Highest Mountains in the World ⛰️

MicroProject Overview

Wikipedia is an absolutely amazing source of information about almost every topic you can imagine! The Wikipedia article "List of mountains by elevation" contains information on hundreds of mountains -- including Mount Everest (tallest in the world), Denali (tallest in the United States), and many more!

In this MicroProject, you will explore how to easily use data in Wikipedia tables as datasets, and perform row selection based on the contents of strings in your DataFrame.

Libraries Needed

In order to complete this MicroProject, you will need an additional library (lxml) that is used to read HTML data. To install it, run the following command in your terminal:

  • Windows: py -m pip install lxml
  • macOS: python3 -m pip install lxml
  • If the above does not work or gives an error, try: pip3 install lxml
MicroProject in Visual Studio Code
MicroProject in Visual Studio Code
Wikipedia Page of the Highest Mountains
Wikipedia Page of the Highest Mountains
DataFrame loaded with Data from Wikipedia tables
DataFrame loaded with Data from Wikipedia tables
Highest Mountains in the United States
Highest Mountains in the United States

First Time Doing a MicroProject?

Each MicroProject starts with a notebook that we provide to you to get started! You will need to configure a git repository to connect to our `microprojects` remote where we release the starter notebook.

Fetch the Initial Files

In your terminal, navigate to your GitHub repository and merge the initial files by running the following commands:

git fetch microprojects
git merge microprojects/microproject-highest-mountains --allow-unrelated-histories -m "Merging initial files"

Complete the Notebook

If the commands above were successful, you have merged in the initial files to start on the MicroProject.

  • Find the new microproject-highest-mountains folder.
  • Open microproject-highest-mountains.ipynb and complete the MicroProject!

Commit and Grade Your Notebook

Once you have finished your notebook, you must use the built-in GitHub Action to preform automated grading of your MicroProject notebook! You will need to commit your work and then manually run the GitHub Action.

Commit Your Work

To commit your notebook, run the standard git commands in your terminal:

git add -u
git commit -m "microproject completed"
git push

Grade Your Notebook

To grade your notebook, you will need to visit your GitHub repository in your browser.

  • Visit your GitHub repository in your browser
  • Click on the "Actions" tab
  • Under "Workflows", find the workflow for this microproject
  • Click the "Run Workflow" in the blue box, and then the green "Run Workflow"
  • After about 10 seconds, you should see a new job that has started running
    • You can click on the job to watch it run in real-time
    • It will take ~1 minute to run and grade
  • Once the running is complete, the autograding summary will be available!