Exploratory data analysis

Now that we have our data, we want to get familiar with it. As we saw in Chapter 5, Visualizing Data with Pandas and Matplotlib and Chapter 6, Plotting with Seaborn and Customization Techniques, creating good visualizations requires knowledge of matplotlib, and—depending on the data format and the end goal for the visualization—seaborn. Just as we did with the StockReader class, we want to make it easier to visualize both individual assets and groups of assets, so rather than expecting users of our package (and, perhaps, our collaborators) to be proficient with matplotlib and seaborn, we will create wrappers around this functionality. This means that users of this package only have to be able to use the stock_analysis package to visualize their financial data. In addition, we are able to set a standard for how the visualizations look and avoid copying and pasting large amounts of code for each new analysis we want to conduct, which brings consistency...