Analyzing a Dataset in Jupyter Notebooks / Python

Question

I have a dataset that I am trying to analyze for a project.

The first step of the project is to basically model the data, and I am running into some issues. The data is on house sales within the past 5 years. Collecting data on buyers, cost of house, income, age, year purchased, years in loan, years at current job, and whether or not this house was foreclosed on with YES or NO.

The goal is to train a model to make predictions using machine learning, but I am stuck on part 1 - describing the data. I am using Jupyter notebooks to analyze the data and trying to put together a linear or multilinear regression model, and I am failing. When I throw together a scatter plot, my data is all over the chart with no way to really "group" the data at intersection point and cast a prediction line. This makes it difficult to figure out what is actually happening, perhaps the data I am comparing is not correlated in any way.

The problem also comes in with the YES or NO data. I was thinking this might need to be converted into 0s and 1s, but then my linear regression model would have an incredible weight on both ends of the spectrum. Perhaps regression is not the best choice?

I'm just struggling to figure out what to do and how to do it. I am kind of new to data analysis, so perhaps I am thinking of this all wrong. If anyone has any insight it would be much appreciated.