This exercise is designed for work experience students to analyse the efficiency of our various test suites.
You should use Python to run and develop your analysis. If you do not have Python and the seaborn library (used for generating graphs) installed, you can use Google Colab (https://colab.research.google.com/). Google Colab provides a free, interactive Python environment with seaborn pre-installed.
- Analyse the average time it takes for tests to run for each service.
- Present the results in a suitable graph (e.g., bar chart, box plot).
- Rank the services from the most tests to least using a separate chart or table.
- Explore other avenues of analysis.
Once you have completed the basic analysis, you can explore additional data provided in advanced_test_data.py.
When your analysis is complete, prepare a short presentation to share your findings with the team.
If you finish early, try tackling some Python problems from the bioinformatics-themed Rosalind site (https://rosalind.info/problems/list-view/).