Problem $1$

Interesting data science projects often combine data from multiple sources to investigate novel relationships. Process the above datasets to link the per$\_$point$\_$diff in the $2020$ Presidential Election results to the Population.Population per Square Mile in the $2020$ census County Demographics.

For each county, per$\_$point$\_$diff measures the differential in the percentage of votes recieved by the $2$ major parties $($as percent$\_$gop minus percent$\_$dem$).$

To measure density, because of skew, we will use numpy.log$10($Population$.$Population per Square Mile$)$ and call it Log$\_$Pop$\_$SqMi.

In Answer$1,$ create a DataFrame with the following form, sorted by per$\_$point$\_$diff. An example row is shown. You should be able to link the variables for $3109$ counties using the given data; ignore any other counties.

County State per$\_$point$\_$diff Log$\_$Pop$\_$SqMi

Montgomery County Virginia $-0\mathrm{.}0574862\mathrm{.}387212$

Hints: StateNameData might help make the link. It is possible to join on multiple key columns.