In your Jupiter notebook display the Seaborn lmplot of deal size on one axis and invite percent on the other. That'll tell us how investors react to being invited to deals of various sizes and being invited to commit larger or smaller percentages of those transactions.

First, we call the Seaborn lmplot function, and we set the X argument to deal size the Y argument to invite percent, the hue argument, which is our target variable to commit, and that is what changes the colors by class. The data argument is our investor data so that our investor data is populating our scatterplot and we do not want a regression line on this, so we're gonna set fit reg to false. Then we're going to call the pyplot show function, and that's going to display our scatterplot.