Python Tutorial: Scatterplots over polygons

Want to learn more? Take the full course at https://learn.datacamp.com/courses/visualizing-geospatial-data-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- In the last exercise of this chapter, you will combine a scatterplot of chicken locations with the polygons showing service districts in order to understand where the chickens are with respect to service district boundaries. In this first chapter, you have learned how longitude and latitude can be used to help visualize geospatial data. You've gotten a taste of wrangling longitude and latitude from a field where they are embedded. You've mastered plotting points as a scatterplot - using longitude as X and latitude as Y. You've learned some ways you can style scatterplots, using color and marker shape. And you have learned how to add axis labels and a title. And you've also learned how to plot polygons from a shapefile and create a legend to tell more about each region. Next you will learn how to combine a plot of points with a plot of polygons. Maps are created from visual layers, with each layer adding reference points and other cues that enhance the ability to get meaning from the map. Here we have a scatterplot of all Nashville public school locations on the left and a plot of school districts on the right. We can combine these plots to get more contextual meaning from the locations of schools with regard to school districts. First, plot the districts to create a map of polygons. Next add a scatterplot to add points that show where the schools are. Adding the scatterplot after plotting the shapes enriches the plot and gives more insight into where schools are in regard to school district locations. Now it's time for you to create your first geospatial visualization with two layers by plotting a polygon map of service districts and then adding a scatterplot to see where the chickens are in Nashville. #PythonTutorial #