Unit 6: Visualization
Now that you've mastered the basic statistical, array, and spreadsheet data processing techniques, it is natural to want to plot, render, and visualize that data. In this unit, we will discuss visualization techniques beyond those introduced using matplotlib and pandas. When you finish this unit, you will be able to implement and visualize data plots applied within the field of data science.
The matplotlib module is convenient for visualizing data formatted using numpy arrays. pandas is similarly equipped for pandas dataframes. The seaborn module is also designed to work with pandas data. It is extremely powerful for rendering data using methods professional data scientists would find useful. While matplotlib provides basic plotting capabilities, seaborn can be used to construct bar charts, violin plots, heat maps, and more. These more advanced forms of visualization for statistical data sets can enable one to immediately draw inferences based on patterns discerned within the plots.
Completing this unit should take you approximately 4 hours.
6.1: The seaborn Module
6.2: Advanced Data Visualization Techniques
6.3: Data Science Applications
Unit 6 Assessment
- Receive a grade