'''
Beavers II

This exercise builds on the beavers exercise from the previous chapter.

As a reminder:
We are working with a small part of a study of the long-term temperature 
dynamics of beaver "Castor canadensis" in north-central Wisconsin. Body 
temperature was measured by telemetry every 10 minutes for four females, but 
data from one period of less than a day of two animals is used here.

In the previous beavers exercise, you combined the data of two beavers into one
table, which you saved on your computer. This file you previously prepared is the
starting point of this exercise.

Exercise A: Import data into Python

Load your table that combines the data of two beavers into Python and perform some
preliminary data exploration using Python:
* Which columns are in the data? What types of values do they contain?
* How many different animals' data do you have?
* How many different values are possible for activity outside retreat, and how 
many of each do you have in the data?
* How many different days and timepoints are in the data?
'''

# Your code here


'''
Exercise B: Exploratory plotting

No matter the dataset you're handling, after getting acquainted with your 
dataset (like you just did in Exercise A) the next thing you will always want 
to do is exploratory data analysis via plotting.

In this exercise, we are not giving you specific directions for plots you 
need to make. Instead, knowing what data you have in your beavers table,
think about what plots could be interesting and make them using Python.

Based on your plots, what can you learn about beavers? Try to learn as much as
possible about these cute rodents from your data.
'''

# Your code here