ABSTRACT
Data visualization is the depiction of complex data in a graphical form using charts and graphs. Data visualization makes it easier to understand complex data and to draw inferences. It facilitates further quality control and downstream analysis. To arrive at biological insights, it is important to be able to visualize biological data. Python has several libraries for graphical representation of data, and these are rich in features and simple to execute. In this chapter, we will discuss data visualization using Python and elaborate on two important Python libraries - Matplotlib and Seaborn. Seaborn is a library used for making statistical graphics in Python. It is built on top of Matplotlib and is closely integrated with pandas data structures. In addition, the Plotly Python library allows the creation of interactive and exportable figures with just a few lines of code that can be displayed in Jupyter Notebooks or saved as standalone HTML files. Plotly Express is the easy-to-use, high-level interface of Plotly, which operates on a variety of types of data and produces easy-to-style figures. In this chapter, readers will be guided through the process of graphical representation of biological data using Python.
