1. Portfolio Setup, Data Science, and Python

Due: 2020-09-12

1.1. Objective & Evaluation

This assignment is an opportunity to earn level 2 achievements for the process and python and confirm that you have all of your tools setup, including your portfolio.

1.2. To Do

Note

If you get stuck on any of this after accepting the assignment and creating a repository, you can create an issue on your repository, describing what you’re stuck on and tag us: @rhodypro4dg/fall21instructors

To do this click Issues at the top, the green “New Issue” button and then type away.

Important

If you have trouble, check the GitHub FAQ on the left before e-mailing

```{warning}
If you have trouble with the (*)d steps, don't worry, we can help work around these later. To help us out, document the errors as bugs on your repository.
```

Your task is to:

1. Install required software from the Tools & Resource page

2. Create your portfolio, by accepting the assignment

3. Learn about your portfolio from the README file on your repository.

4. edit _config.yml to set your name as author and change the logo if you wish

5. Fill in about/index.md with information about yourself(not evaluated, but useful) and your own definition of data science (graded for level 1 process)

6. (*) Install some additional python packages with: pip install pip install -r requirements.txt (this is a python operation, so use anaconda prompt on Windows, if the pip version doesn’t work, try it with conda: conda install --file requirements.txt) form inside the portfolio folder

7. (*) Configure precommit to help keep your repo clean with pre-commit install. If this step doesn’t work, see the portfolio README under “Using your Jupyter Book Portfolio”

8. Add a Jupyter notebook called grading.ipynb to the about folder and write a function that computes a grade for this course, with the following docstring. Include:

   • a Markdown cell with a heading

   • your function called compute_grade

   • three calls to your function that verify it returns the correct value for different number of badges that produce at three different letter grades.

   • a basic function that uses conditionals in python will earn level 1 python

   • to earn level 2 python use pythonic code to write a loop that tests your function’s correctness, by iterating over a list or dictionary. Remember you will have many chances to earn level 2 achievement in python

9. Add the line   - file: about/grading in your _toc.yml file.

Important

remember to add, commit, and push your changes so we can see them

    '''
    Computes a grade for CSC/DSP310 from numbers of achievements at each level

    Parameters:
    ------------
    num_level1 : int
      number of level 1 achievements earned
    num_level2 : int
      number of level 2 achievements earned
    num_level3 : int
      number of level 3 achievements earned

    Returns:
    --------
    letter_grade : string
      letter grade with possible modifier (+/-)
    '''

Here are some sample tests you could run to confirm that your function works correctly:

Warning

your function can have a different name than compute_grade, but make sure it’s your function name, with those parameter values in your tests.

Note

when the value of the expression after assert is True, it will look like nothing happened. assert is used for testing

assert compute_grade(15,15,15) == 'A'

assert compute_grade(15,15,13) == 'A-'

assert compute_grade(15,14,14) == 'B-'

assert compute_grade(14,14,14) == 'C-'

assert compute_grade(4,3,1) == 'D'

assert compute_grade(15,15,6) =='B+'

1.3. Submission Instructions

Create a Jupyter Notebook with your function in your portfolio folder commit and push the changes.

In your browser, view the gh-pages branch to see your compiled submission, as portfolio.pdf or by viewing your website.

There will be a pull request on your repository that is made by GitHub classroom, request a review from @rhodypro4dg/fall21instructors.