In this week's lab, it was easy to see how these skills could be applicable to a GIS project. The plots were all very interesting to look through in matplotlib, but I chose to test out the bar plot and scatter plot examples because I would use those the most. For the bar plot example, I used some open source data available from New York about neighborhood demographics. I replaced the data that was used in that example with that data. In the scatterplot example, I used the random number that was already generated in the example. I displayed the shapefile data that I had in a scatterplot to show the concentration of arsenic found in groundwater as a function of depth. I had a little trouble figuring out how to set up the scatter plot with table data, but was able to figure that out pretty easily by finding an example that loaded data into the graph. I can definitely see how this could be useful for future applications, but would like to become more comfortable with customizing the graph display.