The task is a series of analytics questions focused on understanding the data and its relation to predicting the target(good or bad credit risk). Feel free to use any open source python technologies to complete this task.

I’ve attached the data you will be using for this assignment to this email(credit.csv) Perform some simple exploratory analysis and generate summary statistics to get a sense of what is in the data.

• Describe the quality of the data.
• Describe the relationship of the attributes with the label and share any interesting insights you’ve found.
• Build a model to predict whether a given person is a good or bad credit risk.
• Generate a few visuals to convey data and model characteristics, these should be presentable to a non-technical business audience.

Write all of this into a python notebook, upload to a git repo, and share the link with the us to review. Be prepared to discuss your methodologies and approach. Context:

• Assume the audience for your write-up is a non-technical stakeholder.
• Assume the audience for your code is a colleague who may need to read or modify it in the future.