Numpy arrays in details.

# Import Numpy library import numpy as np # Define a Python list a = [1, 2, 1.3] print('Type "a": ', type(a)) # Turn Python list into a Numpy array of type np.int32 (Integer (-2147483648 to 2147483647)) b = np.int32(a) print('Array "b": ', b) print('Type array "b": ', type(b)) print('Array "b" data type: ', b.dtype) # Turn Python list into a Numpy array of type np.float32 (same as Python float) c = np.float32(a) print('Array "c": ', c) print('Type array "c": ', type(c)) print('Array "c" data type: ', c.dtype)

Type "a": <class 'list'> Array "b": [1 2 1] Type array "b": <class 'numpy.ndarray'> Array "b" data type: int32 Array "c": [1. 2. 1.3] Type array "c": <class 'numpy.ndarray'> Array "c" data type: float32

*We used the . dtype Numpy method to realize what is the data type inside the array.* The recommended way to change the type of a Numpy array is the usage of

**.astype()**

method. Take a look at the following example:# Import Numpy library import numpy as np # Define a Python list a = [1, 2, 4] print('Type "a": ', type(a)) # Turn Python list into a Numpy array of type np.int32 (Integer (-2147483648 to 2147483647)) b = np.int32(a) print('Array "b": ', b) print('Type array "b": ', type(b)) # Turn Python list into a Numpy array of type np.float32 (same as Python float) c = b.astype(np.float32) print('Array "c": ', c) print('Type array "c": ', type(c))

Type "a": <class 'list'> Array "b": [1 2 4] Type array "b": <class 'numpy.ndarray'> Array "c": [1. 2. 4.] Type array "c": <class 'numpy.ndarray'>