NumPy and Basic Stats
NumPy is designed to handle big data swiftly. It includes the following essential components according to the NumPy documentation:
- A powerful n-dimensional array object
- Sophisticated (broadcasting) functions
- Tools for integrating C/C++ and Fortran code
- Useful linear algebra, Fourier transform, and random number capabilities
You will be using NumPy for the rest of the course. Instead of using lists, you will use NumPy arrays. NumPy arrays are the basic elements of the NumPy package. NumPy arrays are designed to handle arrays of any dimension.
Numpy arrays can be indexed easily and can have many types of data, such as float
, int
, string
, and object
, but the types must be consistent to improve speed.
Exercise 128: Converting Lists to NumPy Arrays
In this exercise, you will convert a list to a numpy
array. The following steps will enable you to complete the exercise:
- Open a new Jupyter Notebook.
- Firstly, you need to...