Visualizing loan approval yield

In the realm of financial services, understanding the factors that influence loan approval rates is crucial for both lenders and borrowers. A financial institution has conducted a study and collected data on loan applications, detailing the amount requested, the applicant's credit score, employment status, and the ultimate yield of the approval process. This rich dataset offers a window into the nuanced dynamics at play in loan decision-making. You have been asked to dive into the loan_approval_yield dataset to understand how loan amounts and credit scores influence approval yields.

The loan_approval_yield DataFrame, seaborn as sns, and matplotlib.pyplot as plt have been loaded for you.

Create a side-by-side bar graph, setting the x-axis to 'LoanAmount', the y-axis to 'ApprovalYield', and differentiating the bars with hues for 'CreditScore'.

Exercise

Visualizing loan approval yield

Instructions 1/2

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Instructions 1/2

Exercise