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Practice making heat maps

Heat maps are a great way to visualize correlations between various financial ratios. They can be used to see which ratios correlate strongly with profitability ratios and thus aid us in deciding which companies to invest in.

In this exercise, you'll practice making heat maps. A pandas DataFrame merged_dat has been loaded for you with some ratios already computed. pandas and Seaborn have been loaded with the aliases pd and sns.

This exercise is part of the course

Analyzing Financial Statements in Python

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Make the correlation matrix
corr_mat = merged_dat[["Gross Margin", "Operating Margin", "Debt-to-equity",
                             "Equity Multiplier", "Current Ratio"]]____
Edit and Run Code