Chapter 3: High-Speed Scientific Computing Using NumPy
This chapter introduces us to NumPy, a high-speed Python library for matrix calculations. Most data science/algorithmic trading libraries are built upon NumPy's functionality and conventions.
In this chapter, we are going to cover the following key topics:
- Introduction to NumPy
- Creating NumPy n-dimensional arrays (ndarrays)
- Data types used with NumPy arrays
- Indexing of ndarrays
- Basic ndarray operations
- File operations on ndarrays
Technical requirements
The Python code used in this chapter is available in the Chapter03/numpy.ipynb notebook in the book's code repository.
Introduction to NumPy
Multidimensional heterogeneous arrays can be represented in Python using lists. A list is a 1D array, ...
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