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.