Grading criteria for the final assignment

The grading is based on a typical 0-5 scale.

The following aspects are considered in the assessment

Data preparation, analysis & visualization (3/5 of final grade):

• Reading and manipulating data

• (Spatial) data analysis steps

• Quality of visualizations (maps, graphs)

• Is the code written in a modular way (avoid repetition eg. using functions and for-loops)

• Does everything work as it should

• Overall difficulty of the analysis task is taken into account in the assessment

Overall documentation of the work (1/5 of final grade)

• Is there a general description in about the research problem / purpose of the tool?

• Is the usage of the tool/ available functions described and demonstrated clearly?

• Are all input data and output results (maps, graphs) presented and explained clearly?

• Is the code easy to read and well-formatted (following the PEP8 guidelines)

Other merits in the work (~1/5 of final grade):

• Good style of coding (writing efficient and well-documentent code)

• Something in the work is exceptionally well done

• Some problem in the code is solved in a “smart” way

• The work is exceptionally well documented

• The visualizations are exceptionally good

• Additional features are added (eg. steps 5-6 in accesViz, or some other features that were not required)

The workflow should be repeatable and well documented. In other words, anyone who gets a copy of your repository should be able to run your code, and read your code.