Scientific Python 1

There were a relatively large number of extinctions of mammalian species roughly 10,000 years ago. To help understand why these extinctions happened scientists are interested in understanding whether there were differences in the body size of those species that went extinct and those that did not. Since we’re starting to get pretty good at this whole programming thing let’s stop messing around with made up datasets and do some serious analysis.

Download the largest dataset on mammalian body size in the world. Fortunately this dataset has data on the mass of recently extinct mammals as well as extant mammals (i.e., those that are still alive today). Take a look at the metadata to understand the structure of the data. One key thing to remember is that species can occur on more than one continent, and if they do then they will occur more than once in this dataset. Also let’s ignore species that went extinct in the very recent past (designated by the word ‘historical’ in the ‘status’ column).

Import the data into Python. If you’ve looked at a lot of data you’ll realize that this dataset is tab delimited. The special character to indicate tab in Python is \t.

To start let’s explore the data a little and then start looking at the major question.

1. The following code will determine how many genera (plural of genus) there are in the dataset: len(data.groupby(['genus'])). Modify this code to determine the number of species. Remember that a species is uniquely defined by the combination of its genus name and its species name. Print the result to the screen. The number should be between 4000 and 5000.
2. Find out how many of the species are extinct and how many are extant, print the result to the screen. Hint: first separate the data into the extinct and extant components and then count the number of species.
3. Find out how many families are present in the dataset.
4. Now print the genus name, the species name, and the mass of the largest and smallest species (note, it is not possible for a mammal to have negative mass
5. Now let’s get to work. Calculate the average (i.e., mean) mass of an extinct species and the average mass of an extant species. The function mean() should help you here. It is available as both a numpy function and a Pandas DataFrame method. Don’t worry about species that occur more than once. We’ll consider the values on different continents to represent independent data points. Print out the results in the following sentence: “The average mass of extant species is X and the average mass of extinct species is Y.” with the appropriate values filled in for X and Y.