Visualize Financial Market Data with Matplotlib, Seaborn, and Plotly Dash

The first step when working with data is to visualize and explore it. This is especially true when dealing with financial market data we rely on for trading. This chapter sets the stage by introducing five powerful data visualization techniques: pandas, Matplotlib, Seaborn, Plotly, and Plotly Dash.

Each tool has pros and cons and should be selected depending on the use case. pandas has built-in plotting functionality using both Matplotlib and Plotly to render the charts. Matplotlib offers advanced functionality for building 3-dimensional surfaces and animated charts. Seaborn offers an array of statistical data visualizations. Plotly works with JavaScript for interactive charting. Plotly Dash is a framework for building interactive web apps with Python.

By the end of the chapter, you’ll have a wide range of tools and chart types to visually inspect the financial market data required to research and...