Module 1: GitHub and basic functions

Let’s get started on the project! You have received the script clean_project_data_v4_final2.py from a colleague and in this module you will create a GitHub repository, add the script and improve the script by using functions.

• 1.1 GitHub repo
  • Create a new GitHub repository “timeseriescleaner” on your own GitHub profile (not on your organization’s GitHub)
    • Make it private, no template, add readme, gitignore python, no license
  • Go to repo settings/Collaborators add your instructors and your “buddy”
  • Clone repo to local machine
  • [Optional] Create virtual environment for this course project (use venv or mamba/conda environment)
  • Download the provided Python script and add it to the repo
  • Commit the file and push the changes (Check that the file can be found on GitHub)
  • Open the project in vscode and make a single character change to the file (add a comment)
  • Commit and push the changes (Check that you can find it on GitHub)
• 1.2 Functions
  • Create a local branch “refactor-functions”
  • Refactor the code to use functions (clean_spikes, clean_outofrange, clean_flat, plot_timeseries)
  • You should be able to run the cleaning using this loop:
    

  for data in [data1, data2, data3]:
    data_original = data.copy()
    data = clean_spikes(data, max_jump=10)
    data = clean_outofrange(data, min_val=0, max_val=50)
    data = clean_flat(data, flat_period=5)
    plot_timeseries(data_original, data)

  • Check that your code runs and produce the same results as before (you should not change the functionality when refactoring!)
  • Commit your code in one or more commits (in the end, your code should be approximately 75 lines long)
• Create a pull request in GitHub and “request review” from your reviewers
• Wait for feedback, Adjust code until approval, then merge (and delete branch)

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