Exercise $1$

We did not introduce them in the notebook, but sns$.$lineplot$)$ gives a way to plot lines charts with seaborn.

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What does this imply is happening with the fuel efficency of cars over time?

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One thing that often happens with datasets like this, is that several of the variables are highly corrolated, so we might be able to reduce the size of our dataset, which will help predictive models run faster.

Create a plot of all quantitative variables with all the other quantitative variables. We still want to distinguish how the fuel economy is Impacted by the various characteristics of the car.

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You can specify the color palette with the palette$=$ command. You can find builtin color palettes here.

NOTE THIS MAY TAKE A WHILE TO RUN

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Based upon your analysis, are there any variables that are highly correlated and could be removed?

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The pairplot created earlier is nice, but there is a lot to get distracted by$.$ Create a scatterplot to justify your answer to the previous question.

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