Combining Basics

Shrub Volume 5

This is a follow-up to Shrub Volume 4.

Now that you’re familiar with the data, Dr. Granger wants you to conduct a preliminary analysis of these data to include in a grant proposal (she might be a world renowned expert in carbon storage in plants, but she sure doesn’t know much about computers). If you missed it, the data file is still on the web.

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 an R script that:

• Imports the data using read.csv().
• Uses a for loop to check each row in the dataset and groups by height: "tall" if (height > 5), "medium" if (2 <= height < 5), or "short" if (height < 2), and builds a list of the results.
• Uses dplyr to determine the total amount of carbon in the shrub and transmute() rows in the dataset to produce the results table. The total amount of carbon is equal to 1.8 + 2 * log(volume) where volume is the volume (length * width * height) of the shrub.
• Stores this information as table in a data.frame with each of these row holding the results for one shrub. The first column should have the experiment number. The second column should have the string "tall", "medium" or "short" depending on the height of the shrub. And, the third column should have the shrub carbon. Be sure to use descriptive column names.
• Exports this table to a csv (comma delimited text) file titled shrubs_experiment_results.csv.
• Uses functions to break the code up into manageable pieces.

Optional: If you’d like to test your skills a little more, try determining the average carbon in a shrub for each of the different experiments and printing those values to the screen.

[click here for output]