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Homework: Automating Text Processing and Word Cloud Generation in Python

In this lesson, we learned how to:
Read text from online files using urllib.request.
Work with strings: slicing, splitting, indexing.
Loop through words and letters using for
Install and use the WordCloud library.
Download an image from Google Drive and use it as a mask.
Add stopwords to clean a word cloud.
These skills help us automatically read, clean, and transform text into visual data.

Apply what you learned to automate text processing and generate word clouds.
Task 1 – Read Text and Work With It
Write Python code that reads a file from a URL, or you can simply write your own sentences. You may decide how to read the text and what operations to perform on it (for example: splitting, selecting certain words, printing parts of the text, etc.). Show the code you used and briefly explain what it does. (Do everything in your .ipynb file)

Task 2 – Create a Basic Word Cloud
Create a word cloud using a text file. You may choose any style, settings, or additional steps (for example: stopwords, colors, text selection, etc.). The most important part is interpreting the word cloud: explain what it shows about the text. Show your code and describe your observations.
Submission Instructions
Submit the URL of the .ipynb file from your GitHub repository. Make sure all your work in the Codespace is fully synced with the repository.