Data Science with R for the Life Sciences

Shrub Volume (Combining Basics)

Dr. Granger is interested in studying the factors controlling the size and carbon storage of shrubs. This research is part of a larger area of research trying to understand carbon storage by plants. She has conducted a small preliminary experiment looking at the effect of three different treatments on shrub volume at four different locations. She wants to conduct a preliminary analysis of these data to include in a grant proposal and she would like you to conduct the analysis for her (she might be a world renowned expert in carbon storage in plants, but she sure doesn’t know much about computers). She has placed a data file on the web for you to download.

You might be able to do this analysis by hand in Excel, but Dr. Granger seems to always get funded meaning that you’ll be doing this again soon with a much larger dataset. So, you decide to write a script so that it will be easy to do the analysis again.

Write a Python script that:

  • Imports the data using numpy. It has a header row so you’ll need to tell numpy.loadtxt() to ignore it by providing the optional argument skiprows=1.
  • Loops over the rows in the dataset

  • Uses a for loop to check each row in the dataset, groups by height as 'tall' if (height > 5), 'medium' if (2 <= height < 5), or 'short' if (height < 2), and determines the total amount of carbon in the shrub.

    The total amount of carbon is equal to 1.8 + 2 * log(volume) where volume is the volume of the shrub (length * width * height).

  • Stores this information as table in a nested list (i.e., a list that contains a bunch of lists, with each of these sub-lists holding the results for one shrub) where the first column has the experiment number, the second column contains the string 'tall', 'medium' or 'short' depending on the height of the shrub, and the third column contains the shrub carbon.
  • Exports this table to a csv (comma delimited text) file titled shrubs_experiment_results.csv.
  • Use functions to break the code up into manageable pieces.

To help you get started here is a function for exporting the results to a CSV file. To use it you’ll need to copy and paste it into your code. It uses the csv module so you’ll need to remember to import it.

def export_to_csv(data, filename):
    """Export list of lists to comma delimited text file"""
	outputfile = open(filename, 'wb')
	datawriter = csv.writer(outputfile)
	datawriter.writerows(data)
	outputfile.close()

Optional: If you’d like to test your skills a little more, try: 1. Adding a header row to you output file; and 2. Determining the average carbon in a shrub for each of the different experiments and printing those values to the screen.

Expected outputs for Shrub Volume: 1