Class 19 (Maybe).   Groupby and Categorical Data

I numbered this class 19 to try and have it go to the correct spot on the website.  I have the most trouble wrapping my mind around this data.  It is hard thinking like this.  It is when you have a lot of categorical data describing each point.  So for each data point you know all these other details.  Plus we have a time series of points.  We are going to use our tree data from around campus that the Professor Terryanne Maenza-Gmelch and Professor Rodriguez have been collecting since 2015.  We are going to make the plots.  Here is a map I made of the data.  Click on a point!  You see the graphs!  We are going to make all of them!  We can make the map in the future!  You could make the same map.  We are just short on time.

BIG WARNING:  For some people with new python we get an error when doing the first mean on groupby.  You need to update it to this

df.groupby(‘old tree number’).mean(numeric_only=True)

I will update the packet and GitHub soon

Files we need

• Groupby folder on GitHub
• (pdf=groupby-Barnard-Trees)
• my pdf answer is in the GitHub folder

Homework Due TBA

• Hand in a jupyter notebook where you make the percentages of species.  Answer in notebook
• Hand in the notebook and pdf of all the growth fits.  Your name needs to be on each graph either in the title, and axis, or the data box.  The graphs are mad nice!