Chapter 1. Python for Financial Applications
In this introductory chapter, we will explore the aspects of Python in order to judge its suitability as a programming language in finance. Notably, Python is widely practiced in various financial sectors, such as banking, investment management, insurance, and even in real estate for building tools that help in financial modeling, risk management, and trading. To help you get the most from the multitude of features that Python has to offer, we will introduce the IPython Notebook as a beneficial tool to help you visualize data and to perform scientific computing for presentation to end users.
In this chapter, we will cover the following topics:
- Benefits of Python over other programming languages for financial studies
- Features of Python for financial applications
- Implementing object-oriented design and functional design in Python
- Overview of IPython
- Getting IPython and IPython Notebook started
- Creating and saving notebook documents
- Various formats to export a notebook document
- Notebook document user interface
- Inserting Markdown language into a notebook document
- Performing calculations in Python in a notebook document
- Creating plots in a notebook document
- Various ways of displaying mathematical equations in a notebook document
- Inserting images and videos into a notebook document
- Working with HTML and pandas DataFrame in a notebook document
