Python for Finance: Analyze Big Financial Data

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Chapter 5. Data Visualization


Use a picture. It’s worth a thousand words.

β€” Arthur Brisbane (1911)

This chapter is about basic visualization capabilities of the matplotlib library. Although


there are many other visualization libraries available, matplotlib has established itself as


the benchmark and, in many situations, a robust and reliable visualization tool. It is both


easy to use for standard plots and flexible when it comes to more complex plots and


customizations. In addition, it is tightly integrated with NumPy and the data structures that


it provides.


This chapter mainly covers the following topics:


2D plotting


From the most simple to some more advanced plots with two scales or different


subplots; typical financial plots, like candlestick charts, are also covered.


3D plotting


A selection of 3D plots useful for financial applications are presented.


This chapter cannot be comprehensive with regard to data visualization with Python and


matplotlib, but it provides a number of examples for the most basic and most important


capabilities for finance. Other examples are also found in later chapters. For instance,


Chapter 6 shows how to visualize time series data with the pandas library.

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