Homework 0

Homework
Published

December 31, 2023

In this blog post assignment, you’ll create a short post for your new website. The primary purpose is to give you some practice working with Quarto blogging with Python code.

Make sure to check the “Specifications” section at the bottom of this assignment for an explicit list of criteria that your blog post must meet in order to receive credit.

Instructions

To complete this homework assignment, you’ll need to have completed installations of Anaconda, GitHub Desktop, and Quarto as described in the instructions in BruinLearn.

1. Complete the Hello, Quarto activity

Your first step should be to complete the Hello Quarto activity to help you get familiar with blogging with Quarto. If you already completed this activity in Discussion, then you can skip to the next step.

If you haven’t done so already, now is a good time to modify your site. Look around the site’s files and see if you can figure out how to modify the About page and the blog’s title from about.qmd and _quarto.yml.

See these pages for help: about page, config options.

If you are comfortable with css, then you can directly modify style.css and other files in the repo.

All this is optional, and it’s not necessary to put your real name or real photo anywhere on the site.

2. Speedbump: The Autograder

Before we proceed, let’s talk about the autograder. Some of the specs in the homework assignments may require you to go through an autograder. Depending on the homework, you must submit a single Python file (.py) or a compressed .zip file containing multiple code files to the “autograder” submission window. For future homework, the autograder task will be a part of the main programming task. For this one, let’s just do a simple PIC 16A-level task. Remember that for your blog post to be graded, you must first pass the autograder. I strongly encourage you to do so a few days before the deadline. You have an unlimited number of submissions to the autograder.

Problem. Define make_count_dictionary in HW0.py

In a separate file named HW0.py (please do not use a different name), write the function make_count_dictionary that takes a list L and returns a dictionary D where:

  • The keys of D are the unique elements of L (i.e., each element of L appears only once).
  • The value D[i] is the number of times that i appears in list L.

Your code should work for lists of strings, lists of integers, and lists containing both strings and integers.

For example:

# input
L = ["a", "a", "b", "c"]
# output
{"a" : 2, "b" : 1, "c" : 1}

For this homework, you don’t need to mention this task in your blog.

3. Create a post

Create a simple blog post, using the instructions and demonstrations here. Here is the prompt for your post:

Write a tutorial explaining how to construct an interesting data visualization of the Palmer Penguins data set.

You can read the data into Python by running:

import pandas as pd
url = "https://raw.githubusercontent.com/pic16b-ucla/24W/main/datasets/palmer_penguins.csv"
penguins = pd.read_csv(url)

Your visualization does not have to be complex or fancy, but it should be highly readable and appropriately labeled.

Your post should include the image directly under the code that generates it, as demonstrated here.

There will be three Gradescope assignments open for submission, the first one for autograder, the second for PDF, and the third one for files. You have to submit all of them for your homework to earn homework credits.

  • For the autograder assignment, please follow the directions.
  • For the PDF assingment, please submit your newly-created blog page printed as PDF.
    • The file should show the URL to your blog.
  • For the files assignment, please submit any code file you wrote for your homework, not including what you have submitted for autograder. All the .py file, .ipynb file, or .qmd files all included. It should include a .py file converted from any .ipynb file. The grader should be able to reproduce your result from the code portion you submitted.
    • It must include index.ipynb, the Jupyter Notebook you worked on, and index.py, a Python script-converted version of it.

Hint

The easiest way to create a post like this is to solve the problem in a Jupyter Notebook or Python script first, and then transfer the results over to your blog.

Specifications

Format

  1. For the PDF section, you have to submit the PDF-printed version of your Quarto blog. The file should show the URL to your published blog. Anything else will receive “In Progress” grade at best, incuding:
  • Jupyter notebook or JupyterLab screen printed
  • HTML-converted Jupyter notebook printed
  • PDF-converted Jupyter notebook or JupyterLab
  • PDF generated directly from Quarto
  1. For the files section, you have to submit code necessary to reproduce your results, including index.ipynb and index.py, as specified above.

Coding Problem

  1. The autograder task is complete, receiving full mark on Gradescope.
  2. The plot is readable and contains axis labels, a title, and a legend if appropriate.

Style and Documentation

  1. Repeated operations should be enclosed in functions.
  2. For-loops are minimized by making full use of vectorized operations for Numpy arrays and Pandas data frames.
  3. Helpful comments are supplied throughout the code. Docstrings are supplied for any functions and classes you define.

Writing

  1. The overall post is written in engaging and unambiguous English prose. There is written explanation throughout the post, such that a PIC16A student could learn to perform the demonstrated tasks by reading the post.
  2. Each block of code has a clearly-explained purpose.
  3. The post is organized into clearly delimited sections using markdown headers (#), making it easier for the reader to navigate.