Hello, I’m doing a take-home data science assignment for a company and they’ve given me a dataset with some questions to answer. The dataset is similar to one below. They want to understand what features/characteristic are important to the business regarding if a customer will renew their lease or not. They want a simple analysis using core probability and statistical theory to draw insights and conclusions to the business. The dataset is given in terms of binary (1 or 0) with 1 being true and 0 being no/false. The problem is I have never worked with a Binary Dataset so I’m unsure of what kinds of tests I should run to draw up simple conclusions. I’m working in a Juypter notebook (pandas, seaborm, bumpy, matplotlib, sklearn). I would appreciate it if someone could help lead me in a direction to what kind of simple analysis I can run on binary data.

ID	Age 20-29	Age 30-39	Age 40-49	Age 50 >	Lease Length < 1 year	Lease Length 1-2 Years	Lease Length > 3 Years	Late Payment	No Fine Violations	Credit Score Below 600	Renews
312	1	0	0	0	0	1	0	1	0	0	1
313	0	0	1	0	0	0	1	0	1	1	0
314	0	1	0	0	0	1	0	0	0	0	0
315	0	0	0	1	1	0	0	0	0	1	1