This is a follow up to the Scientific Python 7 exercise.

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. She wants you to run an ANOVA to determine if the different experimental treatments lead to differences in shrub carbon.

- Import the data using Pandas and print out the first few rows of the data
using the
`.head()`

method. - Write a function to calculate the shrub carbon using a column of lengths, a
column of widths and a column of heights, using the equation
`1.8 + 2 * log(volume)`

where`volume`

is the volume of the shrub. You’ll need to use the`numpy`

version of the`log()`

function. Call the function to get a column of shrub carbons and then print out that column. - Use this function to get a column of carbons for all of the shrubs in the
table and append that column to your existing dataframe using a command like
`data['carbon'] = get_shrub_carbons(lengths, widths, heights)`

. Print out the entire dataframe. - Do an ANOVA to determine if the experiment has an influence on the shrub
carbon and print out the results in a standard ANOVA table using
`anova_lm()`

. You can import`anova_lm()`

using`from statsmodels.stats.anova import anova_lm`

.