Python for Finance: Analyze Big Financial Data

Part II. Financial Analytics and Development

This part of the book represents its core. It introduces the most important Python libraries,

techniques, and approaches for financial analytics and application development. The sheer

number of topics covered in this part makes it necessary to focus mainly on selected, and

partly rather specific, examples and use cases.

The chapters are organized according to certain topics such that this part can be used as a

reference to which the reader can come to look up examples and details related to a topic

of interest. This core part of the book consists of the following chapters:

Chapter 4 on Python data types and structures

Chapter 5 on 2D and 3D visualization with matplotlib

Chapter 6 on the handling of financial time series data

Chapter 7 on (performant) input/output operations

Chapter 8 on performance techniques and libraries

Chapter 9 on several mathematical tools needed in finance

Chapter 10 on random number generation and simulation of stochastic processes

Chapter 11 on statistical applications with Python

Chapter 12 on the integration of Python and Excel

Chapter 13 on object-oriented programming with Python and the development of

(simple) graphical user interfaces (GUIs)

Chapter 14 on the integration of Python with web technologies as well as the

development of web-based applications and web services