Data-projects-with-R-and-GitHub

The IUCN (International Union for Conservation of Nature) and their “Red List of Threatened Species” aim to draw attention to, and keep track of, how non-human life on earth is faring.

To this end they assess various species and how their populations are developing over time, sorting them into categories, doubtless you’ve seen some of these categories before, like Threatened or even Extinct.

The table you will be working on only covers a small part of the Red Lists scope, namely it provides the number of species from every class and how they are classified according to the red list. (There is also Kingdom data but we will get to that.)

Now Species you’ve all heard before, it is the smallest unit in the taxonomy of life, defined by members of a species being able to produce offspring which itself is able to produce offspring.

Class and Kingdom might feel more foreign to you, but it just comes down to larger umbrellas of life. A Class contains many Species each

• There are also more so-called Taxonomic Ranks in between but we don’t care about those here.

And a Kingdom contains many Classes itself, Kingdom being one of the highest ranks. One Kingdom for example is Animalia which includes all animals. Or Plantae which includes all plants.

• Again there are more intermediary steps between Kingdom and Class.

Tasks:

1. Data import and wrangling

a) Import csv into R

I have placed the .csv in my /dependencies folder, you can import it from there.

After importing the table should look like this:

Name	EX	EW	Subtotal (EX+EW)	CR(PE)	CR(PEW)	Subtotal (EX+EW+ CR(PE)+CR(PEW))	CR	EN	VU	Subtotal (threatened spp.)	LR/cd	NT or LR/nt	LC or LR/lc	DD	Total
ACTINOPTERYGII	90	11	101	143	8	252	777	1359	1502	3638	0	890	17851	5236	27716
AMPHIBIA	37	2	39	187	1	227	825	1291	814	2930	0	453	3733	896	8051
ANTHOZOA	0	0	0	2	0	2	32	246	58	336	0	24	431	147	938
ARACHNIDA	9	0	9	27	0	36	121	165	104	390	0	52	488	114	1053

b) Visit the Website

IUCN Red List

Check out the table and the legend below, familiarize yourself with the column names and what categories they belong to.

c) Add Kingdom data

On the website you will see that they also have data on which Kingdom the various Classes belong to, we want to add this data semi-automatically.

• Manually note the different Kingdoms and in what order they appear in the online table.

• Use lag() and/or fill() alongside the fact that the table is ordered lexicographically by Class-name within each Kingdom to automatically find the boundaries between the different Kingdoms.

• Add the Kingdom information in a new column named Kingdom

2. Data Manipulation

a) Remove unwanted columns

The legend on the website also explains that Possibly Extinct and Possibly Extinct in the Wild are not classifications from the IUCN, as such take them out of your table. Then also remove the column Subtotal (EX+EW+ CR(PE)+CR(PEW)).

c) Simplify columns

I dislike the following categories:

• LR/cd - Lower Risk/conservation dependent

• NT - Near Threatened (includes LR/nt - Lower Risk/near threatened)

I want you to restructure them by integrating them into one singular new column, which is made up of the sum of both. Call this column Near Threatened and remove the old ones.

d) Make column names readable

The website also has an explanation of the column names at the bottom, look them up and replace the column names with the easier to read full names of the categories, shorten in a way where:

• The columns should at the end all have names that are in line with Near Threatened.

• They remain unique.

3. Data Visualisation

a) Create relative amount table

Before you start visualizing, create a separate table. In this table, each of the columns, except the Total column, contain the percent of the Total they make up row-wise.

• So if in the old table, a row contains a Total of 200 and an EX of 8, the new table would say 4 in the EX column.

• The Total column should always display 100

• Also give the column names an update so it says <ColumnName> [%]

b) Visualize difference between Kingdoms

We want to compare the different Kingdoms, especially if they have been affected to different extends:

To this end, create a bar plot as in the picture, one bar per Kingdom. Exclude any Kingdoms that have a total of less than 1000 Species from the plot.

The y-Axis contains the percent of species in that Kingdom that fall into various categories colored as in the picture. The categories are:

• Extinct: EX or EW

• Affected: CR, EN or VU

• Unaffected or no data: Rest

Make sure you find better labels and names for the Legend and the Axis labels.

c) Visualize most and least affected Classes

Next we are interested in the most and least affected Classes, as well as which Kingdom they belong to:

Affected here is defined as the “Percent of at least Critically Endangered Species in a given Class”

Create a bar-plot that contains (from left to right):

• The 10 most affected Classes, ordered from most to least.

• Three dots like in the provided picture.

• the 10 least affected Classes, ordered from most to least

Make sure to also:

• Color the bars according to the Classes’ Kingdom and place a legend that explains the colors.

• Label every bar with the appropriate name of the Class and make sure it looks good (you might want to use diagonal labels or other tricks)